diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 91d53044d..b677d924f 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -272,6 +272,16 @@ jobs:
pip install pyaml
python build_helpers/pre_commit_update.py
+ pre-commit:
+ runs-on: ubuntu-22.04
+ steps:
+ - uses: actions/checkout@v3
+
+ - uses: actions/setup-python@v4
+ with:
+ python-version: "3.10"
+ - uses: pre-commit/action@v3.0.0
+
docs_check:
runs-on: ubuntu-20.04
steps:
@@ -302,7 +312,7 @@ jobs:
# Notify only once - when CI completes (and after deploy) in case it's successfull
notify-complete:
- needs: [ build_linux, build_macos, build_windows, docs_check, mypy_version_check ]
+ needs: [ build_linux, build_macos, build_windows, docs_check, mypy_version_check, pre-commit ]
runs-on: ubuntu-20.04
# Discord notification can't handle schedule events
if: (github.event_name != 'schedule')
@@ -327,7 +337,7 @@ jobs:
webhookUrl: ${{ secrets.DISCORD_WEBHOOK }}
deploy:
- needs: [ build_linux, build_macos, build_windows, docs_check, mypy_version_check ]
+ needs: [ build_linux, build_macos, build_windows, docs_check, mypy_version_check, pre-commit ]
runs-on: ubuntu-20.04
if: (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'release') && github.repository == 'freqtrade/freqtrade'
diff --git a/config_examples/config_freqai.example.json b/config_examples/config_freqai.example.json
index 12eb30128..fe5e35c1d 100644
--- a/config_examples/config_freqai.example.json
+++ b/config_examples/config_freqai.example.json
@@ -77,7 +77,8 @@
"indicator_periods_candles": [
10,
20
- ]
+ ],
+ "plot_feature_importance": false
},
"data_split_parameters": {
"test_size": 0.33,
diff --git a/config_examples/config_full.example.json b/config_examples/config_full.example.json
index 8155cb145..5a5096f81 100644
--- a/config_examples/config_full.example.json
+++ b/config_examples/config_full.example.json
@@ -172,7 +172,24 @@
"jwt_secret_key": "somethingrandom",
"CORS_origins": [],
"username": "freqtrader",
- "password": "SuperSecurePassword"
+ "password": "SuperSecurePassword",
+ "ws_token": "secret_ws_t0ken."
+ },
+ "external_message_consumer": {
+ "enabled": false,
+ "producers": [
+ {
+ "name": "default",
+ "host": "127.0.0.2",
+ "port": 8080,
+ "ws_token": "secret_ws_t0ken."
+ }
+ ],
+ "wait_timeout": 300,
+ "ping_timeout": 10,
+ "sleep_time": 10,
+ "remove_entry_exit_signals": false,
+ "message_size_limit": 8
},
"bot_name": "freqtrade",
"db_url": "sqlite:///tradesv3.sqlite",
diff --git a/docker/Dockerfile.freqai b/docker/Dockerfile.freqai
index 9a2f75700..e9f04f3d6 100644
--- a/docker/Dockerfile.freqai
+++ b/docker/Dockerfile.freqai
@@ -6,4 +6,3 @@ FROM ${sourceimage}:${sourcetag}
COPY requirements-freqai.txt /freqtrade/
RUN pip install -r requirements-freqai.txt --user --no-cache-dir
-
diff --git a/docs/advanced-hyperopt.md b/docs/advanced-hyperopt.md
index 8a1ebaff3..9933628d1 100644
--- a/docs/advanced-hyperopt.md
+++ b/docs/advanced-hyperopt.md
@@ -17,6 +17,7 @@ from typing import Any, Dict
from pandas import DataFrame
+from freqtrade.constants import Config
from freqtrade.optimize.hyperopt import IHyperOptLoss
TARGET_TRADES = 600
@@ -31,7 +32,7 @@ class SuperDuperHyperOptLoss(IHyperOptLoss):
@staticmethod
def hyperopt_loss_function(results: DataFrame, trade_count: int,
min_date: datetime, max_date: datetime,
- config: Dict, processed: Dict[str, DataFrame],
+ config: Config, processed: Dict[str, DataFrame],
backtest_stats: Dict[str, Any],
*args, **kwargs) -> float:
"""
diff --git a/docs/configuration.md b/docs/configuration.md
index f8a600e76..556414e21 100644
--- a/docs/configuration.md
+++ b/docs/configuration.md
@@ -57,7 +57,7 @@ You can specify additional configuration files in `add_config_files`. Files spec
This is similar to using multiple `--config` parameters, but simpler in usage as you don't have to specify all files for all commands.
!!! Tip "Use multiple configuration files to keep secrets secret"
- You can use a 2nd configuration file containing your secrets. That way you can share your "primary" configuration file, while still keeping your API keys for yourself.
+ You can use a 2nd configuration file containing your secrets. That way you can share your "primary" configuration file, while still keeping your API keys for yourself.
The 2nd file should only specify what you intend to override.
If a key is in more than one of the configurations, then the "last specified configuration" wins (in the above example, `config-private.json`).
@@ -110,7 +110,7 @@ This is similar to using multiple `--config` parameters, but simpler in usage as
"stake_amount": "unlimited"
}
```
-
+
If multiple files are in the `add_config_files` section, then they will be assumed to be at identical levels, having the last occurrence override the earlier config (unless a parent already defined such a key).
## Configuration parameters
@@ -225,14 +225,16 @@ Mandatory parameters are marked as **Required**, which means that they are requi
| `webhook.webhookexitcancel` | Payload to send on exit order cancel. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String
| `webhook.webhookexitfill` | Payload to send on exit order filled. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String
| `webhook.webhookstatus` | Payload to send on status calls. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
**Datatype:** String
-| | **Rest API / FreqUI**
+| | **Rest API / FreqUI / Producer-Consumer**
| `api_server.enabled` | Enable usage of API Server. See the [API Server documentation](rest-api.md) for more details.
**Datatype:** Boolean
| `api_server.listen_ip_address` | Bind IP address. See the [API Server documentation](rest-api.md) for more details.
**Datatype:** IPv4
| `api_server.listen_port` | Bind Port. See the [API Server documentation](rest-api.md) for more details.
**Datatype:** Integer between 1024 and 65535
| `api_server.verbosity` | Logging verbosity. `info` will print all RPC Calls, while "error" will only display errors.
**Datatype:** Enum, either `info` or `error`. Defaults to `info`.
| `api_server.username` | Username for API server. See the [API Server documentation](rest-api.md) for more details.
**Keep it in secret, do not disclose publicly.**
**Datatype:** String
| `api_server.password` | Password for API server. See the [API Server documentation](rest-api.md) for more details.
**Keep it in secret, do not disclose publicly.**
**Datatype:** String
+| `api_server.ws_token` | API token for the Message WebSocket. See the [API Server documentation](rest-api.md) for more details.
**Keep it in secret, do not disclose publicly.**
**Datatype:** String
| `bot_name` | Name of the bot. Passed via API to a client - can be shown to distinguish / name bots.
*Defaults to `freqtrade`*
**Datatype:** String
+| `external_message_consumer` | Enable [Producer/Consumer mode](producer-consumer.md) for more details.
**Datatype:** Dict
| | **Other**
| `initial_state` | Defines the initial application state. If set to stopped, then the bot has to be explicitly started via `/start` RPC command.
*Defaults to `stopped`.*
**Datatype:** Enum, either `stopped` or `running`
| `force_entry_enable` | Enables the RPC Commands to force a Trade entry. More information below.
**Datatype:** Boolean
@@ -659,17 +661,7 @@ You should also make sure to read the [Exchanges](exchanges.md) section of the d
### Using proxy with Freqtrade
-To use a proxy with freqtrade, add the kwarg `"aiohttp_trust_env"=true` to the `"ccxt_async_kwargs"` dict in the exchange section of the configuration.
-
-An example for this can be found in `config_examples/config_full.example.json`
-
-``` json
-"ccxt_async_config": {
- "aiohttp_trust_env": true
-}
-```
-
-Then, export your proxy settings using the variables `"HTTP_PROXY"` and `"HTTPS_PROXY"` set to the appropriate values
+To use a proxy with freqtrade, export your proxy settings using the variables `"HTTP_PROXY"` and `"HTTPS_PROXY"` set to the appropriate values.
``` bash
export HTTP_PROXY="http://addr:port"
@@ -677,6 +669,20 @@ export HTTPS_PROXY="http://addr:port"
freqtrade
```
+#### Proxy just exchange requests
+
+To use a proxy just for exchange connections (skips/ignores telegram and coingecko) - you can also define the proxies as part of the ccxt configuration.
+
+``` json
+"ccxt_config": {
+ "aiohttp_proxy": "http://addr:port",
+ "proxies": {
+ "http": "http://addr:port",
+ "https": "http://addr:port"
+ },
+}
+```
+
## Next step
Now you have configured your config.json, the next step is to [start your bot](bot-usage.md).
diff --git a/docs/data-download.md b/docs/data-download.md
index 2b76d4f74..700ca04f4 100644
--- a/docs/data-download.md
+++ b/docs/data-download.md
@@ -26,7 +26,7 @@ usage: freqtrade download-data [-h] [-v] [--logfile FILE] [-V] [-c PATH]
[--timerange TIMERANGE] [--dl-trades]
[--exchange EXCHANGE]
[-t TIMEFRAMES [TIMEFRAMES ...]] [--erase]
- [--data-format-ohlcv {json,jsongz,hdf5}]
+ [--data-format-ohlcv {json,jsongz,hdf5,feather,parquet}]
[--data-format-trades {json,jsongz,hdf5}]
[--trading-mode {spot,margin,futures}]
[--prepend]
@@ -55,7 +55,7 @@ optional arguments:
list. Default: `1m 5m`.
--erase Clean all existing data for the selected
exchange/pairs/timeframes.
- --data-format-ohlcv {json,jsongz,hdf5}
+ --data-format-ohlcv {json,jsongz,hdf5,feather,parquet}
Storage format for downloaded candle (OHLCV) data.
(default: `json`).
--data-format-trades {json,jsongz,hdf5}
@@ -76,7 +76,7 @@ Common arguments:
`userdir/config.json` or `config.json` whichever
exists). Multiple --config options may be used. Can be
set to `-` to read config from stdin.
- -d PATH, --datadir PATH
+ -d PATH, --datadir PATH, --data-dir PATH
Path to directory with historical backtesting data.
--userdir PATH, --user-data-dir PATH
Path to userdata directory.
@@ -179,9 +179,11 @@ freqtrade download-data --exchange binance --pairs ETH/USDT XRP/USDT BTC/USDT --
Freqtrade currently supports 3 data-formats for both OHLCV and trades data:
-* `json` (plain "text" json files)
-* `jsongz` (a gzip-zipped version of json files)
-* `hdf5` (a high performance datastore)
+* `json` - plain "text" json files
+* `jsongz` - a gzip-zipped version of json files
+* `hdf5` - a high performance datastore
+* `feather` - a dataformat based on Apache Arrow
+* `parquet` - columnar datastore
By default, OHLCV data is stored as `json` data, while trades data is stored as `jsongz` data.
@@ -200,38 +202,74 @@ If the default data-format has been changed during download, then the keys `data
!!! Note
You can convert between data-formats using the [convert-data](#sub-command-convert-data) and [convert-trade-data](#sub-command-convert-trade-data) methods.
+#### Dataformat comparison
+
+The following comparisons have been made with the following data, and by using the linux `time` command.
+
+```
+Found 6 pair / timeframe combinations.
++----------+-------------+--------+---------------------+---------------------+
+| Pair | Timeframe | Type | From | To |
+|----------+-------------+--------+---------------------+---------------------|
+| BTC/USDT | 5m | spot | 2017-08-17 04:00:00 | 2022-09-13 19:25:00 |
+| ETH/USDT | 1m | spot | 2017-08-17 04:00:00 | 2022-09-13 19:26:00 |
+| BTC/USDT | 1m | spot | 2017-08-17 04:00:00 | 2022-09-13 19:30:00 |
+| XRP/USDT | 5m | spot | 2018-05-04 08:10:00 | 2022-09-13 19:15:00 |
+| XRP/USDT | 1m | spot | 2018-05-04 08:11:00 | 2022-09-13 19:22:00 |
+| ETH/USDT | 5m | spot | 2017-08-17 04:00:00 | 2022-09-13 19:20:00 |
++----------+-------------+--------+---------------------+---------------------+
+```
+
+Timings have been taken in a not very scientific way with the following command, which forces reading the data into memory.
+
+``` bash
+time freqtrade list-data --show-timerange --data-format-ohlcv
+```
+
+| Format | Size | timing |
+|------------|-------------|-------------|
+| `json` | 149Mb | 25.6s |
+| `jsongz` | 39Mb | 27s |
+| `hdf5` | 145Mb | 3.9s |
+| `feather` | 72Mb | 3.5s |
+| `parquet` | 83Mb | 3.8s |
+
+Size has been taken from the BTC/USDT 1m spot combination for the timerange specified above.
+
+To have a best performance/size mix, we recommend the use of either feather or parquet.
+
#### Sub-command convert data
```
usage: freqtrade convert-data [-h] [-v] [--logfile FILE] [-V] [-c PATH]
[-d PATH] [--userdir PATH]
[-p PAIRS [PAIRS ...]] --format-from
- {json,jsongz,hdf5} --format-to
- {json,jsongz,hdf5} [--erase]
- [-t {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...]]
+ {json,jsongz,hdf5,feather,parquet} --format-to
+ {json,jsongz,hdf5,feather,parquet} [--erase]
[--exchange EXCHANGE]
+ [-t TIMEFRAMES [TIMEFRAMES ...]]
[--trading-mode {spot,margin,futures}]
- [--candle-types {spot,,futures,mark,index,premiumIndex,funding_rate} [{spot,,futures,mark,index,premiumIndex,funding_rate} ...]]
+ [--candle-types {spot,futures,mark,index,premiumIndex,funding_rate} [{spot,futures,mark,index,premiumIndex,funding_rate} ...]]
optional arguments:
-h, --help show this help message and exit
-p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
Limit command to these pairs. Pairs are space-
separated.
- --format-from {json,jsongz,hdf5}
+ --format-from {json,jsongz,hdf5,feather,parquet}
Source format for data conversion.
- --format-to {json,jsongz,hdf5}
+ --format-to {json,jsongz,hdf5,feather,parquet}
Destination format for data conversion.
--erase Clean all existing data for the selected
exchange/pairs/timeframes.
- -t {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...], --timeframes {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...]
- Specify which tickers to download. Space-separated
- list. Default: `1m 5m`.
--exchange EXCHANGE Exchange name (default: `bittrex`). Only valid if no
config is provided.
- --trading-mode {spot,margin,futures}
+ -t TIMEFRAMES [TIMEFRAMES ...], --timeframes TIMEFRAMES [TIMEFRAMES ...]
+ Specify which tickers to download. Space-separated
+ list. Default: `1m 5m`.
+ --trading-mode {spot,margin,futures}, --tradingmode {spot,margin,futures}
Select Trading mode
- --candle-types {spot,,futures,mark,index,premiumIndex,funding_rate} [{spot,,futures,mark,index,premiumIndex,funding_rate} ...]
+ --candle-types {spot,futures,mark,index,premiumIndex,funding_rate} [{spot,futures,mark,index,premiumIndex,funding_rate} ...]
Select candle type to use
Common arguments:
@@ -245,7 +283,7 @@ Common arguments:
`userdir/config.json` or `config.json` whichever
exists). Multiple --config options may be used. Can be
set to `-` to read config from stdin.
- -d PATH, --datadir PATH
+ -d PATH, --datadir PATH, --data-dir PATH
Path to directory with historical backtesting data.
--userdir PATH, --user-data-dir PATH
Path to userdata directory.
@@ -267,20 +305,24 @@ freqtrade convert-data --format-from json --format-to jsongz --datadir ~/.freqtr
usage: freqtrade convert-trade-data [-h] [-v] [--logfile FILE] [-V] [-c PATH]
[-d PATH] [--userdir PATH]
[-p PAIRS [PAIRS ...]] --format-from
- {json,jsongz,hdf5} --format-to
- {json,jsongz,hdf5} [--erase]
+ {json,jsongz,hdf5,feather,parquet}
+ --format-to
+ {json,jsongz,hdf5,feather,parquet}
+ [--erase] [--exchange EXCHANGE]
optional arguments:
-h, --help show this help message and exit
-p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
- Show profits for only these pairs. Pairs are space-
+ Limit command to these pairs. Pairs are space-
separated.
- --format-from {json,jsongz,hdf5}
+ --format-from {json,jsongz,hdf5,feather,parquet}
Source format for data conversion.
- --format-to {json,jsongz,hdf5}
+ --format-to {json,jsongz,hdf5,feather,parquet}
Destination format for data conversion.
--erase Clean all existing data for the selected
exchange/pairs/timeframes.
+ --exchange EXCHANGE Exchange name (default: `bittrex`). Only valid if no
+ config is provided.
Common arguments:
-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).
@@ -293,7 +335,7 @@ Common arguments:
`userdir/config.json` or `config.json` whichever
exists). Multiple --config options may be used. Can be
set to `-` to read config from stdin.
- -d PATH, --datadir PATH
+ -d PATH, --datadir PATH, --data-dir PATH
Path to directory with historical backtesting data.
--userdir PATH, --user-data-dir PATH
Path to userdata directory.
@@ -318,9 +360,9 @@ This command will allow you to repeat this last step for additional timeframes w
usage: freqtrade trades-to-ohlcv [-h] [-v] [--logfile FILE] [-V] [-c PATH]
[-d PATH] [--userdir PATH]
[-p PAIRS [PAIRS ...]]
- [-t {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...]]
+ [-t TIMEFRAMES [TIMEFRAMES ...]]
[--exchange EXCHANGE]
- [--data-format-ohlcv {json,jsongz,hdf5}]
+ [--data-format-ohlcv {json,jsongz,hdf5,feather,parquet}]
[--data-format-trades {json,jsongz,hdf5}]
optional arguments:
@@ -328,12 +370,12 @@ optional arguments:
-p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
Limit command to these pairs. Pairs are space-
separated.
- -t {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...], --timeframes {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...]
+ -t TIMEFRAMES [TIMEFRAMES ...], --timeframes TIMEFRAMES [TIMEFRAMES ...]
Specify which tickers to download. Space-separated
list. Default: `1m 5m`.
--exchange EXCHANGE Exchange name (default: `bittrex`). Only valid if no
config is provided.
- --data-format-ohlcv {json,jsongz,hdf5}
+ --data-format-ohlcv {json,jsongz,hdf5,feather,parquet}
Storage format for downloaded candle (OHLCV) data.
(default: `json`).
--data-format-trades {json,jsongz,hdf5}
@@ -351,7 +393,7 @@ Common arguments:
`userdir/config.json` or `config.json` whichever
exists). Multiple --config options may be used. Can be
set to `-` to read config from stdin.
- -d PATH, --datadir PATH
+ -d PATH, --datadir PATH, --data-dir PATH
Path to directory with historical backtesting data.
--userdir PATH, --user-data-dir PATH
Path to userdata directory.
@@ -371,7 +413,7 @@ You can get a list of downloaded data using the `list-data` sub-command.
```
usage: freqtrade list-data [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
[--userdir PATH] [--exchange EXCHANGE]
- [--data-format-ohlcv {json,jsongz,hdf5}]
+ [--data-format-ohlcv {json,jsongz,hdf5,feather,parquet}]
[-p PAIRS [PAIRS ...]]
[--trading-mode {spot,margin,futures}]
[--show-timerange]
@@ -380,13 +422,13 @@ optional arguments:
-h, --help show this help message and exit
--exchange EXCHANGE Exchange name (default: `bittrex`). Only valid if no
config is provided.
- --data-format-ohlcv {json,jsongz,hdf5}
+ --data-format-ohlcv {json,jsongz,hdf5,feather,parquet}
Storage format for downloaded candle (OHLCV) data.
(default: `json`).
-p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
Limit command to these pairs. Pairs are space-
separated.
- --trading-mode {spot,margin,futures}
+ --trading-mode {spot,margin,futures}, --tradingmode {spot,margin,futures}
Select Trading mode
--show-timerange Show timerange available for available data. (May take
a while to calculate).
@@ -402,7 +444,7 @@ Common arguments:
`userdir/config.json` or `config.json` whichever
exists). Multiple --config options may be used. Can be
set to `-` to read config from stdin.
- -d PATH, --datadir PATH
+ -d PATH, --datadir PATH, --data-dir PATH
Path to directory with historical backtesting data.
--userdir PATH, --user-data-dir PATH
Path to userdata directory.
diff --git a/docs/exchanges.md b/docs/exchanges.md
index dc2003f9c..a9ba16c64 100644
--- a/docs/exchanges.md
+++ b/docs/exchanges.md
@@ -233,7 +233,7 @@ OKX requires a passphrase for each api key, you will therefore need to add this
!!! Warning "Futures"
OKX Futures has the concept of "position mode" - which can be Net or long/short (hedge mode).
- Freqtrade supports both modes - but changing the mode mid-trading is not supported and will lead to exceptions and failures to place trades.
+ Freqtrade supports both modes (we recommend to use net mode) - but changing the mode mid-trading is not supported and will lead to exceptions and failures to place trades.
OKX also only provides MARK candles for the past ~3 months. Backtesting futures prior to that date will therefore lead to slight deviations, as funding-fees cannot be calculated correctly without this data.
## Gate.io
diff --git a/docs/freqai.md b/docs/freqai.md
index b00c9fe98..4a61e63cd 100644
--- a/docs/freqai.md
+++ b/docs/freqai.md
@@ -109,11 +109,12 @@ Mandatory parameters are marked as **Required**, which means that they are requi
| `indicator_max_period_candles` | **No longer used**. User must use the strategy set `startup_candle_count` which defines the maximum *period* used in `populate_any_indicators()` for indicator creation (timeframe independent). FreqAI uses this information in combination with the maximum timeframe to calculate how many data points it should download so that the first data point does not have a NaN
**Datatype:** positive integer.
| `indicator_periods_candles` | Calculate indicators for `indicator_periods_candles` time periods and add them to the feature set.
**Datatype:** List of positive integers.
| `stratify_training_data` | This value is used to indicate the grouping of the data. For example, 2 would set every 2nd data point into a separate dataset to be pulled from during training/testing. See details about how it works [here](#stratifying-the-data-for-training-and-testing-the-model)
**Datatype:** Positive integer.
-| `principal_component_analysis` | Automatically reduce the dimensionality of the data set using Principal Component Analysis. See details about how it works [here](#reducing-data-dimensionality-with-principal-component-analysis)
**Datatype:** Boolean.
+| `principal_component_analysis` | Automatically reduce the dimensionality of the data set using Principal Component Analysis. See details about how it works [here](#reducing-data-dimensionality-with-principal-component-analysis)
+| `plot_feature_importance` | Create an interactive feature importance plot for each model.
**Datatype:** Boolean.
**Datatype:** Boolean, defaults to `False`
| `DI_threshold` | Activates the Dissimilarity Index for outlier detection when > 0. See details about how it works [here](#removing-outliers-with-the-dissimilarity-index).
**Datatype:** Positive float (typically < 1).
| `use_SVM_to_remove_outliers` | Train a support vector machine to detect and remove outliers from the training data set, as well as from incoming data points. See details about how it works [here](#removing-outliers-using-a-support-vector-machine-svm).
**Datatype:** Boolean.
| `svm_params` | All parameters available in Sklearn's `SGDOneClassSVM()`. See details about some select parameters [here](#removing-outliers-using-a-support-vector-machine-svm).
**Datatype:** Dictionary.
-| `use_DBSCAN_to_remove_outliers` | Cluster data using DBSCAN to identify and remove outliers from training and prediction data. See details about how it works [here](#removing-outliers-with-dbscan).
**Datatype:** Boolean.
+| `use_DBSCAN_to_remove_outliers` | Cluster data using DBSCAN to identify and remove outliers from training and prediction data. See details about how it works [here](#removing-outliers-with-dbscan).
**Datatype:** Boolean.
| `inlier_metric_window` | If set, FreqAI will add the `inlier_metric` to the training feature set and set the lookback to be the `inlier_metric_window`. Details of how the `inlier_metric` is computed can be found [here](#using-the-inliermetric)
**Datatype:** int. Default: 0
| `noise_standard_deviation` | If > 0, FreqAI adds noise to the training features. FreqAI generates random deviates from a gaussian distribution with a standard deviation of `noise_standard_deviation` and adds them to all data points. Value should be kept relative to the normalized space between -1 and 1). In other words, since data is always normalized between -1 and 1 in FreqAI, the user can expect a `noise_standard_deviation: 0.05` to see 32% of data randomly increased/decreased by more than 2.5% (i.e. the percent of data falling within the first standard deviation). Good for preventing overfitting.
**Datatype:** int. Default: 0
| `outlier_protection_percentage` | If more than `outlier_protection_percentage` % of points are detected as outliers by the SVM or DBSCAN, FreqAI will log a warning message and ignore outlier detection while keeping the original dataset intact. If the outlier protection is triggered, no predictions will be made based on the training data.
**Datatype:** Float. Default: `30`
@@ -510,7 +511,7 @@ The FreqAI backtesting module can be executed with the following command:
freqtrade backtesting --strategy FreqaiExampleStrategy --strategy-path freqtrade/templates --config config_examples/config_freqai.example.json --freqaimodel LightGBMRegressor --timerange 20210501-20210701
```
-Backtesting mode requires the user to have the data [pre-downloaded](#downloading-data-for-backtesting) (unlike in dry/live mode where FreqAI automatically downloads the necessary data). The user should be careful to consider that the time range of the downloaded data is more than the backtesting time range. This is because FreqAI needs data prior to the desired backtesting time range in order to train a model to be ready to make predictions on the first candle of the user-set backtesting time range. More details on how to calculate the data to download can be found [here](#deciding-the-sliding-training-window-and-backtesting-duration).
+Backtesting mode requires the user to have the data [pre-downloaded](#downloading-data-for-backtesting) (unlike in dry/live mode where FreqAI automatically downloads the necessary data). The user should be careful to consider that the time range of the downloaded data is more than the backtesting time range. This is because FreqAI needs data prior to the desired backtesting time range in order to train a model to be ready to make predictions on the first candle of the user-set backtesting time range. More details on how to calculate the data to download can be found [here](#deciding-the-sliding-training-window-and-backtesting-duration).
If this command has never been executed with the existing config file, it will train a new model
for each pair, for each backtesting window within the expanded `--timerange`.
@@ -538,7 +539,7 @@ Users need to have the data pre-downloaded in the same fashion as if they were d
- It's not possible to hyperopt indicators in `populate_any_indicators()` function. This means that the user cannot optimize model parameters using hyperopt. Apart from this exception, it is possible to optimize all other [spaces](hyperopt.md#running-hyperopt-with-smaller-search-space).
- The [Backtesting](#backtesting) instructions also apply to Hyperopt.
-The best method for combining hyperopt and FreqAI is to focus on hyperopting entry/exit thresholds/criteria. Users need to focus on hyperopting parameters that are not used in their FreqAI features. For example, users should not try to hyperopt rolling window lengths in their feature creation, or any of their FreqAI config which changes predictions. In order to efficiently hyperopt the FreqAI strategy, FreqAI stores predictions as dataframes and reuses them. Hence the requirement to hyperopt entry/exit thresholds/criteria only.
+The best method for combining hyperopt and FreqAI is to focus on hyperopting entry/exit thresholds/criteria. Users need to focus on hyperopting parameters that are not used in their FreqAI features. For example, users should not try to hyperopt rolling window lengths in their feature creation, or any of their FreqAI config which changes predictions. In order to efficiently hyperopt the FreqAI strategy, FreqAI stores predictions as dataframes and reuses them. Hence the requirement to hyperopt entry/exit thresholds/criteria only.
A good example of a hyperoptable parameter in FreqAI is a value for `DI_values` beyond which we consider outliers and below which we consider inliers:
@@ -563,7 +564,7 @@ FreqAI will train have trained 8 separate models at the end of `--timerange` (be
Although fractional `backtest_period_days` is allowed, the user should be aware that the `--timerange` is divided by this value to determine the number of models that FreqAI will need to train in order to backtest the full range. For example, if the user wants to set a `--timerange` of 10 days, and asks for a `backtest_period_days` of 0.1, FreqAI will need to train 100 models per pair to complete the full backtest. Because of this, a true backtest of FreqAI adaptive training would take a *very* long time. The best way to fully test a model is to run it dry and let it constantly train. In this case, backtesting would take the exact same amount of time as a dry run.
### Downloading data for backtesting
-Live/dry instances will download the data automatically for the user, but users who wish to use backtesting functionality still need to download the necessary data using `download-data` (details [here](data-download.md#data-downloading)). FreqAI users need to pay careful attention to understanding how much *additional* data needs to be downloaded to ensure that they have a sufficient amount of training data *before* the start of their backtesting timerange. The amount of additional data can be roughly estimated by moving the start date of the timerange backwards by `train_period_days` and the `startup_candle_count` ([details](#setting-the-startupcandlecount)) from the beginning of the desired backtesting timerange.
+Live/dry instances will download the data automatically for the user, but users who wish to use backtesting functionality still need to download the necessary data using `download-data` (details [here](data-download.md#data-downloading)). FreqAI users need to pay careful attention to understanding how much *additional* data needs to be downloaded to ensure that they have a sufficient amount of training data *before* the start of their backtesting timerange. The amount of additional data can be roughly estimated by moving the start date of the timerange backwards by `train_period_days` and the `startup_candle_count` ([details](#setting-the-startupcandlecount)) from the beginning of the desired backtesting timerange.
As an example, if we wish to backtest the `--timerange` above of `20210501-20210701`, and we use the example config which sets `train_period_days` to 15. The startup candle count is 40 on a maximum `include_timeframes` of 1h. We would need 20210501 - 15 days - 40 * 1h / 24 hours = 20210414 (16.7 days earlier than the start of the desired training timerange).
@@ -662,13 +663,13 @@ The test data is used to evaluate the performance of the model after training. I
### Using the `inlier_metric`
-The `inlier_metric` is a metric aimed at quantifying how different a prediction data point is from the most recent historic data points.
+The `inlier_metric` is a metric aimed at quantifying how different a prediction data point is from the most recent historic data points.
-User can set `inlier_metric_window` to set the look back window. FreqAI will compute the distance between the present prediction point and each of the previous data points (total of `inlier_metric_window` points).
+User can set `inlier_metric_window` to set the look back window. FreqAI will compute the distance between the present prediction point and each of the previous data points (total of `inlier_metric_window` points).
-This function goes one step further - during training, it computes the `inlier_metric` for all training data points and builds weibull distributions for each each lookback point. The cumulative distribution function for the weibull distribution is used to produce a quantile for each of the data points. The quantiles for each lookback point are averaged to create the `inlier_metric`.
+This function goes one step further - during training, it computes the `inlier_metric` for all training data points and builds weibull distributions for each each lookback point. The cumulative distribution function for the weibull distribution is used to produce a quantile for each of the data points. The quantiles for each lookback point are averaged to create the `inlier_metric`.
-FreqAI adds this `inlier_metric` score to the training features! In other words, your model is trained to recognize how this temporal inlier metric is related to the user set labels.
+FreqAI adds this `inlier_metric` score to the training features! In other words, your model is trained to recognize how this temporal inlier metric is related to the user set labels.
This function does **not** remove outliers from the data set.
diff --git a/docs/producer-consumer.md b/docs/producer-consumer.md
new file mode 100644
index 000000000..b69406edf
--- /dev/null
+++ b/docs/producer-consumer.md
@@ -0,0 +1,163 @@
+# Producer / Consumer mode
+
+freqtrade provides a mechanism whereby an instance (also called `consumer`) may listen to messages from an upstream freqtrade instance (also called `producer`) using the message websocket. Mainly, `analyzed_df` and `whitelist` messages. This allows the reuse of computed indicators (and signals) for pairs in multiple bots without needing to compute them multiple times.
+
+See [Message Websocket](rest-api.md#message-websocket) in the Rest API docs for setting up the `api_server` configuration for your message websocket (this will be your producer).
+
+!!! Note
+ We strongly recommend to set `ws_token` to something random and known only to yourself to avoid unauthorized access to your bot.
+
+## Configuration
+
+Enable subscribing to an instance by adding the `external_message_consumer` section to the consumer's config file.
+
+```json
+{
+ //...
+ "external_message_consumer": {
+ "enabled": true,
+ "producers": [
+ {
+ "name": "default", // This can be any name you'd like, default is "default"
+ "host": "127.0.0.1", // The host from your producer's api_server config
+ "port": 8080, // The port from your producer's api_server config
+ "ws_token": "sercet_Ws_t0ken" // The ws_token from your producer's api_server config
+ }
+ ],
+ // The following configurations are optional, and usually not required
+ // "wait_timeout": 300,
+ // "ping_timeout": 10,
+ // "sleep_time": 10,
+ // "remove_entry_exit_signals": false,
+ // "message_size_limit": 8
+ }
+ //...
+}
+```
+
+| Parameter | Description |
+|------------|-------------|
+| `enabled` | **Required.** Enable consumer mode. If set to false, all other settings in this section are ignored.
*Defaults to `false`.*
**Datatype:** boolean .
+| `producers` | **Required.** List of producers
**Datatype:** Array.
+| `producers.name` | **Required.** Name of this producer. This name must be used in calls to `get_producer_pairs()` and `get_producer_df()` if more than one producer is used.
**Datatype:** string
+| `producers.host` | **Required.** The hostname or IP address from your producer.
**Datatype:** string
+| `producers.port` | **Required.** The port matching the above host.
**Datatype:** string
+| `producers.ws_token` | **Required.** `ws_token` as configured on the producer.
**Datatype:** string
+| | **Optional settings**
+| `wait_timeout` | Timeout until we ping again if no message is received.
*Defaults to `300`.*
**Datatype:** Integer - in seconds.
+| `wait_timeout` | Ping timeout
*Defaults to `10`.*
**Datatype:** Integer - in seconds.
+| `sleep_time` | Sleep time before retrying to connect.
*Defaults to `10`.*
**Datatype:** Integer - in seconds.
+| `remove_entry_exit_signals` | Remove signal columns from the dataframe (set them to 0) on dataframe receipt.
*Defaults to `10`.*
**Datatype:** Integer - in seconds.
+| `message_size_limit` | Size limit per message
*Defaults to `8`.*
**Datatype:** Integer - Megabytes.
+
+Instead of (or as well as) calculating indicators in `populate_indicators()` the follower instance listens on the connection to a producer instance's messages (or multiple producer instances in advanced configurations) and requests the producer's most recently analyzed dataframes for each pair in the active whitelist.
+
+A consumer instance will then have a full copy of the analyzed dataframes without the need to calculate them itself.
+
+## Examples
+
+### Example - Producer Strategy
+
+A simple strategy with multiple indicators. No special considerations are required in the strategy itself.
+
+```py
+class ProducerStrategy(IStrategy):
+ #...
+ def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+ """
+ Calculate indicators in the standard freqtrade way which can then be broadcast to other instances
+ """
+ dataframe['rsi'] = ta.RSI(dataframe)
+ bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
+ dataframe['bb_lowerband'] = bollinger['lower']
+ dataframe['bb_middleband'] = bollinger['mid']
+ dataframe['bb_upperband'] = bollinger['upper']
+ dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
+
+ return dataframe
+
+ def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+ """
+ Populates the entry signal for the given dataframe
+ """
+ dataframe.loc[
+ (
+ (qtpylib.crossed_above(dataframe['rsi'], self.buy_rsi.value)) &
+ (dataframe['tema'] <= dataframe['bb_middleband']) &
+ (dataframe['tema'] > dataframe['tema'].shift(1)) &
+ (dataframe['volume'] > 0)
+ ),
+ 'enter_long'] = 1
+
+ return dataframe
+```
+
+!!! Tip "FreqAI"
+ You can use this to setup [FreqAI](freqai.md) on a powerful machine, while you run consumers on simple machines like raspberries, which can interpret the signals generated from the producer in different ways.
+
+
+### Example - Consumer Strategy
+
+A logically equivalent strategy which calculates no indicators itself, but will have the same analyzed dataframes available to make trading decisions based on the indicators calculated in the producer. In this example the consumer has the same entry criteria, however this is not necessary. The consumer may use different logic to enter/exit trades, and only use the indicators as specified.
+
+```py
+class ConsumerStrategy(IStrategy):
+ #...
+ process_only_new_candles = False # required for consumers
+
+ _columns_to_expect = ['rsi_default', 'tema_default', 'bb_middleband_default']
+
+ def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+ """
+ Use the websocket api to get pre-populated indicators from another freqtrade instance.
+ Use `self.dp.get_producer_df(pair)` to get the dataframe
+ """
+ pair = metadata['pair']
+ timeframe = self.timeframe
+
+ producer_pairs = self.dp.get_producer_pairs()
+ # You can specify which producer to get pairs from via:
+ # self.dp.get_producer_pairs("my_other_producer")
+
+ # This func returns the analyzed dataframe, and when it was analyzed
+ producer_dataframe, _ = self.dp.get_producer_df(pair)
+ # You can get other data if the producer makes it available:
+ # self.dp.get_producer_df(
+ # pair,
+ # timeframe="1h",
+ # candle_type=CandleType.SPOT,
+ # producer_name="my_other_producer"
+ # )
+
+ if not producer_dataframe.empty:
+ # If you plan on passing the producer's entry/exit signal directly,
+ # specify ffill=False or it will have unintended results
+ merged_dataframe = merge_informative_pair(dataframe, producer_dataframe,
+ timeframe, timeframe,
+ append_timeframe=False,
+ suffix="default")
+ return merged_dataframe
+ else:
+ dataframe[self._columns_to_expect] = 0
+
+ return dataframe
+
+ def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+ """
+ Populates the entry signal for the given dataframe
+ """
+ # Use the dataframe columns as if we calculated them ourselves
+ dataframe.loc[
+ (
+ (qtpylib.crossed_above(dataframe['rsi_default'], self.buy_rsi.value)) &
+ (dataframe['tema_default'] <= dataframe['bb_middleband_default']) &
+ (dataframe['tema_default'] > dataframe['tema_default'].shift(1)) &
+ (dataframe['volume'] > 0)
+ ),
+ 'enter_long'] = 1
+
+ return dataframe
+```
+
+!!! Tip "Using upstream signals"
+ By setting `remove_entry_exit_signals=false`, you can also use the producer's signals directly. They should be available as `enter_long_default` (assuming `suffix="default"` was used) - and can be used as either signal directly, or as additional indicator.
diff --git a/docs/requirements-docs.txt b/docs/requirements-docs.txt
index d63e79004..da6713b76 100644
--- a/docs/requirements-docs.txt
+++ b/docs/requirements-docs.txt
@@ -1,6 +1,6 @@
markdown==3.3.7
mkdocs==1.3.1
-mkdocs-material==8.4.3
+mkdocs-material==8.5.2
mdx_truly_sane_lists==1.3
pymdown-extensions==9.5
jinja2==3.1.2
diff --git a/docs/rest-api.md b/docs/rest-api.md
index cc82aadda..c7d762648 100644
--- a/docs/rest-api.md
+++ b/docs/rest-api.md
@@ -31,7 +31,8 @@ Sample configuration:
"jwt_secret_key": "somethingrandom",
"CORS_origins": [],
"username": "Freqtrader",
- "password": "SuperSecret1!"
+ "password": "SuperSecret1!",
+ "ws_token": "sercet_Ws_t0ken"
},
```
@@ -66,7 +67,7 @@ secrets.token_hex()
!!! Danger "Password selection"
Please make sure to select a very strong, unique password to protect your bot from unauthorized access.
- Also change `jwt_secret_key` to something random (no need to remember this, but it'll be used to encrypt your session, so it better be something unique!).
+ Also change `jwt_secret_key` to something random (no need to remember this, but it'll be used to encrypt your session, so it better be something unique!).
### Configuration with docker
@@ -93,7 +94,6 @@ Make sure that the following 2 lines are available in your docker-compose file:
!!! Danger "Security warning"
By using `8080:8080` in the docker port mapping, the API will be available to everyone connecting to the server under the correct port, so others may be able to control your bot.
-
## Rest API
### Consuming the API
@@ -274,7 +274,7 @@ reload_config
Reload configuration.
show_config
-
+
Returns part of the configuration, relevant for trading operations.
start
@@ -322,6 +322,73 @@ whitelist
```
+### Message WebSocket
+
+The API Server includes a websocket endpoint for subscribing to RPC messages from the freqtrade Bot.
+This can be used to consume real-time data from your bot, such as entry/exit fill messages, whitelist changes, populated indicators for pairs, and more.
+
+This is also used to setup [Producer/Consumer mode](producer-consumer.md) in Freqtrade.
+
+Assuming your rest API is set to `127.0.0.1` on port `8080`, the endpoint is available at `http://localhost:8080/api/v1/message/ws`.
+
+To access the websocket endpoint, the `ws_token` is required as a query parameter in the endpoint URL.
+
+To generate a safe `ws_token` you can run the following code:
+
+``` python
+>>> import secrets
+>>> secrets.token_urlsafe(25)
+'hZ-y58LXyX_HZ8O1cJzVyN6ePWrLpNQv4Q'
+```
+
+You would then add that token under `ws_token` in your `api_server` config. Like so:
+
+``` json
+"api_server": {
+ "enabled": true,
+ "listen_ip_address": "127.0.0.1",
+ "listen_port": 8080,
+ "verbosity": "error",
+ "enable_openapi": false,
+ "jwt_secret_key": "somethingrandom",
+ "CORS_origins": [],
+ "username": "Freqtrader",
+ "password": "SuperSecret1!",
+ "ws_token": "hZ-y58LXyX_HZ8O1cJzVyN6ePWrLpNQv4Q" // <-----
+},
+```
+
+You can now connect to the endpoint at `http://localhost:8080/api/v1/message/ws?token=hZ-y58LXyX_HZ8O1cJzVyN6ePWrLpNQv4Q`.
+
+!!! Danger "Reuse of example tokens"
+ Please do not use the above example token. To make sure you are secure, generate a completely new token.
+
+#### Using the WebSocket
+
+Once connected to the WebSocket, the bot will broadcast RPC messages to anyone who is subscribed to them. To subscribe to a list of messages, you must send a JSON request through the WebSocket like the one below. The `data` key must be a list of message type strings.
+
+``` json
+{
+ "type": "subscribe",
+ "data": ["whitelist", "analyzed_df"] // A list of string message types
+}
+```
+
+For a list of message types, please refer to the RPCMessageType enum in `freqtrade/enums/rpcmessagetype.py`
+
+Now anytime those types of RPC messages are sent in the bot, you will receive them through the WebSocket as long as the connection is active. They typically take the same form as the request:
+
+``` json
+{
+ "type": "analyzed_df",
+ "data": {
+ "key": ["NEO/BTC", "5m", "spot"],
+ "df": {}, // The dataframe
+ "la": "2022-09-08 22:14:41.457786+00:00"
+ }
+}
+```
+
### OpenAPI interface
To enable the builtin openAPI interface (Swagger UI), specify `"enable_openapi": true` in the api_server configuration.
diff --git a/docs/strategy-advanced.md b/docs/strategy-advanced.md
index a3115bfb2..f55cda5e2 100644
--- a/docs/strategy-advanced.md
+++ b/docs/strategy-advanced.md
@@ -106,6 +106,12 @@ def custom_exit(self, pair: str, trade: Trade, current_time: datetime, current_r
!!! Note
`enter_tag` is limited to 100 characters, remaining data will be truncated.
+!!! Warning
+ There is only one `enter_tag` column, which is used for both long and short trades.
+ As a consequence, this column must be treated as "last write wins" (it's just a dataframe column after all).
+ In fancy situations, where multiple signals collide (or if signals are deactivated again based on different conditions), this can lead to odd results with the wrong tag applied to an entry signal.
+ These results are a consequence of the strategy overwriting prior tags - where the last tag will "stick" and will be the one freqtrade will use.
