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176 Commits

Author SHA1 Message Date
gcarq
b115963a70 Merge branch 'release/0.14.2' 2017-11-16 00:40:44 +01:00
gcarq
2e953a937d version bump 2017-11-16 00:40:36 +01:00
gcarq
4e05691cab check if balance list is empty (fixes #105) 2017-11-16 00:01:47 +01:00
gcarq
b5f58724a0 get_ticker_history: check if result is set (fixes #103) 2017-11-15 23:16:54 +01:00
gcarq
b83309b55d reduce calls_per_second to 1 2017-11-15 23:16:39 +01:00
gcarq
e8101a6da5 default BaseVolume to 0.0 if null 2017-11-14 17:48:19 +01:00
gcarq
dd9cb008fb refresh whitelist based on wallet health (fixes #60)
Refreshs the whitelist in each iteration based on the wallet health,
disabled wallets will be removed from the whitelist automatically.
2017-11-13 21:34:47 +01:00
gcarq
81f7172c4a sanitize get_ticker_history (fixes #100) 2017-11-13 19:54:09 +01:00
Michael Egger
bab59fbacd Merge pull request #99 from gcarq/more_triggers2
Expanding hyperopt
2017-11-13 12:11:15 +01:00
Janne Sinivirta
0f0b10b6cc adjust search spaces 2017-11-13 07:28:56 +02:00
Janne Sinivirta
8e68c5358e clean up prints during hyperopt 2017-11-12 09:44:31 +02:00
Janne Sinivirta
660f01b514 add hilbert transform leadsine trigger 2017-11-12 09:13:54 +02:00
Janne Sinivirta
13537e3ce4 add short ema guard to hyperopt 2017-11-12 08:45:32 +02:00
Janne Sinivirta
2963a90008 add stochastics trigger 2017-11-12 08:38:52 +02:00
Janne Sinivirta
15b20b83fa optimize hyperopt objective function 2017-11-12 08:30:58 +02:00
gcarq
1c3c316e45 reduce calls_per_second 2017-11-11 21:29:35 +01:00
gcarq
517879382b Add argument for dynamic-whitelist handling
If --dynamic-whitelist is passed the whitelist in the config file
is ignored. It gets automatically refreshed every 30 minutes and
currently selects the 20 topmost BaseVolume markets
2017-11-11 19:20:53 +01:00
gcarq
bcd3340a80 implement get_market_summaries 2017-11-11 19:20:16 +01:00
gcarq
12ae1e111e use get_candles from python-bittrex 2017-11-11 17:14:55 +01:00
gcarq
d3b3370f23 Add configurable throttle mechanism 2017-11-11 16:47:19 +01:00
gcarq
8f817a3634 use TTLCache for get_ticker_history 2017-11-11 15:29:31 +01:00
Janne Sinivirta
cf79b15651 use discrete values for filters 2017-11-11 11:50:10 +02:00
Janne Sinivirta
a4284351e3 fix green_candle 2017-11-11 11:22:12 +02:00
Janne Sinivirta
906caf329b remove two unused or poorly performing indicators 2017-11-11 11:22:12 +02:00
Janne Sinivirta
3db13fae13 add green_candle guard 2017-11-11 11:22:12 +02:00
Janne Sinivirta
274972f7af make faststoch trigger use crossed_above helper 2017-11-11 11:22:11 +02:00
Janne Sinivirta
83fd27e031 add sar reversal as trigger 2017-11-11 11:22:11 +02:00
gcarq
3126dcfcea drop sleep_time and use python-bittrex request delay 2017-11-10 23:39:49 +01:00
Michael Egger
72aec6c320 Merge pull request #96 from gcarq/feature/add-argparse
add argparse and implement basic arguments
2017-11-10 18:04:03 +01:00
gcarq
b709ccbf53 enhance logging messages 2017-11-10 17:56:03 +01:00
gcarq
7e99b13742 add missing commands to README 2017-11-10 17:27:19 +01:00
gcarq
8b464033ff add missing commands to README 2017-11-10 17:26:52 +01:00
gcarq
93c525a8fa Merge branch 'master' into develop 2017-11-10 17:18:21 +01:00
gcarq
54b15c1556 update README 2017-11-10 17:17:51 +01:00
gcarq
029f32af63 Merge tag '0.14.1' into develop
0.14.1
2017-11-09 23:53:14 +01:00
gcarq
de13df6ede Merge branch 'release/0.14.1' 2017-11-09 23:53:10 +01:00
gcarq
0de211674d version bump 2017-11-09 23:52:34 +01:00
gcarq
f7a27c156c add /version command handler 2017-11-09 23:51:32 +01:00
gcarq