+
## Exit tag
Similar to [Buy Tagging](#buy-tag), you can also specify a sell tag.
diff --git a/docs/telegram-usage.md b/docs/telegram-usage.md
index b9324def4..055512f26 100644
--- a/docs/telegram-usage.md
+++ b/docs/telegram-usage.md
@@ -82,6 +82,8 @@ Example configuration showing the different settings:
"warning": "on",
"startup": "off",
"entry": "silent",
+ "entry_fill": "on",
+ "entry_cancel": "silent",
"exit": {
"roi": "silent",
"emergency_exit": "on",
@@ -93,9 +95,7 @@ Example configuration showing the different settings:
"custom_exit": "silent",
"partial_exit": "on"
},
- "entry_cancel": "silent",
"exit_cancel": "on",
- "entry_fill": "off",
"exit_fill": "off",
"protection_trigger": "off",
"protection_trigger_global": "on",
diff --git a/environment.yml b/environment.yml
index d6d85de9d..5298b2baa 100644
--- a/environment.yml
+++ b/environment.yml
@@ -34,6 +34,7 @@ dependencies:
- schedule
- python-dateutil
- joblib
+ - pyarrow
# ============================
diff --git a/freqtrade/commands/arguments.py b/freqtrade/commands/arguments.py
index 2835f8582..97d8cc130 100644
--- a/freqtrade/commands/arguments.py
+++ b/freqtrade/commands/arguments.py
@@ -62,9 +62,9 @@ ARGS_BUILD_CONFIG = ["config"]
ARGS_BUILD_STRATEGY = ["user_data_dir", "strategy", "template"]
-ARGS_CONVERT_DATA = ["pairs", "format_from", "format_to", "erase"]
+ARGS_CONVERT_DATA = ["pairs", "format_from", "format_to", "erase", "exchange"]
-ARGS_CONVERT_DATA_OHLCV = ARGS_CONVERT_DATA + ["timeframes", "exchange", "trading_mode",
+ARGS_CONVERT_DATA_OHLCV = ARGS_CONVERT_DATA + ["timeframes", "trading_mode",
"candle_types"]
ARGS_CONVERT_TRADES = ["pairs", "timeframes", "exchange", "dataformat_ohlcv", "dataformat_trades"]
diff --git a/freqtrade/commands/build_config_commands.py b/freqtrade/commands/build_config_commands.py
index 01cfa800a..1abd26328 100644
--- a/freqtrade/commands/build_config_commands.py
+++ b/freqtrade/commands/build_config_commands.py
@@ -211,6 +211,7 @@ def ask_user_config() -> Dict[str, Any]:
)
# Force JWT token to be a random string
answers['api_server_jwt_key'] = secrets.token_hex()
+ answers['api_server_ws_token'] = secrets.token_urlsafe(25)
return answers
diff --git a/freqtrade/commands/cli_options.py b/freqtrade/commands/cli_options.py
index 9aacbcc97..e50fb86d8 100644
--- a/freqtrade/commands/cli_options.py
+++ b/freqtrade/commands/cli_options.py
@@ -69,7 +69,7 @@ AVAILABLE_CLI_OPTIONS = {
metavar='PATH',
),
"datadir": Arg(
- '-d', '--datadir',
+ '-d', '--datadir', '--data-dir',
help='Path to directory with historical backtesting data.',
metavar='PATH',
),
@@ -440,7 +440,7 @@ AVAILABLE_CLI_OPTIONS = {
"dataformat_trades": Arg(
'--data-format-trades',
help='Storage format for downloaded trades data. (default: `jsongz`).',
- choices=constants.AVAILABLE_DATAHANDLERS,
+ choices=constants.AVAILABLE_DATAHANDLERS_TRADES,
),
"show_timerange": Arg(
'--show-timerange',
diff --git a/freqtrade/commands/deploy_commands.py b/freqtrade/commands/deploy_commands.py
index 92c9adf66..9ec33eac4 100644
--- a/freqtrade/commands/deploy_commands.py
+++ b/freqtrade/commands/deploy_commands.py
@@ -36,24 +36,24 @@ def deploy_new_strategy(strategy_name: str, strategy_path: Path, subtemplate: st
"""
fallback = 'full'
indicators = render_template_with_fallback(
- templatefile=f"subtemplates/indicators_{subtemplate}.j2",
- templatefallbackfile=f"subtemplates/indicators_{fallback}.j2",
+ templatefile=f"strategy_subtemplates/indicators_{subtemplate}.j2",
+ templatefallbackfile=f"strategy_subtemplates/indicators_{fallback}.j2",
)
buy_trend = render_template_with_fallback(
- templatefile=f"subtemplates/buy_trend_{subtemplate}.j2",
- templatefallbackfile=f"subtemplates/buy_trend_{fallback}.j2",
+ templatefile=f"strategy_subtemplates/buy_trend_{subtemplate}.j2",
+ templatefallbackfile=f"strategy_subtemplates/buy_trend_{fallback}.j2",
)
sell_trend = render_template_with_fallback(
- templatefile=f"subtemplates/sell_trend_{subtemplate}.j2",
- templatefallbackfile=f"subtemplates/sell_trend_{fallback}.j2",
+ templatefile=f"strategy_subtemplates/sell_trend_{subtemplate}.j2",
+ templatefallbackfile=f"strategy_subtemplates/sell_trend_{fallback}.j2",
)
plot_config = render_template_with_fallback(
- templatefile=f"subtemplates/plot_config_{subtemplate}.j2",
- templatefallbackfile=f"subtemplates/plot_config_{fallback}.j2",
+ templatefile=f"strategy_subtemplates/plot_config_{subtemplate}.j2",
+ templatefallbackfile=f"strategy_subtemplates/plot_config_{fallback}.j2",
)
additional_methods = render_template_with_fallback(
- templatefile=f"subtemplates/strategy_methods_{subtemplate}.j2",
- templatefallbackfile="subtemplates/strategy_methods_empty.j2",
+ templatefile=f"strategy_subtemplates/strategy_methods_{subtemplate}.j2",
+ templatefallbackfile="strategy_subtemplates/strategy_methods_empty.j2",
)
strategy_text = render_template(templatefile='base_strategy.py.j2',
diff --git a/freqtrade/configuration/check_exchange.py b/freqtrade/configuration/check_exchange.py
index 2be13ce4f..c3d859275 100644
--- a/freqtrade/configuration/check_exchange.py
+++ b/freqtrade/configuration/check_exchange.py
@@ -1,6 +1,6 @@
import logging
-from typing import Any, Dict
+from freqtrade.constants import Config
from freqtrade.enums import RunMode
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import (available_exchanges, is_exchange_known_ccxt,
@@ -10,7 +10,7 @@ from freqtrade.exchange import (available_exchanges, is_exchange_known_ccxt,
logger = logging.getLogger(__name__)
-def check_exchange(config: Dict[str, Any], check_for_bad: bool = True) -> bool:
+def check_exchange(config: Config, check_for_bad: bool = True) -> bool:
"""
Check if the exchange name in the config file is supported by Freqtrade
:param check_for_bad: if True, check the exchange against the list of known 'bad'
diff --git a/freqtrade/configuration/config_validation.py b/freqtrade/configuration/config_validation.py
index 8d9112bef..7055d9551 100644
--- a/freqtrade/configuration/config_validation.py
+++ b/freqtrade/configuration/config_validation.py
@@ -1,4 +1,5 @@
import logging
+from collections import Counter
from copy import deepcopy
from typing import Any, Dict
@@ -85,6 +86,7 @@ def validate_config_consistency(conf: Dict[str, Any], preliminary: bool = False)
_validate_unlimited_amount(conf)
_validate_ask_orderbook(conf)
_validate_freqai_hyperopt(conf)
+ _validate_consumers(conf)
validate_migrated_strategy_settings(conf)
# validate configuration before returning
@@ -332,6 +334,23 @@ def _validate_freqai_hyperopt(conf: Dict[str, Any]) -> None:
'Using analyze-per-epoch parameter is not supported with a FreqAI strategy.')
+def _validate_consumers(conf: Dict[str, Any]) -> None:
+ emc_conf = conf.get('external_message_consumer', {})
+ if emc_conf.get('enabled', False):
+ if len(emc_conf.get('producers', [])) < 1:
+ raise OperationalException("You must specify at least 1 Producer to connect to.")
+
+ producer_names = [p['name'] for p in emc_conf.get('producers', [])]
+ duplicates = [item for item, count in Counter(producer_names).items() if count > 1]
+ if duplicates:
+ raise OperationalException(
+ f"Producer names must be unique. Duplicate: {', '.join(duplicates)}")
+ if conf.get('process_only_new_candles', True):
+ # Warning here or require it?
+ logger.warning("To receive best performance with external data, "
+ "please set `process_only_new_candles` to False")
+
+
def _strategy_settings(conf: Dict[str, Any]) -> None:
process_deprecated_setting(conf, None, 'use_sell_signal', None, 'use_exit_signal')
diff --git a/freqtrade/configuration/configuration.py b/freqtrade/configuration/configuration.py
index 7c68ac46c..76105cc4d 100644
--- a/freqtrade/configuration/configuration.py
+++ b/freqtrade/configuration/configuration.py
@@ -13,6 +13,7 @@ from freqtrade.configuration.deprecated_settings import process_temporary_deprec
from freqtrade.configuration.directory_operations import create_datadir, create_userdata_dir
from freqtrade.configuration.environment_vars import enironment_vars_to_dict
from freqtrade.configuration.load_config import load_file, load_from_files
+from freqtrade.constants import Config
from freqtrade.enums import NON_UTIL_MODES, TRADING_MODES, CandleType, RunMode, TradingMode
from freqtrade.exceptions import OperationalException
from freqtrade.loggers import setup_logging
@@ -30,10 +31,10 @@ class Configuration:
def __init__(self, args: Dict[str, Any], runmode: RunMode = None) -> None:
self.args = args
- self.config: Optional[Dict[str, Any]] = None
+ self.config: Optional[Config] = None
self.runmode = runmode
- def get_config(self) -> Dict[str, Any]:
+ def get_config(self) -> Config:
"""
Return the config. Use this method to get the bot config
:return: Dict: Bot config
@@ -65,7 +66,7 @@ class Configuration:
:return: Configuration dictionary
"""
# Load all configs
- config: Dict[str, Any] = load_from_files(self.args.get("config", []))
+ config: Config = load_from_files(self.args.get("config", []))
# Load environment variables
env_data = enironment_vars_to_dict()
@@ -108,7 +109,7 @@ class Configuration:
return config
- def _process_logging_options(self, config: Dict[str, Any]) -> None:
+ def _process_logging_options(self, config: Config) -> None:
"""
Extract information for sys.argv and load logging configuration:
the -v/--verbose, --logfile options
@@ -121,7 +122,7 @@ class Configuration:
setup_logging(config)
- def _process_trading_options(self, config: Dict[str, Any]) -> None:
+ def _process_trading_options(self, config: Config) -> None:
if config['runmode'] not in TRADING_MODES:
return
@@ -137,7 +138,7 @@ class Configuration:
logger.info(f'Using DB: "{parse_db_uri_for_logging(config["db_url"])}"')
- def _process_common_options(self, config: Dict[str, Any]) -> None:
+ def _process_common_options(self, config: Config) -> None:
# Set strategy if not specified in config and or if it's non default
if self.args.get('strategy') or not config.get('strategy'):
@@ -161,7 +162,7 @@ class Configuration:
if 'sd_notify' in self.args and self.args['sd_notify']:
config['internals'].update({'sd_notify': True})
- def _process_datadir_options(self, config: Dict[str, Any]) -> None:
+ def _process_datadir_options(self, config: Config) -> None:
"""
Extract information for sys.argv and load directory configurations
--user-data, --datadir
@@ -195,7 +196,7 @@ class Configuration:
config['exportfilename'] = (config['user_data_dir']
/ 'backtest_results')
- def _process_optimize_options(self, config: Dict[str, Any]) -> None:
+ def _process_optimize_options(self, config: Config) -> None:
# This will override the strategy configuration
self._args_to_config(config, argname='timeframe',
@@ -380,7 +381,7 @@ class Configuration:
self._args_to_config(config, argname="hyperopt_ignore_missing_space",
logstring="Paramter --ignore-missing-space detected: {}")
- def _process_plot_options(self, config: Dict[str, Any]) -> None:
+ def _process_plot_options(self, config: Config) -> None:
self._args_to_config(config, argname='pairs',
logstring='Using pairs {}')
@@ -432,7 +433,7 @@ class Configuration:
self._args_to_config(config, argname='show_timerange',
logstring='Detected --show-timerange')
- def _process_data_options(self, config: Dict[str, Any]) -> None:
+ def _process_data_options(self, config: Config) -> None:
self._args_to_config(config, argname='new_pairs_days',
logstring='Detected --new-pairs-days: {}')
self._args_to_config(config, argname='trading_mode',
@@ -443,7 +444,7 @@ class Configuration:
self._args_to_config(config, argname='candle_types',
logstring='Detected --candle-types: {}')
- def _process_analyze_options(self, config: Dict[str, Any]) -> None:
+ def _process_analyze_options(self, config: Config) -> None:
self._args_to_config(config, argname='analysis_groups',
logstring='Analysis reason groups: {}')
@@ -456,7 +457,7 @@ class Configuration:
self._args_to_config(config, argname='indicator_list',
logstring='Analysis indicator list: {}')
- def _process_runmode(self, config: Dict[str, Any]) -> None:
+ def _process_runmode(self, config: Config) -> None:
self._args_to_config(config, argname='dry_run',
logstring='Parameter --dry-run detected, '
@@ -469,7 +470,7 @@ class Configuration:
config.update({'runmode': self.runmode})
- def _process_freqai_options(self, config: Dict[str, Any]) -> None:
+ def _process_freqai_options(self, config: Config) -> None:
self._args_to_config(config, argname='freqaimodel',
logstring='Using freqaimodel class name: {}')
@@ -479,7 +480,7 @@ class Configuration:
return
- def _args_to_config(self, config: Dict[str, Any], argname: str,
+ def _args_to_config(self, config: Config, argname: str,
logstring: str, logfun: Optional[Callable] = None,
deprecated_msg: Optional[str] = None) -> None:
"""
@@ -502,7 +503,7 @@ class Configuration:
if deprecated_msg:
warnings.warn(f"DEPRECATED: {deprecated_msg}", DeprecationWarning)
- def _resolve_pairs_list(self, config: Dict[str, Any]) -> None:
+ def _resolve_pairs_list(self, config: Config) -> None:
"""
Helper for download script.
Takes first found:
diff --git a/freqtrade/configuration/deprecated_settings.py b/freqtrade/configuration/deprecated_settings.py
index e88383785..46c19a5b2 100644
--- a/freqtrade/configuration/deprecated_settings.py
+++ b/freqtrade/configuration/deprecated_settings.py
@@ -3,15 +3,16 @@ Functions to handle deprecated settings
"""
import logging
-from typing import Any, Dict, Optional
+from typing import Optional
+from freqtrade.constants import Config
from freqtrade.exceptions import OperationalException
logger = logging.getLogger(__name__)
-def check_conflicting_settings(config: Dict[str, Any],
+def check_conflicting_settings(config: Config,
section_old: Optional[str], name_old: str,
section_new: Optional[str], name_new: str) -> None:
section_new_config = config.get(section_new, {}) if section_new else config
@@ -28,7 +29,7 @@ def check_conflicting_settings(config: Dict[str, Any],
)
-def process_removed_setting(config: Dict[str, Any],
+def process_removed_setting(config: Config,
section1: str, name1: str,
section2: Optional[str], name2: str) -> None:
"""
@@ -47,7 +48,7 @@ def process_removed_setting(config: Dict[str, Any],
)
-def process_deprecated_setting(config: Dict[str, Any],
+def process_deprecated_setting(config: Config,
section_old: Optional[str], name_old: str,
section_new: Optional[str], name_new: str
) -> None:
@@ -69,7 +70,7 @@ def process_deprecated_setting(config: Dict[str, Any],
del section_old_config[name_old]
-def process_temporary_deprecated_settings(config: Dict[str, Any]) -> None:
+def process_temporary_deprecated_settings(config: Config) -> None:
# Kept for future deprecated / moved settings
# check_conflicting_settings(config, 'ask_strategy', 'use_sell_signal',
diff --git a/freqtrade/configuration/directory_operations.py b/freqtrade/configuration/directory_operations.py
index 771fd53cc..f70310ee1 100644
--- a/freqtrade/configuration/directory_operations.py
+++ b/freqtrade/configuration/directory_operations.py
@@ -1,16 +1,16 @@
import logging
import shutil
from pathlib import Path
-from typing import Any, Dict, Optional
+from typing import Optional
-from freqtrade.constants import USER_DATA_FILES
+from freqtrade.constants import USER_DATA_FILES, Config
from freqtrade.exceptions import OperationalException
logger = logging.getLogger(__name__)
-def create_datadir(config: Dict[str, Any], datadir: Optional[str] = None) -> Path:
+def create_datadir(config: Config, datadir: Optional[str] = None) -> Path:
folder = Path(datadir) if datadir else Path(f"{config['user_data_dir']}/data")
if not datadir:
diff --git a/freqtrade/configuration/load_config.py b/freqtrade/configuration/load_config.py
index 3fcbd1f2f..6d0321ba0 100644
--- a/freqtrade/configuration/load_config.py
+++ b/freqtrade/configuration/load_config.py
@@ -10,7 +10,7 @@ from typing import Any, Dict, List
import rapidjson
-from freqtrade.constants import MINIMAL_CONFIG
+from freqtrade.constants import MINIMAL_CONFIG, Config
from freqtrade.exceptions import OperationalException
from freqtrade.misc import deep_merge_dicts
@@ -80,7 +80,7 @@ def load_from_files(files: List[str], base_path: Path = None, level: int = 0) ->
Recursively load configuration files if specified.
Sub-files are assumed to be relative to the initial config.
"""
- config: Dict[str, Any] = {}
+ config: Config = {}
if level > 5:
raise OperationalException("Config loop detected.")
diff --git a/freqtrade/constants.py b/freqtrade/constants.py
index bab8c4816..4c2bd6e18 100644
--- a/freqtrade/constants.py
+++ b/freqtrade/constants.py
@@ -3,7 +3,7 @@
"""
bot constants
"""
-from typing import List, Literal, Tuple
+from typing import Any, Dict, List, Literal, Tuple
from freqtrade.enums import CandleType
@@ -36,7 +36,8 @@ AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList',
'PrecisionFilter', 'PriceFilter', 'RangeStabilityFilter',
'ShuffleFilter', 'SpreadFilter', 'VolatilityFilter']
AVAILABLE_PROTECTIONS = ['CooldownPeriod', 'LowProfitPairs', 'MaxDrawdown', 'StoplossGuard']
-AVAILABLE_DATAHANDLERS = ['json', 'jsongz', 'hdf5']
+AVAILABLE_DATAHANDLERS_TRADES = ['json', 'jsongz', 'hdf5']
+AVAILABLE_DATAHANDLERS = AVAILABLE_DATAHANDLERS_TRADES + ['feather', 'parquet']
BACKTEST_BREAKDOWNS = ['day', 'week', 'month']
BACKTEST_CACHE_AGE = ['none', 'day', 'week', 'month']
BACKTEST_CACHE_DEFAULT = 'day'
@@ -243,6 +244,7 @@ CONF_SCHEMA = {
'exchange': {'$ref': '#/definitions/exchange'},
'edge': {'$ref': '#/definitions/edge'},
'freqai': {'$ref': '#/definitions/freqai'},
+ 'external_message_consumer': {'$ref': '#/definitions/external_message_consumer'},
'experimental': {
'type': 'object',
'properties': {
@@ -289,11 +291,12 @@ CONF_SCHEMA = {
'warning': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
'startup': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
'entry': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
- 'entry_cancel': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
- 'entry_fill': {'type': 'string',
- 'enum': TELEGRAM_SETTING_OPTIONS,
- 'default': 'off'
- },
+ 'entry_fill': {
+ 'type': 'string',
+ 'enum': TELEGRAM_SETTING_OPTIONS,
+ 'default': 'off'
+ },
+ 'entry_cancel': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS, },
'exit': {
'type': ['string', 'object'],
'additionalProperties': {
@@ -301,12 +304,12 @@ CONF_SCHEMA = {
'enum': TELEGRAM_SETTING_OPTIONS
}
},
- 'exit_cancel': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
'exit_fill': {
'type': 'string',
'enum': TELEGRAM_SETTING_OPTIONS,
'default': 'on'
},
+ 'exit_cancel': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
'protection_trigger': {
'type': 'string',
'enum': TELEGRAM_SETTING_OPTIONS,
@@ -315,14 +318,17 @@ CONF_SCHEMA = {
'protection_trigger_global': {
'type': 'string',
'enum': TELEGRAM_SETTING_OPTIONS,
+ 'default': 'on'
},
'show_candle': {
'type': 'string',
'enum': ['off', 'ohlc'],
+ 'default': 'off'
},
'strategy_msg': {
'type': 'string',
'enum': TELEGRAM_SETTING_OPTIONS,
+ 'default': 'on'
},
}
},
@@ -400,6 +406,7 @@ CONF_SCHEMA = {
},
'username': {'type': 'string'},
'password': {'type': 'string'},
+ 'ws_token': {'type': ['string', 'array'], 'items': {'type': 'string'}},
'jwt_secret_key': {'type': 'string'},
'CORS_origins': {'type': 'array', 'items': {'type': 'string'}},
'verbosity': {'type': 'string', 'enum': ['error', 'info']},
@@ -428,7 +435,7 @@ CONF_SCHEMA = {
},
'dataformat_trades': {
'type': 'string',
- 'enum': AVAILABLE_DATAHANDLERS,
+ 'enum': AVAILABLE_DATAHANDLERS_TRADES,
'default': 'jsongz'
},
'position_adjustment_enable': {'type': 'boolean'},
@@ -484,6 +491,47 @@ CONF_SCHEMA = {
},
'required': ['process_throttle_secs', 'allowed_risk']
},
+ 'external_message_consumer': {
+ 'type': 'object',
+ 'properties': {
+ 'enabled': {'type': 'boolean', 'default': False},
+ 'producers': {
+ 'type': 'array',
+ 'items': {
+ 'type': 'object',
+ 'properties': {
+ 'name': {'type': 'string'},
+ 'host': {'type': 'string'},
+ 'port': {
+ 'type': 'integer',
+ 'default': 8080,
+ 'minimum': 0,
+ 'maximum': 65535
+ },
+ 'ws_token': {'type': 'string'},
+ },
+ 'required': ['name', 'host', 'ws_token']
+ }
+ },
+ 'wait_timeout': {'type': 'integer', 'minimum': 0},
+ 'sleep_time': {'type': 'integer', 'minimum': 0},
+ 'ping_timeout': {'type': 'integer', 'minimum': 0},
+ 'remove_entry_exit_signals': {'type': 'boolean', 'default': False},
+ 'initial_candle_limit': {
+ 'type': 'integer',
+ 'minimum': 0,
+ 'maximum': 1500,
+ 'default': 1500
+ },
+ 'message_size_limit': { # In megabytes
+ 'type': 'integer',
+ 'minimum': 1,
+ 'maxmium': 20,
+ 'default': 8,
+ }
+ },
+ 'required': ['producers']
+ },
"freqai": {
"type": "object",
"properties": {
@@ -504,6 +552,7 @@ CONF_SCHEMA = {
"weight_factor": {"type": "number", "default": 0},
"principal_component_analysis": {"type": "boolean", "default": False},
"use_SVM_to_remove_outliers": {"type": "boolean", "default": False},
+ "plot_feature_importance": {"type": "boolean", "default": False},
"svm_params": {"type": "object",
"properties": {
"shuffle": {"type": "boolean", "default": False},
@@ -603,3 +652,5 @@ LongShort = Literal['long', 'short']
EntryExit = Literal['entry', 'exit']
BuySell = Literal['buy', 'sell']
MakerTaker = Literal['maker', 'taker']
+
+Config = Dict[str, Any]
diff --git a/freqtrade/data/converter.py b/freqtrade/data/converter.py
index 84c57be41..67461973f 100644
--- a/freqtrade/data/converter.py
+++ b/freqtrade/data/converter.py
@@ -5,12 +5,12 @@ import itertools
import logging
from datetime import datetime, timezone
from operator import itemgetter
-from typing import Any, Dict, List
+from typing import Dict, List
import pandas as pd
from pandas import DataFrame, to_datetime
-from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, DEFAULT_TRADES_COLUMNS, TradeList
+from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, DEFAULT_TRADES_COLUMNS, Config, TradeList
from freqtrade.enums import CandleType
@@ -237,7 +237,7 @@ def trades_to_ohlcv(trades: TradeList, timeframe: str) -> DataFrame:
return df_new.loc[:, DEFAULT_DATAFRAME_COLUMNS]
-def convert_trades_format(config: Dict[str, Any], convert_from: str, convert_to: str, erase: bool):
+def convert_trades_format(config: Config, convert_from: str, convert_to: str, erase: bool):
"""
Convert trades from one format to another format.
:param config: Config dictionary
@@ -263,7 +263,7 @@ def convert_trades_format(config: Dict[str, Any], convert_from: str, convert_to:
def convert_ohlcv_format(
- config: Dict[str, Any],
+ config: Config,
convert_from: str,
convert_to: str,
erase: bool,
@@ -292,6 +292,7 @@ def convert_ohlcv_format(
timeframe,
candle_type=candle_type
))
+ config['pairs'] = sorted(set(config['pairs']))
logger.info(f"Converting candle (OHLCV) data for {config['pairs']}")
for timeframe in timeframes:
@@ -302,7 +303,7 @@ def convert_ohlcv_format(
drop_incomplete=False,
startup_candles=0,
candle_type=candle_type)
- logger.info(f"Converting {len(data)} {candle_type} candles for {pair}")
+ logger.info(f"Converting {len(data)} {timeframe} {candle_type} candles for {pair}")
if len(data) > 0:
trg.ohlcv_store(
pair=pair,
diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py
index c6519d2b8..4d7296ee7 100644
--- a/freqtrade/data/dataprovider.py
+++ b/freqtrade/data/dataprovider.py
@@ -12,11 +12,12 @@ from typing import Any, Dict, List, Optional, Tuple
from pandas import DataFrame
from freqtrade.configuration import TimeRange
-from freqtrade.constants import ListPairsWithTimeframes, PairWithTimeframe
+from freqtrade.constants import Config, ListPairsWithTimeframes, PairWithTimeframe
from freqtrade.data.history import load_pair_history
-from freqtrade.enums import CandleType, RunMode
+from freqtrade.enums import CandleType, RPCMessageType, RunMode
from freqtrade.exceptions import ExchangeError, OperationalException
from freqtrade.exchange import Exchange, timeframe_to_seconds
+from freqtrade.rpc import RPCManager
from freqtrade.util import PeriodicCache
@@ -28,17 +29,33 @@ MAX_DATAFRAME_CANDLES = 1000
class DataProvider:
- def __init__(self, config: dict, exchange: Optional[Exchange], pairlists=None) -> None:
+ def __init__(
+ self,
+ config: Config,
+ exchange: Optional[Exchange],
+ pairlists=None,
+ rpc: Optional[RPCManager] = None
+ ) -> None:
self._config = config
self._exchange = exchange
self._pairlists = pairlists
+ self.__rpc = rpc
self.__cached_pairs: Dict[PairWithTimeframe, Tuple[DataFrame, datetime]] = {}
self.__slice_index: Optional[int] = None
self.__cached_pairs_backtesting: Dict[PairWithTimeframe, DataFrame] = {}
+ self.__producer_pairs_df: Dict[str,
+ Dict[PairWithTimeframe, Tuple[DataFrame, datetime]]] = {}
+ self.__producer_pairs: Dict[str, List[str]] = {}
self._msg_queue: deque = deque()
+ self._default_candle_type = self._config.get('candle_type_def', CandleType.SPOT)
+ self._default_timeframe = self._config.get('timeframe', '1h')
+
self.__msg_cache = PeriodicCache(
- maxsize=1000, ttl=timeframe_to_seconds(self._config.get('timeframe', '1h')))
+ maxsize=1000, ttl=timeframe_to_seconds(self._default_timeframe))
+
+ self.producers = self._config.get('external_message_consumer', {}).get('producers', [])
+ self.external_data_enabled = len(self.producers) > 0
def _set_dataframe_max_index(self, limit_index: int):
"""
@@ -63,9 +80,110 @@ class DataProvider:
:param dataframe: analyzed dataframe
:param candle_type: Any of the enum CandleType (must match trading mode!)
"""
- self.__cached_pairs[(pair, timeframe, candle_type)] = (
+ pair_key = (pair, timeframe, candle_type)
+ self.__cached_pairs[pair_key] = (
dataframe, datetime.now(timezone.utc))
+ # For multiple producers we will want to merge the pairlists instead of overwriting
+ def _set_producer_pairs(self, pairlist: List[str], producer_name: str = "default"):
+ """
+ Set the pairs received to later be used.
+
+ :param pairlist: List of pairs
+ """
+ self.__producer_pairs[producer_name] = pairlist
+
+ def get_producer_pairs(self, producer_name: str = "default") -> List[str]:
+ """
+ Get the pairs cached from the producer
+
+ :returns: List of pairs
+ """
+ return self.__producer_pairs.get(producer_name, []).copy()
+
+ def _emit_df(
+ self,
+ pair_key: PairWithTimeframe,
+ dataframe: DataFrame
+ ) -> None:
+ """
+ Send this dataframe as an ANALYZED_DF message to RPC
+
+ :param pair_key: PairWithTimeframe tuple
+ :param data: Tuple containing the DataFrame and the datetime it was cached
+ """
+ if self.__rpc:
+ self.__rpc.send_msg(
+ {
+ 'type': RPCMessageType.ANALYZED_DF,
+ 'data': {
+ 'key': pair_key,
+ 'df': dataframe,
+ 'la': datetime.now(timezone.utc)
+ }
+ }
+ )
+
+ def _add_external_df(
+ self,
+ pair: str,
+ dataframe: DataFrame,
+ last_analyzed: datetime,
+ timeframe: str,
+ candle_type: CandleType,
+ producer_name: str = "default"
+ ) -> None:
+ """
+ Add the pair data to this class from an external source.
+
+ :param pair: pair to get the data for
+ :param timeframe: Timeframe to get data for
+ :param candle_type: Any of the enum CandleType (must match trading mode!)
+ """
+ pair_key = (pair, timeframe, candle_type)
+
+ if producer_name not in self.__producer_pairs_df:
+ self.__producer_pairs_df[producer_name] = {}
+
+ _last_analyzed = datetime.now(timezone.utc) if not last_analyzed else last_analyzed
+
+ self.__producer_pairs_df[producer_name][pair_key] = (dataframe, _last_analyzed)
+ logger.debug(f"External DataFrame for {pair_key} from {producer_name} added.")
+
+ def get_producer_df(
+ self,
+ pair: str,
+ timeframe: Optional[str] = None,
+ candle_type: Optional[CandleType] = None,
+ producer_name: str = "default"
+ ) -> Tuple[DataFrame, datetime]:
+ """
+ Get the pair data from producers.
+
+ :param pair: pair to get the data for
+ :param timeframe: Timeframe to get data for
+ :param candle_type: Any of the enum CandleType (must match trading mode!)
+ :returns: Tuple of the DataFrame and last analyzed timestamp
+ """
+ _timeframe = self._default_timeframe if not timeframe else timeframe
+ _candle_type = self._default_candle_type if not candle_type else candle_type
+
+ pair_key = (pair, _timeframe, _candle_type)
+
+ # If we have no data from this Producer yet
+ if producer_name not in self.__producer_pairs_df:
+ # We don't have this data yet, return empty DataFrame and datetime (01-01-1970)
+ return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc))
+
+ # If we do have data from that Producer, but no data on this pair_key
+ if pair_key not in self.__producer_pairs_df[producer_name]:
+ # We don't have this data yet, return empty DataFrame and datetime (01-01-1970)
+ return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc))
+
+ # We have it, return this data
+ df, la = self.__producer_pairs_df[producer_name][pair_key]
+ return (df.copy(), la)
+
def add_pairlisthandler(self, pairlists) -> None:
"""
Allow adding pairlisthandler after initialization
@@ -90,8 +208,10 @@ class DataProvider:
if saved_pair not in self.__cached_pairs_backtesting:
timerange = TimeRange.parse_timerange(None if self._config.get(
'timerange') is None else str(self._config.get('timerange')))
- # Move informative start time respecting startup_candle_count
- startup_candles = self.get_required_startup(str(timeframe))
+
+ # It is not necessary to add the training candles, as they
+ # were already added at the beginning of the backtest.
+ startup_candles = self.get_required_startup(str(timeframe), False)
tf_seconds = timeframe_to_seconds(str(timeframe))
timerange.subtract_start(tf_seconds * startup_candles)
self.__cached_pairs_backtesting[saved_pair] = load_pair_history(
@@ -105,7 +225,7 @@ class DataProvider:
)
return self.__cached_pairs_backtesting[saved_pair].copy()
- def get_required_startup(self, timeframe: str) -> int:
+ def get_required_startup(self, timeframe: str, add_train_candles: bool = True) -> int:
freqai_config = self._config.get('freqai', {})
if not freqai_config.get('enabled', False):
return self._config.get('startup_candle_count', 0)
@@ -115,7 +235,9 @@ class DataProvider:
# make sure the startupcandles is at least the set maximum indicator periods
self._config['startup_candle_count'] = max(startup_candles, max(indicator_periods))
tf_seconds = timeframe_to_seconds(timeframe)
- train_candles = freqai_config['train_period_days'] * 86400 / tf_seconds
+ train_candles = 0
+ if add_train_candles:
+ train_candles = freqai_config['train_period_days'] * 86400 / tf_seconds
total_candles = int(self._config['startup_candle_count'] + train_candles)
logger.info(f'Increasing startup_candle_count for freqai to {total_candles}')
return total_candles
diff --git a/freqtrade/data/history/featherdatahandler.py b/freqtrade/data/history/featherdatahandler.py
new file mode 100644
index 000000000..22a6805e7
--- /dev/null
+++ b/freqtrade/data/history/featherdatahandler.py
@@ -0,0 +1,130 @@
+import logging
+from typing import Optional
+
+from pandas import DataFrame, read_feather, to_datetime
+
+from freqtrade.configuration import TimeRange
+from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, TradeList
+from freqtrade.enums import CandleType
+
+from .idatahandler import IDataHandler
+
+
+logger = logging.getLogger(__name__)
+
+
+class FeatherDataHandler(IDataHandler):
+
+ _columns = DEFAULT_DATAFRAME_COLUMNS
+
+ def ohlcv_store(
+ self, pair: str, timeframe: str, data: DataFrame, candle_type: CandleType) -> None:
+ """
+ Store data in json format "values".
+ format looks as follows:
+ [[,,,,]]
+ :param pair: Pair - used to generate filename
+ :param timeframe: Timeframe - used to generate filename
+ :param data: Dataframe containing OHLCV data
+ :param candle_type: Any of the enum CandleType (must match trading mode!)
+ :return: None
+ """
+ filename = self._pair_data_filename(self._datadir, pair, timeframe, candle_type)
+ self.create_dir_if_needed(filename)
+
+ data.reset_index(drop=True).loc[:, self._columns].to_feather(
+ filename, compression_level=9, compression='lz4')
+
+ def _ohlcv_load(self, pair: str, timeframe: str,
+ timerange: Optional[TimeRange], candle_type: CandleType
+ ) -> DataFrame:
+ """
+ Internal method used to load data for one pair from disk.
+ Implements the loading and conversion to a Pandas dataframe.
+ Timerange trimming and dataframe validation happens outside of this method.
+ :param pair: Pair to load data
+ :param timeframe: Timeframe (e.g. "5m")
+ :param timerange: Limit data to be loaded to this timerange.
+ Optionally implemented by subclasses to avoid loading
+ all data where possible.
+ :param candle_type: Any of the enum CandleType (must match trading mode!)
+ :return: DataFrame with ohlcv data, or empty DataFrame
+ """
+ filename = self._pair_data_filename(
+ self._datadir, pair, timeframe, candle_type=candle_type)
+ if not filename.exists():
+ # Fallback mode for 1M files
+ filename = self._pair_data_filename(
+ self._datadir, pair, timeframe, candle_type=candle_type, no_timeframe_modify=True)
+ if not filename.exists():
+ return DataFrame(columns=self._columns)
+
+ pairdata = read_feather(filename)
+ pairdata.columns = self._columns
+ pairdata = pairdata.astype(dtype={'open': 'float', 'high': 'float',
+ 'low': 'float', 'close': 'float', 'volume': 'float'})
+ pairdata['date'] = to_datetime(pairdata['date'],
+ unit='ms',
+ utc=True,
+ infer_datetime_format=True)
+ return pairdata
+
+ def ohlcv_append(
+ self,
+ pair: str,
+ timeframe: str,
+ data: DataFrame,
+ candle_type: CandleType
+ ) -> None:
+ """
+ Append data to existing data structures
+ :param pair: Pair
+ :param timeframe: Timeframe this ohlcv data is for
+ :param data: Data to append.
+ :param candle_type: Any of the enum CandleType (must match trading mode!)
+ """
+ raise NotImplementedError()
+
+ def trades_store(self, pair: str, data: TradeList) -> None:
+ """
+ Store trades data (list of Dicts) to file
+ :param pair: Pair - used for filename
+ :param data: List of Lists containing trade data,
+ column sequence as in DEFAULT_TRADES_COLUMNS
+ """
+ # filename = self._pair_trades_filename(self._datadir, pair)
+
+ raise NotImplementedError()
+ # array = pa.array(data)
+ # array
+ # feather.write_feather(data, filename)
+
+ def trades_append(self, pair: str, data: TradeList):
+ """
+ Append data to existing files
+ :param pair: Pair - used for filename
+ :param data: List of Lists containing trade data,
+ column sequence as in DEFAULT_TRADES_COLUMNS
+ """
+ raise NotImplementedError()
+
+ def _trades_load(self, pair: str, timerange: Optional[TimeRange] = None) -> TradeList:
+ """
+ Load a pair from file, either .json.gz or .json
+ # TODO: respect timerange ...
+ :param pair: Load trades for this pair
+ :param timerange: Timerange to load trades for - currently not implemented
+ :return: List of trades
+ """
+ raise NotImplementedError()
+ # filename = self._pair_trades_filename(self._datadir, pair)
+ # tradesdata = misc.file_load_json(filename)
+
+ # if not tradesdata:
+ # return []
+
+ # return tradesdata
+
+ @classmethod
+ def _get_file_extension(cls):
+ return "feather"
diff --git a/freqtrade/data/history/hdf5datahandler.py b/freqtrade/data/history/hdf5datahandler.py
index 135d97c79..fd46115de 100644
--- a/freqtrade/data/history/hdf5datahandler.py
+++ b/freqtrade/data/history/hdf5datahandler.py
@@ -1,7 +1,5 @@
import logging
-import re
-from pathlib import Path
-from typing import List, Optional
+from typing import Optional
import numpy as np
import pandas as pd
@@ -20,26 +18,6 @@ class HDF5DataHandler(IDataHandler):
_columns = DEFAULT_DATAFRAME_COLUMNS
- @classmethod
- def ohlcv_get_pairs(cls, datadir: Path, timeframe: str, candle_type: CandleType) -> List[str]:
- """
- Returns a list of all pairs with ohlcv data available in this datadir
- for the specified timeframe
- :param datadir: Directory to search for ohlcv files
- :param timeframe: Timeframe to search pairs for
- :param candle_type: Any of the enum CandleType (must match trading mode!)
- :return: List of Pairs
- """
- candle = ""
- if candle_type != CandleType.SPOT:
- datadir = datadir.joinpath('futures')
- candle = f"-{candle_type}"
-
- _tmp = [re.search(r'^(\S+)(?=\-' + timeframe + candle + '.h5)', p.name)
- for p in datadir.glob(f"*{timeframe}{candle}.h5")]
- # Check if regex found something and only return these results
- return [cls.rebuild_pair_from_filename(match[0]) for match in _tmp if match]
-
def ohlcv_store(
self, pair: str, timeframe: str, data: pd.DataFrame, candle_type: CandleType) -> None:
"""
@@ -103,6 +81,7 @@ class HDF5DataHandler(IDataHandler):
raise ValueError("Wrong dataframe format")
pairdata = pairdata.astype(dtype={'open': 'float', 'high': 'float',
'low': 'float', 'close': 'float', 'volume': 'float'})
+ pairdata = pairdata.reset_index(drop=True)
return pairdata
def ohlcv_append(
@@ -121,18 +100,6 @@ class HDF5DataHandler(IDataHandler):
"""
raise NotImplementedError()
- @classmethod
- def trades_get_pairs(cls, datadir: Path) -> List[str]:
- """
- Returns a list of all pairs for which trade data is available in this
- :param datadir: Directory to search for ohlcv files
- :return: List of Pairs
- """
- _tmp = [re.search(r'^(\S+)(?=\-trades.h5)', p.name)
- for p in datadir.glob("*trades.h5")]
- # Check if regex found something and only return these results to avoid exceptions.
- return [cls.rebuild_pair_from_filename(match[0]) for match in _tmp if match]
-
def trades_store(self, pair: str, data: TradeList) -> None:
"""
Store trades data (list of Dicts) to file
diff --git a/freqtrade/data/history/idatahandler.py b/freqtrade/data/history/idatahandler.py
index 846bcc607..eb5ad3621 100644
--- a/freqtrade/data/history/idatahandler.py
+++ b/freqtrade/data/history/idatahandler.py
@@ -26,7 +26,7 @@ logger = logging.getLogger(__name__)
class IDataHandler(ABC):
- _OHLCV_REGEX = r'^([a-zA-Z_-]+)\-(\d+[a-zA-Z]{1,2})\-?([a-zA-Z_]*)?(?=\.)'
+ _OHLCV_REGEX = r'^([a-zA-Z_\d-]+)\-(\d+[a-zA-Z]{1,2})\-?([a-zA-Z_]*)?(?=\.)'
def __init__(self, datadir: Path) -> None:
self._datadir = datadir
@@ -61,7 +61,6 @@ class IDataHandler(ABC):
) for match in _tmp if match and len(match.groups()) > 1]
@classmethod
- @abstractmethod
def ohlcv_get_pairs(cls, datadir: Path, timeframe: str, candle_type: CandleType) -> List[str]:
"""
Returns a list of all pairs with ohlcv data available in this datadir
@@ -71,6 +70,15 @@ class IDataHandler(ABC):
:param candle_type: Any of the enum CandleType (must match trading mode!)
:return: List of Pairs
"""
+ candle = ""
+ if candle_type != CandleType.SPOT:
+ datadir = datadir.joinpath('futures')
+ candle = f"-{candle_type}"
+ ext = cls._get_file_extension()
+ _tmp = [re.search(r'^(\S+)(?=\-' + timeframe + candle + f'.{ext})', p.name)
+ for p in datadir.glob(f"*{timeframe}{candle}.{ext}")]
+ # Check if regex found something and only return these results
+ return [cls.rebuild_pair_from_filename(match[0]) for match in _tmp if match]
@abstractmethod
def ohlcv_store(
@@ -144,13 +152,17 @@ class IDataHandler(ABC):
"""
@classmethod
- @abstractmethod
def trades_get_pairs(cls, datadir: Path) -> List[str]:
"""
Returns a list of all pairs for which trade data is available in this
:param datadir: Directory to search for ohlcv files
:return: List of Pairs
"""
+ _ext = cls._get_file_extension()
+ _tmp = [re.search(r'^(\S+)(?=\-trades.' + _ext + ')', p.name)
+ for p in datadir.glob(f"*trades.{_ext}")]
+ # Check if regex found something and only return these results to avoid exceptions.
+ return [cls.rebuild_pair_from_filename(match[0]) for match in _tmp if match]
@abstractmethod
def trades_store(self, pair: str, data: TradeList) -> None:
@@ -255,7 +267,7 @@ class IDataHandler(ABC):
Rebuild pair name from filename
Assumes a asset name of max. 7 length to also support BTC-PERP and BTC-PERP:USD names.
"""
- res = re.sub(r'^(([A-Za-z]{1,10})|^([A-Za-z\-]{1,6}))(_)', r'\g<1>/', pair, 1)
+ res = re.sub(r'^(([A-Za-z\d]{1,10})|^([A-Za-z\-]{1,6}))(_)', r'\g<1>/', pair, 1)
res = re.sub('_', ':', res, 1)
return res
@@ -363,6 +375,12 @@ def get_datahandlerclass(datatype: str) -> Type[IDataHandler]:
elif datatype == 'hdf5':
from .hdf5datahandler import HDF5DataHandler
return HDF5DataHandler
+ elif datatype == 'feather':
+ from .featherdatahandler import FeatherDataHandler
+ return FeatherDataHandler
+ elif datatype == 'parquet':
+ from .parquetdatahandler import ParquetDataHandler
+ return ParquetDataHandler
else:
raise ValueError(f"No datahandler for datatype {datatype} available.")
diff --git a/freqtrade/data/history/jsondatahandler.py b/freqtrade/data/history/jsondatahandler.py
index a62e5e381..f016c0ec1 100644
--- a/freqtrade/data/history/jsondatahandler.py
+++ b/freqtrade/data/history/jsondatahandler.py
@@ -1,7 +1,5 @@
import logging
-import re
-from pathlib import Path
-from typing import List, Optional
+from typing import Optional
import numpy as np
from pandas import DataFrame, read_json, to_datetime
@@ -23,26 +21,6 @@ class JsonDataHandler(IDataHandler):
_use_zip = False
_columns = DEFAULT_DATAFRAME_COLUMNS
- @classmethod
- def ohlcv_get_pairs(cls, datadir: Path, timeframe: str, candle_type: CandleType) -> List[str]:
- """
- Returns a list of all pairs with ohlcv data available in this datadir
- for the specified timeframe
- :param datadir: Directory to search for ohlcv files
- :param timeframe: Timeframe to search pairs for
- :param candle_type: Any of the enum CandleType (must match trading mode!)
- :return: List of Pairs
- """
- candle = ""
- if candle_type != CandleType.SPOT:
- datadir = datadir.joinpath('futures')
- candle = f"-{candle_type}"
-
- _tmp = [re.search(r'^(\S+)(?=\-' + timeframe + candle + '.json)', p.name)
- for p in datadir.glob(f"*{timeframe}{candle}.{cls._get_file_extension()}")]
- # Check if regex found something and only return these results
- return [cls.rebuild_pair_from_filename(match[0]) for match in _tmp if match]
-
def ohlcv_store(
self, pair: str, timeframe: str, data: DataFrame, candle_type: CandleType) -> None:
"""
@@ -119,18 +97,6 @@ class JsonDataHandler(IDataHandler):
"""
raise NotImplementedError()
- @classmethod
- def trades_get_pairs(cls, datadir: Path) -> List[str]:
- """
- Returns a list of all pairs for which trade data is available in this
- :param datadir: Directory to search for ohlcv files
- :return: List of Pairs
- """
- _tmp = [re.search(r'^(\S+)(?=\-trades.json)', p.name)
- for p in datadir.glob(f"*trades.{cls._get_file_extension()}")]
- # Check if regex found something and only return these results to avoid exceptions.
- return [cls.rebuild_pair_from_filename(match[0]) for match in _tmp if match]
-
def trades_store(self, pair: str, data: TradeList) -> None:
"""
Store trades data (list of Dicts) to file
diff --git a/freqtrade/data/history/parquetdatahandler.py b/freqtrade/data/history/parquetdatahandler.py
new file mode 100644
index 000000000..57581861d
--- /dev/null
+++ b/freqtrade/data/history/parquetdatahandler.py
@@ -0,0 +1,129 @@
+import logging
+from typing import Optional
+
+from pandas import DataFrame, read_parquet, to_datetime
+
+from freqtrade.configuration import TimeRange
+from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, TradeList
+from freqtrade.enums import CandleType
+
+from .idatahandler import IDataHandler
+
+
+logger = logging.getLogger(__name__)
+
+
+class ParquetDataHandler(IDataHandler):
+
+ _columns = DEFAULT_DATAFRAME_COLUMNS
+
+ def ohlcv_store(
+ self, pair: str, timeframe: str, data: DataFrame, candle_type: CandleType) -> None:
+ """
+ Store data in json format "values".
+ format looks as follows:
+ [[,,,,]]
+ :param pair: Pair - used to generate filename
+ :param timeframe: Timeframe - used to generate filename
+ :param data: Dataframe containing OHLCV data
+ :param candle_type: Any of the enum CandleType (must match trading mode!)
+ :return: None
+ """
+ filename = self._pair_data_filename(self._datadir, pair, timeframe, candle_type)
+ self.create_dir_if_needed(filename)
+
+ data.reset_index(drop=True).loc[:, self._columns].to_parquet(filename)
+
+ def _ohlcv_load(self, pair: str, timeframe: str,
+ timerange: Optional[TimeRange], candle_type: CandleType
+ ) -> DataFrame:
+ """
+ Internal method used to load data for one pair from disk.
+ Implements the loading and conversion to a Pandas dataframe.
+ Timerange trimming and dataframe validation happens outside of this method.
+ :param pair: Pair to load data
+ :param timeframe: Timeframe (e.g. "5m")
+ :param timerange: Limit data to be loaded to this timerange.
+ Optionally implemented by subclasses to avoid loading
+ all data where possible.
+ :param candle_type: Any of the enum CandleType (must match trading mode!)
+ :return: DataFrame with ohlcv data, or empty DataFrame
+ """
+ filename = self._pair_data_filename(
+ self._datadir, pair, timeframe, candle_type=candle_type)
+ if not filename.exists():
+ # Fallback mode for 1M files
+ filename = self._pair_data_filename(
+ self._datadir, pair, timeframe, candle_type=candle_type, no_timeframe_modify=True)
+ if not filename.exists():
+ return DataFrame(columns=self._columns)
+
+ pairdata = read_parquet(filename)
+ pairdata.columns = self._columns
+ pairdata = pairdata.astype(dtype={'open': 'float', 'high': 'float',
+ 'low': 'float', 'close': 'float', 'volume': 'float'})
+ pairdata['date'] = to_datetime(pairdata['date'],
+ unit='ms',
+ utc=True,
+ infer_datetime_format=True)
+ return pairdata
+
+ def ohlcv_append(
+ self,
+ pair: str,
+ timeframe: str,
+ data: DataFrame,
+ candle_type: CandleType
+ ) -> None:
+ """
+ Append data to existing data structures
+ :param pair: Pair
+ :param timeframe: Timeframe this ohlcv data is for
+ :param data: Data to append.
+ :param candle_type: Any of the enum CandleType (must match trading mode!)
+ """
+ raise NotImplementedError()
+
+ def trades_store(self, pair: str, data: TradeList) -> None:
+ """
+ Store trades data (list of Dicts) to file
+ :param pair: Pair - used for filename
+ :param data: List of Lists containing trade data,
+ column sequence as in DEFAULT_TRADES_COLUMNS
+ """
+ # filename = self._pair_trades_filename(self._datadir, pair)
+
+ raise NotImplementedError()
+ # array = pa.array(data)
+ # array
+ # feather.write_feather(data, filename)
+
+ def trades_append(self, pair: str, data: TradeList):
+ """
+ Append data to existing files
+ :param pair: Pair - used for filename
+ :param data: List of Lists containing trade data,
+ column sequence as in DEFAULT_TRADES_COLUMNS
+ """
+ raise NotImplementedError()
+
+ def _trades_load(self, pair: str, timerange: Optional[TimeRange] = None) -> TradeList:
+ """
+ Load a pair from file, either .json.gz or .json
+ # TODO: respect timerange ...
+ :param pair: Load trades for this pair
+ :param timerange: Timerange to load trades for - currently not implemented
+ :return: List of trades
+ """
+ raise NotImplementedError()
+ # filename = self._pair_trades_filename(self._datadir, pair)
+ # tradesdata = misc.file_load_json(filename)
+
+ # if not tradesdata:
+ # return []
+
+ # return tradesdata
+
+ @classmethod
+ def _get_file_extension(cls):
+ return "parquet"
diff --git a/freqtrade/edge/edge_positioning.py b/freqtrade/edge/edge_positioning.py
index af20e1645..45b4cd8f1 100644
--- a/freqtrade/edge/edge_positioning.py
+++ b/freqtrade/edge/edge_positioning.py
@@ -11,7 +11,7 @@ import utils_find_1st as utf1st
from pandas import DataFrame
from freqtrade.configuration import TimeRange
-from freqtrade.constants import DATETIME_PRINT_FORMAT, UNLIMITED_STAKE_AMOUNT
+from freqtrade.constants import DATETIME_PRINT_FORMAT, UNLIMITED_STAKE_AMOUNT, Config
from freqtrade.data.history import get_timerange, load_data, refresh_data
from freqtrade.enums import CandleType, ExitType, RunMode
from freqtrade.exceptions import OperationalException
@@ -42,10 +42,9 @@ class Edge:
Author: https://github.com/mishaker
"""
- config: Dict = {}
_cached_pairs: Dict[str, Any] = {} # Keeps a list of pairs
- def __init__(self, config: Dict[str, Any], exchange, strategy) -> None:
+ def __init__(self, config: Config, exchange, strategy) -> None:
self.config = config
self.exchange = exchange
diff --git a/freqtrade/enums/__init__.py b/freqtrade/enums/__init__.py
index d2f5474fc..146d65f2d 100644
--- a/freqtrade/enums/__init__.py
+++ b/freqtrade/enums/__init__.py
@@ -6,7 +6,7 @@ from freqtrade.enums.exittype import ExitType
from freqtrade.enums.hyperoptstate import HyperoptState
from freqtrade.enums.marginmode import MarginMode
from freqtrade.enums.ordertypevalue import OrderTypeValues
-from freqtrade.enums.rpcmessagetype import RPCMessageType
+from freqtrade.enums.rpcmessagetype import RPCMessageType, RPCRequestType
from freqtrade.enums.runmode import NON_UTIL_MODES, OPTIMIZE_MODES, TRADING_MODES, RunMode
from freqtrade.enums.signaltype import SignalDirection, SignalTagType, SignalType
from freqtrade.enums.state import State
diff --git a/freqtrade/enums/rpcmessagetype.py b/freqtrade/enums/rpcmessagetype.py
index 415d8f18c..fae121a09 100644
--- a/freqtrade/enums/rpcmessagetype.py
+++ b/freqtrade/enums/rpcmessagetype.py
@@ -1,7 +1,7 @@
from enum import Enum
-class RPCMessageType(Enum):
+class RPCMessageType(str, Enum):
STATUS = 'status'
WARNING = 'warning'
STARTUP = 'startup'
@@ -19,8 +19,19 @@ class RPCMessageType(Enum):
STRATEGY_MSG = 'strategy_msg'
+ WHITELIST = 'whitelist'
+ ANALYZED_DF = 'analyzed_df'
+
def __repr__(self):
return self.value
def __str__(self):
return self.value
+
+
+# Enum for parsing requests from ws consumers
+class RPCRequestType(str, Enum):
+ SUBSCRIBE = 'subscribe'
+
+ WHITELIST = 'whitelist'
+ ANALYZED_DF = 'analyzed_df'
diff --git a/freqtrade/exchange/binance.py b/freqtrade/exchange/binance.py
index faa780529..f9fb4a8b1 100644
--- a/freqtrade/exchange/binance.py
+++ b/freqtrade/exchange/binance.py
@@ -1,5 +1,4 @@
""" Binance exchange subclass """
-import json
import logging
from datetime import datetime
from pathlib import Path
@@ -12,7 +11,7 @@ from freqtrade.enums import CandleType, MarginMode, TradingMode
from freqtrade.exceptions import DDosProtection, OperationalException, TemporaryError
from freqtrade.exchange import Exchange
from freqtrade.exchange.common import retrier
-from freqtrade.misc import deep_merge_dicts
+from freqtrade.misc import deep_merge_dicts, json_load
logger = logging.getLogger(__name__)
@@ -200,7 +199,7 @@ class Binance(Exchange):
Path(__file__).parent / 'binance_leverage_tiers.json'
)
with open(leverage_tiers_path) as json_file:
- return json.load(json_file)
+ return json_load(json_file)
else:
try:
return self._api.fetch_leverage_tiers()
diff --git a/freqtrade/exchange/binance_leverage_tiers.json b/freqtrade/exchange/binance_leverage_tiers.json
index 2fa326bb1..c3b86684b 100644
--- a/freqtrade/exchange/binance_leverage_tiers.json
+++ b/freqtrade/exchange/binance_leverage_tiers.json
@@ -19209,4 +19209,4 @@
}
}
]
-}
\ No newline at end of file
+}
diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py
index a2ddc16e8..f01e464fa 100644
--- a/freqtrade/exchange/exchange.py
+++ b/freqtrade/exchange/exchange.py
@@ -21,7 +21,8 @@ from dateutil import parser
from pandas import DataFrame
from freqtrade.constants import (DEFAULT_AMOUNT_RESERVE_PERCENT, NON_OPEN_EXCHANGE_STATES, BuySell,
- EntryExit, ListPairsWithTimeframes, MakerTaker, PairWithTimeframe)
+ Config, EntryExit, ListPairsWithTimeframes, MakerTaker,
+ PairWithTimeframe)
from freqtrade.data.converter import ohlcv_to_dataframe, trades_dict_to_list
from freqtrade.enums import OPTIMIZE_MODES, CandleType, MarginMode, TradingMode
from freqtrade.exceptions import (DDosProtection, ExchangeError, InsufficientFundsError,
@@ -91,7 +92,7 @@ class Exchange:
# TradingMode.SPOT always supported and not required in this list
]
- def __init__(self, config: Dict[str, Any], validate: bool = True,
+ def __init__(self, config: Config, validate: bool = True,
load_leverage_tiers: bool = False) -> None:
"""
Initializes this module with the given config,
@@ -108,7 +109,7 @@ class Exchange:
self._loop_lock = Lock()
self.loop = asyncio.new_event_loop()
asyncio.set_event_loop(self.loop)
- self._config: Dict = {}
+ self._config: Config = {}
self._config.update(config)
@@ -2890,7 +2891,7 @@ def amount_to_contracts(amount: float, contract_size: Optional[float]) -> float:
:return: num-contracts
"""
if contract_size and contract_size != 1:
- return amount / contract_size
+ return float(FtPrecise(amount) / FtPrecise(contract_size))
else:
return amount
@@ -2904,7 +2905,7 @@ def contracts_to_amount(num_contracts: float, contract_size: Optional[float]) ->
"""
if contract_size and contract_size != 1:
- return num_contracts * contract_size
+ return float(FtPrecise(num_contracts) * FtPrecise(contract_size))
else:
return num_contracts
diff --git a/freqtrade/exchange/okx.py b/freqtrade/exchange/okx.py
index 49f8ea107..2db5fb6a9 100644
--- a/freqtrade/exchange/okx.py
+++ b/freqtrade/exchange/okx.py
@@ -71,6 +71,7 @@ class Okx(Exchange):
try:
if self.trading_mode == TradingMode.FUTURES and not self._config['dry_run']:
accounts = self._api.fetch_accounts()
+ self._log_exchange_response('fetch_accounts', accounts)
if len(accounts) > 0:
self.net_only = accounts[0].get('info', {}).get('posMode') == 'net_mode'
except ccxt.DDoSProtection as e:
diff --git a/freqtrade/freqai/base_models/BaseClassifierModel.py b/freqtrade/freqai/base_models/BaseClassifierModel.py
index 5142ffb0d..70f212d2a 100644
--- a/freqtrade/freqai/base_models/BaseClassifierModel.py
+++ b/freqtrade/freqai/base_models/BaseClassifierModel.py
@@ -1,4 +1,5 @@
import logging
+from time import time
from typing import Any, Tuple
import numpy as np
@@ -32,7 +33,9 @@ class BaseClassifierModel(IFreqaiModel):
:model: Trained model which can be used to inference (self.predict)
"""
- logger.info("-------------------- Starting training " f"{pair} --------------------")
+ logger.info(f"-------------------- Starting training {pair} --------------------")
+
+ start_time = time()
# filter the features requested by user in the configuration file and elegantly handle NaNs
features_filtered, labels_filtered = dk.filter_features(
@@ -45,10 +48,10 @@ class BaseClassifierModel(IFreqaiModel):
start_date = unfiltered_df["date"].iloc[0].strftime("%Y-%m-%d")
end_date = unfiltered_df["date"].iloc[-1].strftime("%Y-%m-%d")
logger.info(f"-------------------- Training on data from {start_date} to "
- f"{end_date}--------------------")
+ f"{end_date} --------------------")
# split data into train/test data.
data_dictionary = dk.make_train_test_datasets(features_filtered, labels_filtered)
- if not self.freqai_info.get('fit_live_predictions', 0) or not self.live:
+ if not self.freqai_info.get("fit_live_predictions", 0) or not self.live:
dk.fit_labels()
# normalize all data based on train_dataset only
data_dictionary = dk.normalize_data(data_dictionary)
@@ -57,13 +60,16 @@ class BaseClassifierModel(IFreqaiModel):
self.data_cleaning_train(dk)
logger.info(
- f'Training model on {len(dk.data_dictionary["train_features"].columns)}' " features"
+ f"Training model on {len(dk.data_dictionary['train_features'].columns)} features"
)
- logger.info(f'Training model on {len(data_dictionary["train_features"])} data points')
+ logger.info(f"Training model on {len(data_dictionary['train_features'])} data points")
model = self.fit(data_dictionary, dk)
- logger.info(f"--------------------done training {pair}--------------------")
+ end_time = time()
+
+ logger.info(f"-------------------- Done training {pair} "
+ f"({end_time - start_time:.2f} secs) --------------------")
return model
diff --git a/freqtrade/freqai/base_models/BaseRegressionModel.py b/freqtrade/freqai/base_models/BaseRegressionModel.py
index 1d87e42c0..2450bf305 100644
--- a/freqtrade/freqai/base_models/BaseRegressionModel.py
+++ b/freqtrade/freqai/base_models/BaseRegressionModel.py
@@ -1,4 +1,5 @@
import logging
+from time import time
from typing import Any, Tuple
import numpy as np
@@ -31,7 +32,9 @@ class BaseRegressionModel(IFreqaiModel):
:model: Trained model which can be used to inference (self.predict)
"""
- logger.info("-------------------- Starting training " f"{pair} --------------------")
+ logger.info(f"-------------------- Starting training {pair} --------------------")
+
+ start_time = time()
# filter the features requested by user in the configuration file and elegantly handle NaNs
features_filtered, labels_filtered = dk.filter_features(
@@ -44,10 +47,10 @@ class BaseRegressionModel(IFreqaiModel):
start_date = unfiltered_df["date"].iloc[0].strftime("%Y-%m-%d")
end_date = unfiltered_df["date"].iloc[-1].strftime("%Y-%m-%d")
logger.info(f"-------------------- Training on data from {start_date} to "
- f"{end_date}--------------------")
+ f"{end_date} --------------------")
# split data into train/test data.
data_dictionary = dk.make_train_test_datasets(features_filtered, labels_filtered)
- if not self.freqai_info.get('fit_live_predictions', 0) or not self.live:
+ if not self.freqai_info.get("fit_live_predictions", 0) or not self.live:
dk.fit_labels()
# normalize all data based on train_dataset only
data_dictionary = dk.normalize_data(data_dictionary)
@@ -56,13 +59,16 @@ class BaseRegressionModel(IFreqaiModel):
self.data_cleaning_train(dk)
logger.info(
- f'Training model on {len(dk.data_dictionary["train_features"].columns)}' " features"
+ f"Training model on {len(dk.data_dictionary['train_features'].columns)} features"
)
- logger.info(f'Training model on {len(data_dictionary["train_features"])} data points')
+ logger.info(f"Training model on {len(data_dictionary['train_features'])} data points")
model = self.fit(data_dictionary, dk)
- logger.info(f"--------------------done training {pair}--------------------")
+ end_time = time()
+
+ logger.info(f"-------------------- Done training {pair} "
+ f"({end_time - start_time:.2f} secs) --------------------")
return model
diff --git a/freqtrade/freqai/base_models/BaseTensorFlowModel.py b/freqtrade/freqai/base_models/BaseTensorFlowModel.py
index eea80f3a2..00f9d6cba 100644
--- a/freqtrade/freqai/base_models/BaseTensorFlowModel.py
+++ b/freqtrade/freqai/base_models/BaseTensorFlowModel.py
@@ -1,4 +1,5 @@
import logging
+from time import time
from typing import Any
from pandas import DataFrame
@@ -28,7 +29,9 @@ class BaseTensorFlowModel(IFreqaiModel):
:model: Trained model which can be used to inference (self.predict)
"""
- logger.info("-------------------- Starting training " f"{pair} --------------------")
+ logger.info(f"-------------------- Starting training {pair} --------------------")
+
+ start_time = time()
# filter the features requested by user in the configuration file and elegantly handle NaNs
features_filtered, labels_filtered = dk.filter_features(
@@ -41,10 +44,10 @@ class BaseTensorFlowModel(IFreqaiModel):
start_date = unfiltered_df["date"].iloc[0].strftime("%Y-%m-%d")
end_date = unfiltered_df["date"].iloc[-1].strftime("%Y-%m-%d")
logger.info(f"-------------------- Training on data from {start_date} to "
- f"{end_date}--------------------")
+ f"{end_date} --------------------")
# split data into train/test data.
data_dictionary = dk.make_train_test_datasets(features_filtered, labels_filtered)
- if not self.freqai_info.get('fit_live_predictions', 0) or not self.live:
+ if not self.freqai_info.get("fit_live_predictions", 0) or not self.live:
dk.fit_labels()
# normalize all data based on train_dataset only
data_dictionary = dk.normalize_data(data_dictionary)
@@ -53,12 +56,15 @@ class BaseTensorFlowModel(IFreqaiModel):
self.data_cleaning_train(dk)
logger.info(
- f'Training model on {len(dk.data_dictionary["train_features"].columns)}' " features"
+ f"Training model on {len(dk.data_dictionary['train_features'].columns)} features"
)
- logger.info(f'Training model on {len(data_dictionary["train_features"])} data points')
+ logger.info(f"Training model on {len(data_dictionary['train_features'])} data points")
model = self.fit(data_dictionary, dk)
- logger.info(f"--------------------done training {pair}--------------------")
+ end_time = time()
+
+ logger.info(f"-------------------- Done training {pair} "
+ f"({end_time - start_time:.2f} secs) --------------------")
return model
diff --git a/freqtrade/freqai/base_models/FreqaiMultiOutputRegressor.py b/freqtrade/freqai/base_models/FreqaiMultiOutputRegressor.py
index a9db81e31..54136d5e0 100644
--- a/freqtrade/freqai/base_models/FreqaiMultiOutputRegressor.py
+++ b/freqtrade/freqai/base_models/FreqaiMultiOutputRegressor.py
@@ -1,4 +1,3 @@
-
from joblib import Parallel
from sklearn.multioutput import MultiOutputRegressor, _fit_estimator
from sklearn.utils.fixes import delayed
diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py
index 02d63a071..bb4cadc52 100644
--- a/freqtrade/freqai/data_drawer.py
+++ b/freqtrade/freqai/data_drawer.py
@@ -16,6 +16,7 @@ from numpy.typing import NDArray
from pandas import DataFrame
from freqtrade.configuration import TimeRange
+from freqtrade.constants import Config
from freqtrade.data.history import load_pair_history
from freqtrade.exceptions import OperationalException
from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
@@ -27,9 +28,7 @@ logger = logging.getLogger(__name__)
class pair_info(TypedDict):
model_filename: str
- first: bool
trained_timestamp: int
- priority: int
data_path: str
extras: dict
@@ -58,7 +57,7 @@ class FreqaiDataDrawer:
Juha Nykänen @suikula, Wagner Costa @wagnercosta, Johan Vlugt @Jooopieeert
"""
- def __init__(self, full_path: Path, config: dict, follow_mode: bool = False):
+ def __init__(self, full_path: Path, config: Config, follow_mode: bool = False):
self.config = config
self.freqai_info = config.get("freqai", {})
@@ -91,7 +90,7 @@ class FreqaiDataDrawer:
self.old_DBSCAN_eps: Dict[str, float] = {}
self.empty_pair_dict: pair_info = {
"model_filename": "", "trained_timestamp": 0,
- "priority": 1, "first": True, "data_path": "", "extras": {}}
+ "data_path": "", "extras": {}}
def load_drawer_from_disk(self):
"""
@@ -216,7 +215,6 @@ class FreqaiDataDrawer:
self.pair_dict[pair] = self.empty_pair_dict.copy()
model_filename = ""
trained_timestamp = 0
- self.pair_dict[pair]["priority"] = len(self.pair_dict)
if not data_path_set and self.follow_mode:
logger.warning(
@@ -236,18 +234,9 @@ class FreqaiDataDrawer:
return
else:
self.pair_dict[metadata["pair"]] = self.empty_pair_dict.copy()
- self.pair_dict[metadata["pair"]]["priority"] = len(self.pair_dict)
return
- def pair_to_end_of_training_queue(self, pair: str) -> None:
- # march all pairs up in the queue
- with self.pair_dict_lock:
- for p in self.pair_dict:
- self.pair_dict[p]["priority"] -= 1
- # send pair to end of queue
- self.pair_dict[pair]["priority"] = len(self.pair_dict)
-
def set_initial_return_values(self, pair: str, pred_df: DataFrame) -> None:
"""
Set the initial return values to the historical predictions dataframe. This avoids needing
@@ -441,6 +430,16 @@ class FreqaiDataDrawer:
return
+ def load_metadata(self, dk: FreqaiDataKitchen) -> None:
+ """
+ Load only metadata into datakitchen to increase performance during
+ presaved backtesting (prediction file loading).
+ """
+ with open(dk.data_path / f"{dk.model_filename}_metadata.json", "r") as fp:
+ dk.data = json.load(fp)
+ dk.training_features_list = dk.data["training_features_list"]
+ dk.label_list = dk.data["label_list"]
+
def load_data(self, coin: str, dk: FreqaiDataKitchen) -> Any:
"""
loads all data required to make a prediction on a sub-train time range
diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index dee52f6eb..2446bcc99 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -18,6 +18,7 @@ from sklearn.model_selection import train_test_split
from sklearn.neighbors import NearestNeighbors
from freqtrade.configuration import TimeRange
+from freqtrade.constants import Config
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import timeframe_to_seconds
from freqtrade.strategy.interface import IStrategy
@@ -57,7 +58,7 @@ class FreqaiDataKitchen:
def __init__(
self,
- config: Dict[str, Any],
+ config: Config,
live: bool = False,
pair: str = "",
):
@@ -466,27 +467,6 @@ class FreqaiDataKitchen:
return df
- def remove_training_from_backtesting(
- self
- ) -> DataFrame:
- """
- Function which takes the backtesting time range and
- remove training data from dataframe, keeping only the
- startup_candle_count candles
- """
- startup_candle_count = self.config.get('startup_candle_count', 0)
- tf = self.config['timeframe']
- tr = self.config["timerange"]
-
- backtesting_timerange = TimeRange.parse_timerange(tr)
- if startup_candle_count > 0 and backtesting_timerange:
- backtesting_timerange.subtract_start(timeframe_to_seconds(tf) * startup_candle_count)
-
- start = datetime.fromtimestamp(backtesting_timerange.startts, tz=timezone.utc)
- df = self.return_dataframe
- df = df.loc[df["date"] >= start, :]
- return df
-
def principal_component_analysis(self) -> None:
"""
Performs Principal Component Analysis on the data for dimensionality reduction
@@ -775,12 +755,22 @@ class FreqaiDataKitchen:
def compute_inlier_metric(self, set_='train') -> None:
"""
-
Compute inlier metric from backwards distance distributions.
This metric defines how well features from a timepoint fit
into previous timepoints.
"""
+ def normalise(dataframe: DataFrame, key: str) -> DataFrame:
+ if set_ == 'train':
+ min_value = dataframe.min()
+ max_value = dataframe.max()
+ self.data[f'{key}_min'] = min_value
+ self.data[f'{key}_max'] = max_value
+ else:
+ min_value = self.data[f'{key}_min']
+ max_value = self.data[f'{key}_max']
+ return (dataframe - min_value) / (max_value - min_value)
+
no_prev_pts = self.freqai_config["feature_parameters"]["inlier_metric_window"]
if set_ == 'train':
@@ -825,7 +815,12 @@ class FreqaiDataKitchen:
inliers = pd.DataFrame(index=distances.index)
for key in distances.keys():
current_distances = distances[key].dropna()
- fit_params = stats.weibull_min.fit(current_distances)
+ current_distances = normalise(current_distances, key)
+ if set_ == 'train':
+ fit_params = stats.weibull_min.fit(current_distances)
+ self.data[f'{key}_fit_params'] = fit_params
+ else:
+ fit_params = self.data[f'{key}_fit_params']
quantiles = stats.weibull_min.cdf(current_distances, *fit_params)
df_inlier = pd.DataFrame(
@@ -979,8 +974,6 @@ class FreqaiDataKitchen:
to_keep = [col for col in dataframe.columns if not col.startswith("&")]
self.return_dataframe = pd.concat([dataframe[to_keep], self.full_df], axis=1)
-
- # self.return_dataframe = self.remove_training_from_backtesting()
self.full_df = DataFrame()
return
diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py
index 5981db92f..b6bf26da7 100644
--- a/freqtrade/freqai/freqai_interface.py
+++ b/freqtrade/freqai/freqai_interface.py
@@ -3,6 +3,7 @@ import shutil
import threading
import time
from abc import ABC, abstractmethod
+from collections import deque
from datetime import datetime, timezone
from pathlib import Path
from threading import Lock
@@ -14,12 +15,13 @@ from numpy.typing import NDArray
from pandas import DataFrame
from freqtrade.configuration import TimeRange
-from freqtrade.constants import DATETIME_PRINT_FORMAT
+from freqtrade.constants import DATETIME_PRINT_FORMAT, Config
from freqtrade.enums import RunMode
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import timeframe_to_seconds
from freqtrade.freqai.data_drawer import FreqaiDataDrawer
from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
+from freqtrade.freqai.utils import plot_feature_importance
from freqtrade.strategy.interface import IStrategy
@@ -50,7 +52,7 @@ class IFreqaiModel(ABC):
Juha Nykänen @suikula, Wagner Costa @wagnercosta, Johan Vlugt @Jooopieeert
"""
- def __init__(self, config: Dict[str, Any]) -> None:
+ def __init__(self, config: Config) -> None:
self.config = config
self.assert_config(self.config)
@@ -63,7 +65,7 @@ class IFreqaiModel(ABC):
self.first = True
self.set_full_path()
self.follow_mode: bool = self.freqai_info.get("follow_mode", False)
- self.save_backtest_models: bool = self.freqai_info.get("save_backtest_models", False)
+ self.save_backtest_models: bool = self.freqai_info.get("save_backtest_models", True)
if self.save_backtest_models:
logger.info('Backtesting module configured to save all models.')
self.dd = FreqaiDataDrawer(Path(self.full_path), self.config, self.follow_mode)
@@ -80,6 +82,7 @@ class IFreqaiModel(ABC):
self.pair_it = 0
self.pair_it_train = 0
self.total_pairs = len(self.config.get("exchange", {}).get("pair_whitelist"))
+ self.train_queue = self._set_train_queue()
self.last_trade_database_summary: DataFrame = {}
self.current_trade_database_summary: DataFrame = {}
self.analysis_lock = Lock()
@@ -99,7 +102,7 @@ class IFreqaiModel(ABC):
"""
return ({})
- def assert_config(self, config: Dict[str, Any]) -> None:
+ def assert_config(self, config: Config) -> None:
if not config.get("freqai", {}):
raise OperationalException("No freqai parameters found in configuration file.")
@@ -181,29 +184,40 @@ class IFreqaiModel(ABC):
"""
while not self._stop_event.is_set():
time.sleep(1)
- for pair in self.config.get("exchange", {}).get("pair_whitelist"):
+ pair = self.train_queue[0]
- (_, trained_timestamp, _) = self.dd.get_pair_dict_info(pair)
+ # ensure pair is avaialble in dp
+ if pair not in strategy.dp.current_whitelist():
+ self.train_queue.popleft()
+ logger.warning(f'{pair} not in current whitelist, removing from train queue.')
+ continue
- if self.dd.pair_dict[pair]["priority"] != 1:
- continue
- dk = FreqaiDataKitchen(self.config, self.live, pair)
- dk.set_paths(pair, trained_timestamp)
- (
- retrain,
- new_trained_timerange,
- data_load_timerange,
- ) = dk.check_if_new_training_required(trained_timestamp)
- dk.set_paths(pair, new_trained_timerange.stopts)
+ (_, trained_timestamp, _) = self.dd.get_pair_dict_info(pair)
- if retrain:
- self.train_timer('start')
+ dk = FreqaiDataKitchen(self.config, self.live, pair)
+ dk.set_paths(pair, trained_timestamp)
+ (
+ retrain,
+ new_trained_timerange,
+ data_load_timerange,
+ ) = dk.check_if_new_training_required(trained_timestamp)
+ dk.set_paths(pair, new_trained_timerange.stopts)
+
+ if retrain:
+ self.train_timer('start')
+ try:
self.extract_data_and_train_model(
new_trained_timerange, pair, strategy, dk, data_load_timerange
)
- self.train_timer('stop')
+ except Exception as msg:
+ logger.warning(f'Training {pair} raised exception {msg}, skipping.')
- self.dd.save_historic_predictions_to_disk()
+ self.train_timer('stop')
+
+ # only rotate the queue after the first has been trained.
+ self.train_queue.rotate(-1)
+
+ self.dd.save_historic_predictions_to_disk()
def start_backtesting(
self, dataframe: DataFrame, metadata: dict, dk: FreqaiDataKitchen
@@ -230,7 +244,8 @@ class IFreqaiModel(ABC):
# following tr_train. Both of these windows slide through the
# entire backtest
for tr_train, tr_backtest in zip(dk.training_timeranges, dk.backtesting_timeranges):
- (_, _, _) = self.dd.get_pair_dict_info(metadata["pair"])
+ pair = metadata["pair"]
+ (_, _, _) = self.dd.get_pair_dict_info(pair)
train_it += 1
total_trains = len(dk.backtesting_timeranges)
self.training_timerange = tr_train
@@ -245,37 +260,37 @@ class IFreqaiModel(ABC):
tr_train.stopts,
tz=timezone.utc).strftime(DATETIME_PRINT_FORMAT)
logger.info(
- f"Training {metadata['pair']}, {self.pair_it}/{self.total_pairs} pairs"
+ f"Training {pair}, {self.pair_it}/{self.total_pairs} pairs"
f" from {tr_train_startts_str} to {tr_train_stopts_str}, {train_it}/{total_trains} "
"trains"
)
trained_timestamp_int = int(trained_timestamp.stopts)
dk.data_path = Path(
- dk.full_path
- /
- f"sub-train-{metadata['pair'].split('/')[0]}_{trained_timestamp_int}"
+ dk.full_path / f"sub-train-{pair.split('/')[0]}_{trained_timestamp_int}"
)
- dk.set_new_model_names(metadata["pair"], trained_timestamp)
+ dk.set_new_model_names(pair, trained_timestamp)
if dk.check_if_backtest_prediction_exists():
+ self.dd.load_metadata(dk)
+ self.check_if_feature_list_matches_strategy(dataframe_train, dk)
append_df = dk.get_backtesting_prediction()
dk.append_predictions(append_df)
else:
if not self.model_exists(
- metadata["pair"], dk, trained_timestamp=trained_timestamp_int
+ pair, dk, trained_timestamp=trained_timestamp_int
):
dk.find_features(dataframe_train)
- self.model = self.train(dataframe_train, metadata["pair"], dk)
- self.dd.pair_dict[metadata["pair"]]["trained_timestamp"] = int(
+ self.model = self.train(dataframe_train, pair, dk)
+ self.dd.pair_dict[pair]["trained_timestamp"] = int(
trained_timestamp.stopts)
if self.save_backtest_models:
logger.info('Saving backtest model to disk.')
- self.dd.save_data(self.model, metadata["pair"], dk)
+ self.dd.save_data(self.model, pair, dk)
else:
- self.model = self.dd.load_data(metadata["pair"], dk)
+ self.model = self.dd.load_data(pair, dk)
self.check_if_feature_list_matches_strategy(dataframe_train, dk)
@@ -416,14 +431,16 @@ class IFreqaiModel(ABC):
if "training_features_list_raw" in dk.data:
feature_list = dk.data["training_features_list_raw"]
else:
- feature_list = dk.training_features_list
+ feature_list = dk.data['training_features_list']
if dk.training_features_list != feature_list:
raise OperationalException(
"Trying to access pretrained model with `identifier` "
"but found different features furnished by current strategy."
"Change `identifier` to train from scratch, or ensure the"
"strategy is furnishing the same features as the pretrained"
- "model"
+ "model. In case of --strategy-list, please be aware that FreqAI "
+ "requires all strategies to maintain identical "
+ "populate_any_indicator() functions"
)
def data_cleaning_train(self, dk: FreqaiDataKitchen) -> None:
@@ -557,11 +574,11 @@ class IFreqaiModel(ABC):
self.dd.pair_dict[pair]["trained_timestamp"] = new_trained_timerange.stopts
dk.set_new_model_names(pair, new_trained_timerange)
- self.dd.pair_dict[pair]["first"] = False
- if self.dd.pair_dict[pair]["priority"] == 1 and self.scanning:
- self.dd.pair_to_end_of_training_queue(pair)
self.dd.save_data(model, pair, dk)
+ if self.freqai_info["feature_parameters"].get("plot_feature_importance", False):
+ plot_feature_importance(model, pair, dk)
+
if self.freqai_info.get("purge_old_models", False):
self.dd.purge_old_models()
@@ -685,6 +702,32 @@ class IFreqaiModel(ABC):
return init_model
+ def _set_train_queue(self):
+ """
+ Sets train queue from existing train timestamps if they exist
+ otherwise it sets the train queue based on the provided whitelist.
+ """
+ current_pairlist = self.config.get("exchange", {}).get("pair_whitelist")
+ if not self.dd.pair_dict:
+ logger.info('Set fresh train queue from whitelist. '
+ f'Queue: {current_pairlist}')
+ return deque(current_pairlist)
+
+ best_queue = deque()
+
+ pair_dict_sorted = sorted(self.dd.pair_dict.items(),
+ key=lambda k: k[1]['trained_timestamp'])
+ for pair in pair_dict_sorted:
+ if pair[0] in current_pairlist:
+ best_queue.append(pair[0])
+ for pair in current_pairlist:
+ if pair not in best_queue:
+ best_queue.appendleft(pair)
+
+ logger.info('Set existing queue from trained timestamps. '
+ f'Best approximation queue: {best_queue}')
+ return best_queue
+
def spice_rack(self, indicator: str, dataframe: DataFrame,
metadata: dict, strategy: IStrategy) -> NDArray:
if not self.spice_rack_open:
diff --git a/freqtrade/freqai/utils.py b/freqtrade/freqai/utils.py
index 60e0d0ffe..bbe846098 100644
--- a/freqtrade/freqai/utils.py
+++ b/freqtrade/freqai/utils.py
@@ -10,11 +10,13 @@ from scipy.signal import argrelextrema
from technical import qtpylib
from freqtrade.configuration import TimeRange
+from freqtrade.constants import Config
from freqtrade.data.dataprovider import DataProvider
from freqtrade.data.history.history_utils import refresh_backtest_ohlcv_data
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import Exchange, timeframe_to_seconds
from freqtrade.exchange.exchange import market_is_active
+from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
from freqtrade.plugins.pairlist.pairlist_helpers import dynamic_expand_pairlist
from freqtrade.strategy import merge_informative_pair
@@ -22,7 +24,7 @@ from freqtrade.strategy import merge_informative_pair
logger = logging.getLogger(__name__)
-def download_all_data_for_training(dp: DataProvider, config: dict) -> None:
+def download_all_data_for_training(dp: DataProvider, config: Config) -> None:
"""
Called only once upon start of bot to download the necessary data for
populating indicators and training the model.
@@ -56,9 +58,7 @@ def download_all_data_for_training(dp: DataProvider, config: dict) -> None:
)
-def get_required_data_timerange(
- config: dict
-) -> TimeRange:
+def get_required_data_timerange(config: Config) -> TimeRange:
"""
Used to compute the required data download time range
for auto data-download in FreqAI
@@ -226,7 +226,7 @@ def setup_freqai_spice_rack(config: dict, exchange: Optional[Exchange]) -> Dict[
return config
# Keep below for when we wish to download heterogeneously lengthed data for FreqAI.
-# def download_all_data_for_training(dp: DataProvider, config: dict) -> None:
+# def download_all_data_for_training(dp: DataProvider, config: Config) -> None:
# """
# Called only once upon start of bot to download the necessary data for
# populating indicators and training a FreqAI model.
@@ -272,3 +272,58 @@ def setup_freqai_spice_rack(config: dict, exchange: Optional[Exchange]) -> Dict[
# trading_mode=config.get("trading_mode", "spot"),
# prepend=config.get("prepend_data", False),
# )
+
+
+def plot_feature_importance(model: Any, pair: str, dk: FreqaiDataKitchen,
+ count_max: int = 25) -> None:
+ """
+ Plot Best and worst features by importance for a single sub-train.
+ :param model: Any = A model which was `fit` using a common library
+ such as catboost or lightgbm
+ :param pair: str = pair e.g. BTC/USD
+ :param dk: FreqaiDataKitchen = non-persistent data container for current coin/loop
+ :param count_max: int = the amount of features to be loaded per column
+ """
+ from freqtrade.plot.plotting import go, make_subplots, store_plot_file
+
+ # Extract feature importance from model
+ models = {}
+ if 'FreqaiMultiOutputRegressor' in str(model.__class__):
+ for estimator, label in zip(model.estimators_, dk.label_list):
+ models[label] = estimator
+ else:
+ models[dk.label_list[0]] = model
+
+ for label in models:
+ mdl = models[label]
+ if "catboost.core" in str(mdl.__class__):
+ feature_importance = mdl.get_feature_importance()
+ elif "lightgbm.sklearn" or "xgb" in str(mdl.__class__):
+ feature_importance = mdl.feature_importances_
+ else:
+ logger.info('Model type not support for generating feature importances.')
+ return
+
+ # Data preparation
+ fi_df = pd.DataFrame({
+ "feature_names": np.array(dk.training_features_list),
+ "feature_importance": np.array(feature_importance)
+ })
+ fi_df_top = fi_df.nlargest(count_max, "feature_importance")[::-1]
+ fi_df_worst = fi_df.nsmallest(count_max, "feature_importance")[::-1]
+
+ # Plotting
+ def add_feature_trace(fig, fi_df, col):
+ return fig.add_trace(
+ go.Bar(
+ x=fi_df["feature_importance"],
+ y=fi_df["feature_names"],
+ orientation='h', showlegend=False
+ ), row=1, col=col
+ )
+ fig = make_subplots(rows=1, cols=2, horizontal_spacing=0.5)
+ fig = add_feature_trace(fig, fi_df_top, 1)
+ fig = add_feature_trace(fig, fi_df_worst, 2)
+ fig.update_layout(title_text=f"Best and worst features by importance {pair}")
+ label = label.replace('&', '').replace('%', '') # escape two FreqAI specific characters
+ store_plot_file(fig, f"{dk.model_filename}-{label}.html", dk.data_path)
diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py
index 3eaec5c98..72b88a82f 100644
--- a/freqtrade/freqtradebot.py
+++ b/freqtrade/freqtradebot.py
@@ -11,9 +11,9 @@ from typing import Any, Dict, List, Optional, Tuple
from schedule import Scheduler
-from freqtrade import __version__, constants
+from freqtrade import constants
from freqtrade.configuration import validate_config_consistency
-from freqtrade.constants import BuySell, LongShort
+from freqtrade.constants import BuySell, Config, LongShort
from freqtrade.data.converter import order_book_to_dataframe
from freqtrade.data.dataprovider import DataProvider
from freqtrade.edge import Edge
@@ -29,6 +29,7 @@ from freqtrade.plugins.pairlistmanager import PairListManager
from freqtrade.plugins.protectionmanager import ProtectionManager
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
from freqtrade.rpc import RPCManager
+from freqtrade.rpc.external_message_consumer import ExternalMessageConsumer
from freqtrade.strategy.interface import IStrategy
from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
from freqtrade.util import FtPrecise
@@ -44,7 +45,7 @@ class FreqtradeBot(LoggingMixin):
This is from here the bot start its logic.