98f11fc7bb fix sqlite threading issue 2017-11-09 23:45:22 +01:00
gcarq
013e13e546 use tabulate for /count 2017-11-09 23:45:03 +01:00
gcarq
6ff26c561a move plot_dataframe to scripts/ folder 2017-11-09 22:29:23 +01:00
gcarq
c81358c291 remove MagicBot 2017-11-09 22:11:02 +01:00
gcarq
ed34d9f22f add tests for /forcesell all 2017-11-09 22:08:28 +01:00
gcarq
ee05561ef3 refactor forcesellall to /forcesell all 2017-11-09 22:07:51 +01:00
Eoin
69ae99406a add telegram handler for forcesellall 2017-11-09 21:52:08 +01:00
gcarq
0cfbb56b6c enhance and test pair validation 2017-11-09 21:47:47 +01:00
gcarq
8960373f1c Merge tag '0.14.0' into develop
0.14.0
2017-11-09 20:56:12 +01:00
gcarq
349a91bd92 Merge branch 'release/0.14.0' 2017-11-09 20:56:07 +01:00
gcarq
991b43b7e5 version bump 2017-11-09 20:55:45 +01:00
gcarq
a0fa6abcdc use in-memory db for dry_run 2017-11-09 20:26:52 +01:00
gcarq
86501b43c0 adjust message formatting 2017-11-09 20:25:17 +01:00
gcarq
80592970e9 add more tests 2017-11-09 20:02:41 +01:00
gcarq
567ed4ecda remove version pinning from setup.py 2017-11-09 00:33:22 +01:00
gcarq
fafbb0abfe update python-bittrex to 0.2.0 2017-11-09 00:31:53 +01:00
gcarq
0f1a36b8e9 force to python3 2017-11-08 23:39:29 +01:00
gcarq
31c03cdce1 fix linter issue 2017-11-08 22:44:32 +01:00
gcarq
e01c85bb3a add argparse and implement basic arguments 2017-11-08 22:43:47 +01:00
gcarq
a1b91ad1ea remove unneeded wrapper function 2017-11-08 21:17:51 +01:00
gcarq
6ce6018bb7 add more tests 2017-11-07 22:27:44 +01:00
gcarq
18eec0f4d4 catch BaseException in command_handler 2017-11-07 22:27:16 +01:00
gcarq
32327c45c2 set close_date on sell_order update 2017-11-07 22:26:44 +01:00
gcarq
ba485fe2b2 return state changes 2017-11-07 22:26:08 +01:00
gcarq
f8084b117e apply pylint recommendations 2017-11-07 20:13:36 +01:00
gcarq
abdddd5193 define common fixtures 2017-11-07 20:12:56 +01:00
gcarq
8eeb02e592 make ticker interval configurable 2017-11-07 18:59:47 +01:00
gcarq
8555271102 remove unneeded header from get_ticker_history 2017-11-07 18:49:16 +01:00
gcarq
d921bae75e set executable bit 2017-11-07 18:42:40 +01:00
gcarq
a1388ef296 add tick_interval to get_ticker_history as an optional parameter 2017-11-07 18:41:48 +01:00
gcarq
ddc7c94a1d Merge branch 'develop' of https://github.com/gcarq/freqtrade into develop 2017-11-07 18:40:56 +01:00
Michael Egger
e36444df27 Merge pull request #95 from gcarq/improve_backtests
Share pytest fixtures. Cache testfile loading.
2017-11-07 18:40:00 +01:00
Janne Sinivirta
0395c92260 move testdata file loading to pytest fixture 2017-11-07 19:24:51 +02:00
gcarq
f03395b90d force python3 via shebang 2017-11-07 17:54:44 +01:00
gcarq
20d5628786 catch broader RequestException instead ConnectionError 2017-11-07 17:45:13 +01:00
gcarq
57e089efd3 fix NoneType issue in status command handle 2017-11-07 17:39:57 +01:00
Janne Sinivirta
fbbde9de25 put shared fixtures to conftest.py 2017-11-07 17:29:00 +02:00
Samuel Husso
3d42b9fd75 Merge pull request #94 from gcarq/autopep
autoformat with autopep8
2017-11-06 19:41:57 +02:00
Janne Sinivirta
adfae9e75c autoformat with autopep8 2017-11-06 19:17:23 +02:00
gcarq
117dfbb563 fix wording 2017-11-06 18:15:33 +01:00
Michael Egger
e66dc8b027 Merge pull request #93 from gcarq/feature/interpreter-version-check
add interpreter version check
2017-11-06 17:23:53 +01:00
Michael Egger
ae0b49f532 Merge pull request #92 from gcarq/feature/rework-dry_run-mode
rework dry_run
2017-11-06 16:54:55 +01:00
gcarq
a37ea13fd1 catch RuntimeError earlier
This makes it possible to to restart the bot, if there are temporary
server issues.