"""
- def __init__(self, config: Dict[str, Any]) -> None:
+ def __init__(self, config: Config) -> None:
"""
Init all variables and objects the bot needs to work
:param config: configuration dict, you can use Configuration.get_config()
@@ -52,8 +53,6 @@ class FreqtradeBot(LoggingMixin):
"""
self.active_pair_whitelist: List[str] = []
- logger.info('Starting freqtrade %s', __version__)
-
# Init bot state
self.state = State.STOPPED
@@ -74,6 +73,8 @@ class FreqtradeBot(LoggingMixin):
PairLocks.timeframe = self.config['timeframe']
+ self.pairlists = PairListManager(self.exchange, self.config)
+
# RPC runs in separate threads, can start handling external commands just after
# initialization, even before Freqtradebot has a chance to start its throttling,
# so anything in the Freqtradebot instance should be ready (initialized), including
@@ -81,9 +82,7 @@ class FreqtradeBot(LoggingMixin):
# Keep this at the end of this initialization method.
self.rpc: RPCManager = RPCManager(self)
- self.pairlists = PairListManager(self.exchange, self.config)
-
- self.dataprovider = DataProvider(self.config, self.exchange, self.pairlists)
+ self.dataprovider = DataProvider(self.config, self.exchange, self.pairlists, self.rpc)
# Attach Dataprovider to strategy instance
self.strategy.dp = self.dataprovider
@@ -94,6 +93,10 @@ class FreqtradeBot(LoggingMixin):
self.edge = Edge(self.config, self.exchange, self.strategy) if \
self.config.get('edge', {}).get('enabled', False) else None
+ # Init ExternalMessageConsumer if enabled
+ self.emc = ExternalMessageConsumer(self.config, self.dataprovider) if \
+ self.config.get('external_message_consumer', {}).get('enabled', False) else None
+
self.active_pair_whitelist = self._refresh_active_whitelist()
# Set initial bot state from config
@@ -153,9 +156,11 @@ class FreqtradeBot(LoggingMixin):
finally:
self.strategy.ft_bot_cleanup()
- self.rpc.cleanup()
- Trade.commit()
- self.exchange.close()
+ self.rpc.cleanup()
+ if self.emc:
+ self.emc.shutdown()
+ Trade.commit()
+ self.exchange.close()
def startup(self) -> None:
"""
@@ -256,6 +261,7 @@ class FreqtradeBot(LoggingMixin):
pairs that have open trades.
"""
# Refresh whitelist
+ _prev_whitelist = self.pairlists.whitelist
self.pairlists.refresh_pairlist()
_whitelist = self.pairlists.whitelist
@@ -268,6 +274,11 @@ class FreqtradeBot(LoggingMixin):
# Extend active-pair whitelist with pairs of open trades
# It ensures that candle (OHLCV) data are downloaded for open trades as well
_whitelist.extend([trade.pair for trade in trades if trade.pair not in _whitelist])
+
+ # Called last to include the included pairs
+ if _prev_whitelist != _whitelist:
+ self.rpc.send_msg({'type': RPCMessageType.WHITELIST, 'data': _whitelist})
+
return _whitelist
def get_free_open_trades(self) -> int:
@@ -596,7 +607,7 @@ class FreqtradeBot(LoggingMixin):
amount = trade.amount
if amount == 0.0:
- logger.info("Amount to sell is 0.0 due to exchange limits - not selling.")
+ logger.info("Amount to exit is 0.0 due to exchange limits - not exiting.")
return
remaining = (trade.amount - amount) * current_exit_rate
@@ -923,7 +934,7 @@ class FreqtradeBot(LoggingMixin):
'stake_amount': trade.stake_amount,
'stake_currency': self.config['stake_currency'],
'fiat_currency': self.config.get('fiat_display_currency', None),
- 'amount': order.safe_amount_after_fee if fill else order.amount,
+ 'amount': order.safe_amount_after_fee if fill else (order.amount or trade.amount),
'open_date': trade.open_date or datetime.utcnow(),
'current_rate': current_rate,
'sub_trade': sub_trade,
@@ -1599,14 +1610,14 @@ class FreqtradeBot(LoggingMixin):
# second condition is for mypy only; order will always be passed during sub trade
if sub_trade and order is not None:
amount = order.safe_filled if fill else order.amount
- profit_rate = order.safe_price
+ order_rate: float = order.safe_price
- profit = trade.calc_profit(rate=profit_rate, amount=amount, open_rate=trade.open_rate)
- profit_ratio = trade.calc_profit_ratio(profit_rate, amount, trade.open_rate)
+ profit = trade.calc_profit(rate=order_rate, amount=amount, open_rate=trade.open_rate)
+ profit_ratio = trade.calc_profit_ratio(order_rate, amount, trade.open_rate)
else:
- profit_rate = trade.close_rate if trade.close_rate else trade.close_rate_requested
- profit = trade.calc_profit(rate=profit_rate) + (0.0 if fill else trade.realized_profit)
- profit_ratio = trade.calc_profit_ratio(profit_rate)
+ order_rate = trade.close_rate if trade.close_rate else trade.close_rate_requested
+ profit = trade.calc_profit(rate=order_rate) + (0.0 if fill else trade.realized_profit)
+ profit_ratio = trade.calc_profit_ratio(order_rate)
amount = trade.amount
gain = "profit" if profit_ratio > 0 else "loss"
@@ -1619,11 +1630,12 @@ class FreqtradeBot(LoggingMixin):
'leverage': trade.leverage,
'direction': 'Short' if trade.is_short else 'Long',
'gain': gain,
- 'limit': profit_rate,
+ 'limit': order_rate, # Deprecated
+ 'order_rate': order_rate,
'order_type': order_type,
'amount': amount,
'open_rate': trade.open_rate,
- 'close_rate': profit_rate,
+ 'close_rate': order_rate,
'current_rate': current_rate,
'profit_amount': profit,
'profit_ratio': profit_ratio,
diff --git a/freqtrade/loggers.py b/freqtrade/loggers.py
index e5b6ddbe9..f365053c9 100644
--- a/freqtrade/loggers.py
+++ b/freqtrade/loggers.py
@@ -2,8 +2,8 @@ import logging
import sys
from logging import Formatter
from logging.handlers import BufferingHandler, RotatingFileHandler, SysLogHandler
-from typing import Any, Dict
+from freqtrade.constants import Config
from freqtrade.exceptions import OperationalException
@@ -73,7 +73,7 @@ def setup_logging_pre() -> None:
)
-def setup_logging(config: Dict[str, Any]) -> None:
+def setup_logging(config: Config) -> None:
"""
Process -v/--verbose, --logfile options
"""
diff --git a/freqtrade/main.py b/freqtrade/main.py
index 162b4d029..754c536d0 100755
--- a/freqtrade/main.py
+++ b/freqtrade/main.py
@@ -12,6 +12,7 @@ from typing import Any, List
if sys.version_info < (3, 8): # pragma: no cover
sys.exit("Freqtrade requires Python version >= 3.8")
+from freqtrade import __version__
from freqtrade.commands import Arguments
from freqtrade.exceptions import FreqtradeException, OperationalException
from freqtrade.loggers import setup_logging_pre
@@ -34,6 +35,7 @@ def main(sysargv: List[str] = None) -> None:
# Call subcommand.
if 'func' in args:
+ logger.info(f'freqtrade {__version__}')
return_code = args['func'](args)
else:
# No subcommand was issued.
diff --git a/freqtrade/misc.py b/freqtrade/misc.py
index c3968e61c..56b3fef0e 100644
--- a/freqtrade/misc.py
+++ b/freqtrade/misc.py
@@ -10,9 +10,11 @@ from typing import Any, Iterator, List
from typing.io import IO
from urllib.parse import urlparse
+import pandas
import rapidjson
from freqtrade.constants import DECIMAL_PER_COIN_FALLBACK, DECIMALS_PER_COIN
+from freqtrade.enums import SignalTagType, SignalType
logger = logging.getLogger(__name__)
@@ -249,3 +251,41 @@ def parse_db_uri_for_logging(uri: str):
return uri
pwd = parsed_db_uri.netloc.split(':')[1].split('@')[0]
return parsed_db_uri.geturl().replace(f':{pwd}@', ':*****@')
+
+
+def dataframe_to_json(dataframe: pandas.DataFrame) -> str:
+ """
+ Serialize a DataFrame for transmission over the wire using JSON
+ :param dataframe: A pandas DataFrame
+ :returns: A JSON string of the pandas DataFrame
+ """
+ return dataframe.to_json(orient='split')
+
+
+def json_to_dataframe(data: str) -> pandas.DataFrame:
+ """
+ Deserialize JSON into a DataFrame
+ :param data: A JSON string
+ :returns: A pandas DataFrame from the JSON string
+ """
+ dataframe = pandas.read_json(data, orient='split')
+ if 'date' in dataframe.columns:
+ dataframe['date'] = pandas.to_datetime(dataframe['date'], unit='ms', utc=True)
+
+ return dataframe
+
+
+def remove_entry_exit_signals(dataframe: pandas.DataFrame):
+ """
+ Remove Entry and Exit signals from a DataFrame
+
+ :param dataframe: The DataFrame to remove signals from
+ """
+ dataframe[SignalType.ENTER_LONG.value] = 0
+ dataframe[SignalType.EXIT_LONG.value] = 0
+ dataframe[SignalType.ENTER_SHORT.value] = 0
+ dataframe[SignalType.EXIT_SHORT.value] = 0
+ dataframe[SignalTagType.ENTER_TAG.value] = None
+ dataframe[SignalTagType.EXIT_TAG.value] = None
+
+ return dataframe
diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py
index f54d59b5a..a09dae232 100644
--- a/freqtrade/optimize/backtesting.py
+++ b/freqtrade/optimize/backtesting.py
@@ -15,7 +15,7 @@ from pandas import DataFrame
from freqtrade import constants
from freqtrade.configuration import TimeRange, validate_config_consistency
-from freqtrade.constants import DATETIME_PRINT_FORMAT, LongShort
+from freqtrade.constants import DATETIME_PRINT_FORMAT, Config, LongShort
from freqtrade.data import history
from freqtrade.data.btanalysis import find_existing_backtest_stats, trade_list_to_dataframe
from freqtrade.data.converter import trim_dataframe, trim_dataframes
@@ -70,7 +70,7 @@ class Backtesting:
backtesting.start()
"""
- def __init__(self, config: Dict[str, Any]) -> None:
+ def __init__(self, config: Config) -> None:
LoggingMixin.show_output = False
self.config = config
@@ -95,8 +95,8 @@ class Backtesting:
if self.config.get('strategy_list'):
if self.config.get('freqai', {}).get('enabled', False):
- raise OperationalException(
- "You can't use strategy_list and freqai at the same time.")
+ logger.warning("Using --strategy-list with FreqAI REQUIRES all strategies "
+ "to have identical populate_any_indicators.")
for strat in list(self.config['strategy_list']):
stratconf = deepcopy(self.config)
stratconf['strategy'] = strat
@@ -143,9 +143,14 @@ class Backtesting:
# Get maximum required startup period
self.required_startup = max([strat.startup_candle_count for strat in self.strategylist])
+ self.exchange.validate_required_startup_candles(self.required_startup, self.timeframe)
+
+ if self.config.get('freqai', {}).get('enabled', False):
+ # For FreqAI, increase the required_startup to includes the training data
+ self.required_startup = self.dataprovider.get_required_startup(self.timeframe)
+
# Add maximum startup candle count to configuration for informative pairs support
self.config['startup_candle_count'] = self.required_startup
- self.exchange.validate_required_startup_candles(self.required_startup, self.timeframe)
self.trading_mode: TradingMode = config.get('trading_mode', TradingMode.SPOT)
# strategies which define "can_short=True" will fail to load in Spot mode.
@@ -221,7 +226,7 @@ class Backtesting:
pairs=self.pairlists.whitelist,
timeframe=self.timeframe,
timerange=self.timerange,
- startup_candles=self.dataprovider.get_required_startup(self.timeframe),
+ startup_candles=self.config['startup_candle_count'],
fail_without_data=True,
data_format=self.config.get('dataformat_ohlcv', 'json'),
candle_type=self.config.get('candle_type_def', CandleType.SPOT)
diff --git a/freqtrade/optimize/edge_cli.py b/freqtrade/optimize/edge_cli.py
index aa3b02529..2eb1c53f5 100644
--- a/freqtrade/optimize/edge_cli.py
+++ b/freqtrade/optimize/edge_cli.py
@@ -4,10 +4,10 @@
This module contains the edge backtesting interface
"""
import logging
-from typing import Any, Dict
from freqtrade import constants
from freqtrade.configuration import TimeRange, validate_config_consistency
+from freqtrade.constants import Config
from freqtrade.data.dataprovider import DataProvider
from freqtrade.edge import Edge
from freqtrade.optimize.optimize_reports import generate_edge_table
@@ -26,7 +26,7 @@ class EdgeCli:
edge.start()
"""
- def __init__(self, config: Dict[str, Any]) -> None:
+ def __init__(self, config: Config) -> None:
self.config = config
# Ensure using dry-run
diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py
index f15e0b7d8..aef8405d5 100644
--- a/freqtrade/optimize/hyperopt.py
+++ b/freqtrade/optimize/hyperopt.py
@@ -21,7 +21,7 @@ from joblib import Parallel, cpu_count, delayed, dump, load, wrap_non_picklable_
from joblib.externals import cloudpickle
from pandas import DataFrame
-from freqtrade.constants import DATETIME_PRINT_FORMAT, FTHYPT_FILEVERSION, LAST_BT_RESULT_FN
+from freqtrade.constants import DATETIME_PRINT_FORMAT, FTHYPT_FILEVERSION, LAST_BT_RESULT_FN, Config
from freqtrade.data.converter import trim_dataframes
from freqtrade.data.history import get_timerange
from freqtrade.enums import HyperoptState
@@ -66,7 +66,7 @@ class Hyperopt:
hyperopt.start()
"""
- def __init__(self, config: Dict[str, Any]) -> None:
+ def __init__(self, config: Config) -> None:
self.buy_space: List[Dimension] = []
self.sell_space: List[Dimension] = []
self.protection_space: List[Dimension] = []
@@ -132,7 +132,7 @@ class Hyperopt:
self.print_json = self.config.get('print_json', False)
@staticmethod
- def get_lock_filename(config: Dict[str, Any]) -> str:
+ def get_lock_filename(config: Config) -> str:
return str(config['user_data_dir'] / 'hyperopt.lock')
diff --git a/freqtrade/optimize/hyperopt_interface.py b/freqtrade/optimize/hyperopt_interface.py
index b1c68caca..a7c64ffb0 100644
--- a/freqtrade/optimize/hyperopt_interface.py
+++ b/freqtrade/optimize/hyperopt_interface.py
@@ -10,6 +10,7 @@ from typing import Dict, List, Union
from sklearn.base import RegressorMixin
from skopt.space import Categorical, Dimension, Integer
+from freqtrade.constants import Config
from freqtrade.exchange import timeframe_to_minutes
from freqtrade.misc import round_dict
from freqtrade.optimize.space import SKDecimal
@@ -32,7 +33,7 @@ class IHyperOpt(ABC):
timeframe: str
strategy: IStrategy
- def __init__(self, config: dict) -> None:
+ def __init__(self, config: Config) -> None:
self.config = config
# Assign timeframe to be used in hyperopt
diff --git a/freqtrade/optimize/hyperopt_loss/hyperopt_loss_calmar.py b/freqtrade/optimize/hyperopt_loss/hyperopt_loss_calmar.py
index ea6c151e5..2b591824f 100644
--- a/freqtrade/optimize/hyperopt_loss/hyperopt_loss_calmar.py
+++ b/freqtrade/optimize/hyperopt_loss/hyperopt_loss_calmar.py
@@ -10,6 +10,7 @@ from typing import Any, Dict
from pandas import DataFrame
+from freqtrade.constants import Config
from freqtrade.data.metrics import calculate_max_drawdown
from freqtrade.optimize.hyperopt import IHyperOptLoss
@@ -27,7 +28,7 @@ class CalmarHyperOptLoss(IHyperOptLoss):
trade_count: int,
min_date: datetime,
max_date: datetime,
- config: Dict,
+ config: Config,
processed: Dict[str, DataFrame],
backtest_stats: Dict[str, Any],
*args,
diff --git a/freqtrade/optimize/hyperopt_loss/hyperopt_loss_max_drawdown_relative.py b/freqtrade/optimize/hyperopt_loss/hyperopt_loss_max_drawdown_relative.py
index 3182afb47..669d12ddf 100644
--- a/freqtrade/optimize/hyperopt_loss/hyperopt_loss_max_drawdown_relative.py
+++ b/freqtrade/optimize/hyperopt_loss/hyperopt_loss_max_drawdown_relative.py
@@ -4,10 +4,9 @@ MaxDrawDownRelativeHyperOptLoss
This module defines the alternative HyperOptLoss class which can be used for
Hyperoptimization.
"""
-from typing import Dict
-
from pandas import DataFrame
+from freqtrade.constants import Config
from freqtrade.data.metrics import calculate_underwater
from freqtrade.optimize.hyperopt import IHyperOptLoss
@@ -22,7 +21,7 @@ class MaxDrawDownRelativeHyperOptLoss(IHyperOptLoss):
"""
@staticmethod
- def hyperopt_loss_function(results: DataFrame, config: Dict,
+ def hyperopt_loss_function(results: DataFrame, config: Config,
*args, **kwargs) -> float:
"""
diff --git a/freqtrade/optimize/hyperopt_loss_interface.py b/freqtrade/optimize/hyperopt_loss_interface.py
index 8366dcc4f..d7b30dfd3 100644
--- a/freqtrade/optimize/hyperopt_loss_interface.py
+++ b/freqtrade/optimize/hyperopt_loss_interface.py
@@ -9,6 +9,8 @@ from typing import Any, Dict
from pandas import DataFrame
+from freqtrade.constants import Config
+
class IHyperOptLoss(ABC):
"""
@@ -21,7 +23,7 @@ class IHyperOptLoss(ABC):
@abstractmethod
def hyperopt_loss_function(*, results: DataFrame, trade_count: int,
min_date: datetime, max_date: datetime,
- config: Dict, processed: Dict[str, DataFrame],
+ config: Config, processed: Dict[str, DataFrame],
backtest_stats: Dict[str, Any],
**kwargs) -> float:
"""
diff --git a/freqtrade/optimize/hyperopt_tools.py b/freqtrade/optimize/hyperopt_tools.py
index 9b022d519..65bdc4db5 100755
--- a/freqtrade/optimize/hyperopt_tools.py
+++ b/freqtrade/optimize/hyperopt_tools.py
@@ -12,7 +12,7 @@ import tabulate
from colorama import Fore, Style
from pandas import isna, json_normalize
-from freqtrade.constants import FTHYPT_FILEVERSION, USERPATH_STRATEGIES
+from freqtrade.constants import FTHYPT_FILEVERSION, USERPATH_STRATEGIES, Config
from freqtrade.enums import HyperoptState
from freqtrade.exceptions import OperationalException
from freqtrade.misc import deep_merge_dicts, round_coin_value, round_dict, safe_value_fallback2
@@ -45,7 +45,7 @@ class HyperoptStateContainer():
class HyperoptTools():
@staticmethod
- def get_strategy_filename(config: Dict, strategy_name: str) -> Optional[Path]:
+ def get_strategy_filename(config: Config, strategy_name: str) -> Optional[Path]:
"""
Get Strategy-location (filename) from strategy_name
"""
@@ -81,7 +81,7 @@ class HyperoptTools():
)
@staticmethod
- def try_export_params(config: Dict[str, Any], strategy_name: str, params: Dict):
+ def try_export_params(config: Config, strategy_name: str, params: Dict):
if params.get(FTHYPT_FILEVERSION, 1) >= 2 and not config.get('disableparamexport', False):
# Export parameters ...
fn = HyperoptTools.get_strategy_filename(config, strategy_name)
@@ -91,7 +91,7 @@ class HyperoptTools():
logger.warning("Strategy not found, not exporting parameter file.")
@staticmethod
- def has_space(config: Dict[str, Any], space: str) -> bool:
+ def has_space(config: Config, space: str) -> bool:
"""
Tell if the space value is contained in the configuration
"""
@@ -131,7 +131,7 @@ class HyperoptTools():
return False
@staticmethod
- def load_filtered_results(results_file: Path, config: Dict[str, Any]) -> Tuple[List, int]:
+ def load_filtered_results(results_file: Path, config: Config) -> Tuple[List, int]:
filteroptions = {
'only_best': config.get('hyperopt_list_best', False),
'only_profitable': config.get('hyperopt_list_profitable', False),
@@ -346,7 +346,7 @@ class HyperoptTools():
return trials
@staticmethod
- def get_result_table(config: dict, results: list, total_epochs: int, highlight_best: bool,
+ def get_result_table(config: Config, results: list, total_epochs: int, highlight_best: bool,
print_colorized: bool, remove_header: int) -> str:
"""
Log result table
@@ -444,7 +444,7 @@ class HyperoptTools():
return table
@staticmethod
- def export_csv_file(config: dict, results: list, csv_file: str) -> None:
+ def export_csv_file(config: Config, results: list, csv_file: str) -> None:
"""
Log result to csv-file
"""
diff --git a/freqtrade/optimize/optimize_reports.py b/freqtrade/optimize/optimize_reports.py
index fa6c3f161..6c4dbcfef 100644
--- a/freqtrade/optimize/optimize_reports.py
+++ b/freqtrade/optimize/optimize_reports.py
@@ -7,7 +7,8 @@ from typing import Any, Dict, List, Union
from pandas import DataFrame, to_datetime
from tabulate import tabulate
-from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN, UNLIMITED_STAKE_AMOUNT
+from freqtrade.constants import (DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN, UNLIMITED_STAKE_AMOUNT,
+ Config)
from freqtrade.data.metrics import (calculate_cagr, calculate_csum, calculate_market_change,
calculate_max_drawdown)
from freqtrade.misc import decimals_per_coin, file_dump_joblib, file_dump_json, round_coin_value
@@ -898,7 +899,7 @@ def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency:
print()
-def show_backtest_results(config: Dict, backtest_stats: Dict):
+def show_backtest_results(config: Config, backtest_stats: Dict):
stake_currency = config['stake_currency']
for strategy, results in backtest_stats['strategy'].items():
@@ -918,7 +919,7 @@ def show_backtest_results(config: Dict, backtest_stats: Dict):
print('\nFor more details, please look at the detail tables above')
-def show_sorted_pairlist(config: Dict, backtest_stats: Dict):
+def show_sorted_pairlist(config: Config, backtest_stats: Dict):
if config.get('backtest_show_pair_list', False):
for strategy, results in backtest_stats['strategy'].items():
print(f"Pairs for Strategy {strategy}: \n[")
diff --git a/freqtrade/plot/plotting.py b/freqtrade/plot/plotting.py
index f8e95300a..9c8787242 100644
--- a/freqtrade/plot/plotting.py
+++ b/freqtrade/plot/plotting.py
@@ -1,10 +1,11 @@
import logging
from pathlib import Path
-from typing import Any, Dict, List, Optional
+from typing import Dict, List, Optional
import pandas as pd
from freqtrade.configuration import TimeRange
+from freqtrade.constants import Config
from freqtrade.data.btanalysis import (analyze_trade_parallelism, extract_trades_of_period,
load_trades)
from freqtrade.data.converter import trim_dataframe
@@ -618,7 +619,7 @@ def store_plot_file(fig, filename: str, directory: Path, auto_open: bool = False
logger.info(f"Stored plot as {_filename}")
-def load_and_plot_trades(config: Dict[str, Any]):
+def load_and_plot_trades(config: Config):
"""
From configuration provided
- Initializes plot-script
@@ -666,7 +667,7 @@ def load_and_plot_trades(config: Dict[str, Any]):
logger.info('End of plotting process. %s plots generated', pair_counter)
-def plot_profit(config: Dict[str, Any]) -> None:
+def plot_profit(config: Config) -> None:
"""
Plots the total profit for all pairs.
Note, the profit calculation isn't realistic.
diff --git a/freqtrade/plugins/pairlist/AgeFilter.py b/freqtrade/plugins/pairlist/AgeFilter.py
index 13c992c87..70638936a 100644
--- a/freqtrade/plugins/pairlist/AgeFilter.py
+++ b/freqtrade/plugins/pairlist/AgeFilter.py
@@ -8,7 +8,7 @@ from typing import Any, Dict, List, Optional
import arrow
from pandas import DataFrame
-from freqtrade.constants import ListPairsWithTimeframes
+from freqtrade.constants import Config, ListPairsWithTimeframes
from freqtrade.exceptions import OperationalException
from freqtrade.misc import plural
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -21,7 +21,7 @@ logger = logging.getLogger(__name__)
class AgeFilter(IPairList):
def __init__(self, exchange, pairlistmanager,
- config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+ config: Config, pairlistconfig: Dict[str, Any],
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
diff --git a/freqtrade/plugins/pairlist/IPairList.py b/freqtrade/plugins/pairlist/IPairList.py
index 0155f918b..c02ba5ef5 100644
--- a/freqtrade/plugins/pairlist/IPairList.py
+++ b/freqtrade/plugins/pairlist/IPairList.py
@@ -6,6 +6,7 @@ from abc import ABC, abstractmethod, abstractproperty
from copy import deepcopy
from typing import Any, Dict, List
+from freqtrade.constants import Config
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import Exchange, market_is_active
from freqtrade.mixins import LoggingMixin
@@ -17,7 +18,7 @@ logger = logging.getLogger(__name__)
class IPairList(LoggingMixin, ABC):
def __init__(self, exchange: Exchange, pairlistmanager,
- config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+ config: Config, pairlistconfig: Dict[str, Any],
pairlist_pos: int) -> None:
"""
:param exchange: Exchange instance
diff --git a/freqtrade/plugins/pairlist/OffsetFilter.py b/freqtrade/plugins/pairlist/OffsetFilter.py
index e0f8414ef..149befdeb 100644
--- a/freqtrade/plugins/pairlist/OffsetFilter.py
+++ b/freqtrade/plugins/pairlist/OffsetFilter.py
@@ -4,6 +4,7 @@ Offset pair list filter
import logging
from typing import Any, Dict, List
+from freqtrade.constants import Config
from freqtrade.exceptions import OperationalException
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -14,7 +15,7 @@ logger = logging.getLogger(__name__)
class OffsetFilter(IPairList):
def __init__(self, exchange, pairlistmanager,
- config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+ config: Config, pairlistconfig: Dict[str, Any],
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
diff --git a/freqtrade/plugins/pairlist/PerformanceFilter.py b/freqtrade/plugins/pairlist/PerformanceFilter.py
index 8e0b407c3..c29b4f337 100644
--- a/freqtrade/plugins/pairlist/PerformanceFilter.py
+++ b/freqtrade/plugins/pairlist/PerformanceFilter.py
@@ -6,6 +6,7 @@ from typing import Any, Dict, List
import pandas as pd
+from freqtrade.constants import Config
from freqtrade.persistence import Trade
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -16,7 +17,7 @@ logger = logging.getLogger(__name__)
class PerformanceFilter(IPairList):
def __init__(self, exchange, pairlistmanager,
- config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+ config: Config, pairlistconfig: Dict[str, Any],
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
diff --git a/freqtrade/plugins/pairlist/PrecisionFilter.py b/freqtrade/plugins/pairlist/PrecisionFilter.py
index 61150f03d..8f1c9b839 100644
--- a/freqtrade/plugins/pairlist/PrecisionFilter.py
+++ b/freqtrade/plugins/pairlist/PrecisionFilter.py
@@ -4,6 +4,7 @@ Precision pair list filter
import logging
from typing import Any, Dict
+from freqtrade.constants import Config
from freqtrade.exceptions import OperationalException
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -14,7 +15,7 @@ logger = logging.getLogger(__name__)
class PrecisionFilter(IPairList):
def __init__(self, exchange, pairlistmanager,
- config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+ config: Config, pairlistconfig: Dict[str, Any],
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
diff --git a/freqtrade/plugins/pairlist/PriceFilter.py b/freqtrade/plugins/pairlist/PriceFilter.py
index 009789eaf..f2952001a 100644
--- a/freqtrade/plugins/pairlist/PriceFilter.py
+++ b/freqtrade/plugins/pairlist/PriceFilter.py
@@ -4,6 +4,7 @@ Price pair list filter
import logging
from typing import Any, Dict
+from freqtrade.constants import Config
from freqtrade.exceptions import OperationalException
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -14,7 +15,7 @@ logger = logging.getLogger(__name__)
class PriceFilter(IPairList):
def __init__(self, exchange, pairlistmanager,
- config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+ config: Config, pairlistconfig: Dict[str, Any],
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
diff --git a/freqtrade/plugins/pairlist/ShuffleFilter.py b/freqtrade/plugins/pairlist/ShuffleFilter.py
index 663bba49b..b6b5fc3c8 100644
--- a/freqtrade/plugins/pairlist/ShuffleFilter.py
+++ b/freqtrade/plugins/pairlist/ShuffleFilter.py
@@ -5,6 +5,7 @@ import logging
import random
from typing import Any, Dict, List
+from freqtrade.constants import Config
from freqtrade.enums import RunMode
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -15,7 +16,7 @@ logger = logging.getLogger(__name__)
class ShuffleFilter(IPairList):
def __init__(self, exchange, pairlistmanager,
- config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+ config: Config, pairlistconfig: Dict[str, Any],
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
diff --git a/freqtrade/plugins/pairlist/SpreadFilter.py b/freqtrade/plugins/pairlist/SpreadFilter.py
index 43856b451..1f20af305 100644
--- a/freqtrade/plugins/pairlist/SpreadFilter.py
+++ b/freqtrade/plugins/pairlist/SpreadFilter.py
@@ -4,6 +4,7 @@ Spread pair list filter
import logging
from typing import Any, Dict
+from freqtrade.constants import Config
from freqtrade.exceptions import OperationalException
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -14,7 +15,7 @@ logger = logging.getLogger(__name__)
class SpreadFilter(IPairList):
def __init__(self, exchange, pairlistmanager,
- config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+ config: Config, pairlistconfig: Dict[str, Any],
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
diff --git a/freqtrade/plugins/pairlist/StaticPairList.py b/freqtrade/plugins/pairlist/StaticPairList.py
index 30fa474e4..83a0fa0c8 100644
--- a/freqtrade/plugins/pairlist/StaticPairList.py
+++ b/freqtrade/plugins/pairlist/StaticPairList.py
@@ -7,6 +7,7 @@ import logging
from copy import deepcopy
from typing import Any, Dict, List
+from freqtrade.constants import Config
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -16,7 +17,7 @@ logger = logging.getLogger(__name__)
class StaticPairList(IPairList):
def __init__(self, exchange, pairlistmanager,
- config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+ config: Config, pairlistconfig: Dict[str, Any],
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
diff --git a/freqtrade/plugins/pairlist/VolatilityFilter.py b/freqtrade/plugins/pairlist/VolatilityFilter.py
index bab44bdd1..c9af3a7b3 100644
--- a/freqtrade/plugins/pairlist/VolatilityFilter.py
+++ b/freqtrade/plugins/pairlist/VolatilityFilter.py
@@ -11,7 +11,7 @@ import numpy as np
from cachetools import TTLCache
from pandas import DataFrame
-from freqtrade.constants import ListPairsWithTimeframes
+from freqtrade.constants import Config, ListPairsWithTimeframes
from freqtrade.exceptions import OperationalException
from freqtrade.misc import plural
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -26,7 +26,7 @@ class VolatilityFilter(IPairList):
"""
def __init__(self, exchange, pairlistmanager,
- config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+ config: Config, pairlistconfig: Dict[str, Any],
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
diff --git a/freqtrade/plugins/pairlist/VolumePairList.py b/freqtrade/plugins/pairlist/VolumePairList.py
index d7cc6e5ec..9dcada291 100644
--- a/freqtrade/plugins/pairlist/VolumePairList.py
+++ b/freqtrade/plugins/pairlist/VolumePairList.py
@@ -9,7 +9,7 @@ from typing import Any, Dict, List
from cachetools import TTLCache
-from freqtrade.constants import ListPairsWithTimeframes
+from freqtrade.constants import Config, ListPairsWithTimeframes
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_prev_date
from freqtrade.misc import format_ms_time
@@ -25,7 +25,7 @@ SORT_VALUES = ['quoteVolume']
class VolumePairList(IPairList):
def __init__(self, exchange, pairlistmanager,
- config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+ config: Config, pairlistconfig: Dict[str, Any],
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
diff --git a/freqtrade/plugins/pairlist/pairlist_helpers.py b/freqtrade/plugins/pairlist/pairlist_helpers.py
index 0cec734fb..9ef3e4614 100644
--- a/freqtrade/plugins/pairlist/pairlist_helpers.py
+++ b/freqtrade/plugins/pairlist/pairlist_helpers.py
@@ -1,5 +1,7 @@
import re
-from typing import Any, Dict, List
+from typing import List
+
+from freqtrade.constants import Config
def expand_pairlist(wildcardpl: List[str], available_pairs: List[str],
@@ -42,7 +44,7 @@ def expand_pairlist(wildcardpl: List[str], available_pairs: List[str],
return result
-def dynamic_expand_pairlist(config: Dict[str, Any], markets: List[str]) -> List[str]:
+def dynamic_expand_pairlist(config: Config, markets: List[str]) -> List[str]:
expanded_pairs = expand_pairlist(config['pairs'], markets)
if config.get('freqai', {}).get('enabled', False):
corr_pairlist = config['freqai']['feature_parameters']['include_corr_pairlist']
diff --git a/freqtrade/plugins/pairlist/rangestabilityfilter.py b/freqtrade/plugins/pairlist/rangestabilityfilter.py
index f3e7bc0d6..1bc7ad48f 100644
--- a/freqtrade/plugins/pairlist/rangestabilityfilter.py
+++ b/freqtrade/plugins/pairlist/rangestabilityfilter.py
@@ -9,7 +9,7 @@ import arrow
from cachetools import TTLCache
from pandas import DataFrame
-from freqtrade.constants import ListPairsWithTimeframes
+from freqtrade.constants import Config, ListPairsWithTimeframes
from freqtrade.exceptions import OperationalException
from freqtrade.misc import plural
from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -21,7 +21,7 @@ logger = logging.getLogger(__name__)
class RangeStabilityFilter(IPairList):
def __init__(self, exchange, pairlistmanager,
- config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+ config: Config, pairlistconfig: Dict[str, Any],
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
@@ -100,23 +100,19 @@ class RangeStabilityFilter(IPairList):
if cached_res is not None:
return cached_res
- result = False
+ result = True
if daily_candles is not None and not daily_candles.empty:
highest_high = daily_candles['high'].max()
lowest_low = daily_candles['low'].min()
pct_change = ((highest_high - lowest_low) / lowest_low) if lowest_low > 0 else 0
- if pct_change >= self._min_rate_of_change:
- result = True
- else:
+ if pct_change < self._min_rate_of_change:
self.log_once(f"Removed {pair} from whitelist, because rate of change "
f"over {self._days} {plural(self._days, 'day')} is {pct_change:.3f}, "
f"which is below the threshold of {self._min_rate_of_change}.",
logger.info)
result = False
if self._max_rate_of_change:
- if pct_change <= self._max_rate_of_change:
- result = True
- else:
+ if pct_change > self._max_rate_of_change:
self.log_once(
f"Removed {pair} from whitelist, because rate of change "
f"over {self._days} {plural(self._days, 'day')} is {pct_change:.3f}, "
diff --git a/freqtrade/plugins/pairlistmanager.py b/freqtrade/plugins/pairlistmanager.py
index 3ddad4a5e..e01abb297 100644
--- a/freqtrade/plugins/pairlistmanager.py
+++ b/freqtrade/plugins/pairlistmanager.py
@@ -7,7 +7,7 @@ from typing import Dict, List
from cachetools import TTLCache, cached
-from freqtrade.constants import ListPairsWithTimeframes
+from freqtrade.constants import Config, ListPairsWithTimeframes
from freqtrade.enums import CandleType
from freqtrade.exceptions import OperationalException
from freqtrade.mixins import LoggingMixin
@@ -21,7 +21,7 @@ logger = logging.getLogger(__name__)
class PairListManager(LoggingMixin):
- def __init__(self, exchange, config: dict) -> None:
+ def __init__(self, exchange, config: Config) -> None:
self._exchange = exchange
self._config = config
self._whitelist = self._config['exchange'].get('pair_whitelist')
diff --git a/freqtrade/plugins/protectionmanager.py b/freqtrade/plugins/protectionmanager.py
index d33294fa7..54432e677 100644
--- a/freqtrade/plugins/protectionmanager.py
+++ b/freqtrade/plugins/protectionmanager.py
@@ -5,7 +5,7 @@ import logging
from datetime import datetime, timezone
from typing import Dict, List, Optional
-from freqtrade.constants import LongShort
+from freqtrade.constants import Config, LongShort
from freqtrade.persistence import PairLocks
from freqtrade.persistence.models import PairLock
from freqtrade.plugins.protections import IProtection
@@ -17,7 +17,7 @@ logger = logging.getLogger(__name__)
class ProtectionManager():
- def __init__(self, config: Dict, protections: List) -> None:
+ def __init__(self, config: Config, protections: List) -> None:
self._config = config
self._protection_handlers: List[IProtection] = []
diff --git a/freqtrade/plugins/protections/iprotection.py b/freqtrade/plugins/protections/iprotection.py
index 890988226..8e1589217 100644
--- a/freqtrade/plugins/protections/iprotection.py
+++ b/freqtrade/plugins/protections/iprotection.py
@@ -5,7 +5,7 @@ from dataclasses import dataclass
from datetime import datetime, timedelta, timezone
from typing import Any, Dict, List, Optional
-from freqtrade.constants import LongShort
+from freqtrade.constants import Config, LongShort
from freqtrade.exchange import timeframe_to_minutes
from freqtrade.misc import plural
from freqtrade.mixins import LoggingMixin
@@ -30,7 +30,7 @@ class IProtection(LoggingMixin, ABC):
# Can stop trading for one pair
has_local_stop: bool = False
- def __init__(self, config: Dict[str, Any], protection_config: Dict[str, Any]) -> None:
+ def __init__(self, config: Config, protection_config: Dict[str, Any]) -> None:
self._config = config
self._protection_config = protection_config
self._stop_duration_candles: Optional[int] = None
diff --git a/freqtrade/plugins/protections/low_profit_pairs.py b/freqtrade/plugins/protections/low_profit_pairs.py
index 099242b8d..f638673fa 100644
--- a/freqtrade/plugins/protections/low_profit_pairs.py
+++ b/freqtrade/plugins/protections/low_profit_pairs.py
@@ -3,7 +3,7 @@ import logging
from datetime import datetime, timedelta
from typing import Any, Dict, Optional
-from freqtrade.constants import LongShort
+from freqtrade.constants import Config, LongShort
from freqtrade.persistence import Trade
from freqtrade.plugins.protections import IProtection, ProtectionReturn
@@ -16,7 +16,7 @@ class LowProfitPairs(IProtection):
has_global_stop: bool = False
has_local_stop: bool = True
- def __init__(self, config: Dict[str, Any], protection_config: Dict[str, Any]) -> None:
+ def __init__(self, config: Config, protection_config: Dict[str, Any]) -> None:
super().__init__(config, protection_config)
self._trade_limit = protection_config.get('trade_limit', 1)
diff --git a/freqtrade/plugins/protections/max_drawdown_protection.py b/freqtrade/plugins/protections/max_drawdown_protection.py
index e0b016cb8..8193dc7e4 100644
--- a/freqtrade/plugins/protections/max_drawdown_protection.py
+++ b/freqtrade/plugins/protections/max_drawdown_protection.py
@@ -5,7 +5,7 @@ from typing import Any, Dict, Optional
import pandas as pd
-from freqtrade.constants import LongShort
+from freqtrade.constants import Config, LongShort
from freqtrade.data.metrics import calculate_max_drawdown
from freqtrade.persistence import Trade
from freqtrade.plugins.protections import IProtection, ProtectionReturn
@@ -19,7 +19,7 @@ class MaxDrawdown(IProtection):
has_global_stop: bool = True
has_local_stop: bool = False
- def __init__(self, config: Dict[str, Any], protection_config: Dict[str, Any]) -> None:
+ def __init__(self, config: Config, protection_config: Dict[str, Any]) -> None:
super().__init__(config, protection_config)
self._trade_limit = protection_config.get('trade_limit', 1)
diff --git a/freqtrade/plugins/protections/stoploss_guard.py b/freqtrade/plugins/protections/stoploss_guard.py
index e80d13e9d..23ceebbc9 100644
--- a/freqtrade/plugins/protections/stoploss_guard.py
+++ b/freqtrade/plugins/protections/stoploss_guard.py
@@ -3,7 +3,7 @@ import logging
from datetime import datetime, timedelta
from typing import Any, Dict, Optional
-from freqtrade.constants import LongShort
+from freqtrade.constants import Config, LongShort
from freqtrade.enums import ExitType
from freqtrade.persistence import Trade
from freqtrade.plugins.protections import IProtection, ProtectionReturn
@@ -17,7 +17,7 @@ class StoplossGuard(IProtection):
has_global_stop: bool = True
has_local_stop: bool = True
- def __init__(self, config: Dict[str, Any], protection_config: Dict[str, Any]) -> None:
+ def __init__(self, config: Config, protection_config: Dict[str, Any]) -> None:
super().__init__(config, protection_config)
self._trade_limit = protection_config.get('trade_limit', 10)
diff --git a/freqtrade/resolvers/exchange_resolver.py b/freqtrade/resolvers/exchange_resolver.py
index a2f572ff2..54a488e8d 100644
--- a/freqtrade/resolvers/exchange_resolver.py
+++ b/freqtrade/resolvers/exchange_resolver.py
@@ -4,6 +4,7 @@ This module loads custom exchanges
import logging
import freqtrade.exchange as exchanges
+from freqtrade.constants import Config
from freqtrade.exchange import MAP_EXCHANGE_CHILDCLASS, Exchange
from freqtrade.resolvers import IResolver
@@ -18,7 +19,7 @@ class ExchangeResolver(IResolver):
object_type = Exchange
@staticmethod
- def load_exchange(exchange_name: str, config: dict, validate: bool = True,
+ def load_exchange(exchange_name: str, config: Config, validate: bool = True,
load_leverage_tiers: bool = False) -> Exchange:
"""
Load the custom class from config parameter
diff --git a/freqtrade/resolvers/freqaimodel_resolver.py b/freqtrade/resolvers/freqaimodel_resolver.py
index 5a847bb2b..aa5228ca1 100644
--- a/freqtrade/resolvers/freqaimodel_resolver.py
+++ b/freqtrade/resolvers/freqaimodel_resolver.py
@@ -5,9 +5,8 @@ This module load a custom model for freqai
"""
import logging
from pathlib import Path
-from typing import Dict
-from freqtrade.constants import USERPATH_FREQAIMODELS
+from freqtrade.constants import USERPATH_FREQAIMODELS, Config
from freqtrade.exceptions import OperationalException
from freqtrade.freqai.freqai_interface import IFreqaiModel
from freqtrade.resolvers import IResolver
@@ -29,7 +28,7 @@ class FreqaiModelResolver(IResolver):
)
@staticmethod
- def load_freqaimodel(config: Dict) -> IFreqaiModel:
+ def load_freqaimodel(config: Config) -> IFreqaiModel:
"""
Load the custom class from config parameter
:param config: configuration dictionary
diff --git a/freqtrade/resolvers/hyperopt_resolver.py b/freqtrade/resolvers/hyperopt_resolver.py
index bcfe5e1d8..d050c6fbc 100644
--- a/freqtrade/resolvers/hyperopt_resolver.py
+++ b/freqtrade/resolvers/hyperopt_resolver.py
@@ -5,9 +5,8 @@ This module load custom hyperopt
"""
import logging
from pathlib import Path
-from typing import Dict
-from freqtrade.constants import HYPEROPT_LOSS_BUILTIN, USERPATH_HYPEROPTS
+from freqtrade.constants import HYPEROPT_LOSS_BUILTIN, USERPATH_HYPEROPTS, Config
from freqtrade.exceptions import OperationalException
from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss
from freqtrade.resolvers import IResolver
@@ -26,7 +25,7 @@ class HyperOptLossResolver(IResolver):
initial_search_path = Path(__file__).parent.parent.joinpath('optimize/hyperopt_loss').resolve()
@staticmethod
- def load_hyperoptloss(config: Dict) -> IHyperOptLoss:
+ def load_hyperoptloss(config: Config) -> IHyperOptLoss:
"""
Load the custom class from config parameter
:param config: configuration dictionary
diff --git a/freqtrade/resolvers/iresolver.py b/freqtrade/resolvers/iresolver.py
index b99e7a94b..9682e1c2b 100644
--- a/freqtrade/resolvers/iresolver.py
+++ b/freqtrade/resolvers/iresolver.py
@@ -10,6 +10,7 @@ import sys
from pathlib import Path
from typing import Any, Dict, Iterator, List, Optional, Tuple, Type, Union
+from freqtrade.constants import Config
from freqtrade.exceptions import OperationalException
@@ -43,7 +44,7 @@ class IResolver:
initial_search_path: Optional[Path]
@classmethod
- def build_search_paths(cls, config: Dict[str, Any], user_subdir: Optional[str] = None,
+ def build_search_paths(cls, config: Config, user_subdir: Optional[str] = None,
extra_dirs: List[str] = []) -> List[Path]:
abs_paths: List[Path] = []
@@ -153,7 +154,7 @@ class IResolver:
return None
@classmethod
- def load_object(cls, object_name: str, config: dict, *, kwargs: dict,
+ def load_object(cls, object_name: str, config: Config, *, kwargs: dict,
extra_dir: Optional[str] = None) -> Any:
"""
Search and loads the specified object as configured in hte child class.
diff --git a/freqtrade/resolvers/pairlist_resolver.py b/freqtrade/resolvers/pairlist_resolver.py
index 72a3cc1dd..f492bcb54 100644
--- a/freqtrade/resolvers/pairlist_resolver.py
+++ b/freqtrade/resolvers/pairlist_resolver.py
@@ -6,6 +6,7 @@ This module load custom pairlists
import logging
from pathlib import Path
+from freqtrade.constants import Config
from freqtrade.plugins.pairlist.IPairList import IPairList
from freqtrade.resolvers import IResolver
@@ -24,7 +25,7 @@ class PairListResolver(IResolver):
@staticmethod
def load_pairlist(pairlist_name: str, exchange, pairlistmanager,
- config: dict, pairlistconfig: dict, pairlist_pos: int) -> IPairList:
+ config: Config, pairlistconfig: dict, pairlist_pos: int) -> IPairList:
"""
Load the pairlist with pairlist_name
:param pairlist_name: Classname of the pairlist
diff --git a/freqtrade/resolvers/protection_resolver.py b/freqtrade/resolvers/protection_resolver.py
index c54ae1011..11cd6f224 100644
--- a/freqtrade/resolvers/protection_resolver.py
+++ b/freqtrade/resolvers/protection_resolver.py
@@ -5,6 +5,7 @@ import logging
from pathlib import Path
from typing import Dict
+from freqtrade.constants import Config
from freqtrade.plugins.protections import IProtection
from freqtrade.resolvers import IResolver
@@ -22,7 +23,8 @@ class ProtectionResolver(IResolver):
initial_search_path = Path(__file__).parent.parent.joinpath('plugins/protections').resolve()
@staticmethod
- def load_protection(protection_name: str, config: Dict, protection_config: Dict) -> IProtection:
+ def load_protection(protection_name: str, config: Config,
+ protection_config: Dict) -> IProtection:
"""
Load the protection with protection_name
:param protection_name: Classname of the pairlist
diff --git a/freqtrade/resolvers/strategy_resolver.py b/freqtrade/resolvers/strategy_resolver.py
index 8b01980ce..c574246ac 100644
--- a/freqtrade/resolvers/strategy_resolver.py
+++ b/freqtrade/resolvers/strategy_resolver.py
@@ -9,10 +9,10 @@ from base64 import urlsafe_b64decode
from inspect import getfullargspec
from os import walk
from pathlib import Path
-from typing import Any, Dict, List, Optional
+from typing import Any, List, Optional
from freqtrade.configuration.config_validation import validate_migrated_strategy_settings
-from freqtrade.constants import REQUIRED_ORDERTIF, REQUIRED_ORDERTYPES, USERPATH_STRATEGIES
+from freqtrade.constants import REQUIRED_ORDERTIF, REQUIRED_ORDERTYPES, USERPATH_STRATEGIES, Config
from freqtrade.enums import TradingMode
from freqtrade.exceptions import OperationalException
from freqtrade.resolvers import IResolver
@@ -32,7 +32,7 @@ class StrategyResolver(IResolver):
initial_search_path = None
@staticmethod
- def load_strategy(config: Dict[str, Any] = None) -> IStrategy:
+ def load_strategy(config: Config = None) -> IStrategy:
"""
Load the custom class from config parameter
:param config: configuration dictionary or None
@@ -91,8 +91,7 @@ class StrategyResolver(IResolver):
return strategy
@staticmethod
- def _override_attribute_helper(strategy, config: Dict[str, Any],
- attribute: str, default: Any):
+ def _override_attribute_helper(strategy, config: Config, attribute: str, default: Any):
"""
Override attributes in the strategy.
Prevalence:
@@ -215,7 +214,7 @@ class StrategyResolver(IResolver):
@staticmethod
def _load_strategy(strategy_name: str,
- config: dict, extra_dir: Optional[str] = None) -> IStrategy:
+ config: Config, extra_dir: Optional[str] = None) -> IStrategy:
"""
Search and loads the specified strategy.
:param strategy_name: name of the module to import
diff --git a/freqtrade/rpc/api_server/api_auth.py b/freqtrade/rpc/api_server/api_auth.py
index a39e31b85..ee66fce2b 100644
--- a/freqtrade/rpc/api_server/api_auth.py
+++ b/freqtrade/rpc/api_server/api_auth.py
@@ -1,8 +1,10 @@
+import logging
import secrets
from datetime import datetime, timedelta
+from typing import Any, Dict, Union
import jwt
-from fastapi import APIRouter, Depends, HTTPException, status
+from fastapi import APIRouter, Depends, HTTPException, Query, WebSocket, status
from fastapi.security import OAuth2PasswordBearer
from fastapi.security.http import HTTPBasic, HTTPBasicCredentials
@@ -10,6 +12,8 @@ from freqtrade.rpc.api_server.api_schemas import AccessAndRefreshToken, AccessTo
from freqtrade.rpc.api_server.deps import get_api_config
+logger = logging.getLogger(__name__)
+
ALGORITHM = "HS256"
router_login = APIRouter()
@@ -25,7 +29,7 @@ httpbasic = HTTPBasic(auto_error=False)
oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token", auto_error=False)
-def get_user_from_token(token, secret_key: str, token_type: str = "access"):
+def get_user_from_token(token, secret_key: str, token_type: str = "access") -> str:
credentials_exception = HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="Could not validate credentials",
@@ -44,6 +48,45 @@ def get_user_from_token(token, secret_key: str, token_type: str = "access"):
return username
+# This should be reimplemented to better realign with the existing tools provided
+# by FastAPI regarding API Tokens
+# https://github.com/tiangolo/fastapi/blob/master/fastapi/security/api_key.py
+async def validate_ws_token(
+ ws: WebSocket,
+ ws_token: Union[str, None] = Query(default=None, alias="token"),
+ api_config: Dict[str, Any] = Depends(get_api_config)
+):
+ secret_ws_token = api_config.get('ws_token', None)
+ secret_jwt_key = api_config.get('jwt_secret_key', 'super-secret')
+
+ # Check if ws_token is/in secret_ws_token
+ if ws_token and secret_ws_token:
+ is_valid_ws_token = False
+ if isinstance(secret_ws_token, str):
+ is_valid_ws_token = secrets.compare_digest(secret_ws_token, ws_token)
+ elif isinstance(secret_ws_token, list):
+ is_valid_ws_token = any([
+ secrets.compare_digest(potential, ws_token)
+ for potential in secret_ws_token
+ ])
+
+ if is_valid_ws_token:
+ return ws_token
+
+ # Check if ws_token is a JWT
+ try:
+ user = get_user_from_token(ws_token, secret_jwt_key)
+ return user
+ # If the token is a jwt, and it's valid return the user
+ except HTTPException:
+ pass
+
+ # No checks passed, deny the connection
+ logger.debug("Denying websocket request.")
+ # If it doesn't match, close the websocket connection
+ await ws.close(code=status.WS_1008_POLICY_VIOLATION)
+
+
def create_token(data: dict, secret_key: str, token_type: str = "access") -> str:
to_encode = data.copy()
if token_type == "access":
diff --git a/freqtrade/rpc/api_server/api_v1.py b/freqtrade/rpc/api_server/api_v1.py
index bf21715b7..53f5c16d7 100644
--- a/freqtrade/rpc/api_server/api_v1.py
+++ b/freqtrade/rpc/api_server/api_v1.py
@@ -38,7 +38,8 @@ logger = logging.getLogger(__name__)
# 2.15: Add backtest history endpoints
# 2.16: Additional daily metrics
# 2.17: Forceentry - leverage, partial force_exit
-API_VERSION = 2.17
+# 2.20: Add websocket endpoints
+API_VERSION = 2.20
# Public API, requires no auth.
router_public = APIRouter()
diff --git a/freqtrade/rpc/api_server/api_ws.py b/freqtrade/rpc/api_server/api_ws.py
new file mode 100644
index 000000000..f55b2dbd3
--- /dev/null
+++ b/freqtrade/rpc/api_server/api_ws.py
@@ -0,0 +1,140 @@
+import logging
+from typing import Any, Dict
+
+from fastapi import APIRouter, Depends, WebSocketDisconnect
+from fastapi.websockets import WebSocket, WebSocketState
+from pydantic import ValidationError
+
+from freqtrade.enums import RPCMessageType, RPCRequestType
+from freqtrade.rpc.api_server.api_auth import validate_ws_token
+from freqtrade.rpc.api_server.deps import get_channel_manager, get_rpc
+from freqtrade.rpc.api_server.ws import WebSocketChannel
+from freqtrade.rpc.api_server.ws_schemas import (WSAnalyzedDFMessage, WSMessageSchema,
+ WSRequestSchema, WSWhitelistMessage)
+from freqtrade.rpc.rpc import RPC
+
+
+logger = logging.getLogger(__name__)
+
+# Private router, protected by API Key authentication
+router = APIRouter()
+
+
+async def is_websocket_alive(ws: WebSocket) -> bool:
+ """
+ Check if a FastAPI Websocket is still open
+ """
+ if (
+ ws.application_state == WebSocketState.CONNECTED and
+ ws.client_state == WebSocketState.CONNECTED
+ ):
+ return True
+ return False
+
+
+async def _process_consumer_request(
+ request: Dict[str, Any],
+ channel: WebSocketChannel,
+ rpc: RPC
+):
+ """
+ Validate and handle a request from a websocket consumer
+ """
+ # Validate the request, makes sure it matches the schema
+ try:
+ websocket_request = WSRequestSchema.parse_obj(request)
+ except ValidationError as e:
+ logger.error(f"Invalid request from {channel}: {e}")
+ return
+
+ type, data = websocket_request.type, websocket_request.data
+ response: WSMessageSchema
+
+ logger.debug(f"Request of type {type} from {channel}")
+
+ # If we have a request of type SUBSCRIBE, set the topics in this channel
+ if type == RPCRequestType.SUBSCRIBE:
+ # If the request is empty, do nothing
+ if not data:
+ return
+
+ # If all topics passed are a valid RPCMessageType, set subscriptions on channel
+ if all([any(x.value == topic for x in RPCMessageType) for topic in data]):
+ channel.set_subscriptions(data)
+
+ # We don't send a response for subscriptions
+ return
+
+ elif type == RPCRequestType.WHITELIST:
+ # Get whitelist
+ whitelist = rpc._ws_request_whitelist()
+
+ # Format response
+ response = WSWhitelistMessage(data=whitelist)
+ # Send it back
+ await channel.send(response.dict(exclude_none=True))
+
+ elif type == RPCRequestType.ANALYZED_DF:
+ limit = None
+
+ if data:
+ # Limit the amount of candles per dataframe to 'limit' or 1500
+ limit = max(data.get('limit', 1500), 1500)
+
+ # They requested the full historical analyzed dataframes
+ analyzed_df = rpc._ws_request_analyzed_df(limit)
+
+ # For every dataframe, send as a separate message
+ for _, message in analyzed_df.items():
+ response = WSAnalyzedDFMessage(data=message)
+ await channel.send(response.dict(exclude_none=True))
+
+
+@router.websocket("/message/ws")
+async def message_endpoint(
+ ws: WebSocket,
+ rpc: RPC = Depends(get_rpc),
+ channel_manager=Depends(get_channel_manager),
+ token: str = Depends(validate_ws_token)
+):
+ """
+ Message WebSocket endpoint, facilitates sending RPC messages
+ """
+ try:
+ channel = await channel_manager.on_connect(ws)
+
+ if await is_websocket_alive(ws):
+
+ logger.info(f"Consumer connected - {channel}")
+
+ # Keep connection open until explicitly closed, and process requests
+ try:
+ while not channel.is_closed():
+ request = await channel.recv()
+
+ # Process the request here
+ await _process_consumer_request(request, channel, rpc)
+
+ except WebSocketDisconnect:
+ # Handle client disconnects
+ logger.info(f"Consumer disconnected - {channel}")
+ await channel_manager.on_disconnect(ws)
+ except Exception as e:
+ logger.info(f"Consumer connection failed - {channel}")
+ logger.exception(e)
+ # Handle cases like -
+ # RuntimeError('Cannot call "send" once a closed message has been sent')
+ await channel_manager.on_disconnect(ws)
+
+ else:
+ await ws.close()
+
+ except RuntimeError:
+ # WebSocket was closed
+ await channel_manager.on_disconnect(ws)
+
+ except Exception as e:
+ logger.error(f"Failed to serve - {ws.client}")
+ # Log tracebacks to keep track of what errors are happening
+ logger.exception(e)
+ await channel_manager.on_disconnect(ws)
diff --git a/freqtrade/rpc/api_server/deps.py b/freqtrade/rpc/api_server/deps.py
index 66654c0b1..abd3db036 100644
--- a/freqtrade/rpc/api_server/deps.py
+++ b/freqtrade/rpc/api_server/deps.py
@@ -41,6 +41,10 @@ def get_exchange(config=Depends(get_config)):
return ApiServer._exchange
+def get_channel_manager():
+ return ApiServer._ws_channel_manager
+
+
def is_webserver_mode(config=Depends(get_config)):
if config['runmode'] != RunMode.WEBSERVER:
raise RPCException('Bot is not in the correct state')
diff --git a/freqtrade/rpc/api_server/webserver.py b/freqtrade/rpc/api_server/webserver.py
index 0da129583..df4324740 100644
--- a/freqtrade/rpc/api_server/webserver.py
+++ b/freqtrade/rpc/api_server/webserver.py
@@ -1,15 +1,21 @@
+import asyncio
import logging
from ipaddress import IPv4Address
+from threading import Thread
from typing import Any, Dict
import orjson
import uvicorn
from fastapi import Depends, FastAPI
from fastapi.middleware.cors import CORSMiddleware
+# Look into alternatives
+from janus import Queue as ThreadedQueue
from starlette.responses import JSONResponse
+from freqtrade.constants import Config
from freqtrade.exceptions import OperationalException
from freqtrade.rpc.api_server.uvicorn_threaded import UvicornServer
+from freqtrade.rpc.api_server.ws import ChannelManager
from freqtrade.rpc.rpc import RPC, RPCException, RPCHandler
@@ -37,12 +43,16 @@ class ApiServer(RPCHandler):
_bt = None
_bt_data = None
_bt_timerange = None
- _bt_last_config: Dict[str, Any] = {}
+ _bt_last_config: Config = {}
_has_rpc: bool = False
_bgtask_running: bool = False
- _config: Dict[str, Any] = {}
+ _config: Config = {}
# Exchange - only available in webserver mode.
_exchange = None
+ # websocket message queue stuff
+ _ws_channel_manager = None
+ _ws_thread = None
+ _ws_loop = None
def __new__(cls, *args, **kwargs):
"""
@@ -54,23 +64,27 @@ class ApiServer(RPCHandler):
ApiServer.__initialized = False
return ApiServer.__instance
- def __init__(self, config: Dict[str, Any], standalone: bool = False) -> None:
+ def __init__(self, config: Config, standalone: bool = False) -> None:
ApiServer._config = config
if self.__initialized and (standalone or self._standalone):
return
self._standalone: bool = standalone
self._server = None
+ self._ws_queue = None
+ self._ws_background_task = None
+
ApiServer.__initialized = True
api_config = self._config['api_server']
+ ApiServer._ws_channel_manager = ChannelManager()
+
self.app = FastAPI(title="Freqtrade API",
docs_url='/docs' if api_config.get('enable_openapi', False) else None,
redoc_url=None,
default_response_class=FTJSONResponse,
)
self.configure_app(self.app, self._config)
-
self.start_api()
def add_rpc_handler(self, rpc: RPC):
@@ -92,6 +106,19 @@ class ApiServer(RPCHandler):
logger.info("Stopping API Server")
self._server.cleanup()
+ if self._ws_thread and self._ws_loop:
+ logger.info("Stopping API Server background tasks")
+
+ if self._ws_background_task:
+ # Cancel the queue task
+ self._ws_background_task.cancel()
+
+ self._ws_thread.join()
+
+ self._ws_thread = None
+ self._ws_loop = None
+ self._ws_background_task = None
+
@classmethod
def shutdown(cls):
cls.__initialized = False
@@ -101,7 +128,9 @@ class ApiServer(RPCHandler):
cls._rpc = None
def send_msg(self, msg: Dict[str, str]) -> None:
- pass
+ if self._ws_queue:
+ sync_q = self._ws_queue.sync_q
+ sync_q.put(msg)
def handle_rpc_exception(self, request, exc):
logger.exception(f"API Error calling: {exc}")
@@ -115,6 +144,7 @@ class ApiServer(RPCHandler):
from freqtrade.rpc.api_server.api_backtest import router as api_backtest
from freqtrade.rpc.api_server.api_v1 import router as api_v1
from freqtrade.rpc.api_server.api_v1 import router_public as api_v1_public
+ from freqtrade.rpc.api_server.api_ws import router as ws_router
from freqtrade.rpc.api_server.web_ui import router_ui
app.include_router(api_v1_public, prefix="/api/v1")
@@ -125,6 +155,7 @@ class ApiServer(RPCHandler):
app.include_router(api_backtest, prefix="/api/v1",
dependencies=[Depends(http_basic_or_jwt_token)],
)
+ app.include_router(ws_router, prefix="/api/v1")
app.include_router(router_login, prefix="/api/v1", tags=["auth"])
# UI Router MUST be last!
app.include_router(router_ui, prefix='')
@@ -139,6 +170,48 @@ class ApiServer(RPCHandler):
app.add_exception_handler(RPCException, self.handle_rpc_exception)
+ def start_message_queue(self):
+ if self._ws_thread:
+ return
+
+ # Create a new loop, as it'll be just for the background thread
+ self._ws_loop = asyncio.new_event_loop()
+
+ # Start the thread
+ self._ws_thread = Thread(target=self._ws_loop.run_forever)
+ self._ws_thread.start()
+
+ # Finally, submit the coro to the thread
+ self._ws_background_task = asyncio.run_coroutine_threadsafe(
+ self._broadcast_queue_data(), loop=self._ws_loop)
+
+ async def _broadcast_queue_data(self):
+ # Instantiate the queue in this coroutine so it's attached to our loop
+ self._ws_queue = ThreadedQueue()
+ async_queue = self._ws_queue.async_q
+
+ try:
+ while True:
+ logger.debug("Getting queue messages...")
+ # Get data from queue
+ message = await async_queue.get()
+ logger.debug(f"Found message of type: {message.get('type')}")
+ # Broadcast it
+ await self._ws_channel_manager.broadcast(message)
+ # Sleep, make this configurable?
+ await asyncio.sleep(0.1)
+ except asyncio.CancelledError:
+ pass
+
+ # For testing, shouldn't happen when stable
+ except Exception as e:
+ logger.exception(f"Exception happened in background task: {e}")
+
+ finally:
+ # Disconnect channels and stop the loop on cancel
+ await self._ws_channel_manager.disconnect_all()
+ self._ws_loop.stop()
+
def start_api(self):
"""
Start API ... should be run in thread.
@@ -176,6 +249,7 @@ class ApiServer(RPCHandler):
if self._standalone:
self._server.run()
else:
+ self.start_message_queue()
self._server.run_in_thread()
except Exception:
logger.exception("Api server failed to start.")
diff --git a/freqtrade/rpc/api_server/ws/__init__.py b/freqtrade/rpc/api_server/ws/__init__.py
new file mode 100644
index 000000000..055b20a9d
--- /dev/null
+++ b/freqtrade/rpc/api_server/ws/__init__.py
@@ -0,0 +1,6 @@
+# flake8: noqa: F401
+# isort: off
+from freqtrade.rpc.api_server.ws.types import WebSocketType
+from freqtrade.rpc.api_server.ws.proxy import WebSocketProxy
+from freqtrade.rpc.api_server.ws.serializer import HybridJSONWebSocketSerializer
+from freqtrade.rpc.api_server.ws.channel import ChannelManager, WebSocketChannel
diff --git a/freqtrade/rpc/api_server/ws/channel.py b/freqtrade/rpc/api_server/ws/channel.py
new file mode 100644
index 000000000..cffe3092d
--- /dev/null
+++ b/freqtrade/rpc/api_server/ws/channel.py
@@ -0,0 +1,178 @@
+import logging
+from threading import RLock
+from typing import List, Optional, Type
+from uuid import uuid4
+
+from fastapi import WebSocket as FastAPIWebSocket
+
+from freqtrade.rpc.api_server.ws.proxy import WebSocketProxy
+from freqtrade.rpc.api_server.ws.serializer import (HybridJSONWebSocketSerializer,
+ WebSocketSerializer)
+from freqtrade.rpc.api_server.ws.types import WebSocketType
+
+
+logger = logging.getLogger(__name__)
+
+
+class WebSocketChannel:
+ """
+ Object to help facilitate managing a websocket connection
+ """
+
+ def __init__(
+ self,
+ websocket: WebSocketType,
+ channel_id: Optional[str] = None,
+ serializer_cls: Type[WebSocketSerializer] = HybridJSONWebSocketSerializer
+ ):
+
+ self.channel_id = channel_id if channel_id else uuid4().hex[:8]
+
+ # The WebSocket object
+ self._websocket = WebSocketProxy(websocket)
+ # The Serializing class for the WebSocket object
+ self._serializer_cls = serializer_cls
+
+ self._subscriptions: List[str] = []
+
+ # Internal event to signify a closed websocket
+ self._closed = False
+
+ # Wrap the WebSocket in the Serializing class
+ self._wrapped_ws = self._serializer_cls(self._websocket)
+
+ def __repr__(self):
+ return f"WebSocketChannel({self.channel_id}, {self.remote_addr})"
+
+ @property
+ def remote_addr(self):
+ return self._websocket.remote_addr
+
+ async def send(self, data):
+ """
+ Send data on the wrapped websocket
+ """
+ await self._wrapped_ws.send(data)
+
+ async def recv(self):
+ """
+ Receive data on the wrapped websocket
+ """
+ return await self._wrapped_ws.recv()
+
+ async def ping(self):
+ """
+ Ping the websocket
+ """
+ return await self._websocket.ping()
+
+ async def close(self):
+ """
+ Close the WebSocketChannel
+ """
+
+ self._closed = True
+
+ def is_closed(self) -> bool:
+ """
+ Closed flag
+ """
+ return self._closed
+
+ def set_subscriptions(self, subscriptions: List[str] = []) -> None:
+ """
+ Set which subscriptions this channel is subscribed to
+
+ :param subscriptions: List of subscriptions, List[str]
+ """
+ self._subscriptions = subscriptions
+
+ def subscribed_to(self, message_type: str) -> bool:
+ """
+ Check if this channel is subscribed to the message_type
+
+ :param message_type: The message type to check
+ """
+ return message_type in self._subscriptions
+
+
+class ChannelManager:
+ def __init__(self):
+ self.channels = dict()
+ self._lock = RLock() # Re-entrant Lock
+
+ async def on_connect(self, websocket: WebSocketType):
+ """
+ Wrap websocket connection into Channel and add to list
+
+ :param websocket: The WebSocket object to attach to the Channel
+ """
+ if isinstance(websocket, FastAPIWebSocket):
+ try:
+ await websocket.accept()
+ except RuntimeError:
+ # The connection was closed before we could accept it
+ return
+
+ ws_channel = WebSocketChannel(websocket)
+
+ with self._lock:
+ self.channels[websocket] = ws_channel
+
+ return ws_channel
+
+ async def on_disconnect(self, websocket: WebSocketType):
+ """
+ Call close on the channel if it's not, and remove from channel list
+
+ :param websocket: The WebSocket objet attached to the Channel
+ """
+ with self._lock:
+ channel = self.channels.get(websocket)
+ if channel:
+ if not channel.is_closed():
+ await channel.close()
+
+ del self.channels[websocket]
+
+ async def disconnect_all(self):
+ """
+ Disconnect all Channels
+ """
+ with self._lock:
+ for websocket, channel in self.channels.items():
+ if not channel.is_closed():
+ await channel.close()
+
+ self.channels = dict()
+
+ async def broadcast(self, data):
+ """
+ Broadcast data on all Channels
+
+ :param data: The data to send
+ """
+ with self._lock:
+ message_type = data.get('type')
+ for websocket, channel in self.channels.items():
+ try:
+ if channel.subscribed_to(message_type):
+ await channel.send(data)
+ except RuntimeError:
+ # Handle cannot send after close cases
+ await self.on_disconnect(websocket)
+
+ async def send_direct(self, channel, data):
+ """
+ Send data directly through direct_channel only
+
+ :param direct_channel: The WebSocketChannel object to send data through
+ :param data: The data to send
+ """
+ await channel.send(data)
+
+ def has_channels(self):
+ """
+ Flag for more than 0 channels
+ """
+ return len(self.channels) > 0
diff --git a/freqtrade/rpc/api_server/ws/proxy.py b/freqtrade/rpc/api_server/ws/proxy.py
new file mode 100644
index 000000000..2e5a59f05
--- /dev/null
+++ b/freqtrade/rpc/api_server/ws/proxy.py
@@ -0,0 +1,69 @@
+from typing import Any, Tuple, Union
+
+from fastapi import WebSocket as FastAPIWebSocket
+from websockets.client import WebSocketClientProtocol as WebSocket
+
+from freqtrade.rpc.api_server.ws.types import WebSocketType
+
+
+class WebSocketProxy:
+ """
+ WebSocketProxy object to bring the FastAPIWebSocket and websockets.WebSocketClientProtocol
+ under the same API
+ """
+
+ def __init__(self, websocket: WebSocketType):
+ self._websocket: Union[FastAPIWebSocket, WebSocket] = websocket
+
+ @property
+ def remote_addr(self) -> Tuple[Any, ...]:
+ if isinstance(self._websocket, WebSocket):
+ return self._websocket.remote_address
+ elif isinstance(self._websocket, FastAPIWebSocket):
+ if self._websocket.client:
+ client, port = self._websocket.client.host, self._websocket.client.port
+ return (client, port)
+ return ("unknown", 0)
+
+ async def send(self, data):
+ """
+ Send data on the wrapped websocket
+ """
+ if hasattr(self._websocket, "send_text"):
+ await self._websocket.send_text(data)
+ else:
+ await self._websocket.send(data)
+
+ async def recv(self):
+ """
+ Receive data on the wrapped websocket
+ """
+ if hasattr(self._websocket, "receive_text"):
+ return await self._websocket.receive_text()
+ else:
+ return await self._websocket.recv()
+
+ async def ping(self):
+ """
+ Ping the websocket, not supported by FastAPI WebSockets
+ """
+ if hasattr(self._websocket, "ping"):
+ return await self._websocket.ping()
+ return False
+
+ async def close(self, code: int = 1000):
+ """
+ Close the websocket connection, only supported by FastAPI WebSockets
+ """
+ if hasattr(self._websocket, "close"):
+ try:
+ return await self._websocket.close(code)
+ except RuntimeError:
+ pass
+
+ async def accept(self):
+ """
+ Accept the WebSocket connection, only support by FastAPI WebSockets
+ """
+ if hasattr(self._websocket, "accept"):
+ return await self._websocket.accept()
diff --git a/freqtrade/rpc/api_server/ws/serializer.py b/freqtrade/rpc/api_server/ws/serializer.py
new file mode 100644
index 000000000..6c402a100
--- /dev/null
+++ b/freqtrade/rpc/api_server/ws/serializer.py
@@ -0,0 +1,62 @@
+import logging
+from abc import ABC, abstractmethod
+
+import orjson
+import rapidjson
+from pandas import DataFrame
+
+from freqtrade.misc import dataframe_to_json, json_to_dataframe
+from freqtrade.rpc.api_server.ws.proxy import WebSocketProxy
+
+
+logger = logging.getLogger(__name__)
+
+
+class WebSocketSerializer(ABC):
+ def __init__(self, websocket: WebSocketProxy):
+ self._websocket: WebSocketProxy = websocket
+
+ @abstractmethod
+ def _serialize(self, data):
+ raise NotImplementedError()
+
+ @abstractmethod
+ def _deserialize(self, data):
+ raise NotImplementedError()
+
+ async def send(self, data: bytes):
+ await self._websocket.send(self._serialize(data))
+
+ async def recv(self) -> bytes:
+ data = await self._websocket.recv()
+
+ return self._deserialize(data)
+
+ async def close(self, code: int = 1000):
+ await self._websocket.close(code)
+
+
+class HybridJSONWebSocketSerializer(WebSocketSerializer):
+ def _serialize(self, data) -> str:
+ return str(orjson.dumps(data, default=_json_default), "utf-8")
+
+ def _deserialize(self, data: str):
+ # RapidJSON expects strings
+ return rapidjson.loads(data, object_hook=_json_object_hook)
+
+
+# Support serializing pandas DataFrames
+def _json_default(z):
+ if isinstance(z, DataFrame):
+ return {
+ '__type__': 'dataframe',
+ '__value__': dataframe_to_json(z)
+ }
+ raise TypeError
+
+
+# Support deserializing JSON to pandas DataFrames
+def _json_object_hook(z):
+ if z.get('__type__') == 'dataframe':
+ return json_to_dataframe(z.get('__value__'))
+ return z
diff --git a/freqtrade/rpc/api_server/ws/types.py b/freqtrade/rpc/api_server/ws/types.py
new file mode 100644
index 000000000..9855f9e06
--- /dev/null
+++ b/freqtrade/rpc/api_server/ws/types.py
@@ -0,0 +1,8 @@
+from typing import Any, Dict, TypeVar
+
+from fastapi import WebSocket as FastAPIWebSocket
+from websockets.client import WebSocketClientProtocol as WebSocket
+
+
+WebSocketType = TypeVar("WebSocketType", FastAPIWebSocket, WebSocket)
+MessageType = Dict[str, Any]
diff --git a/freqtrade/rpc/api_server/ws_schemas.py b/freqtrade/rpc/api_server/ws_schemas.py
new file mode 100644
index 000000000..255226d84
--- /dev/null
+++ b/freqtrade/rpc/api_server/ws_schemas.py
@@ -0,0 +1,63 @@
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+from pandas import DataFrame
+from pydantic import BaseModel
+
+from freqtrade.constants import PairWithTimeframe
+from freqtrade.enums.rpcmessagetype import RPCMessageType, RPCRequestType
+
+
+class BaseArbitraryModel(BaseModel):
+ class Config:
+ arbitrary_types_allowed = True
+
+
+class WSRequestSchema(BaseArbitraryModel):
+ type: RPCRequestType
+ data: Optional[Any] = None
+
+
+class WSMessageSchema(BaseArbitraryModel):
+ type: RPCMessageType
+ data: Optional[Any] = None
+
+ class Config:
+ extra = 'allow'
+
+
+# ------------------------------ REQUEST SCHEMAS ----------------------------
+
+
+class WSSubscribeRequest(WSRequestSchema):
+ type: RPCRequestType = RPCRequestType.SUBSCRIBE
+ data: List[RPCMessageType]
+
+
+class WSWhitelistRequest(WSRequestSchema):
+ type: RPCRequestType = RPCRequestType.WHITELIST
+ data: None = None
+
+
+class WSAnalyzedDFRequest(WSRequestSchema):
+ type: RPCRequestType = RPCRequestType.ANALYZED_DF
+ data: Dict[str, Any] = {"limit": 1500}
+
+
+# ------------------------------ MESSAGE SCHEMAS ----------------------------
+
+class WSWhitelistMessage(WSMessageSchema):
+ type: RPCMessageType = RPCMessageType.WHITELIST
+ data: List[str]
+
+
+class WSAnalyzedDFMessage(WSMessageSchema):
+ class AnalyzedDFData(BaseArbitraryModel):
+ key: PairWithTimeframe
+ df: DataFrame
+ la: datetime
+
+ type: RPCMessageType = RPCMessageType.ANALYZED_DF
+ data: AnalyzedDFData
+
+# --------------------------------------------------------------------------
diff --git a/freqtrade/rpc/discord.py b/freqtrade/rpc/discord.py
index 85acfae4e..9efe6f427 100644
--- a/freqtrade/rpc/discord.py
+++ b/freqtrade/rpc/discord.py
@@ -1,6 +1,6 @@
import logging
-from typing import Any, Dict
+from freqtrade.constants import Config
from freqtrade.enums import RPCMessageType
from freqtrade.rpc import RPC
from freqtrade.rpc.webhook import Webhook
@@ -10,7 +10,7 @@ logger = logging.getLogger(__name__)
class Discord(Webhook):
- def __init__(self, rpc: 'RPC', config: Dict[str, Any]):
+ def __init__(self, rpc: 'RPC', config: Config):
# super().__init__(rpc, config)
self.rpc = rpc
self.config = config
diff --git a/freqtrade/rpc/external_message_consumer.py b/freqtrade/rpc/external_message_consumer.py
new file mode 100644
index 000000000..dcfe1d109
--- /dev/null
+++ b/freqtrade/rpc/external_message_consumer.py
@@ -0,0 +1,335 @@
+"""
+ExternalMessageConsumer module
+
+Main purpose is to connect to external bot's message websocket to consume data
+from it
+"""
+import asyncio
+import logging
+import socket
+from threading import Thread
+from typing import TYPE_CHECKING, Any, Callable, Dict, List, TypedDict
+
+import websockets
+from pydantic import ValidationError
+
+from freqtrade.data.dataprovider import DataProvider
+from freqtrade.enums import RPCMessageType
+from freqtrade.misc import remove_entry_exit_signals
+from freqtrade.rpc.api_server.ws import WebSocketChannel
+from freqtrade.rpc.api_server.ws_schemas import (WSAnalyzedDFMessage, WSAnalyzedDFRequest,
+ WSMessageSchema, WSRequestSchema,
+ WSSubscribeRequest, WSWhitelistMessage,
+ WSWhitelistRequest)
+
+
+if TYPE_CHECKING:
+ import websockets.connect
+
+
+class Producer(TypedDict):
+ name: str
+ host: str
+ port: int
+ ws_token: str
+
+
+logger = logging.getLogger(__name__)
+
+
+class ExternalMessageConsumer:
+ """
+ The main controller class for consuming external messages from
+ other freqtrade bot's
+ """
+
+ def __init__(
+ self,
+ config: Dict[str, Any],
+ dataprovider: DataProvider
+ ):
+ self._config = config
+ self._dp = dataprovider
+
+ self._running = False
+ self._thread = None
+ self._loop = None
+ self._main_task = None
+ self._sub_tasks = None
+
+ self._emc_config = self._config.get('external_message_consumer', {})
+
+ self.enabled = self._emc_config.get('enabled', False)
+ self.producers: List[Producer] = self._emc_config.get('producers', [])
+
+ self.wait_timeout = self._emc_config.get('wait_timeout', 300) # in seconds
+ self.ping_timeout = self._emc_config.get('ping_timeout', 10) # in seconds
+ self.sleep_time = self._emc_config.get('sleep_time', 10) # in seconds
+
+ # The amount of candles per dataframe on the initial request
+ self.initial_candle_limit = self._emc_config.get('initial_candle_limit', 1500)
+
+ # Message size limit, in megabytes. Default 8mb, Use bitwise operator << 20 to convert
+ # as the websockets client expects bytes.
+ self.message_size_limit = (self._emc_config.get('message_size_limit', 8) << 20)
+
+ # Setting these explicitly as they probably shouldn't be changed by a user
+ # Unless we somehow integrate this with the strategy to allow creating
+ # callbacks for the messages
+ self.topics = [RPCMessageType.WHITELIST, RPCMessageType.ANALYZED_DF]
+
+ # Allow setting data for each initial request
+ self._initial_requests: List[WSRequestSchema] = [
+ WSSubscribeRequest(data=self.topics),
+ WSWhitelistRequest(),
+ WSAnalyzedDFRequest()
+ ]
+
+ # Specify which function to use for which RPCMessageType
+ self._message_handlers: Dict[str, Callable[[str, WSMessageSchema], None]] = {
+ RPCMessageType.WHITELIST: self._consume_whitelist_message,
+ RPCMessageType.ANALYZED_DF: self._consume_analyzed_df_message,
+ }
+
+ self.start()
+
+ def start(self):
+ """
+ Start the main internal loop in another thread to run coroutines
+ """
+ if self._thread and self._loop:
+ return
+
+ logger.info("Starting ExternalMessageConsumer")
+
+ self._loop = asyncio.new_event_loop()
+ self._thread = Thread(target=self._loop.run_forever)
+ self._running = True
+ self._thread.start()
+
+ self._main_task = asyncio.run_coroutine_threadsafe(self._main(), loop=self._loop)
+
+ def shutdown(self):
+ """
+ Shutdown the loop, thread, and tasks
+ """
+ if self._thread and self._loop:
+ logger.info("Stopping ExternalMessageConsumer")
+ self._running = False
+
+ if self._sub_tasks:
+ # Cancel sub tasks
+ for task in self._sub_tasks:
+ task.cancel()
+
+ if self._main_task:
+ # Cancel the main task
+ self._main_task.cancel()
+
+ self._thread.join()
+
+ self._thread = None
+ self._loop = None
+ self._sub_tasks = None
+ self._main_task = None
+
+ async def _main(self):
+ """
+ The main task coroutine
+ """
+ lock = asyncio.Lock()
+
+ try:
+ # Create a connection to each producer
+ self._sub_tasks = [
+ self._loop.create_task(self._handle_producer_connection(producer, lock))
+ for producer in self.producers
+ ]
+
+ await asyncio.gather(*self._sub_tasks)
+ except asyncio.CancelledError:
+ pass
+ finally:
+ # Stop the loop once we are done
+ self._loop.stop()
+
+ async def _handle_producer_connection(self, producer: Producer, lock: asyncio.Lock):
+ """
+ Main connection loop for the consumer
+
+ :param producer: Dictionary containing producer info
+ :param lock: An asyncio Lock
+ """
+ try:
+ await self._create_connection(producer, lock)
+ except asyncio.CancelledError:
+ # Exit silently
+ pass
+
+ async def _create_connection(self, producer: Producer, lock: asyncio.Lock):
+ """
+ Actually creates and handles the websocket connection, pinging on timeout
+ and handling connection errors.
+
+ :param producer: Dictionary containing producer info
+ :param lock: An asyncio Lock
+ """
+ while self._running:
+ try:
+ host, port = producer['host'], producer['port']
+ token = producer['ws_token']
+ name = producer['name']
+ ws_url = f"ws://{host}:{port}/api/v1/message/ws?token={token}"
+
+ # This will raise InvalidURI if the url is bad
+ async with websockets.connect(ws_url, max_size=self.message_size_limit) as ws:
+ channel = WebSocketChannel(ws, channel_id=name)
+
+ logger.info(f"Producer connection success - {channel}")
+
+ # Now request the initial data from this Producer
+ for request in self._initial_requests:
+ await channel.send(
+ request.dict(exclude_none=True)
+ )
+
+ # Now receive data, if none is within the time limit, ping
+ await self._receive_messages(channel, producer, lock)
+
+ except (websockets.exceptions.InvalidURI, ValueError) as e:
+ logger.error(f"{ws_url} is an invalid WebSocket URL - {e}")
+ break
+
+ except (
+ socket.gaierror,
+ ConnectionRefusedError,
+ websockets.exceptions.InvalidStatusCode,
+ websockets.exceptions.InvalidMessage
+ ) as e:
+ logger.error(f"Connection Refused - {e} retrying in {self.sleep_time}s")
+ await asyncio.sleep(self.sleep_time)
+ continue
+
+ except (
+ websockets.exceptions.ConnectionClosedError,
+ websockets.exceptions.ConnectionClosedOK
+ ):
+ # Just keep trying to connect again indefinitely
+ await asyncio.sleep(self.sleep_time)
+ continue
+
+ except Exception as e:
+ # An unforseen error has occurred, log and continue
+ logger.error("Unexpected error has occurred:")
+ logger.exception(e)
+ continue
+
+ async def _receive_messages(
+ self,
+ channel: WebSocketChannel,
+ producer: Producer,
+ lock: asyncio.Lock
+ ):
+ """
+ Loop to handle receiving messages from a Producer
+
+ :param channel: The WebSocketChannel object for the WebSocket
+ :param producer: Dictionary containing producer info
+ :param lock: An asyncio Lock
+ """
+ while self._running:
+ try:
+ message = await asyncio.wait_for(
+ channel.recv(),
+ timeout=self.wait_timeout
+ )
+
+ try:
+ async with lock:
+ # Handle the message
+ self.handle_producer_message(producer, message)
+ except Exception as e:
+ logger.exception(f"Error handling producer message: {e}")
+
+ except (asyncio.TimeoutError, websockets.exceptions.ConnectionClosed):
+ # We haven't received data yet. Check the connection and continue.
+ try:
+ # ping
+ ping = await channel.ping()
+
+ await asyncio.wait_for(ping, timeout=self.ping_timeout)
+ logger.debug(f"Connection to {channel} still alive...")
+
+ continue
+ except Exception as e:
+ logger.warning(f"Ping error {channel} - retrying in {self.sleep_time}s")
+ logger.debug(e, exc_info=e)
+ await asyncio.sleep(self.sleep_time)
+
+ break
+
+ def handle_producer_message(self, producer: Producer, message: Dict[str, Any]):
+ """
+ Handles external messages from a Producer
+ """
+ producer_name = producer.get('name', 'default')
+
+ try:
+ producer_message = WSMessageSchema.parse_obj(message)
+ except ValidationError as e:
+ logger.error(f"Invalid message from `{producer_name}`: {e}")
+ return
+
+ if not producer_message.data:
+ logger.error(f"Empty message received from `{producer_name}`")
+ return
+
+ logger.info(f"Received message of type `{producer_message.type}` from `{producer_name}`")
+
+ message_handler = self._message_handlers.get(producer_message.type)
+
+ if not message_handler:
+ logger.info(f"Received unhandled message: `{producer_message.data}`, ignoring...")
+ return
+
+ message_handler(producer_name, producer_message)
+
+ def _consume_whitelist_message(self, producer_name: str, message: WSMessageSchema):
+ try:
+ # Validate the message
+ whitelist_message = WSWhitelistMessage.parse_obj(message)
+ except ValidationError as e:
+ logger.error(f"Invalid message from `{producer_name}`: {e}")
+ return
+
+ # Add the pairlist data to the DataProvider
+ self._dp._set_producer_pairs(whitelist_message.data, producer_name=producer_name)
+
+ logger.debug(f"Consumed message from `{producer_name}` of type `RPCMessageType.WHITELIST`")
+
+ def _consume_analyzed_df_message(self, producer_name: str, message: WSMessageSchema):
+ try:
+ df_message = WSAnalyzedDFMessage.parse_obj(message)
+ except ValidationError as e:
+ logger.error(f"Invalid message from `{producer_name}`: {e}")
+ return
+
+ key = df_message.data.key
+ df = df_message.data.df
+ la = df_message.data.la
+
+ pair, timeframe, candle_type = key
+
+ # If set, remove the Entry and Exit signals from the Producer
+ if self._emc_config.get('remove_entry_exit_signals', False):
+ df = remove_entry_exit_signals(df)
+
+ # Add the dataframe to the dataprovider
+ self._dp._add_external_df(pair, df,
+ last_analyzed=la,
+ timeframe=timeframe,
+ candle_type=candle_type,
+ producer_name=producer_name)
+
+ logger.debug(
+ f"Consumed message from `{producer_name}` of type `RPCMessageType.ANALYZED_DF`")
diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py
index 05599074c..57fc7f473 100644
--- a/freqtrade/rpc/rpc.py
+++ b/freqtrade/rpc/rpc.py
@@ -16,7 +16,7 @@ from pandas import DataFrame, NaT
from freqtrade import __version__
from freqtrade.configuration.timerange import TimeRange
-from freqtrade.constants import CANCEL_REASON, DATETIME_PRINT_FORMAT
+from freqtrade.constants import CANCEL_REASON, DATETIME_PRINT_FORMAT, Config
from freqtrade.data.history import load_data
from freqtrade.data.metrics import calculate_max_drawdown
from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, SignalDirection, State,
@@ -58,7 +58,7 @@ class RPCException(Exception):
class RPCHandler:
- def __init__(self, rpc: 'RPC', config: Dict[str, Any]) -> None:
+ def __init__(self, rpc: 'RPC', config: Config) -> None:
"""
Initializes RPCHandlers
:param rpc: instance of RPC Helper class
@@ -66,7 +66,7 @@ class RPCHandler:
:return: None
"""
self._rpc = rpc
- self._config: Dict[str, Any] = config
+ self._config: Config = config
@property
def name(self) -> str:
@@ -96,7 +96,7 @@ class RPC:
:return: None
"""
self._freqtrade = freqtrade
- self._config: Dict[str, Any] = freqtrade.config
+ self._config: Config = freqtrade.config
if self._config.get('fiat_display_currency'):
self._fiat_converter = CryptoToFiatConverter()
@@ -1039,14 +1039,52 @@ class RPC:
def _rpc_analysed_dataframe(self, pair: str, timeframe: str,
limit: Optional[int]) -> Dict[str, Any]:
+ """ Analyzed dataframe in Dict form """
+ _data, last_analyzed = self.__rpc_analysed_dataframe_raw(pair, timeframe, limit)
+ return self._convert_dataframe_to_dict(self._freqtrade.config['strategy'],
+ pair, timeframe, _data, last_analyzed)
+
+ def __rpc_analysed_dataframe_raw(self, pair: str, timeframe: str,
+ limit: Optional[int]) -> Tuple[DataFrame, datetime]:
+ """ Get the dataframe and last analyze from the dataprovider """
_data, last_analyzed = self._freqtrade.dataprovider.get_analyzed_dataframe(
pair, timeframe)
_data = _data.copy()
+
if limit:
_data = _data.iloc[-limit:]
- return self._convert_dataframe_to_dict(self._freqtrade.config['strategy'],
- pair, timeframe, _data, last_analyzed)
+ return _data, last_analyzed
+
+ def _ws_all_analysed_dataframes(
+ self,
+ pairlist: List[str],
+ limit: Optional[int]
+ ) -> Dict[str, Any]:
+ """ Get the analysed dataframes of each pair in the pairlist """
+ timeframe = self._freqtrade.config['timeframe']
+ candle_type = self._freqtrade.config.get('candle_type_def', CandleType.SPOT)
+ _data = {}
+
+ for pair in pairlist:
+ dataframe, last_analyzed = self.__rpc_analysed_dataframe_raw(pair, timeframe, limit)
+
+ _data[pair] = {
+ "key": (pair, timeframe, candle_type),
+ "df": dataframe,
+ "la": last_analyzed
+ }
+
+ return _data
+
+ def _ws_request_analyzed_df(self, limit: Optional[int]):
+ """ Historical Analyzed Dataframes for WebSocket """
+ whitelist = self._freqtrade.active_pair_whitelist
+ return self._ws_all_analysed_dataframes(whitelist, limit)
+
+ def _ws_request_whitelist(self):
+ """ Whitelist data for WebSocket """
+ return self._freqtrade.active_pair_whitelist
@staticmethod
def _rpc_analysed_history_full(config, pair: str, timeframe: str,
diff --git a/freqtrade/rpc/rpc_manager.py b/freqtrade/rpc/rpc_manager.py
index 3ccf23228..e286487ff 100644
--- a/freqtrade/rpc/rpc_manager.py
+++ b/freqtrade/rpc/rpc_manager.py
@@ -5,6 +5,7 @@ import logging
from collections import deque
from typing import Any, Dict, List
+from freqtrade.constants import Config
from freqtrade.enums import RPCMessageType
from freqtrade.rpc import RPC, RPCHandler
@@ -66,7 +67,8 @@ class RPCManager:
'status': 'stopping bot'
}
"""
- logger.info('Sending rpc message: %s', msg)
+ if msg.get('type') is not RPCMessageType.ANALYZED_DF:
+ logger.info('Sending rpc message: %s', msg)
if 'pair' in msg:
msg.update({
'base_currency': self._rpc._freqtrade.exchange.get_pair_base_currency(msg['pair'])
@@ -77,6 +79,8 @@ class RPCManager:
mod.send_msg(msg)
except NotImplementedError:
logger.error(f"Message type '{msg['type']}' not implemented by handler {mod.name}.")
+ except Exception:
+ logger.exception('Exception occurred within RPC module %s', mod.name)
def process_msg_queue(self, queue: deque) -> None:
"""
@@ -89,7 +93,7 @@ class RPCManager:
'msg': msg,
})
- def startup_messages(self, config: Dict[str, Any], pairlist, protections) -> None:
+ def startup_messages(self, config: Config, pairlist, protections) -> None:
if config['dry_run']:
self.send_msg({
'type': RPCMessageType.WARNING,
diff --git a/freqtrade/rpc/telegram.py b/freqtrade/rpc/telegram.py
index 4a759f6ec..247373817 100644
--- a/freqtrade/rpc/telegram.py
+++ b/freqtrade/rpc/telegram.py
@@ -24,7 +24,7 @@ from telegram.ext import CallbackContext, CallbackQueryHandler, CommandHandler,
from telegram.utils.helpers import escape_markdown
from freqtrade.__init__ import __version__
-from freqtrade.constants import DUST_PER_COIN
+from freqtrade.constants import DUST_PER_COIN, Config
from freqtrade.enums import RPCMessageType, SignalDirection, TradingMode
from freqtrade.exceptions import OperationalException
from freqtrade.misc import chunks, plural, round_coin_value
@@ -88,7 +88,7 @@ def authorized_only(command_handler: Callable[..., None]) -> Callable[..., Any]:
class Telegram(RPCHandler):
""" This class handles all telegram communication """
- def __init__(self, rpc: RPC, config: Dict[str, Any]) -> None:
+ def __init__(self, rpc: RPC, config: Config) -> None:
"""
Init the Telegram call, and init the super class RPCHandler
:param rpc: instance of RPC Helper class
@@ -286,7 +286,7 @@ class Telegram(RPCHandler):
if msg['type'] in [RPCMessageType.ENTRY_FILL]:
message += f"*Open Rate:* `{msg['open_rate']:.8f}`\n"
elif msg['type'] in [RPCMessageType.ENTRY]:
- message += f"*Open Rate:* `{msg['limit']:.8f}`\n"\
+ message += f"*Open Rate:* `{msg['open_rate']:.8f}`\n"\
f"*Current Rate:* `{msg['current_rate']:.8f}`\n"
message += f"*Total:* `({round_coin_value(msg['stake_amount'], msg['stake_currency'])}"
@@ -353,8 +353,9 @@ class Telegram(RPCHandler):
f"*Open Rate:* `{msg['open_rate']:.8f}`\n"
)
if msg['type'] == RPCMessageType.EXIT:
- message += (f"*Current Rate:* `{msg['current_rate']:.8f}`\n"
- f"*Exit Rate:* `{msg['limit']:.8f}`")
+ message += f"*Current Rate:* `{msg['current_rate']:.8f}`\n"
+ if msg['order_rate']:
+ message += f"*Exit Rate:* `{msg['order_rate']:.8f}`"
elif msg['type'] == RPCMessageType.EXIT_FILL:
message += f"*Exit Rate:* `{msg['close_rate']:.8f}`"
diff --git a/freqtrade/rpc/webhook.py b/freqtrade/rpc/webhook.py
index 1b39a29b7..6109e80bc 100644
--- a/freqtrade/rpc/webhook.py
+++ b/freqtrade/rpc/webhook.py
@@ -7,6 +7,7 @@ from typing import Any, Dict
from requests import RequestException, post
+from freqtrade.constants import Config
from freqtrade.enums import RPCMessageType
from freqtrade.rpc import RPC, RPCHandler
@@ -19,7 +20,7 @@ logger.debug('Included module rpc.webhook ...')
class Webhook(RPCHandler):
""" This class handles all webhook communication """
- def __init__(self, rpc: RPC, config: Dict[str, Any]) -> None:
+ def __init__(self, rpc: RPC, config: Config) -> None:
"""
Init the Webhook class, and init the super class RPCHandler
:param rpc: instance of RPC Helper class
diff --git a/freqtrade/strategy/hyper.py b/freqtrade/strategy/hyper.py
index 47377f238..6f62c9d3d 100644
--- a/freqtrade/strategy/hyper.py
+++ b/freqtrade/strategy/hyper.py
@@ -6,6 +6,7 @@ import logging
from pathlib import Path
from typing import Any, Dict, Iterator, List, Tuple, Type, Union
+from freqtrade.constants import Config
from freqtrade.exceptions import OperationalException
from freqtrade.misc import deep_merge_dicts, json_load
from freqtrade.optimize.hyperopt_tools import HyperoptTools
@@ -21,7 +22,7 @@ class HyperStrategyMixin:
strategy logic.
"""
- def __init__(self, config: Dict[str, Any], *args, **kwargs):
+ def __init__(self, config: Config, *args, **kwargs):
"""
Initialize hyperoptable strategy mixin.
"""
diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py
index a29d6228a..e80c09c72 100644
--- a/freqtrade/strategy/interface.py
+++ b/freqtrade/strategy/interface.py
@@ -10,12 +10,13 @@ from typing import Dict, List, Optional, Tuple, Union
import arrow
from pandas import DataFrame
-from freqtrade.constants import ListPairsWithTimeframes
+from freqtrade.constants import Config, ListPairsWithTimeframes
from freqtrade.data.dataprovider import DataProvider
from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, RunMode, SignalDirection,
SignalTagType, SignalType, TradingMode)
from freqtrade.exceptions import OperationalException, StrategyError
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_next_date, timeframe_to_seconds
+from freqtrade.misc import remove_entry_exit_signals
from freqtrade.persistence import Order, PairLocks, Trade
from freqtrade.strategy.hyper import HyperStrategyMixin
from freqtrade.strategy.informative_decorator import (InformativeData, PopulateIndicators,
@@ -118,7 +119,7 @@ class IStrategy(ABC, HyperStrategyMixin):
# Definition of plot_config. See plotting documentation for more details.
plot_config: Dict = {}
- def __init__(self, config: dict) -> None:
+ def __init__(self, config: Config) -> None:
self.config = config
# Dict to determine if analysis is necessary
self._last_candle_seen_per_pair: Dict[str, datetime] = {}
@@ -759,20 +760,19 @@ class IStrategy(ABC, HyperStrategyMixin):
# always run if process_only_new_candles is set to false
if (not self.process_only_new_candles or
self._last_candle_seen_per_pair.get(pair, None) != dataframe.iloc[-1]['date']):
+
# Defs that only make change on new candle data.
dataframe = self.analyze_ticker(dataframe, metadata)
+
self._last_candle_seen_per_pair[pair] = dataframe.iloc[-1]['date']
- self.dp._set_cached_df(
- pair, self.timeframe, dataframe,
- candle_type=self.config.get('candle_type_def', CandleType.SPOT))
+
+ candle_type = self.config.get('candle_type_def', CandleType.SPOT)
+ self.dp._set_cached_df(pair, self.timeframe, dataframe, candle_type=candle_type)
+ self.dp._emit_df((pair, self.timeframe, candle_type), dataframe)
+
else:
logger.debug("Skipping TA Analysis for already analyzed candle")
- dataframe[SignalType.ENTER_LONG.value] = 0
- dataframe[SignalType.EXIT_LONG.value] = 0
- dataframe[SignalType.ENTER_SHORT.value] = 0
- dataframe[SignalType.EXIT_SHORT.value] = 0
- dataframe[SignalTagType.ENTER_TAG.value] = None
- dataframe[SignalTagType.EXIT_TAG.value] = None
+ dataframe = remove_entry_exit_signals(dataframe)
logger.debug("Loop Analysis Launched")
diff --git a/freqtrade/templates/FreqaiExampleStrategy.py b/freqtrade/templates/FreqaiExampleStrategy.py
index 907106453..d58d61025 100644
--- a/freqtrade/templates/FreqaiExampleStrategy.py
+++ b/freqtrade/templates/FreqaiExampleStrategy.py
@@ -45,7 +45,7 @@ class FreqaiExampleStrategy(IStrategy):
std_dev_multiplier_buy = CategoricalParameter(
[0.75, 1, 1.25, 1.5, 1.75], default=1.25, space="buy", optimize=True)
std_dev_multiplier_sell = CategoricalParameter(
- [0.1, 0.25, 0.4], space="sell", default=0.2, optimize=True)
+ [0.75, 1, 1.25, 1.5, 1.75], space="sell", default=1.25, optimize=True)
def populate_any_indicators(
self, pair, df, tf, informative=None, set_generalized_indicators=False
@@ -170,25 +170,31 @@ class FreqaiExampleStrategy(IStrategy):
dataframe = self.freqai.start(dataframe, metadata, self)
for val in self.std_dev_multiplier_buy.range:
- dataframe[f'target_roi_{val}'] = dataframe["&-s_close_mean"] + \
- dataframe["&-s_close_std"] * val
+ dataframe[f'target_roi_{val}'] = (
+ dataframe["&-s_close_mean"] + dataframe["&-s_close_std"] * val
+ )
for val in self.std_dev_multiplier_sell.range:
- dataframe[f'sell_roi_{val}'] = dataframe["&-s_close_mean"] - \
- dataframe["&-s_close_std"] * val
+ dataframe[f'sell_roi_{val}'] = (
+ dataframe["&-s_close_mean"] - dataframe["&-s_close_std"] * val
+ )
return dataframe
def populate_entry_trend(self, df: DataFrame, metadata: dict) -> DataFrame:
- enter_long_conditions = [df["do_predict"] == 1, df["&-s_close"]
- > df[f"target_roi_{self.std_dev_multiplier_buy.value}"]]
+ enter_long_conditions = [
+ df["do_predict"] == 1,
+ df["&-s_close"] > df[f"target_roi_{self.std_dev_multiplier_buy.value}"],
+ ]
if enter_long_conditions:
df.loc[
reduce(lambda x, y: x & y, enter_long_conditions), ["enter_long", "enter_tag"]
] = (1, "long")
- enter_short_conditions = [df["do_predict"] == 1, df["&-s_close"]
- < df[f"sell_roi_{self.std_dev_multiplier_sell.value}"]]
+ enter_short_conditions = [
+ df["do_predict"] == 1,
+ df["&-s_close"] < df[f"sell_roi_{self.std_dev_multiplier_sell.value}"],
+ ]
if enter_short_conditions:
df.loc[
@@ -198,13 +204,17 @@ class FreqaiExampleStrategy(IStrategy):
return df
def populate_exit_trend(self, df: DataFrame, metadata: dict) -> DataFrame:
- exit_long_conditions = [df["do_predict"] == 1, df["&-s_close"] <
- df[f"sell_roi_{self.std_dev_multiplier_sell.value}"] * 0.25]
+ exit_long_conditions = [
+ df["do_predict"] == 1,
+ df["&-s_close"] < df[f"sell_roi_{self.std_dev_multiplier_sell.value}"] * 0.25,
+ ]
if exit_long_conditions:
df.loc[reduce(lambda x, y: x & y, exit_long_conditions), "exit_long"] = 1
- exit_short_conditions = [df["do_predict"] == 1, df["&-s_close"] >
- df[f"target_roi_{self.std_dev_multiplier_buy.value}"] * 0.25]
+ exit_short_conditions = [
+ df["do_predict"] == 1,
+ df["&-s_close"] > df[f"target_roi_{self.std_dev_multiplier_buy.value}"] * 0.25,
+ ]
if exit_short_conditions:
df.loc[reduce(lambda x, y: x & y, exit_short_conditions), "exit_short"] = 1
diff --git a/freqtrade/templates/base_config.json.j2 b/freqtrade/templates/base_config.json.j2
index 681af84c6..299734a50 100644
--- a/freqtrade/templates/base_config.json.j2
+++ b/freqtrade/templates/base_config.json.j2
@@ -67,6 +67,7 @@
"verbosity": "error",
"enable_openapi": false,
"jwt_secret_key": "{{ api_server_jwt_key }}",
+ "ws_token": "{{ api_server_ws_token }}",
"CORS_origins": [],
"username": "{{ api_server_username }}",
"password": "{{ api_server_password }}"
diff --git a/freqtrade/templates/base_strategy.py.j2 b/freqtrade/templates/base_strategy.py.j2
index 5a4504687..53426b211 100644
--- a/freqtrade/templates/base_strategy.py.j2
+++ b/freqtrade/templates/base_strategy.py.j2
@@ -1,21 +1,21 @@
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# flake8: noqa: F401
-
+# isort: skip_file
# --- Do not remove these libs ---
-import numpy as np # noqa
-import pandas as pd # noqa
-from pandas import DataFrame # noqa
-from datetime import datetime # noqa
-from typing import Optional, Union # noqa
+import numpy as np
+import pandas as pd
+from pandas import DataFrame
+from datetime import datetime
+from typing import Optional, Union
from freqtrade.strategy import (BooleanParameter, CategoricalParameter, DecimalParameter,
- IStrategy, IntParameter)
+ IntParameter, IStrategy, merge_informative_pair)
# --------------------------------
# Add your lib to import here
import talib.abstract as ta
import pandas_ta as pta
-import freqtrade.vendor.qtpylib.indicators as qtpylib
+from technical import qtpylib
class {{ strategy }}(IStrategy):
diff --git a/freqtrade/templates/sample_hyperopt_loss.py b/freqtrade/templates/sample_hyperopt_loss.py
index 343349508..5eab92a0c 100644
--- a/freqtrade/templates/sample_hyperopt_loss.py
+++ b/freqtrade/templates/sample_hyperopt_loss.py
@@ -4,6 +4,7 @@ from typing import Dict
from pandas import DataFrame
+from freqtrade.constants import Config
from freqtrade.optimize.hyperopt import IHyperOptLoss
@@ -36,7 +37,7 @@ class SampleHyperOptLoss(IHyperOptLoss):
@staticmethod
def hyperopt_loss_function(results: DataFrame, trade_count: int,
min_date: datetime, max_date: datetime,
- config: Dict, processed: Dict[str, DataFrame],
+ config: Config, processed: Dict[str, DataFrame],
*args, **kwargs) -> float:
"""
Objective function, returns smaller number for better results
diff --git a/freqtrade/templates/subtemplates/buy_trend_full.j2 b/freqtrade/templates/strategy_subtemplates/buy_trend_full.j2
similarity index 100%
rename from freqtrade/templates/subtemplates/buy_trend_full.j2
rename to freqtrade/templates/strategy_subtemplates/buy_trend_full.j2
diff --git a/freqtrade/templates/subtemplates/buy_trend_minimal.j2 b/freqtrade/templates/strategy_subtemplates/buy_trend_minimal.j2
similarity index 100%
rename from freqtrade/templates/subtemplates/buy_trend_minimal.j2
rename to freqtrade/templates/strategy_subtemplates/buy_trend_minimal.j2
diff --git a/freqtrade/templates/subtemplates/indicators_full.j2 b/freqtrade/templates/strategy_subtemplates/indicators_full.j2
similarity index 100%
rename from freqtrade/templates/subtemplates/indicators_full.j2
rename to freqtrade/templates/strategy_subtemplates/indicators_full.j2
diff --git a/freqtrade/templates/subtemplates/indicators_minimal.j2 b/freqtrade/templates/strategy_subtemplates/indicators_minimal.j2
similarity index 100%
rename from freqtrade/templates/subtemplates/indicators_minimal.j2
rename to freqtrade/templates/strategy_subtemplates/indicators_minimal.j2
diff --git a/freqtrade/templates/subtemplates/plot_config_full.j2 b/freqtrade/templates/strategy_subtemplates/plot_config_full.j2
similarity index 100%
rename from freqtrade/templates/subtemplates/plot_config_full.j2
rename to freqtrade/templates/strategy_subtemplates/plot_config_full.j2
diff --git a/freqtrade/templates/subtemplates/plot_config_minimal.j2 b/freqtrade/templates/strategy_subtemplates/plot_config_minimal.j2
similarity index 100%
rename from freqtrade/templates/subtemplates/plot_config_minimal.j2
rename to freqtrade/templates/strategy_subtemplates/plot_config_minimal.j2
diff --git a/freqtrade/templates/subtemplates/sell_trend_full.j2 b/freqtrade/templates/strategy_subtemplates/sell_trend_full.j2
similarity index 100%
rename from freqtrade/templates/subtemplates/sell_trend_full.j2
rename to freqtrade/templates/strategy_subtemplates/sell_trend_full.j2
diff --git a/freqtrade/templates/subtemplates/sell_trend_minimal.j2 b/freqtrade/templates/strategy_subtemplates/sell_trend_minimal.j2
similarity index 100%
rename from freqtrade/templates/subtemplates/sell_trend_minimal.j2
rename to freqtrade/templates/strategy_subtemplates/sell_trend_minimal.j2
diff --git a/freqtrade/templates/subtemplates/strategy_methods_advanced.j2 b/freqtrade/templates/strategy_subtemplates/strategy_methods_advanced.j2
similarity index 100%
rename from freqtrade/templates/subtemplates/strategy_methods_advanced.j2
rename to freqtrade/templates/strategy_subtemplates/strategy_methods_advanced.j2
diff --git a/freqtrade/templates/subtemplates/strategy_methods_empty.j2 b/freqtrade/templates/strategy_subtemplates/strategy_methods_empty.j2
similarity index 100%
rename from freqtrade/templates/subtemplates/strategy_methods_empty.j2
rename to freqtrade/templates/strategy_subtemplates/strategy_methods_empty.j2
diff --git a/freqtrade/wallets.py b/freqtrade/wallets.py
index 41115c72e..0a9ecc638 100644
--- a/freqtrade/wallets.py
+++ b/freqtrade/wallets.py
@@ -7,7 +7,7 @@ from typing import Dict, NamedTuple, Optional
import arrow
-from freqtrade.constants import UNLIMITED_STAKE_AMOUNT
+from freqtrade.constants import UNLIMITED_STAKE_AMOUNT, Config
from freqtrade.enums import RunMode, TradingMode
from freqtrade.exceptions import DependencyException
from freqtrade.exchange import Exchange
@@ -35,7 +35,7 @@ class PositionWallet(NamedTuple):
class Wallets:
- def __init__(self, config: dict, exchange: Exchange, log: bool = True) -> None:
+ def __init__(self, config: Config, exchange: Exchange, log: bool = True) -> None:
self._config = config
self._log = log
self._exchange = exchange
diff --git a/freqtrade/worker.py b/freqtrade/worker.py
index 66f718af0..dea0acc44 100755
--- a/freqtrade/worker.py
+++ b/freqtrade/worker.py
@@ -9,8 +9,9 @@ from typing import Any, Callable, Dict, Optional
import sdnotify
-from freqtrade import __version__, constants
+from freqtrade import __version__
from freqtrade.configuration import Configuration
+from freqtrade.constants import PROCESS_THROTTLE_SECS, RETRY_TIMEOUT, Config
from freqtrade.enums import State
from freqtrade.exceptions import OperationalException, TemporaryError
from freqtrade.freqtradebot import FreqtradeBot
@@ -24,7 +25,7 @@ class Worker:
Freqtradebot worker class
"""
- def __init__(self, args: Dict[str, Any], config: Dict[str, Any] = None) -> None:
+ def __init__(self, args: Dict[str, Any], config: Config = None) -> None:
"""
Init all variables and objects the bot needs to work
"""
@@ -53,7 +54,7 @@ class Worker:
internals_config = self._config.get('internals', {})
self._throttle_secs = internals_config.get('process_throttle_secs',
- constants.PROCESS_THROTTLE_SECS)
+ PROCESS_THROTTLE_SECS)
self._heartbeat_interval = internals_config.get('heartbeat_interval', 60)
self._sd_notify = sdnotify.SystemdNotifier() if \
@@ -151,8 +152,8 @@ class Worker:
try:
self.freqtrade.process()
except TemporaryError as error:
- logger.warning(f"Error: {error}, retrying in {constants.RETRY_TIMEOUT} seconds...")
- time.sleep(constants.RETRY_TIMEOUT)
+ logger.warning(f"Error: {error}, retrying in {RETRY_TIMEOUT} seconds...")
+ time.sleep(RETRY_TIMEOUT)
except OperationalException:
tb = traceback.format_exc()
hint = 'Issue `/start` if you think it is safe to restart.'
diff --git a/mkdocs.yml b/mkdocs.yml
index 257db7867..fd0280e83 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -35,6 +35,7 @@ nav:
- Advanced Post-installation Tasks: advanced-setup.md
- Advanced Strategy: strategy-advanced.md
- Advanced Hyperopt: advanced-hyperopt.md
+ - Producer/Consumer mode: producer-consumer.md
- FreqAI: freqai.md
- Edge Positioning: edge.md
- Sandbox Testing: sandbox-testing.md
diff --git a/requirements-freqai.txt b/requirements-freqai.txt
index e8d950382..9cdd431fe 100644
--- a/requirements-freqai.txt
+++ b/requirements-freqai.txt
@@ -3,7 +3,7 @@
# Required for freqai
scikit-learn==1.1.2
-joblib==1.1.0
+joblib==1.2.0
catboost==1.0.6; platform_machine != 'aarch64'
lightgbm==3.3.2
xgboost==1.6.2
diff --git a/requirements.txt b/requirements.txt
index 91d3d3c8c..c12d3fb08 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -2,7 +2,7 @@ numpy==1.23.3
pandas==1.4.4
pandas-ta==0.3.14b
-ccxt==1.93.35
+ccxt==1.93.66
# Pin cryptography for now due to rust build errors with piwheels
cryptography==38.0.1
aiohttp==3.8.1
@@ -20,7 +20,8 @@ pycoingecko==3.0.0
jinja2==3.1.2
tables==3.7.0
blosc==1.10.6
-joblib==1.1.0
+joblib==1.2.0
+pyarrow==9.0.0
# find first, C search in arrays
py_find_1st==1.1.5
@@ -34,9 +35,9 @@ orjson==3.8.0
sdnotify==0.3.2
# API Server
-fastapi==0.83.0
+fastapi==0.85.0
uvicorn==0.18.3
-pyjwt==2.4.0
+pyjwt==2.5.0
aiofiles==22.1.0
psutil==5.9.2
@@ -50,3 +51,8 @@ python-dateutil==2.8.2
#Futures
schedule==1.1.0
+
+#WS Messages
+websockets==10.3
+janus==1.0.0
+
diff --git a/setup.cfg b/setup.cfg
index d711534d9..60ec8a75f 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -49,4 +49,3 @@ exclude =
__pycache__,
.eggs,
user_data,
-
diff --git a/setup.py b/setup.py
index 8f04e75f7..1547b7974 100644
--- a/setup.py
+++ b/setup.py
@@ -8,13 +8,11 @@ hyperopt = [
'scikit-learn',
'scikit-optimize>=0.7.0',
'filelock',
- 'joblib',
'progressbar2',
]
freqai = [
'scikit-learn',
- 'joblib',
'catboost; platform_machine != "aarch64"',
'lightgbm',
]
@@ -74,12 +72,16 @@ setup(
'pandas',
'tables',
'blosc',
+ 'joblib',
+ 'pyarrow',
'fastapi',
'uvicorn',
'psutil',
'pyjwt',
'aiofiles',
- 'schedule'
+ 'schedule',
+ 'websockets',
+ 'janus'
],
extras_require={
'dev': all_extra,
diff --git a/tests/conftest.py b/tests/conftest.py
index fffac8e0a..51b1b03e3 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -58,6 +58,11 @@ def log_has(line, logs):
return any(line == message for message in logs.messages)
+def log_has_when(line, logs, when):
+ """Check if line is found in caplog's messages during a specified stage"""
+ return any(line == message.message for message in logs.get_records(when))
+
+
def log_has_re(line, logs):
"""Check if line matches some caplog's message."""
return any(re.match(line, message) for message in logs.messages)
@@ -2282,7 +2287,7 @@ def tickers():
@pytest.fixture
-def result(testdatadir):
+def dataframe_1m(testdatadir):
with (testdatadir / 'UNITTEST_BTC-1m.json').open('r') as data_file:
return ohlcv_to_dataframe(json.load(data_file), '1m', pair="UNITTEST/BTC",
fill_missing=True)
diff --git a/tests/data/test_converter.py b/tests/data/test_converter.py
index c6b0059a2..f74383d15 100644
--- a/tests/data/test_converter.py
+++ b/tests/data/test_converter.py
@@ -18,8 +18,8 @@ from tests.conftest import log_has, log_has_re
from tests.data.test_history import _clean_test_file
-def test_dataframe_correct_columns(result):
- assert result.columns.tolist() == ['date', 'open', 'high', 'low', 'close', 'volume']
+def test_dataframe_correct_columns(dataframe_1m):
+ assert dataframe_1m.columns.tolist() == ['date', 'open', 'high', 'low', 'close', 'volume']
def test_ohlcv_to_dataframe(ohlcv_history_list, caplog):
diff --git a/tests/data/test_datahandler.py b/tests/data/test_datahandler.py
new file mode 100644
index 000000000..8e1b0050a
--- /dev/null
+++ b/tests/data/test_datahandler.py
@@ -0,0 +1,436 @@
+# pragma pylint: disable=missing-docstring, protected-access, C0103
+
+import re
+from pathlib import Path
+from unittest.mock import MagicMock
+
+import pytest
+from pandas import DataFrame
+
+from freqtrade.configuration import TimeRange
+from freqtrade.constants import AVAILABLE_DATAHANDLERS
+from freqtrade.data.history.featherdatahandler import FeatherDataHandler
+from freqtrade.data.history.hdf5datahandler import HDF5DataHandler
+from freqtrade.data.history.idatahandler import IDataHandler, get_datahandler, get_datahandlerclass
+from freqtrade.data.history.jsondatahandler import JsonDataHandler, JsonGzDataHandler
+from freqtrade.data.history.parquetdatahandler import ParquetDataHandler
+from freqtrade.enums import CandleType, TradingMode
+from tests.conftest import log_has
+
+
+def test_datahandler_ohlcv_get_pairs(testdatadir):
+ pairs = JsonDataHandler.ohlcv_get_pairs(testdatadir, '5m', candle_type=CandleType.SPOT)
+ # Convert to set to avoid failures due to sorting
+ assert set(pairs) == {'UNITTEST/BTC', 'XLM/BTC', 'ETH/BTC', 'TRX/BTC', 'LTC/BTC',
+ 'XMR/BTC', 'ZEC/BTC', 'ADA/BTC', 'ETC/BTC', 'NXT/BTC',
+ 'DASH/BTC', 'XRP/ETH'}
+
+ pairs = JsonGzDataHandler.ohlcv_get_pairs(testdatadir, '8m', candle_type=CandleType.SPOT)
+ assert set(pairs) == {'UNITTEST/BTC'}
+
+ pairs = HDF5DataHandler.ohlcv_get_pairs(testdatadir, '5m', candle_type=CandleType.SPOT)
+ assert set(pairs) == {'UNITTEST/BTC'}
+
+ pairs = JsonDataHandler.ohlcv_get_pairs(testdatadir, '1h', candle_type=CandleType.MARK)
+ assert set(pairs) == {'UNITTEST/USDT', 'XRP/USDT'}
+
+ pairs = JsonGzDataHandler.ohlcv_get_pairs(testdatadir, '1h', candle_type=CandleType.FUTURES)
+ assert set(pairs) == {'XRP/USDT'}
+
+ pairs = HDF5DataHandler.ohlcv_get_pairs(testdatadir, '1h', candle_type=CandleType.MARK)
+ assert set(pairs) == {'UNITTEST/USDT:USDT'}
+
+
+@pytest.mark.parametrize('filename,pair,timeframe,candletype', [
+ ('XMR_BTC-5m.json', 'XMR_BTC', '5m', ''),
+ ('XMR_USDT-1h.h5', 'XMR_USDT', '1h', ''),
+ ('BTC-PERP-1h.h5', 'BTC-PERP', '1h', ''),
+ ('BTC_USDT-2h.jsongz', 'BTC_USDT', '2h', ''),
+ ('BTC_USDT-2h-mark.jsongz', 'BTC_USDT', '2h', 'mark'),
+ ('XMR_USDT-1h-mark.h5', 'XMR_USDT', '1h', 'mark'),
+ ('XMR_USDT-1h-random.h5', 'XMR_USDT', '1h', 'random'),
+ ('BTC-PERP-1h-index.h5', 'BTC-PERP', '1h', 'index'),
+ ('XMR_USDT_USDT-1h-mark.h5', 'XMR_USDT_USDT', '1h', 'mark'),
+])
+def test_datahandler_ohlcv_regex(filename, pair, timeframe, candletype):
+ regex = JsonDataHandler._OHLCV_REGEX
+
+ match = re.search(regex, filename)
+ assert len(match.groups()) > 1
+ assert match[1] == pair
+ assert match[2] == timeframe
+ assert match[3] == candletype
+
+
+@pytest.mark.parametrize('input,expected', [
+ ('XMR_USDT', 'XMR/USDT'),
+ ('BTC_USDT', 'BTC/USDT'),
+ ('USDT_BUSD', 'USDT/BUSD'),
+ ('BTC_USDT_USDT', 'BTC/USDT:USDT'), # Futures
+ ('XRP_USDT_USDT', 'XRP/USDT:USDT'), # futures
+ ('BTC-PERP', 'BTC-PERP'),
+ ('BTC-PERP_USDT', 'BTC-PERP:USDT'), # potential FTX case
+ ('UNITTEST_USDT', 'UNITTEST/USDT'),
+])
+def test_rebuild_pair_from_filename(input, expected):
+
+ assert IDataHandler.rebuild_pair_from_filename(input) == expected
+
+
+def test_datahandler_ohlcv_get_available_data(testdatadir):
+ paircombs = JsonDataHandler.ohlcv_get_available_data(testdatadir, TradingMode.SPOT)
+ # Convert to set to avoid failures due to sorting
+ assert set(paircombs) == {
+ ('UNITTEST/BTC', '5m', CandleType.SPOT),
+ ('ETH/BTC', '5m', CandleType.SPOT),
+ ('XLM/BTC', '5m', CandleType.SPOT),
+ ('TRX/BTC', '5m', CandleType.SPOT),
+ ('LTC/BTC', '5m', CandleType.SPOT),
+ ('XMR/BTC', '5m', CandleType.SPOT),
+ ('ZEC/BTC', '5m', CandleType.SPOT),
+ ('UNITTEST/BTC', '1m', CandleType.SPOT),
+ ('ADA/BTC', '5m', CandleType.SPOT),
+ ('ETC/BTC', '5m', CandleType.SPOT),
+ ('NXT/BTC', '5m', CandleType.SPOT),
+ ('DASH/BTC', '5m', CandleType.SPOT),
+ ('XRP/ETH', '1m', CandleType.SPOT),
+ ('XRP/ETH', '5m', CandleType.SPOT),
+ ('UNITTEST/BTC', '30m', CandleType.SPOT),
+ ('UNITTEST/BTC', '8m', CandleType.SPOT),
+ ('NOPAIR/XXX', '4m', CandleType.SPOT),
+ }
+
+ paircombs = JsonDataHandler.ohlcv_get_available_data(testdatadir, TradingMode.FUTURES)
+ # Convert to set to avoid failures due to sorting
+ assert set(paircombs) == {
+ ('UNITTEST/USDT', '1h', 'mark'),
+ ('XRP/USDT', '1h', 'futures'),
+ ('XRP/USDT', '1h', 'mark'),
+ ('XRP/USDT', '8h', 'mark'),
+ ('XRP/USDT', '8h', 'funding_rate'),
+ }
+
+ paircombs = JsonGzDataHandler.ohlcv_get_available_data(testdatadir, TradingMode.SPOT)
+ assert set(paircombs) == {('UNITTEST/BTC', '8m', CandleType.SPOT)}
+ paircombs = HDF5DataHandler.ohlcv_get_available_data(testdatadir, TradingMode.SPOT)
+ assert set(paircombs) == {('UNITTEST/BTC', '5m', CandleType.SPOT)}
+
+
+def test_jsondatahandler_trades_get_pairs(testdatadir):
+ pairs = JsonGzDataHandler.trades_get_pairs(testdatadir)
+ # Convert to set to avoid failures due to sorting
+ assert set(pairs) == {'XRP/ETH', 'XRP/OLD'}
+
+
+def test_jsondatahandler_ohlcv_purge(mocker, testdatadir):
+ mocker.patch.object(Path, "exists", MagicMock(return_value=False))
+ unlinkmock = mocker.patch.object(Path, "unlink", MagicMock())
+ dh = JsonGzDataHandler(testdatadir)
+ assert not dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', '')
+ assert not dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', candle_type='mark')
+ assert unlinkmock.call_count == 0
+
+ mocker.patch.object(Path, "exists", MagicMock(return_value=True))
+ assert dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', '')
+ assert dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', candle_type='mark')
+ assert unlinkmock.call_count == 2
+
+
+def test_jsondatahandler_ohlcv_load(testdatadir, caplog):
+ dh = JsonDataHandler(testdatadir)
+ df = dh.ohlcv_load('XRP/ETH', '5m', 'spot')
+ assert len(df) == 711
+
+ df_mark = dh.ohlcv_load('UNITTEST/USDT', '1h', candle_type="mark")
+ assert len(df_mark) == 99
+
+ df_no_mark = dh.ohlcv_load('UNITTEST/USDT', '1h', 'spot')
+ assert len(df_no_mark) == 0
+
+ # Failure case (empty array)
+ df1 = dh.ohlcv_load('NOPAIR/XXX', '4m', 'spot')
+ assert len(df1) == 0
+ assert log_has("Could not load data for NOPAIR/XXX.", caplog)
+ assert df.columns.equals(df1.columns)
+
+
+@pytest.mark.parametrize('datahandler', ['feather', 'parquet'])
+def test_datahandler_trades_not_supported(datahandler, testdatadir, ):
+ dh = get_datahandler(testdatadir, datahandler)
+ with pytest.raises(NotImplementedError):
+ dh.trades_load('UNITTEST/ETH')
+ with pytest.raises(NotImplementedError):
+ dh.trades_store('UNITTEST/ETH', MagicMock())
+
+
+def test_jsondatahandler_trades_load(testdatadir, caplog):
+ dh = JsonGzDataHandler(testdatadir)
+ logmsg = "Old trades format detected - converting"
+ dh.trades_load('XRP/ETH')
+ assert not log_has(logmsg, caplog)
+
+ # Test conversation is happening
+ dh.trades_load('XRP/OLD')
+ assert log_has(logmsg, caplog)
+
+
+def test_jsondatahandler_trades_purge(mocker, testdatadir):
+ mocker.patch.object(Path, "exists", MagicMock(return_value=False))
+ unlinkmock = mocker.patch.object(Path, "unlink", MagicMock())
+ dh = JsonGzDataHandler(testdatadir)
+ assert not dh.trades_purge('UNITTEST/NONEXIST')
+ assert unlinkmock.call_count == 0
+
+ mocker.patch.object(Path, "exists", MagicMock(return_value=True))
+ assert dh.trades_purge('UNITTEST/NONEXIST')
+ assert unlinkmock.call_count == 1
+
+
+@pytest.mark.parametrize('datahandler', AVAILABLE_DATAHANDLERS)
+def test_datahandler_ohlcv_append(datahandler, testdatadir, ):
+ dh = get_datahandler(testdatadir, datahandler)
+ with pytest.raises(NotImplementedError):
+ dh.ohlcv_append('UNITTEST/ETH', '5m', DataFrame(), CandleType.SPOT)
+ with pytest.raises(NotImplementedError):
+ dh.ohlcv_append('UNITTEST/ETH', '5m', DataFrame(), CandleType.MARK)
+
+
+@pytest.mark.parametrize('datahandler', AVAILABLE_DATAHANDLERS)
+def test_datahandler_trades_append(datahandler, testdatadir):
+ dh = get_datahandler(testdatadir, datahandler)
+ with pytest.raises(NotImplementedError):
+ dh.trades_append('UNITTEST/ETH', [])
+
+
+def test_hdf5datahandler_trades_get_pairs(testdatadir):
+ pairs = HDF5DataHandler.trades_get_pairs(testdatadir)
+ # Convert to set to avoid failures due to sorting
+ assert set(pairs) == {'XRP/ETH'}
+
+
+def test_hdf5datahandler_trades_load(testdatadir):
+ dh = get_datahandler(testdatadir, 'hdf5')
+ trades = dh.trades_load('XRP/ETH')
+ assert isinstance(trades, list)
+
+ trades1 = dh.trades_load('UNITTEST/NONEXIST')
+ assert trades1 == []
+ # data goes from 2019-10-11 - 2019-10-13
+ timerange = TimeRange.parse_timerange('20191011-20191012')
+
+ trades2 = dh._trades_load('XRP/ETH', timerange)
+ assert len(trades) > len(trades2)
+ # Check that ID is None (If it's nan, it's wrong)
+ assert trades2[0][2] is None
+
+ # unfiltered load has trades before starttime
+ assert len([t for t in trades if t[0] < timerange.startts * 1000]) >= 0
+ # filtered list does not have trades before starttime
+ assert len([t for t in trades2 if t[0] < timerange.startts * 1000]) == 0
+ # unfiltered load has trades after endtime
+ assert len([t for t in trades if t[0] > timerange.stopts * 1000]) > 0
+ # filtered list does not have trades after endtime
+ assert len([t for t in trades2 if t[0] > timerange.stopts * 1000]) == 0
+
+
+def test_hdf5datahandler_trades_store(testdatadir, tmpdir):
+ tmpdir1 = Path(tmpdir)
+ dh = get_datahandler(testdatadir, 'hdf5')
+ trades = dh.trades_load('XRP/ETH')
+
+ dh1 = get_datahandler(tmpdir1, 'hdf5')
+ dh1.trades_store('XRP/NEW', trades)
+ file = tmpdir1 / 'XRP_NEW-trades.h5'
+ assert file.is_file()
+ # Load trades back
+ trades_new = dh1.trades_load('XRP/NEW')
+
+ assert len(trades_new) == len(trades)
+ assert trades[0][0] == trades_new[0][0]
+ assert trades[0][1] == trades_new[0][1]
+ # assert trades[0][2] == trades_new[0][2] # This is nan - so comparison does not make sense
+ assert trades[0][3] == trades_new[0][3]
+ assert trades[0][4] == trades_new[0][4]
+ assert trades[0][5] == trades_new[0][5]
+ assert trades[0][6] == trades_new[0][6]
+ assert trades[-1][0] == trades_new[-1][0]
+ assert trades[-1][1] == trades_new[-1][1]
+ # assert trades[-1][2] == trades_new[-1][2] # This is nan - so comparison does not make sense
+ assert trades[-1][3] == trades_new[-1][3]
+ assert trades[-1][4] == trades_new[-1][4]
+ assert trades[-1][5] == trades_new[-1][5]
+ assert trades[-1][6] == trades_new[-1][6]
+
+
+def test_hdf5datahandler_trades_purge(mocker, testdatadir):
+ mocker.patch.object(Path, "exists", MagicMock(return_value=False))
+ unlinkmock = mocker.patch.object(Path, "unlink", MagicMock())
+ dh = get_datahandler(testdatadir, 'hdf5')
+ assert not dh.trades_purge('UNITTEST/NONEXIST')
+ assert unlinkmock.call_count == 0
+
+ mocker.patch.object(Path, "exists", MagicMock(return_value=True))
+ assert dh.trades_purge('UNITTEST/NONEXIST')
+ assert unlinkmock.call_count == 1
+
+
+@pytest.mark.parametrize('pair,timeframe,candle_type,candle_append,startdt,enddt', [
+ # Data goes from 2018-01-10 - 2018-01-30
+ ('UNITTEST/BTC', '5m', 'spot', '', '2018-01-15', '2018-01-19'),
+ # Mark data goes from to 2021-11-15 2021-11-19
+ ('UNITTEST/USDT:USDT', '1h', 'mark', '-mark', '2021-11-16', '2021-11-18'),
+])
+def test_hdf5datahandler_ohlcv_load_and_resave(
+ testdatadir,
+ tmpdir,
+ pair,
+ timeframe,
+ candle_type,
+ candle_append,
+ startdt, enddt
+):
+ tmpdir1 = Path(tmpdir)
+ tmpdir2 = tmpdir1
+ if candle_type not in ('', 'spot'):
+ tmpdir2 = tmpdir1 / 'futures'
+ tmpdir2.mkdir()
+ dh = get_datahandler(testdatadir, 'hdf5')
+ ohlcv = dh._ohlcv_load(pair, timeframe, None, candle_type=candle_type)
+ assert isinstance(ohlcv, DataFrame)
+ assert len(ohlcv) > 0
+
+ file = tmpdir2 / f"UNITTEST_NEW-{timeframe}{candle_append}.h5"
+ assert not file.is_file()
+
+ dh1 = get_datahandler(tmpdir1, 'hdf5')
+ dh1.ohlcv_store('UNITTEST/NEW', timeframe, ohlcv, candle_type=candle_type)
+ assert file.is_file()
+
+ assert not ohlcv[ohlcv['date'] < startdt].empty
+
+ timerange = TimeRange.parse_timerange(f"{startdt.replace('-', '')}-{enddt.replace('-', '')}")
+
+ # Call private function to ensure timerange is filtered in hdf5
+ ohlcv = dh._ohlcv_load(pair, timeframe, timerange, candle_type=candle_type)
+ ohlcv1 = dh1._ohlcv_load('UNITTEST/NEW', timeframe, timerange, candle_type=candle_type)
+ assert len(ohlcv) == len(ohlcv1)
+ assert ohlcv.equals(ohlcv1)
+ assert ohlcv[ohlcv['date'] < startdt].empty
+ assert ohlcv[ohlcv['date'] > enddt].empty
+
+ # Try loading inexisting file
+ ohlcv = dh.ohlcv_load('UNITTEST/NONEXIST', timeframe, candle_type=candle_type)
+ assert ohlcv.empty
+
+
+@pytest.mark.parametrize('pair,timeframe,candle_type,candle_append,startdt,enddt', [
+ # Data goes from 2018-01-10 - 2018-01-30
+ ('UNITTEST/BTC', '5m', 'spot', '', '2018-01-15', '2018-01-19'),
+ # Mark data goes from to 2021-11-15 2021-11-19
+ ('UNITTEST/USDT', '1h', 'mark', '-mark', '2021-11-16', '2021-11-18'),
+])
+@pytest.mark.parametrize('datahandler', ['hdf5', 'feather', 'parquet'])
+def test_generic_datahandler_ohlcv_load_and_resave(
+ datahandler,
+ testdatadir,
+ tmpdir,
+ pair,
+ timeframe,
+ candle_type,
+ candle_append,
+ startdt, enddt
+):
+ tmpdir1 = Path(tmpdir)
+ tmpdir2 = tmpdir1
+ if candle_type not in ('', 'spot'):
+ tmpdir2 = tmpdir1 / 'futures'
+ tmpdir2.mkdir()
+ # Load data from one common file
+ dhbase = get_datahandler(testdatadir, 'json')
+ ohlcv = dhbase._ohlcv_load(pair, timeframe, None, candle_type=candle_type)
+ assert isinstance(ohlcv, DataFrame)
+ assert len(ohlcv) > 0
+
+ # Get data to test
+ dh = get_datahandler(testdatadir, datahandler)
+
+ file = tmpdir2 / f"UNITTEST_NEW-{timeframe}{candle_append}.{dh._get_file_extension()}"
+ assert not file.is_file()
+
+ dh1 = get_datahandler(tmpdir1, datahandler)
+ dh1.ohlcv_store('UNITTEST/NEW', timeframe, ohlcv, candle_type=candle_type)
+ assert file.is_file()
+
+ assert not ohlcv[ohlcv['date'] < startdt].empty
+
+ timerange = TimeRange.parse_timerange(f"{startdt.replace('-', '')}-{enddt.replace('-', '')}")
+
+ ohlcv = dhbase.ohlcv_load(pair, timeframe, timerange=timerange, candle_type=candle_type)
+ if datahandler == 'hdf5':
+ ohlcv1 = dh1._ohlcv_load('UNITTEST/NEW', timeframe, timerange, candle_type=candle_type)
+ if candle_type == 'mark':
+ ohlcv1['volume'] = 0.0
+ else:
+ ohlcv1 = dh1.ohlcv_load('UNITTEST/NEW', timeframe,
+ timerange=timerange, candle_type=candle_type)
+
+ assert len(ohlcv) == len(ohlcv1)
+ assert ohlcv.equals(ohlcv1)
+ assert ohlcv[ohlcv['date'] < startdt].empty
+ assert ohlcv[ohlcv['date'] > enddt].empty
+
+ # Try loading inexisting file
+ ohlcv = dh.ohlcv_load('UNITTEST/NONEXIST', timeframe, candle_type=candle_type)
+ assert ohlcv.empty
+
+
+def test_hdf5datahandler_ohlcv_purge(mocker, testdatadir):
+ mocker.patch.object(Path, "exists", MagicMock(return_value=False))
+ unlinkmock = mocker.patch.object(Path, "unlink", MagicMock())
+ dh = get_datahandler(testdatadir, 'hdf5')
+ assert not dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', '')
+ assert not dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', candle_type='mark')
+ assert unlinkmock.call_count == 0
+
+ mocker.patch.object(Path, "exists", MagicMock(return_value=True))
+ assert dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', '')
+ assert dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', candle_type='mark')
+ assert unlinkmock.call_count == 2
+
+
+def test_gethandlerclass():
+ cl = get_datahandlerclass('json')
+ assert cl == JsonDataHandler
+ assert issubclass(cl, IDataHandler)
+
+ cl = get_datahandlerclass('jsongz')
+ assert cl == JsonGzDataHandler
+ assert issubclass(cl, IDataHandler)
+ assert issubclass(cl, JsonDataHandler)
+
+ cl = get_datahandlerclass('hdf5')
+ assert cl == HDF5DataHandler
+ assert issubclass(cl, IDataHandler)
+
+ cl = get_datahandlerclass('feather')
+ assert cl == FeatherDataHandler
+ assert issubclass(cl, IDataHandler)
+
+ cl = get_datahandlerclass('parquet')
+ assert cl == ParquetDataHandler
+ assert issubclass(cl, IDataHandler)
+
+ with pytest.raises(ValueError, match=r"No datahandler for .*"):
+ get_datahandlerclass('DeadBeef')
+
+
+def test_get_datahandler(testdatadir):
+ dh = get_datahandler(testdatadir, 'json')
+ assert type(dh) == JsonDataHandler
+ dh = get_datahandler(testdatadir, 'jsongz')
+ assert type(dh) == JsonGzDataHandler
+ dh1 = get_datahandler(testdatadir, 'jsongz', dh)
+ assert id(dh1) == id(dh)
+
+ dh = get_datahandler(testdatadir, 'hdf5')
+ assert type(dh) == HDF5DataHandler
diff --git a/tests/data/test_dataprovider.py b/tests/data/test_dataprovider.py
index 49603feac..8500fa06c 100644
--- a/tests/data/test_dataprovider.py
+++ b/tests/data/test_dataprovider.py
@@ -144,6 +144,77 @@ def test_available_pairs(mocker, default_conf, ohlcv_history):
assert dp.available_pairs == [("XRP/BTC", timeframe), ("UNITTEST/BTC", timeframe), ]
+def test_producer_pairs(mocker, default_conf, ohlcv_history):
+ dataprovider = DataProvider(default_conf, None)
+
+ producer = "default"
+ whitelist = ["XRP/BTC", "ETH/BTC"]
+ assert len(dataprovider.get_producer_pairs(producer)) == 0
+
+ dataprovider._set_producer_pairs(whitelist, producer)
+ assert len(dataprovider.get_producer_pairs(producer)) == 2
+
+ new_whitelist = ["BTC/USDT"]
+ dataprovider._set_producer_pairs(new_whitelist, producer)
+ assert dataprovider.get_producer_pairs(producer) == new_whitelist
+
+ assert dataprovider.get_producer_pairs("bad") == []
+
+
+def test_get_producer_df(mocker, default_conf, ohlcv_history):
+ dataprovider = DataProvider(default_conf, None)
+
+ pair = 'BTC/USDT'
+ timeframe = default_conf['timeframe']
+ candle_type = CandleType.SPOT
+
+ empty_la = datetime.fromtimestamp(0, tz=timezone.utc)
+ now = datetime.now(timezone.utc)
+
+ # no data has been added, any request should return an empty dataframe
+ dataframe, la = dataprovider.get_producer_df(pair, timeframe, candle_type)
+ assert dataframe.empty
+ assert la == empty_la
+
+ # the data is added, should return that added dataframe
+ dataprovider._add_external_df(pair, ohlcv_history, now, timeframe, candle_type)
+ dataframe, la = dataprovider.get_producer_df(pair, timeframe, candle_type)
+ assert len(dataframe) > 0
+ assert la > empty_la
+
+ # no data on this producer, should return empty dataframe
+ dataframe, la = dataprovider.get_producer_df(pair, producer_name='bad')
+ assert dataframe.empty
+ assert la == empty_la
+
+ # non existent timeframe, empty dataframe
+ datframe, la = dataprovider.get_producer_df(pair, timeframe='1h')
+ assert dataframe.empty
+ assert la == empty_la
+
+
+def test_emit_df(mocker, default_conf, ohlcv_history):
+ mocker.patch('freqtrade.rpc.rpc_manager.RPCManager.__init__', MagicMock())
+ rpc_mock = mocker.patch('freqtrade.rpc.rpc_manager.RPCManager', MagicMock())
+ send_mock = mocker.patch('freqtrade.rpc.rpc_manager.RPCManager.send_msg', MagicMock())
+
+ dataprovider = DataProvider(default_conf, exchange=None, rpc=rpc_mock)
+ dataprovider_no_rpc = DataProvider(default_conf, exchange=None)
+
+ pair = "BTC/USDT"
+
+ # No emit yet
+ assert send_mock.call_count == 0
+
+ # Rpc is added, we call emit, should call send_msg
+ dataprovider._emit_df(pair, ohlcv_history)
+ assert send_mock.call_count == 1
+
+ # No rpc added, emit called, should not call send_msg
+ dataprovider_no_rpc._emit_df(pair, ohlcv_history)
+ assert send_mock.call_count == 1
+
+
def test_refresh(mocker, default_conf, ohlcv_history):
refresh_mock = MagicMock()
mocker.patch("freqtrade.exchange.Exchange.refresh_latest_ohlcv", refresh_mock)
diff --git a/tests/data/test_history.py b/tests/data/test_history.py
index 8081e984f..5642442b2 100644
--- a/tests/data/test_history.py
+++ b/tests/data/test_history.py
@@ -1,7 +1,6 @@
# pragma pylint: disable=missing-docstring, protected-access, C0103
import json
-import re
import uuid
from pathlib import Path
from shutil import copyfile
@@ -13,18 +12,17 @@ from pandas import DataFrame
from pandas.testing import assert_frame_equal
from freqtrade.configuration import TimeRange
-from freqtrade.constants import AVAILABLE_DATAHANDLERS, DATETIME_PRINT_FORMAT
+from freqtrade.constants import DATETIME_PRINT_FORMAT
from freqtrade.data.converter import ohlcv_to_dataframe
-from freqtrade.data.history.hdf5datahandler import HDF5DataHandler
from freqtrade.data.history.history_utils import (_download_pair_history, _download_trades_history,
_load_cached_data_for_updating,
convert_trades_to_ohlcv, get_timerange, load_data,
load_pair_history, refresh_backtest_ohlcv_data,
refresh_backtest_trades_data, refresh_data,
validate_backtest_data)
-from freqtrade.data.history.idatahandler import IDataHandler, get_datahandler, get_datahandlerclass
+from freqtrade.data.history.idatahandler import get_datahandler
from freqtrade.data.history.jsondatahandler import JsonDataHandler, JsonGzDataHandler
-from freqtrade.enums import CandleType, TradingMode
+from freqtrade.enums import CandleType
from freqtrade.exchange import timeframe_to_minutes
from freqtrade.misc import file_dump_json
from freqtrade.resolvers import StrategyResolver
@@ -32,25 +30,6 @@ from tests.conftest import (CURRENT_TEST_STRATEGY, get_patched_exchange, log_has
patch_exchange)
-# Change this if modifying UNITTEST/BTC testdatafile
-_BTC_UNITTEST_LENGTH = 13681
-
-
-def _backup_file(file: Path, copy_file: bool = False) -> None:
- """
- Backup existing file to avoid deleting the user file
- :param file: complete path to the file
- :param copy_file: keep file in place too.
- :return: None
- """
- file_swp = str(file) + '.swp'
- if file.is_file():
- file.rename(file_swp)
-
- if copy_file:
- copyfile(file_swp, file)
-
-
def _clean_test_file(file: Path) -> None:
"""
Backup existing file to avoid deleting the user file
@@ -67,7 +46,7 @@ def _clean_test_file(file: Path) -> None:
file_swp.rename(file)
-def test_load_data_30min_timeframe(mocker, caplog, default_conf, testdatadir) -> None:
+def test_load_data_30min_timeframe(caplog, testdatadir) -> None:
ld = load_pair_history(pair='UNITTEST/BTC', timeframe='30m', datadir=testdatadir)
assert isinstance(ld, DataFrame)
assert not log_has(
@@ -76,7 +55,7 @@ def test_load_data_30min_timeframe(mocker, caplog, default_conf, testdatadir) ->
)
-def test_load_data_7min_timeframe(mocker, caplog, default_conf, testdatadir) -> None:
+def test_load_data_7min_timeframe(caplog, testdatadir) -> None:
ld = load_pair_history(pair='UNITTEST/BTC', timeframe='7m', datadir=testdatadir)
assert isinstance(ld, DataFrame)
assert ld.empty
@@ -108,7 +87,7 @@ def test_load_data_mark(ohlcv_history, mocker, caplog, testdatadir) -> None:
)
-def test_load_data_startup_candles(mocker, caplog, default_conf, testdatadir) -> None:
+def test_load_data_startup_candles(mocker, testdatadir) -> None:
ltfmock = mocker.patch(
'freqtrade.data.history.jsondatahandler.JsonDataHandler._ohlcv_load',
MagicMock(return_value=DataFrame()))
@@ -405,7 +384,7 @@ def test_load_partial_missing(testdatadir, caplog) -> None:
caplog)
-def test_init(default_conf, mocker) -> None:
+def test_init(default_conf) -> None:
assert {} == load_data(
datadir=Path(''),
pairs=[],
@@ -685,340 +664,3 @@ def test_convert_trades_to_ohlcv(testdatadir, tmpdir, caplog):
convert_trades_to_ohlcv(['NoDatapair'], timeframes=['1m', '5m'],
datadir=tmpdir1, timerange=tr, erase=True)
assert log_has('Could not convert NoDatapair to OHLCV.', caplog)
-
-
-def test_datahandler_ohlcv_get_pairs(testdatadir):
- pairs = JsonDataHandler.ohlcv_get_pairs(testdatadir, '5m', candle_type=CandleType.SPOT)
- # Convert to set to avoid failures due to sorting
- assert set(pairs) == {'UNITTEST/BTC', 'XLM/BTC', 'ETH/BTC', 'TRX/BTC', 'LTC/BTC',
- 'XMR/BTC', 'ZEC/BTC', 'ADA/BTC', 'ETC/BTC', 'NXT/BTC',
- 'DASH/BTC', 'XRP/ETH'}
-
- pairs = JsonGzDataHandler.ohlcv_get_pairs(testdatadir, '8m', candle_type=CandleType.SPOT)
- assert set(pairs) == {'UNITTEST/BTC'}
-
- pairs = HDF5DataHandler.ohlcv_get_pairs(testdatadir, '5m', candle_type=CandleType.SPOT)
- assert set(pairs) == {'UNITTEST/BTC'}
-
- pairs = JsonDataHandler.ohlcv_get_pairs(testdatadir, '1h', candle_type=CandleType.MARK)
- assert set(pairs) == {'UNITTEST/USDT', 'XRP/USDT'}
-
- pairs = JsonGzDataHandler.ohlcv_get_pairs(testdatadir, '1h', candle_type=CandleType.FUTURES)
- assert set(pairs) == {'XRP/USDT'}
-
- pairs = HDF5DataHandler.ohlcv_get_pairs(testdatadir, '1h', candle_type=CandleType.MARK)
- assert set(pairs) == {'UNITTEST/USDT:USDT'}
-
-
-@pytest.mark.parametrize('filename,pair,timeframe,candletype', [
- ('XMR_BTC-5m.json', 'XMR_BTC', '5m', ''),
- ('XMR_USDT-1h.h5', 'XMR_USDT', '1h', ''),
- ('BTC-PERP-1h.h5', 'BTC-PERP', '1h', ''),
- ('BTC_USDT-2h.jsongz', 'BTC_USDT', '2h', ''),
- ('BTC_USDT-2h-mark.jsongz', 'BTC_USDT', '2h', 'mark'),
- ('XMR_USDT-1h-mark.h5', 'XMR_USDT', '1h', 'mark'),
- ('XMR_USDT-1h-random.h5', 'XMR_USDT', '1h', 'random'),
- ('BTC-PERP-1h-index.h5', 'BTC-PERP', '1h', 'index'),
- ('XMR_USDT_USDT-1h-mark.h5', 'XMR_USDT_USDT', '1h', 'mark'),
-])
-def test_datahandler_ohlcv_regex(filename, pair, timeframe, candletype):
- regex = JsonDataHandler._OHLCV_REGEX
-
- match = re.search(regex, filename)
- assert len(match.groups()) > 1
- assert match[1] == pair
- assert match[2] == timeframe
- assert match[3] == candletype
-
-
-@pytest.mark.parametrize('input,expected', [
- ('XMR_USDT', 'XMR/USDT'),
- ('BTC_USDT', 'BTC/USDT'),
- ('USDT_BUSD', 'USDT/BUSD'),
- ('BTC_USDT_USDT', 'BTC/USDT:USDT'), # Futures
- ('XRP_USDT_USDT', 'XRP/USDT:USDT'), # futures
- ('BTC-PERP', 'BTC-PERP'),
- ('BTC-PERP_USDT', 'BTC-PERP:USDT'), # potential FTX case
- ('UNITTEST_USDT', 'UNITTEST/USDT'),
-])
-def test_rebuild_pair_from_filename(input, expected):
-
- assert IDataHandler.rebuild_pair_from_filename(input) == expected
-
-
-def test_datahandler_ohlcv_get_available_data(testdatadir):
- paircombs = JsonDataHandler.ohlcv_get_available_data(testdatadir, TradingMode.SPOT)
- # Convert to set to avoid failures due to sorting
- assert set(paircombs) == {
- ('UNITTEST/BTC', '5m', CandleType.SPOT),
- ('ETH/BTC', '5m', CandleType.SPOT),
- ('XLM/BTC', '5m', CandleType.SPOT),
- ('TRX/BTC', '5m', CandleType.SPOT),
- ('LTC/BTC', '5m', CandleType.SPOT),
- ('XMR/BTC', '5m', CandleType.SPOT),
- ('ZEC/BTC', '5m', CandleType.SPOT),
- ('UNITTEST/BTC', '1m', CandleType.SPOT),
- ('ADA/BTC', '5m', CandleType.SPOT),
- ('ETC/BTC', '5m', CandleType.SPOT),
- ('NXT/BTC', '5m', CandleType.SPOT),
- ('DASH/BTC', '5m', CandleType.SPOT),
- ('XRP/ETH', '1m', CandleType.SPOT),
- ('XRP/ETH', '5m', CandleType.SPOT),
- ('UNITTEST/BTC', '30m', CandleType.SPOT),
- ('UNITTEST/BTC', '8m', CandleType.SPOT),
- ('NOPAIR/XXX', '4m', CandleType.SPOT),
- }
-
- paircombs = JsonDataHandler.ohlcv_get_available_data(testdatadir, TradingMode.FUTURES)
- # Convert to set to avoid failures due to sorting
- assert set(paircombs) == {
- ('UNITTEST/USDT', '1h', 'mark'),
- ('XRP/USDT', '1h', 'futures'),
- ('XRP/USDT', '1h', 'mark'),
- ('XRP/USDT', '8h', 'mark'),
- ('XRP/USDT', '8h', 'funding_rate'),
- }
-
- paircombs = JsonGzDataHandler.ohlcv_get_available_data(testdatadir, TradingMode.SPOT)
- assert set(paircombs) == {('UNITTEST/BTC', '8m', CandleType.SPOT)}
- paircombs = HDF5DataHandler.ohlcv_get_available_data(testdatadir, TradingMode.SPOT)
- assert set(paircombs) == {('UNITTEST/BTC', '5m', CandleType.SPOT)}
-
-
-def test_jsondatahandler_trades_get_pairs(testdatadir):
- pairs = JsonGzDataHandler.trades_get_pairs(testdatadir)
- # Convert to set to avoid failures due to sorting
- assert set(pairs) == {'XRP/ETH', 'XRP/OLD'}
-
-
-def test_jsondatahandler_ohlcv_purge(mocker, testdatadir):
- mocker.patch.object(Path, "exists", MagicMock(return_value=False))
- unlinkmock = mocker.patch.object(Path, "unlink", MagicMock())
- dh = JsonGzDataHandler(testdatadir)
- assert not dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', '')
- assert not dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', candle_type='mark')
- assert unlinkmock.call_count == 0
-
- mocker.patch.object(Path, "exists", MagicMock(return_value=True))
- assert dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', '')
- assert dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', candle_type='mark')
- assert unlinkmock.call_count == 2
-
-
-def test_jsondatahandler_ohlcv_load(testdatadir, caplog):
- dh = JsonDataHandler(testdatadir)
- df = dh.ohlcv_load('XRP/ETH', '5m', 'spot')
- assert len(df) == 711
-
- df_mark = dh.ohlcv_load('UNITTEST/USDT', '1h', candle_type="mark")
- assert len(df_mark) == 99
-
- df_no_mark = dh.ohlcv_load('UNITTEST/USDT', '1h', 'spot')
- assert len(df_no_mark) == 0
-
- # Failure case (empty array)
- df1 = dh.ohlcv_load('NOPAIR/XXX', '4m', 'spot')
- assert len(df1) == 0
- assert log_has("Could not load data for NOPAIR/XXX.", caplog)
- assert df.columns.equals(df1.columns)
-
-
-def test_jsondatahandler_trades_load(testdatadir, caplog):
- dh = JsonGzDataHandler(testdatadir)
- logmsg = "Old trades format detected - converting"
- dh.trades_load('XRP/ETH')
- assert not log_has(logmsg, caplog)
-
- # Test conversation is happening
- dh.trades_load('XRP/OLD')
- assert log_has(logmsg, caplog)
-
-
-def test_jsondatahandler_trades_purge(mocker, testdatadir):
- mocker.patch.object(Path, "exists", MagicMock(return_value=False))
- unlinkmock = mocker.patch.object(Path, "unlink", MagicMock())
- dh = JsonGzDataHandler(testdatadir)
- assert not dh.trades_purge('UNITTEST/NONEXIST')
- assert unlinkmock.call_count == 0
-
- mocker.patch.object(Path, "exists", MagicMock(return_value=True))
- assert dh.trades_purge('UNITTEST/NONEXIST')
- assert unlinkmock.call_count == 1
-
-
-@pytest.mark.parametrize('datahandler', AVAILABLE_DATAHANDLERS)
-def test_datahandler_ohlcv_append(datahandler, testdatadir, ):
- dh = get_datahandler(testdatadir, datahandler)
- with pytest.raises(NotImplementedError):
- dh.ohlcv_append('UNITTEST/ETH', '5m', DataFrame(), CandleType.SPOT)
- with pytest.raises(NotImplementedError):
- dh.ohlcv_append('UNITTEST/ETH', '5m', DataFrame(), CandleType.MARK)
-
-
-@pytest.mark.parametrize('datahandler', AVAILABLE_DATAHANDLERS)
-def test_datahandler_trades_append(datahandler, testdatadir):
- dh = get_datahandler(testdatadir, datahandler)
- with pytest.raises(NotImplementedError):
- dh.trades_append('UNITTEST/ETH', [])
-
-
-def test_hdf5datahandler_trades_get_pairs(testdatadir):
- pairs = HDF5DataHandler.trades_get_pairs(testdatadir)
- # Convert to set to avoid failures due to sorting
- assert set(pairs) == {'XRP/ETH'}
-
-
-def test_hdf5datahandler_trades_load(testdatadir):
- dh = HDF5DataHandler(testdatadir)
- trades = dh.trades_load('XRP/ETH')
- assert isinstance(trades, list)
-
- trades1 = dh.trades_load('UNITTEST/NONEXIST')
- assert trades1 == []
- # data goes from 2019-10-11 - 2019-10-13
- timerange = TimeRange.parse_timerange('20191011-20191012')
-
- trades2 = dh._trades_load('XRP/ETH', timerange)
- assert len(trades) > len(trades2)
- # Check that ID is None (If it's nan, it's wrong)
- assert trades2[0][2] is None
-
- # unfiltered load has trades before starttime
- assert len([t for t in trades if t[0] < timerange.startts * 1000]) >= 0
- # filtered list does not have trades before starttime
- assert len([t for t in trades2 if t[0] < timerange.startts * 1000]) == 0
- # unfiltered load has trades after endtime
- assert len([t for t in trades if t[0] > timerange.stopts * 1000]) > 0
- # filtered list does not have trades after endtime
- assert len([t for t in trades2 if t[0] > timerange.stopts * 1000]) == 0
-
-
-def test_hdf5datahandler_trades_store(testdatadir, tmpdir):
- tmpdir1 = Path(tmpdir)
- dh = HDF5DataHandler(testdatadir)
- trades = dh.trades_load('XRP/ETH')
-
- dh1 = HDF5DataHandler(tmpdir1)
- dh1.trades_store('XRP/NEW', trades)
- file = tmpdir1 / 'XRP_NEW-trades.h5'
- assert file.is_file()
- # Load trades back
- trades_new = dh1.trades_load('XRP/NEW')
-
- assert len(trades_new) == len(trades)
- assert trades[0][0] == trades_new[0][0]
- assert trades[0][1] == trades_new[0][1]
- # assert trades[0][2] == trades_new[0][2] # This is nan - so comparison does not make sense
- assert trades[0][3] == trades_new[0][3]
- assert trades[0][4] == trades_new[0][4]
- assert trades[0][5] == trades_new[0][5]
- assert trades[0][6] == trades_new[0][6]
- assert trades[-1][0] == trades_new[-1][0]
- assert trades[-1][1] == trades_new[-1][1]
- # assert trades[-1][2] == trades_new[-1][2] # This is nan - so comparison does not make sense
- assert trades[-1][3] == trades_new[-1][3]
- assert trades[-1][4] == trades_new[-1][4]
- assert trades[-1][5] == trades_new[-1][5]
- assert trades[-1][6] == trades_new[-1][6]
-
-
-def test_hdf5datahandler_trades_purge(mocker, testdatadir):
- mocker.patch.object(Path, "exists", MagicMock(return_value=False))
- unlinkmock = mocker.patch.object(Path, "unlink", MagicMock())
- dh = HDF5DataHandler(testdatadir)
- assert not dh.trades_purge('UNITTEST/NONEXIST')
- assert unlinkmock.call_count == 0
-
- mocker.patch.object(Path, "exists", MagicMock(return_value=True))
- assert dh.trades_purge('UNITTEST/NONEXIST')
- assert unlinkmock.call_count == 1
-
-
-@pytest.mark.parametrize('pair,timeframe,candle_type,candle_append,startdt,enddt', [
- # Data goes from 2018-01-10 - 2018-01-30
- ('UNITTEST/BTC', '5m', 'spot', '', '2018-01-15', '2018-01-19'),
- # Mark data goes from to 2021-11-15 2021-11-19
- ('UNITTEST/USDT:USDT', '1h', 'mark', '-mark', '2021-11-16', '2021-11-18'),
-])
-def test_hdf5datahandler_ohlcv_load_and_resave(
- testdatadir,
- tmpdir,
- pair,
- timeframe,
- candle_type,
- candle_append,
- startdt, enddt
-):
- tmpdir1 = Path(tmpdir)
- tmpdir2 = tmpdir1
- if candle_type not in ('', 'spot'):
- tmpdir2 = tmpdir1 / 'futures'
- tmpdir2.mkdir()
- dh = HDF5DataHandler(testdatadir)
- ohlcv = dh._ohlcv_load(pair, timeframe, None, candle_type=candle_type)
- assert isinstance(ohlcv, DataFrame)
- assert len(ohlcv) > 0
-
- file = tmpdir2 / f"UNITTEST_NEW-{timeframe}{candle_append}.h5"
- assert not file.is_file()
-
- dh1 = HDF5DataHandler(tmpdir1)
- dh1.ohlcv_store('UNITTEST/NEW', timeframe, ohlcv, candle_type=candle_type)
- assert file.is_file()
-
- assert not ohlcv[ohlcv['date'] < startdt].empty
-
- timerange = TimeRange.parse_timerange(f"{startdt.replace('-', '')}-{enddt.replace('-', '')}")
-
- # Call private function to ensure timerange is filtered in hdf5
- ohlcv = dh._ohlcv_load(pair, timeframe, timerange, candle_type=candle_type)
- ohlcv1 = dh1._ohlcv_load('UNITTEST/NEW', timeframe, timerange, candle_type=candle_type)
- assert len(ohlcv) == len(ohlcv1)
- assert ohlcv.equals(ohlcv1)
- assert ohlcv[ohlcv['date'] < startdt].empty
- assert ohlcv[ohlcv['date'] > enddt].empty
-
- # Try loading inexisting file
- ohlcv = dh.ohlcv_load('UNITTEST/NONEXIST', timeframe, candle_type=candle_type)
- assert ohlcv.empty
-
-
-def test_hdf5datahandler_ohlcv_purge(mocker, testdatadir):
- mocker.patch.object(Path, "exists", MagicMock(return_value=False))
- unlinkmock = mocker.patch.object(Path, "unlink", MagicMock())
- dh = HDF5DataHandler(testdatadir)
- assert not dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', '')
- assert not dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', candle_type='mark')
- assert unlinkmock.call_count == 0
-
- mocker.patch.object(Path, "exists", MagicMock(return_value=True))
- assert dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', '')
- assert dh.ohlcv_purge('UNITTEST/NONEXIST', '5m', candle_type='mark')
- assert unlinkmock.call_count == 2
-
-
-def test_gethandlerclass():
- cl = get_datahandlerclass('json')
- assert cl == JsonDataHandler
- assert issubclass(cl, IDataHandler)
- cl = get_datahandlerclass('jsongz')
- assert cl == JsonGzDataHandler
- assert issubclass(cl, IDataHandler)
- assert issubclass(cl, JsonDataHandler)
- cl = get_datahandlerclass('hdf5')
- assert cl == HDF5DataHandler
- assert issubclass(cl, IDataHandler)
- with pytest.raises(ValueError, match=r"No datahandler for .*"):
- get_datahandlerclass('DeadBeef')
-
-
-def test_get_datahandler(testdatadir):
- dh = get_datahandler(testdatadir, 'json')
- assert type(dh) == JsonDataHandler
- dh = get_datahandler(testdatadir, 'jsongz')
- assert type(dh) == JsonGzDataHandler
- dh1 = get_datahandler(testdatadir, 'jsongz', dh)
- assert id(dh1) == id(dh)
-
- dh = get_datahandler(testdatadir, 'hdf5')
- assert type(dh) == HDF5DataHandler
diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py
index 71690ecdf..37ba2ca97 100644
--- a/tests/exchange/test_exchange.py
+++ b/tests/exchange/test_exchange.py
@@ -20,6 +20,7 @@ from freqtrade.exchange import (Binance, Bittrex, Exchange, Kraken, amount_to_pr
timeframe_to_prev_date, timeframe_to_seconds)
from freqtrade.exchange.common import (API_FETCH_ORDER_RETRY_COUNT, API_RETRY_COUNT,
calculate_backoff, remove_credentials)
+from freqtrade.exchange.exchange import amount_to_contract_precision
from freqtrade.resolvers.exchange_resolver import ExchangeResolver
from tests.conftest import get_mock_coro, get_patched_exchange, log_has, log_has_re, num_log_has_re
@@ -4470,6 +4471,7 @@ def test__amount_to_contracts(
('ADA/USDT:USDT', 10.4445555, 10.4, 10.444),
('LTC/ETH', 30, 30, 30),
('LTC/USD', 30, 30, 30),
+ ('ADA/USDT:USDT', 1.17, 1.1, 1.17),
# contract size of 10
('ETH/USDT:USDT', 10.111, 10.1, 10),
('ETH/USDT:USDT', 10.188, 10.1, 10),
@@ -4497,6 +4499,20 @@ def test_amount_to_contract_precision(
assert result_size == expected_fut
+@pytest.mark.parametrize('amount,precision,precision_mode,contract_size,expected', [
+ (1.17, 1.0, 4, 0.01, 1.17), # Tick size
+ (1.17, 1.0, 2, 0.01, 1.17), #
+ (1.16, 1.0, 4, 0.01, 1.16), #
+ (1.16, 1.0, 2, 0.01, 1.16), #
+ (1.13, 1.0, 2, 0.01, 1.13), #
+ (10.988, 1.0, 2, 10, 10),
+ (10.988, 1.0, 4, 10, 10),
+])
+def test_amount_to_contract_precision2(amount, precision, precision_mode, contract_size, expected):
+ res = amount_to_contract_precision(amount, precision, precision_mode, contract_size)
+ assert pytest.approx(res) == expected
+
+
@pytest.mark.parametrize('exchange_name,open_rate,is_short,trading_mode,margin_mode', [
# Bittrex
('bittrex', 2.0, False, 'spot', None),
diff --git a/tests/freqai/test_freqai_backtesting.py b/tests/freqai/test_freqai_backtesting.py
index ea127fa99..b1881b2f5 100644
--- a/tests/freqai/test_freqai_backtesting.py
+++ b/tests/freqai/test_freqai_backtesting.py
@@ -3,21 +3,21 @@ from datetime import datetime, timezone
from pathlib import Path
from unittest.mock import PropertyMock
-import pytest
-
-from freqtrade.commands.optimize_commands import start_backtesting
-from freqtrade.exceptions import OperationalException
+from freqtrade.commands.optimize_commands import setup_optimize_configuration
+from freqtrade.enums import RunMode
from freqtrade.optimize.backtesting import Backtesting
from tests.conftest import (CURRENT_TEST_STRATEGY, get_args, log_has_re, patch_exchange,
patched_configuration_load_config_file)
-def test_freqai_backtest_start_backtest_list(freqai_conf, mocker, testdatadir):
+def test_freqai_backtest_start_backtest_list(freqai_conf, mocker, testdatadir, caplog):
patch_exchange(mocker)
+ now = datetime.now(timezone.utc)
mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist',
PropertyMock(return_value=['HULUMULU/USDT', 'XRP/USDT']))
- # mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', backtestmock)
+ mocker.patch('freqtrade.optimize.backtesting.history.load_data')
+ mocker.patch('freqtrade.optimize.backtesting.history.get_timerange', return_value=(now, now))
patched_configuration_load_config_file(mocker, freqai_conf)
@@ -30,9 +30,11 @@ def test_freqai_backtest_start_backtest_list(freqai_conf, mocker, testdatadir):
'--strategy-list', CURRENT_TEST_STRATEGY
]
args = get_args(args)
- with pytest.raises(OperationalException,
- match=r"You can't use strategy_list and freqai at the same time\."):
- start_backtesting(args)
+ bt_config = setup_optimize_configuration(args, RunMode.BACKTEST)
+ Backtesting(bt_config)
+ assert log_has_re('Using --strategy-list with FreqAI REQUIRES all strategies to have identical '
+ 'populate_any_indicators.', caplog)
+ Backtesting.cleanup()
def test_freqai_backtest_load_data(freqai_conf, mocker, caplog):
diff --git a/tests/freqai/test_freqai_interface.py b/tests/freqai/test_freqai_interface.py
index a55914904..196c37c08 100644
--- a/tests/freqai/test_freqai_interface.py
+++ b/tests/freqai/test_freqai_interface.py
@@ -319,6 +319,41 @@ def test_principal_component_analysis(mocker, freqai_conf):
shutil.rmtree(Path(freqai.dk.full_path))
+def test_plot_feature_importance(mocker, freqai_conf):
+
+ from freqtrade.freqai.utils import plot_feature_importance
+
+ freqai_conf.update({"timerange": "20180110-20180130"})
+ freqai_conf.get("freqai", {}).get("feature_parameters", {}).update(
+ {"princpial_component_analysis": "true"})
+
+ strategy = get_patched_freqai_strategy(mocker, freqai_conf)
+ exchange = get_patched_exchange(mocker, freqai_conf)
+ strategy.dp = DataProvider(freqai_conf, exchange)
+ strategy.freqai_info = freqai_conf.get("freqai", {})
+ freqai = strategy.freqai
+ freqai.live = True
+ freqai.dk = FreqaiDataKitchen(freqai_conf)
+ timerange = TimeRange.parse_timerange("20180110-20180130")
+ freqai.dd.load_all_pair_histories(timerange, freqai.dk)
+
+ freqai.dd.pair_dict = MagicMock()
+
+ data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
+ new_timerange = TimeRange.parse_timerange("20180120-20180130")
+
+ freqai.extract_data_and_train_model(
+ new_timerange, "ADA/BTC", strategy, freqai.dk, data_load_timerange)
+
+ model = freqai.dd.load_data("ADA/BTC", freqai.dk)
+
+ plot_feature_importance(model, "ADA/BTC", freqai.dk)
+
+ assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}.html")
+
+ shutil.rmtree(Path(freqai.dk.full_path))
+
+
def test_spice_rack(mocker, default_conf, tmpdir, caplog):
strategy = get_patched_freqai_strategy(mocker, default_conf)
diff --git a/tests/optimize/test_optimize_reports.py b/tests/optimize/test_optimize_reports.py
index 5095f2fde..403075795 100644
--- a/tests/optimize/test_optimize_reports.py
+++ b/tests/optimize/test_optimize_reports.py
@@ -1,6 +1,7 @@
import re
from datetime import timedelta
from pathlib import Path
+from shutil import copyfile
import joblib
import pandas as pd
@@ -25,7 +26,22 @@ from freqtrade.optimize.optimize_reports import (_get_resample_from_period, gene
text_table_exit_reason, text_table_strategy)
from freqtrade.resolvers.strategy_resolver import StrategyResolver
from tests.conftest import CURRENT_TEST_STRATEGY
-from tests.data.test_history import _backup_file, _clean_test_file
+from tests.data.test_history import _clean_test_file
+
+
+def _backup_file(file: Path, copy_file: bool = False) -> None:
+ """
+ Backup existing file to avoid deleting the user file
+ :param file: complete path to the file
+ :param copy_file: keep file in place too.
+ :return: None
+ """
+ file_swp = str(file) + '.swp'
+ if file.is_file():
+ file.rename(file_swp)
+
+ if copy_file:
+ copyfile(file_swp, file)
def test_text_table_bt_results():
diff --git a/tests/plugins/test_pairlist.py b/tests/plugins/test_pairlist.py
index 48a0f81cb..538751251 100644
--- a/tests/plugins/test_pairlist.py
+++ b/tests/plugins/test_pairlist.py
@@ -467,6 +467,10 @@ def test_VolumePairList_refresh_empty(mocker, markets_empty, whitelist_conf):
{"method": "RangeStabilityFilter", "lookback_days": 10,
"max_rate_of_change": 0.01, "refresh_period": 1440}],
"BTC", []), # All removed because of max_rate_of_change being 0.017
+ ([{"method": "StaticPairList"},
+ {"method": "RangeStabilityFilter", "lookback_days": 10,
+ "min_rate_of_change": 0.018, "max_rate_of_change": 0.02, "refresh_period": 1440}],
+ "BTC", []), # All removed - limits are above the highest change_rate
([{"method": "StaticPairList"},
{"method": "VolatilityFilter", "lookback_days": 3,
"min_volatility": 0.002, "max_volatility": 0.004, "refresh_period": 1440}],
diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py
index 5dfa77d8b..e007e0a9e 100644
--- a/tests/rpc/test_rpc_apiserver.py
+++ b/tests/rpc/test_rpc_apiserver.py
@@ -3,6 +3,8 @@ Unit test file for rpc/api_server.py
"""
import json
+import logging
+import time
from datetime import datetime, timedelta, timezone
from pathlib import Path
from unittest.mock import ANY, MagicMock, PropertyMock
@@ -10,7 +12,7 @@ from unittest.mock import ANY, MagicMock, PropertyMock
import pandas as pd
import pytest
import uvicorn
-from fastapi import FastAPI
+from fastapi import FastAPI, WebSocketDisconnect
from fastapi.exceptions import HTTPException
from fastapi.testclient import TestClient
from requests.auth import _basic_auth_str
@@ -31,6 +33,7 @@ from tests.conftest import (CURRENT_TEST_STRATEGY, create_mock_trades, get_mock_
BASE_URI = "/api/v1"
_TEST_USER = "FreqTrader"
_TEST_PASS = "SuperSecurePassword1!"
+_TEST_WS_TOKEN = "secret_Ws_t0ken"
@pytest.fixture
@@ -44,17 +47,21 @@ def botclient(default_conf, mocker):
"CORS_origins": ['http://example.com'],
"username": _TEST_USER,
"password": _TEST_PASS,
+ "ws_token": _TEST_WS_TOKEN
}})
ftbot = get_patched_freqtradebot(mocker, default_conf)
rpc = RPC(ftbot)
mocker.patch('freqtrade.rpc.api_server.ApiServer.start_api', MagicMock())
+ apiserver = None
try:
apiserver = ApiServer(default_conf)
apiserver.add_rpc_handler(rpc)
yield ftbot, TestClient(apiserver.app)
# Cleanup ... ?
finally:
+ if apiserver:
+ apiserver.cleanup()
ApiServer.shutdown()
@@ -154,6 +161,25 @@ def test_api_auth():
get_user_from_token(b'not_a_token', 'secret1234')
+def test_api_ws_auth(botclient):
+ ftbot, client = botclient
+ def url(token): return f"/api/v1/message/ws?token={token}"
+
+ bad_token = "bad-ws_token"
+ with pytest.raises(WebSocketDisconnect):
+ with client.websocket_connect(url(bad_token)) as websocket:
+ websocket.receive()
+
+ good_token = _TEST_WS_TOKEN
+ with client.websocket_connect(url(good_token)) as websocket:
+ pass
+
+ jwt_secret = ftbot.config['api_server'].get('jwt_secret_key', 'super-secret')
+ jwt_token = create_token({'identity': {'u': 'Freqtrade'}}, jwt_secret)
+ with client.websocket_connect(url(jwt_token)) as websocket:
+ pass
+
+
def test_api_unauthorized(botclient):
ftbot, client = botclient
rc = client.get(f"{BASE_URI}/ping")
@@ -261,6 +287,7 @@ def test_api__init__(default_conf, mocker):
with pytest.raises(OperationalException, match="RPC Handler already attached."):
apiserver.add_rpc_handler(RPC(get_patched_freqtradebot(mocker, default_conf)))
+ apiserver.cleanup()
ApiServer.shutdown()
@@ -388,6 +415,7 @@ def test_api_run(default_conf, mocker, caplog):
MagicMock(side_effect=Exception))
apiserver.start_api()
assert log_has("Api server failed to start.", caplog)
+ apiserver.cleanup()
ApiServer.shutdown()
@@ -410,6 +438,7 @@ def test_api_cleanup(default_conf, mocker, caplog):
apiserver.cleanup()
assert apiserver._server.cleanup.call_count == 1
assert log_has("Stopping API Server", caplog)
+ assert log_has("Stopping API Server background tasks", caplog)
ApiServer.shutdown()
@@ -1663,3 +1692,93 @@ def test_health(botclient):
ret = rc.json()
assert ret['last_process_ts'] == 0
assert ret['last_process'] == '1970-01-01T00:00:00+00:00'
+
+
+def test_api_ws_subscribe(botclient, mocker):
+ ftbot, client = botclient
+ ws_url = f"/api/v1/message/ws?token={_TEST_WS_TOKEN}"
+
+ sub_mock = mocker.patch('freqtrade.rpc.api_server.ws.WebSocketChannel.set_subscriptions')
+
+ with client.websocket_connect(ws_url) as ws:
+ ws.send_json({'type': 'subscribe', 'data': ['whitelist']})
+
+ # Check call count is now 1 as we sent a valid subscribe request
+ assert sub_mock.call_count == 1
+
+ with client.websocket_connect(ws_url) as ws:
+ ws.send_json({'type': 'subscribe', 'data': 'whitelist'})
+
+ # Call count hasn't changed as the subscribe request was invalid
+ assert sub_mock.call_count == 1
+
+
+def test_api_ws_requests(botclient, mocker, caplog):
+ caplog.set_level(logging.DEBUG)
+
+ ftbot, client = botclient
+ ws_url = f"/api/v1/message/ws?token={_TEST_WS_TOKEN}"
+
+ # Test whitelist request
+ with client.websocket_connect(ws_url) as ws:
+ ws.send_json({"type": "whitelist", "data": None})
+ response = ws.receive_json()
+
+ assert log_has_re(r"Request of type whitelist from.+", caplog)
+ assert response['type'] == "whitelist"
+
+ # Test analyzed_df request
+ with client.websocket_connect(ws_url) as ws:
+ ws.send_json({"type": "analyzed_df", "data": {}})
+ response = ws.receive_json()
+
+ assert log_has_re(r"Request of type analyzed_df from.+", caplog)
+ assert response['type'] == "analyzed_df"
+
+ caplog.clear()
+ # Test analyzed_df request with data
+ with client.websocket_connect(ws_url) as ws:
+ ws.send_json({"type": "analyzed_df", "data": {"limit": 100}})
+ response = ws.receive_json()
+
+ assert log_has_re(r"Request of type analyzed_df from.+", caplog)
+ assert response['type'] == "analyzed_df"
+
+
+def test_api_ws_send_msg(default_conf, mocker, caplog):
+ try:
+ caplog.set_level(logging.DEBUG)
+
+ default_conf.update({"api_server": {"enabled": True,
+ "listen_ip_address": "127.0.0.1",
+ "listen_port": 8080,
+ "CORS_origins": ['http://example.com'],
+ "username": _TEST_USER,
+ "password": _TEST_PASS,
+ "ws_token": _TEST_WS_TOKEN
+ }})
+ mocker.patch('freqtrade.rpc.telegram.Updater')
+ mocker.patch('freqtrade.rpc.api_server.ApiServer.start_api')
+ apiserver = ApiServer(default_conf)
+ apiserver.add_rpc_handler(RPC(get_patched_freqtradebot(mocker, default_conf)))
+ apiserver.start_message_queue()
+ # Give the queue thread time to start
+ time.sleep(0.2)
+
+ # Test message_queue coro receives the message
+ test_message = {"type": "status", "data": "test"}
+ apiserver.send_msg(test_message)
+ time.sleep(0.1) # Not sure how else to wait for the coro to receive the data
+ assert log_has("Found message of type: status", caplog)
+
+ # Test if exception logged when error occurs in sending
+ mocker.patch('freqtrade.rpc.api_server.ws.channel.ChannelManager.broadcast',
+ side_effect=Exception)
+
+ apiserver.send_msg(test_message)
+ time.sleep(0.1) # Not sure how else to wait for the coro to receive the data
+ assert log_has_re(r"Exception happened in background task.*", caplog)
+
+ finally:
+ apiserver.cleanup()
+ ApiServer.shutdown()
diff --git a/tests/rpc/test_rpc_emc.py b/tests/rpc/test_rpc_emc.py
new file mode 100644
index 000000000..2649c5460
--- /dev/null
+++ b/tests/rpc/test_rpc_emc.py
@@ -0,0 +1,465 @@
+"""
+Unit test file for rpc/external_message_consumer.py
+"""
+import asyncio
+import functools
+import logging
+from datetime import datetime, timezone
+from unittest.mock import MagicMock
+
+import pytest
+import websockets
+
+from freqtrade.data.dataprovider import DataProvider
+from freqtrade.rpc.external_message_consumer import ExternalMessageConsumer
+from tests.conftest import log_has, log_has_re, log_has_when
+
+
+_TEST_WS_TOKEN = "secret_Ws_t0ken"
+_TEST_WS_HOST = "127.0.0.1"
+_TEST_WS_PORT = 9989
+
+
+@pytest.fixture
+def patched_emc(default_conf, mocker):
+ default_conf.update({
+ "external_message_consumer": {
+ "enabled": True,
+ "producers": [
+ {
+ "name": "default",
+ "host": "null",
+ "port": 9891,
+ "ws_token": _TEST_WS_TOKEN
+ }
+ ]
+ }
+ })
+ dataprovider = DataProvider(default_conf, None, None, None)
+ emc = ExternalMessageConsumer(default_conf, dataprovider)
+
+ try:
+ yield emc
+ finally:
+ emc.shutdown()
+
+
+def test_emc_start(patched_emc, caplog):
+ # Test if the message was printed
+ assert log_has_when("Starting ExternalMessageConsumer", caplog, "setup")
+ # Test if the thread and loop objects were created
+ assert patched_emc._thread and patched_emc._loop
+
+ # Test we call start again nothing happens
+ prev_thread = patched_emc._thread
+ patched_emc.start()
+ assert prev_thread == patched_emc._thread
+
+
+def test_emc_shutdown(patched_emc, caplog):
+ patched_emc.shutdown()
+
+ assert log_has("Stopping ExternalMessageConsumer", caplog)
+ # Test the loop has stopped
+ assert patched_emc._loop is None
+ # Test if the thread has stopped
+ assert patched_emc._thread is None
+
+ caplog.clear()
+ patched_emc.shutdown()
+
+ # Test func didn't run again as it was called once already
+ assert not log_has("Stopping ExternalMessageConsumer", caplog)
+
+
+def test_emc_init(patched_emc):
+ # Test the settings were set correctly
+ assert patched_emc.initial_candle_limit <= 1500
+ assert patched_emc.wait_timeout > 0
+ assert patched_emc.sleep_time > 0
+
+
+# Parametrize this?
+def test_emc_handle_producer_message(patched_emc, caplog, ohlcv_history):
+ test_producer = {"name": "test", "url": "ws://test", "ws_token": "test"}
+ producer_name = test_producer['name']
+
+ caplog.set_level(logging.DEBUG)
+
+ # Test handle whitelist message
+ whitelist_message = {"type": "whitelist", "data": ["BTC/USDT"]}
+ patched_emc.handle_producer_message(test_producer, whitelist_message)
+
+ assert log_has(f"Received message of type `whitelist` from `{producer_name}`", caplog)
+ assert log_has(
+ f"Consumed message from `{producer_name}` of type `RPCMessageType.WHITELIST`", caplog)
+
+ # Test handle analyzed_df message
+ df_message = {
+ "type": "analyzed_df",
+ "data": {
+ "key": ("BTC/USDT", "5m", "spot"),
+ "df": ohlcv_history,
+ "la": datetime.now(timezone.utc)
+ }
+ }
+ patched_emc.handle_producer_message(test_producer, df_message)
+
+ assert log_has(f"Received message of type `analyzed_df` from `{producer_name}`", caplog)
+ assert log_has(
+ f"Consumed message from `{producer_name}` of type `RPCMessageType.ANALYZED_DF`", caplog)
+
+ # Test unhandled message
+ unhandled_message = {"type": "status", "data": "RUNNING"}
+ patched_emc.handle_producer_message(test_producer, unhandled_message)
+
+ assert log_has_re(r"Received unhandled message\: .*", caplog)
+
+ # Test malformed messages
+ caplog.clear()
+ malformed_message = {"type": "whitelist", "data": {"pair": "BTC/USDT"}}
+ patched_emc.handle_producer_message(test_producer, malformed_message)
+
+ assert log_has_re(r"Invalid message .+", caplog)
+
+ malformed_message = {
+ "type": "analyzed_df",
+ "data": {
+ "key": "BTC/USDT",
+ "df": ohlcv_history,
+ "la": datetime.now(timezone.utc)
+ }
+ }
+ patched_emc.handle_producer_message(test_producer, malformed_message)
+
+ assert log_has(f"Received message of type `analyzed_df` from `{producer_name}`", caplog)
+ assert log_has_re(r"Invalid message .+", caplog)
+
+ caplog.clear()
+ malformed_message = {"some": "stuff"}
+ patched_emc.handle_producer_message(test_producer, malformed_message)
+
+ assert log_has_re(r"Invalid message .+", caplog)
+
+ caplog.clear()
+ malformed_message = {"type": "whitelist", "data": None}
+ patched_emc.handle_producer_message(test_producer, malformed_message)
+
+ assert log_has_re(r"Empty message .+", caplog)
+
+
+async def test_emc_create_connection_success(default_conf, caplog, mocker):
+ default_conf.update({
+ "external_message_consumer": {
+ "enabled": True,
+ "producers": [
+ {
+ "name": "default",
+ "host": _TEST_WS_HOST,
+ "port": _TEST_WS_PORT,
+ "ws_token": _TEST_WS_TOKEN
+ }
+ ],
+ "wait_timeout": 60,
+ "ping_timeout": 60,
+ "sleep_timeout": 60
+ }
+ })
+
+ mocker.patch('freqtrade.rpc.external_message_consumer.ExternalMessageConsumer.start',
+ MagicMock())
+ dp = DataProvider(default_conf, None, None, None)
+ emc = ExternalMessageConsumer(default_conf, dp)
+
+ test_producer = default_conf['external_message_consumer']['producers'][0]
+ lock = asyncio.Lock()
+
+ emc._running = True
+
+ async def eat(websocket):
+ emc._running = False
+
+ try:
+ async with websockets.serve(eat, _TEST_WS_HOST, _TEST_WS_PORT):
+ await emc._create_connection(test_producer, lock)
+
+ assert log_has_re(r"Producer connection success.+", caplog)
+ finally:
+ emc.shutdown()
+
+
+async def test_emc_create_connection_invalid_port(default_conf, caplog, mocker):
+ default_conf.update({
+ "external_message_consumer": {
+ "enabled": True,
+ "producers": [
+ {
+ "name": "default",
+ "host": _TEST_WS_HOST,
+ "port": -1,
+ "ws_token": _TEST_WS_TOKEN
+ }
+ ],
+ "wait_timeout": 60,
+ "ping_timeout": 60,
+ "sleep_timeout": 60
+ }
+ })
+
+ dp = DataProvider(default_conf, None, None, None)
+ emc = ExternalMessageConsumer(default_conf, dp)
+
+ try:
+ await asyncio.sleep(0.01)
+ assert log_has_re(r".+ is an invalid WebSocket URL .+", caplog)
+ finally:
+ emc.shutdown()
+
+
+async def test_emc_create_connection_invalid_host(default_conf, caplog, mocker):
+ default_conf.update({
+ "external_message_consumer": {
+ "enabled": True,
+ "producers": [
+ {
+ "name": "default",
+ "host": "10000.1241..2121/",
+ "port": _TEST_WS_PORT,
+ "ws_token": _TEST_WS_TOKEN
+ }
+ ],
+ "wait_timeout": 60,
+ "ping_timeout": 60,
+ "sleep_timeout": 60
+ }
+ })
+
+ dp = DataProvider(default_conf, None, None, None)
+ emc = ExternalMessageConsumer(default_conf, dp)
+
+ try:
+ await asyncio.sleep(0.01)
+ assert log_has_re(r".+ is an invalid WebSocket URL .+", caplog)
+ finally:
+ emc.shutdown()
+
+
+async def test_emc_create_connection_error(default_conf, caplog, mocker):
+ default_conf.update({
+ "external_message_consumer": {
+ "enabled": True,
+ "producers": [
+ {
+ "name": "default",
+ "host": _TEST_WS_HOST,
+ "port": _TEST_WS_PORT,
+ "ws_token": _TEST_WS_TOKEN
+ }
+ ],
+ "wait_timeout": 60,
+ "ping_timeout": 60,
+ "sleep_timeout": 60
+ }
+ })
+
+ # Test unexpected error
+ mocker.patch('websockets.connect', side_effect=RuntimeError)
+
+ dp = DataProvider(default_conf, None, None, None)
+ emc = ExternalMessageConsumer(default_conf, dp)
+
+ try:
+ await asyncio.sleep(0.01)
+ assert log_has("Unexpected error has occurred:", caplog)
+ finally:
+ emc.shutdown()
+
+
+async def test_emc_receive_messages_valid(default_conf, caplog, mocker):
+ default_conf.update({
+ "external_message_consumer": {
+ "enabled": True,
+ "producers": [
+ {
+ "name": "default",
+ "host": _TEST_WS_HOST,
+ "port": _TEST_WS_PORT,
+ "ws_token": _TEST_WS_TOKEN
+ }
+ ],
+ "wait_timeout": 1,
+ "ping_timeout": 60,
+ "sleep_time": 60
+ }
+ })
+
+ mocker.patch('freqtrade.rpc.external_message_consumer.ExternalMessageConsumer.start',
+ MagicMock())
+
+ lock = asyncio.Lock()
+ test_producer = default_conf['external_message_consumer']['producers'][0]
+
+ dp = DataProvider(default_conf, None, None, None)
+ emc = ExternalMessageConsumer(default_conf, dp)
+
+ loop = asyncio.get_event_loop()
+ def change_running(emc): emc._running = not emc._running
+
+ class TestChannel:
+ async def recv(self, *args, **kwargs):
+ return {"type": "whitelist", "data": ["BTC/USDT"]}
+
+ async def ping(self, *args, **kwargs):
+ return asyncio.Future()
+
+ try:
+ change_running(emc)
+ loop.call_soon(functools.partial(change_running, emc=emc))
+ await emc._receive_messages(TestChannel(), test_producer, lock)
+
+ assert log_has_re(r"Received message of type `whitelist`.+", caplog)
+ finally:
+ emc.shutdown()
+
+
+async def test_emc_receive_messages_invalid(default_conf, caplog, mocker):
+ default_conf.update({
+ "external_message_consumer": {
+ "enabled": True,
+ "producers": [
+ {
+ "name": "default",
+ "host": _TEST_WS_HOST,
+ "port": _TEST_WS_PORT,
+ "ws_token": _TEST_WS_TOKEN
+ }
+ ],
+ "wait_timeout": 1,
+ "ping_timeout": 60,
+ "sleep_time": 60
+ }
+ })
+
+ mocker.patch('freqtrade.rpc.external_message_consumer.ExternalMessageConsumer.start',
+ MagicMock())
+
+ lock = asyncio.Lock()
+ test_producer = default_conf['external_message_consumer']['producers'][0]
+
+ dp = DataProvider(default_conf, None, None, None)
+ emc = ExternalMessageConsumer(default_conf, dp)
+
+ loop = asyncio.get_event_loop()
+ def change_running(emc): emc._running = not emc._running
+
+ class TestChannel:
+ async def recv(self, *args, **kwargs):
+ return {"type": ["BTC/USDT"]}
+
+ async def ping(self, *args, **kwargs):
+ return asyncio.Future()
+
+ try:
+ change_running(emc)
+ loop.call_soon(functools.partial(change_running, emc=emc))
+ await emc._receive_messages(TestChannel(), test_producer, lock)
+
+ assert log_has_re(r"Invalid message from.+", caplog)
+ finally:
+ emc.shutdown()
+
+
+async def test_emc_receive_messages_timeout(default_conf, caplog, mocker):
+ default_conf.update({
+ "external_message_consumer": {
+ "enabled": True,
+ "producers": [
+ {
+ "name": "default",
+ "host": _TEST_WS_HOST,
+ "port": _TEST_WS_PORT,
+ "ws_token": _TEST_WS_TOKEN
+ }
+ ],
+ "wait_timeout": 0.1,
+ "ping_timeout": 1,
+ "sleep_time": 1
+ }
+ })
+
+ mocker.patch('freqtrade.rpc.external_message_consumer.ExternalMessageConsumer.start',
+ MagicMock())
+
+ lock = asyncio.Lock()
+ test_producer = default_conf['external_message_consumer']['producers'][0]
+
+ dp = DataProvider(default_conf, None, None, None)
+ emc = ExternalMessageConsumer(default_conf, dp)
+
+ loop = asyncio.get_event_loop()
+ def change_running(emc): emc._running = not emc._running
+
+ class TestChannel:
+ async def recv(self, *args, **kwargs):
+ await asyncio.sleep(0.2)
+
+ async def ping(self, *args, **kwargs):
+ return asyncio.Future()
+
+ try:
+ change_running(emc)
+ loop.call_soon(functools.partial(change_running, emc=emc))
+ await emc._receive_messages(TestChannel(), test_producer, lock)
+
+ assert log_has_re(r"Ping error.+", caplog)
+ finally:
+ emc.shutdown()
+
+
+async def test_emc_receive_messages_handle_error(default_conf, caplog, mocker):
+ default_conf.update({
+ "external_message_consumer": {
+ "enabled": True,
+ "producers": [
+ {
+ "name": "default",
+ "host": _TEST_WS_HOST,
+ "port": _TEST_WS_PORT,
+ "ws_token": _TEST_WS_TOKEN
+ }
+ ],
+ "wait_timeout": 1,
+ "ping_timeout": 1,
+ "sleep_time": 1
+ }
+ })
+
+ mocker.patch('freqtrade.rpc.external_message_consumer.ExternalMessageConsumer.start',
+ MagicMock())
+
+ lock = asyncio.Lock()
+ test_producer = default_conf['external_message_consumer']['producers'][0]
+
+ dp = DataProvider(default_conf, None, None, None)
+ emc = ExternalMessageConsumer(default_conf, dp)
+
+ emc.handle_producer_message = MagicMock(side_effect=Exception)
+
+ loop = asyncio.get_event_loop()
+ def change_running(emc): emc._running = not emc._running
+
+ class TestChannel:
+ async def recv(self, *args, **kwargs):
+ return {"type": "whitelist", "data": ["BTC/USDT"]}
+
+ async def ping(self, *args, **kwargs):
+ return asyncio.Future()
+
+ try:
+ change_running(emc)
+ loop.call_soon(functools.partial(change_running, emc=emc))
+ await emc._receive_messages(TestChannel(), test_producer, lock)
+
+ assert log_has_re(r"Error handling producer message.+", caplog)
+ finally:
+ emc.shutdown()
diff --git a/tests/rpc/test_rpc_manager.py b/tests/rpc/test_rpc_manager.py
index b9ae16a20..d71f38259 100644
--- a/tests/rpc/test_rpc_manager.py
+++ b/tests/rpc/test_rpc_manager.py
@@ -82,6 +82,21 @@ def test_send_msg_telegram_disabled(mocker, default_conf, caplog) -> None:
assert telegram_mock.call_count == 0
+def test_send_msg_telegram_error(mocker, default_conf, caplog) -> None:
+ mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
+ mocker.patch('freqtrade.rpc.telegram.Telegram.send_msg', side_effect=ValueError())
+
+ freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+ rpc_manager = RPCManager(freqtradebot)
+ rpc_manager.send_msg({
+ 'type': RPCMessageType.STATUS,
+ 'status': 'test'
+ })
+
+ assert log_has("Sending rpc message: {'type': status, 'status': 'test'}", caplog)
+ assert log_has("Exception occurred within RPC module telegram", caplog)
+
+
def test_process_msg_queue(mocker, default_conf, caplog) -> None:
telegram_mock = mocker.patch('freqtrade.rpc.telegram.Telegram.send_msg')
mocker.patch('freqtrade.rpc.telegram.Telegram._init')
diff --git a/tests/rpc/test_rpc_telegram.py b/tests/rpc/test_rpc_telegram.py
index f2e490dff..3552d5fe7 100644
--- a/tests/rpc/test_rpc_telegram.py
+++ b/tests/rpc/test_rpc_telegram.py
@@ -959,6 +959,7 @@ def test_telegram_forceexit_handle(default_conf, update, ticker, fee,
'gain': 'profit',
'leverage': 1.0,
'limit': 1.173e-05,
+ 'order_rate': 1.173e-05,
'amount': 91.07468123,
'order_type': 'limit',
'open_rate': 1.098e-05,
@@ -1031,6 +1032,7 @@ def test_telegram_force_exit_down_handle(default_conf, update, ticker, fee,
'gain': 'loss',
'leverage': 1.0,
'limit': 1.043e-05,
+ 'order_rate': 1.043e-05,
'amount': 91.07468123,
'order_type': 'limit',
'open_rate': 1.098e-05,
@@ -1092,6 +1094,7 @@ def test_forceexit_all_handle(default_conf, update, ticker, fee, mocker) -> None
'pair': 'ETH/BTC',
'gain': 'loss',
'leverage': 1.0,
+ 'order_rate': 1.099e-05,
'limit': 1.099e-05,
'amount': 91.07468123,
'order_type': 'limit',
@@ -1744,7 +1747,7 @@ def test_send_msg_enter_notification(default_conf, mocker, caplog, message_type,
'exchange': 'Binance',
'pair': 'ETH/BTC',
'leverage': leverage,
- 'limit': 1.099e-05,
+ 'open_rate': 1.099e-05,
'order_type': 'limit',
'direction': enter,
'stake_amount': 0.01465333,
@@ -1915,7 +1918,7 @@ def test_send_msg_sell_notification(default_conf, mocker) -> None:
'leverage': 1.0,
'direction': 'Long',
'gain': 'loss',
- 'limit': 3.201e-05,
+ 'order_rate': 3.201e-05,
'amount': 1333.3333333333335,
'order_type': 'market',
'open_rate': 7.5e-05,
@@ -1950,7 +1953,7 @@ def test_send_msg_sell_notification(default_conf, mocker) -> None:
'pair': 'KEY/ETH',
'direction': 'Long',
'gain': 'loss',
- 'limit': 3.201e-05,
+ 'order_rate': 3.201e-05,
'amount': 1333.3333333333335,
'order_type': 'market',
'open_rate': 7.5e-05,
@@ -1989,7 +1992,7 @@ def test_send_msg_sell_notification(default_conf, mocker) -> None:
'pair': 'KEY/ETH',
'direction': 'Long',
'gain': 'loss',
- 'limit': 3.201e-05,
+ 'order_rate': 3.201e-05,
'amount': 1333.3333333333335,
'order_type': 'market',
'open_rate': 7.5e-05,
@@ -2162,7 +2165,7 @@ def test_send_msg_buy_notification_no_fiat(
'exchange': 'Binance',
'pair': 'ETH/BTC',
'leverage': leverage,
- 'limit': 1.099e-05,
+ 'open_rate': 1.099e-05,
'order_type': 'limit',
'direction': enter,
'stake_amount': 0.01465333,
@@ -2205,7 +2208,7 @@ def test_send_msg_sell_notification_no_fiat(
'gain': 'loss',
'leverage': leverage,
'direction': direction,
- 'limit': 3.201e-05,
+ 'order_rate': 3.201e-05,
'amount': 1333.3333333333335,
'order_type': 'limit',
'open_rate': 7.5e-05,
diff --git a/tests/strategy/test_default_strategy.py b/tests/strategy/test_default_strategy.py
index 5cb8fce16..cb3d61e89 100644
--- a/tests/strategy/test_default_strategy.py
+++ b/tests/strategy/test_default_strategy.py
@@ -21,14 +21,14 @@ def test_strategy_test_v3_structure():
(True, 'short'),
(False, 'long'),
])
-def test_strategy_test_v3(result, fee, is_short, side):
+def test_strategy_test_v3(dataframe_1m, fee, is_short, side):
strategy = StrategyTestV3({})
metadata = {'pair': 'ETH/BTC'}
assert type(strategy.minimal_roi) is dict
assert type(strategy.stoploss) is float
assert type(strategy.timeframe) is str
- indicators = strategy.populate_indicators(result, metadata)
+ indicators = strategy.populate_indicators(dataframe_1m, metadata)
assert type(indicators) is DataFrame
assert type(strategy.populate_buy_trend(indicators, metadata)) is DataFrame
assert type(strategy.populate_sell_trend(indicators, metadata)) is DataFrame
diff --git a/tests/strategy/test_strategy_loading.py b/tests/strategy/test_strategy_loading.py
index bf81cd068..adffd0875 100644
--- a/tests/strategy/test_strategy_loading.py
+++ b/tests/strategy/test_strategy_loading.py
@@ -53,7 +53,7 @@ def test_search_all_strategies_with_failed():
assert len(strategies) == 0
-def test_load_strategy(default_conf, result):
+def test_load_strategy(default_conf, dataframe_1m):
default_conf.update({'strategy': 'SampleStrategy',
'strategy_path': str(Path(__file__).parents[2] / 'freqtrade/templates')
})
@@ -61,22 +61,22 @@ def test_load_strategy(default_conf, result):
assert isinstance(strategy.__source__, str)
assert 'class SampleStrategy' in strategy.__source__
assert isinstance(strategy.__file__, str)
- assert 'rsi' in strategy.advise_indicators(result, {'pair': 'ETH/BTC'})
+ assert 'rsi' in strategy.advise_indicators(dataframe_1m, {'pair': 'ETH/BTC'})
-def test_load_strategy_base64(result, caplog, default_conf):
+def test_load_strategy_base64(dataframe_1m, caplog, default_conf):
filepath = Path(__file__).parents[2] / 'freqtrade/templates/sample_strategy.py'
encoded_string = urlsafe_b64encode(filepath.read_bytes()).decode("utf-8")
default_conf.update({'strategy': 'SampleStrategy:{}'.format(encoded_string)})
strategy = StrategyResolver.load_strategy(default_conf)
- assert 'rsi' in strategy.advise_indicators(result, {'pair': 'ETH/BTC'})
+ assert 'rsi' in strategy.advise_indicators(dataframe_1m, {'pair': 'ETH/BTC'})
# Make sure strategy was loaded from base64 (using temp directory)!!
assert log_has_re(r"Using resolved strategy SampleStrategy from '"
r".*(/|\\).*(/|\\)SampleStrategy\.py'\.\.\.", caplog)
-def test_load_strategy_invalid_directory(result, caplog, default_conf):
+def test_load_strategy_invalid_directory(caplog, default_conf):
default_conf['strategy'] = 'StrategyTestV3'
extra_dir = Path.cwd() / 'some/path'
with pytest.raises(OperationalException):
@@ -104,7 +104,7 @@ def test_load_strategy_noname(default_conf):
@pytest.mark.filterwarnings("ignore:deprecated")
@pytest.mark.parametrize('strategy_name', ['StrategyTestV2'])
-def test_strategy_pre_v3(result, default_conf, strategy_name):
+def test_strategy_pre_v3(dataframe_1m, default_conf, strategy_name):
default_conf.update({'strategy': strategy_name})
strategy = StrategyResolver.load_strategy(default_conf)
@@ -118,7 +118,7 @@ def test_strategy_pre_v3(result, default_conf, strategy_name):
assert strategy.timeframe == '5m'
assert default_conf['timeframe'] == '5m'
- df_indicators = strategy.advise_indicators(result, metadata=metadata)
+ df_indicators = strategy.advise_indicators(dataframe_1m, metadata=metadata)
assert 'adx' in df_indicators
dataframe = strategy.advise_entry(df_indicators, metadata=metadata)
@@ -417,24 +417,24 @@ def test_call_deprecated_function(default_conf):
StrategyResolver.load_strategy(default_conf)
-def test_strategy_interface_versioning(result, default_conf):
+def test_strategy_interface_versioning(dataframe_1m, default_conf):
default_conf.update({'strategy': 'StrategyTestV2'})
strategy = StrategyResolver.load_strategy(default_conf)
metadata = {'pair': 'ETH/BTC'}
assert strategy.INTERFACE_VERSION == 2
- indicator_df = strategy.advise_indicators(result, metadata=metadata)
+ indicator_df = strategy.advise_indicators(dataframe_1m, metadata=metadata)
assert isinstance(indicator_df, DataFrame)
assert 'adx' in indicator_df.columns
- enterdf = strategy.advise_entry(result, metadata=metadata)
+ enterdf = strategy.advise_entry(dataframe_1m, metadata=metadata)
assert isinstance(enterdf, DataFrame)
assert 'buy' not in enterdf.columns
assert 'enter_long' in enterdf.columns
- exitdf = strategy.advise_exit(result, metadata=metadata)
+ exitdf = strategy.advise_exit(dataframe_1m, metadata=metadata)
assert isinstance(exitdf, DataFrame)
assert 'sell' not in exitdf
assert 'exit_long' in exitdf
diff --git a/tests/test_configuration.py b/tests/test_configuration.py
index 2825ede5c..99edf0233 100644
--- a/tests/test_configuration.py
+++ b/tests/test_configuration.py
@@ -1089,6 +1089,58 @@ def test__validate_pricing_rules(default_conf, caplog) -> None:
validate_config_consistency(conf)
+def test__validate_consumers(default_conf, caplog) -> None:
+ conf = deepcopy(default_conf)
+ conf.update({
+ "external_message_consumer": {
+ "enabled": True,
+ "producers": []
+ }
+ })
+ with pytest.raises(OperationalException,
+ match="You must specify at least 1 Producer to connect to."):
+ validate_config_consistency(conf)
+
+ conf = deepcopy(default_conf)
+ conf.update({
+ "external_message_consumer": {
+ "enabled": True,
+ "producers": [
+ {
+ "name": "default",
+ "host": "127.0.0.1",
+ "port": 8081,
+ "ws_token": "secret_ws_t0ken."
+ }, {
+ "name": "default",
+ "host": "127.0.0.1",
+ "port": 8080,
+ "ws_token": "secret_ws_t0ken."
+ }
+ ]}
+ })
+ with pytest.raises(OperationalException,
+ match="Producer names must be unique. Duplicate: default"):
+ validate_config_consistency(conf)
+
+ conf = deepcopy(default_conf)
+ conf.update({
+ "process_only_new_candles": True,
+ "external_message_consumer": {
+ "enabled": True,
+ "producers": [
+ {
+ "name": "default",
+ "host": "127.0.0.1",
+ "port": 8081,
+ "ws_token": "secret_ws_t0ken."
+ }
+ ]}
+ })
+ validate_config_consistency(conf)
+ assert log_has_re("To receive best performance with external data.*", caplog)
+
+
def test_load_config_test_comments() -> None:
"""
Load config with comments
diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py
index c1152ac09..5fe4d4011 100644
--- a/tests/test_freqtradebot.py
+++ b/tests/test_freqtradebot.py
@@ -1319,9 +1319,9 @@ def test_create_stoploss_order_invalid_order(
assert create_order_mock.call_args[1]['amount'] == trade.amount
# Rpc is sending first buy, then sell
- assert rpc_mock.call_count == 2
- assert rpc_mock.call_args_list[1][0][0]['sell_reason'] == ExitType.EMERGENCY_EXIT.value
- assert rpc_mock.call_args_list[1][0][0]['order_type'] == 'market'
+ assert rpc_mock.call_count == 3
+ assert rpc_mock.call_args_list[2][0][0]['sell_reason'] == ExitType.EMERGENCY_EXIT.value
+ assert rpc_mock.call_args_list[2][0][0]['order_type'] == 'market'
@pytest.mark.parametrize("is_short", [False, True])
@@ -2439,7 +2439,7 @@ def test_manage_open_orders_entry_usercustom(
# Trade should be closed since the function returns true
freqtrade.manage_open_orders()
assert cancel_order_wr_mock.call_count == 1
- assert rpc_mock.call_count == 1
+ assert rpc_mock.call_count == 2
trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
nb_trades = len(trades)
assert nb_trades == 0
@@ -2478,7 +2478,7 @@ def test_manage_open_orders_entry(
# check it does cancel buy orders over the time limit
freqtrade.manage_open_orders()
assert cancel_order_mock.call_count == 1
- assert rpc_mock.call_count == 1
+ assert rpc_mock.call_count == 2
trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
nb_trades = len(trades)
assert nb_trades == 0
@@ -2608,7 +2608,7 @@ def test_check_handle_cancelled_buy(
# check it does cancel buy orders over the time limit
freqtrade.manage_open_orders()
assert cancel_order_mock.call_count == 0
- assert rpc_mock.call_count == 1
+ assert rpc_mock.call_count == 2
trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
assert len(trades) == 0
assert log_has_re(
@@ -2639,7 +2639,7 @@ def test_manage_open_orders_buy_exception(
# check it does cancel buy orders over the time limit
freqtrade.manage_open_orders()
assert cancel_order_mock.call_count == 0
- assert rpc_mock.call_count == 0
+ assert rpc_mock.call_count == 1
trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
nb_trades = len(trades)
assert nb_trades == 1
@@ -2686,7 +2686,7 @@ def test_manage_open_orders_exit_usercustom(
# Return false - No impact
freqtrade.manage_open_orders()
assert cancel_order_mock.call_count == 0
- assert rpc_mock.call_count == 0
+ assert rpc_mock.call_count == 1
assert open_trade_usdt.is_open is False
assert freqtrade.strategy.check_exit_timeout.call_count == 1
assert freqtrade.strategy.check_entry_timeout.call_count == 0
@@ -2696,7 +2696,7 @@ def test_manage_open_orders_exit_usercustom(
# Return Error - No impact
freqtrade.manage_open_orders()
assert cancel_order_mock.call_count == 0
- assert rpc_mock.call_count == 0
+ assert rpc_mock.call_count == 1
assert open_trade_usdt.is_open is False
assert freqtrade.strategy.check_exit_timeout.call_count == 1
assert freqtrade.strategy.check_entry_timeout.call_count == 0
@@ -2706,7 +2706,7 @@ def test_manage_open_orders_exit_usercustom(
freqtrade.strategy.check_entry_timeout = MagicMock(return_value=True)
freqtrade.manage_open_orders()
assert cancel_order_mock.call_count == 1
- assert rpc_mock.call_count == 1
+ assert rpc_mock.call_count == 2
assert open_trade_usdt.is_open is True
assert freqtrade.strategy.check_exit_timeout.call_count == 1
assert freqtrade.strategy.check_entry_timeout.call_count == 0
@@ -2766,7 +2766,7 @@ def test_manage_open_orders_exit(
# check it does cancel sell orders over the time limit
freqtrade.manage_open_orders()
assert cancel_order_mock.call_count == 1
- assert rpc_mock.call_count == 1
+ assert rpc_mock.call_count == 2
assert open_trade_usdt.is_open is True
# Custom user sell-timeout is never called
assert freqtrade.strategy.check_exit_timeout.call_count == 0
@@ -2805,7 +2805,7 @@ def test_check_handle_cancelled_exit(
# check it does cancel sell orders over the time limit
freqtrade.manage_open_orders()
assert cancel_order_mock.call_count == 0
- assert rpc_mock.call_count == 1
+ assert rpc_mock.call_count == 2
assert open_trade_usdt.is_open is True
exit_name = 'Buy' if is_short else 'Sell'
assert log_has_re(f"{exit_name} order cancelled on exchange for Trade.*", caplog)
@@ -2843,7 +2843,7 @@ def test_manage_open_orders_partial(
# note this is for a partially-complete buy order
freqtrade.manage_open_orders()
assert cancel_order_mock.call_count == 1
- assert rpc_mock.call_count == 2
+ assert rpc_mock.call_count == 3
trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
assert len(trades) == 1
assert trades[0].amount == 23.0
@@ -2890,7 +2890,7 @@ def test_manage_open_orders_partial_fee(
assert log_has_re(r"Applying fee on amount for Trade.*", caplog)
assert cancel_order_mock.call_count == 1
- assert rpc_mock.call_count == 2
+ assert rpc_mock.call_count == 3
trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
assert len(trades) == 1
# Verify that trade has been updated
@@ -2940,7 +2940,7 @@ def test_manage_open_orders_partial_except(
assert log_has_re(r"Could not update trade amount: .*", caplog)
assert cancel_order_mock.call_count == 1
- assert rpc_mock.call_count == 2
+ assert rpc_mock.call_count == 3
trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
assert len(trades) == 1
# Verify that trade has been updated
@@ -3155,7 +3155,7 @@ def test_handle_cancel_exit_limit(mocker, default_conf_usdt, fee) -> None:
reason = CANCEL_REASON['TIMEOUT']
assert freqtrade.handle_cancel_exit(trade, order, reason)
assert cancel_order_mock.call_count == 1
- assert send_msg_mock.call_count == 1
+ assert send_msg_mock.call_count == 2
assert trade.close_rate is None
assert trade.exit_reason is None
@@ -3256,6 +3256,7 @@ def test_execute_trade_exit_up(default_conf_usdt, ticker_usdt, fee, ticker_usdt_
'pair': 'ETH/USDT',
'gain': 'profit',
'limit': 2.0 if is_short else 2.2,
+ 'order_rate': 2.0 if is_short else 2.2,
'amount': pytest.approx(amt),
'order_type': 'limit',
'buy_tag': None,
@@ -3321,6 +3322,7 @@ def test_execute_trade_exit_down(default_conf_usdt, ticker_usdt, fee, ticker_usd
'leverage': 1.0,
'gain': 'loss',
'limit': 2.2 if is_short else 2.01,
+ 'order_rate': 2.2 if is_short else 2.01,
'amount': pytest.approx(29.70297029) if is_short else 30.0,
'order_type': 'limit',
'buy_tag': None,
@@ -3405,6 +3407,7 @@ def test_execute_trade_exit_custom_exit_price(
'leverage': 1.0,
'gain': profit_or_loss,
'limit': limit,
+ 'order_rate': limit,
'amount': pytest.approx(amount),
'order_type': 'limit',
'buy_tag': None,
@@ -3476,6 +3479,7 @@ def test_execute_trade_exit_down_stoploss_on_exchange_dry_run(
'leverage': 1.0,
'gain': 'loss',
'limit': 2.02 if is_short else 1.98,
+ 'order_rate': 2.02 if is_short else 1.98,
'amount': pytest.approx(29.70297029 if is_short else 30.0),
'order_type': 'limit',
'buy_tag': None,
@@ -3588,7 +3592,7 @@ def test_execute_trade_exit_with_stoploss_on_exchange(
trade.is_short = is_short
assert trade
assert cancel_order.call_count == 1
- assert rpc_mock.call_count == 3
+ assert rpc_mock.call_count == 4
@pytest.mark.parametrize("is_short", [False, True])
@@ -3658,11 +3662,11 @@ def test_may_execute_trade_exit_after_stoploss_on_exchange_hit(
assert trade.stoploss_order_id is None
assert trade.is_open is False
assert trade.exit_reason == ExitType.STOPLOSS_ON_EXCHANGE.value
- assert rpc_mock.call_count == 3
- assert rpc_mock.call_args_list[0][0][0]['type'] == RPCMessageType.ENTRY
- assert rpc_mock.call_args_list[0][0][0]['amount'] > 20
- assert rpc_mock.call_args_list[1][0][0]['type'] == RPCMessageType.ENTRY_FILL
- assert rpc_mock.call_args_list[2][0][0]['type'] == RPCMessageType.EXIT_FILL
+ assert rpc_mock.call_count == 4
+ assert rpc_mock.call_args_list[1][0][0]['type'] == RPCMessageType.ENTRY
+ assert rpc_mock.call_args_list[1][0][0]['amount'] > 20
+ assert rpc_mock.call_args_list[2][0][0]['type'] == RPCMessageType.ENTRY_FILL
+ assert rpc_mock.call_args_list[3][0][0]['type'] == RPCMessageType.EXIT_FILL
@pytest.mark.parametrize(
@@ -3741,6 +3745,7 @@ def test_execute_trade_exit_market_order(
'leverage': 1.0,
'gain': profit_or_loss,
'limit': limit,
+ 'order_rate': limit,
'amount': pytest.approx(amount),
'order_type': 'market',
'buy_tag': None,
diff --git a/tests/test_integration.py b/tests/test_integration.py
index 77ed822d1..a7b4fbdd3 100644
--- a/tests/test_integration.py
+++ b/tests/test_integration.py
@@ -521,4 +521,4 @@ def test_dca_exiting(default_conf_usdt, ticker_usdt, fee, mocker, caplog) -> Non
assert trade.orders[-1].ft_order_side == 'sell'
assert pytest.approx(trade.stake_amount) == 40.198
assert trade.is_open
- assert log_has_re('Amount to sell is 0.0 due to exchange limits - not selling.', caplog)
+ assert log_has_re('Amount to exit is 0.0 due to exchange limits - not exiting.', caplog)
diff --git a/tests/test_misc.py b/tests/test_misc.py
index 107932be4..2da45bad9 100644
--- a/tests/test_misc.py
+++ b/tests/test_misc.py
@@ -7,10 +7,11 @@ from unittest.mock import MagicMock
import pytest
-from freqtrade.misc import (decimals_per_coin, deep_merge_dicts, file_dump_json, file_load_json,
- format_ms_time, pair_to_filename, parse_db_uri_for_logging, plural,
- render_template, render_template_with_fallback, round_coin_value,
- safe_value_fallback, safe_value_fallback2, shorten_date)
+from freqtrade.misc import (dataframe_to_json, decimals_per_coin, deep_merge_dicts, file_dump_json,
+ file_load_json, format_ms_time, json_to_dataframe, pair_to_filename,
+ parse_db_uri_for_logging, plural, render_template,
+ render_template_with_fallback, round_coin_value, safe_value_fallback,
+ safe_value_fallback2, shorten_date)
def test_decimals_per_coin():
@@ -184,8 +185,8 @@ def test_render_template_fallback(mocker):
templatefile='subtemplates/indicators_does-not-exist.j2',)
val = render_template_with_fallback(
- templatefile='subtemplates/indicators_does-not-exist.j2',
- templatefallbackfile='subtemplates/indicators_minimal.j2',
+ templatefile='strategy_subtemplates/indicators_does-not-exist.j2',
+ templatefallbackfile='strategy_subtemplates/indicators_minimal.j2',
)
assert isinstance(val, str)
assert 'if self.dp' in val
@@ -219,3 +220,14 @@ def test_deep_merge_dicts():
res2['first']['rows']['test'] = 'asdf'
assert deep_merge_dicts(a, deepcopy(b), allow_null_overrides=False) == res2
+
+
+def test_dataframe_json(ohlcv_history):
+ from pandas.testing import assert_frame_equal
+ json = dataframe_to_json(ohlcv_history)
+ dataframe = json_to_dataframe(json)
+
+ assert list(ohlcv_history.columns) == list(dataframe.columns)
+ assert len(ohlcv_history) == len(dataframe)
+
+ assert_frame_equal(ohlcv_history, dataframe)