2017-11-06 01:03:37 +01:00
gcarq
cc29126d61 make download_backtest_data.py platform independent 2017-11-06 00:16:24 +01:00
gcarq
810f2f9243 drop minimum_date from get_ticker_history 2017-11-06 00:06:59 +01:00
gcarq
60e651cb4c only return data['result'] from get_ticker_history 2017-11-05 23:47:59 +01:00
gcarq
472ce8566d enhance bittrex exception messages 2017-11-05 22:47:55 +01:00
gcarq
27ac15f298 add tabulate to setup.py 2017-11-05 20:54:41 +01:00
gcarq
d12dba16db simplify status command 2017-11-05 18:35:32 +01:00
Michael Egger
0f1d114c03 Merge pull request #86 from flightcom/feature/advanced-status-command
telegram command: advanced status
2017-11-05 18:13:25 +01:00
gcarq
3e7700e9ac add interpreter version check 2017-11-05 17:44:58 +01:00
Sébastien Moreau
60615c232c Merge branch 'develop' into feature/advanced-status-command 2017-11-05 10:34:17 -05:00
Sébastien Moreau
3884cfb809 Merge branch 'develop' into feature/advanced-status-command 2017-11-05 10:32:53 -05:00
Sebastien Moreau
caa6e22e53 Adds unit tests 2017-11-05 10:26:03 -05:00
gcarq
19f6ff330c adapt float precision asserts 2017-11-05 16:21:13 +01:00
gcarq
8fdd127f72 fix float precision rendering 2017-11-05 16:13:55 +01:00
gcarq
0a5eba64e2 do not remove order from dry_run order list 2017-11-05 16:13:20 +01:00
gcarq
b82c4444b2 apply correct typehint 2017-11-05 16:12:58 +01:00
gcarq
95a17b8f98 dry_run: remove mock value notice 2017-11-05 15:35:15 +01:00
gcarq
325f72fd91 dry_run: keep list of open orders 2017-11-05 15:21:16 +01:00
Janne Sinivirta
a237225683 Merge pull request #91 from gcarq/multiple_builds_travis
Parallel build in Travis
2017-11-05 15:21:20 +02:00
Janne Sinivirta
29b173f4e7 only run four evals of hyperopt, just to check it works 2017-11-05 09:28:42 +02:00
Janne Sinivirta
50a979161c run parallel test envs 2017-11-05 09:27:49 +02:00
gcarq
264d71e29e fix some pylint warnings 2017-11-04 18:55:41 +01:00
gcarq
a873688a44 backtesting: init Trade with Bittrex fee 2017-11-04 18:43:23 +01:00
Michael Egger
7cc8533b8e Merge pull request #89 from gcarq/feature/take-fees-into-account
take fees into account & sell amount equal to amount purchased
2017-11-03 21:47:46 +01:00
gcarq
04342acff1 fix typo 2017-11-03 21:37:20 +01:00
gcarq
c37df0e70d inform about mocked values with dry_run 2017-11-03 21:36:55 +01:00
gcarq
460dfa1031 fix percentage formating in execute_sell 2017-11-02 19:00:25 +01:00
gcarq
08a1d3ca1d pylint changes 2017-11-02 19:00:25 +01:00
gcarq
1daeed4a52 fix assert 2017-11-02 19:00:25 +01:00
gcarq
99724e2458 use Decimal for profit calculation 2017-11-02 19:00:25 +01:00
gcarq
cd18629433 add fee to sqlalchemy model and respecting it in calc_profit 2017-11-02 19:00:25 +01:00
gcarq
41510fdb32 add dry_run for get_balance 2017-11-02 19:00:25 +01:00
gcarq
9cb249610a adapt dry_run return values 2017-11-02 19:00:25 +01:00
gcarq
543857ddb2 set initial open_rate and amount in create_trade
This is mostly needed by dry_run
2017-11-02 19:00:25 +01:00
gcarq
1e5b0e8726 adapt tests 2017-11-02 19:00:25 +01:00
gcarq
0d0d822904 bump dburl to tradesv3 2017-11-02 19:00:25 +01:00
gcarq
9ff4a7b205 refactor _process to update trade state 2017-11-02 19:00:25 +01:00
gcarq
0e96197a94 don't spend the whole coin balance when selling 2017-11-02 19:00:25 +01:00
gcarq
9b9d0250f7 replace get_open_oders() with get_order() and add property for fee 2017-11-02 18:58:55 +01:00
gcarq
4a35676794 rename and exchange instance and mark it as private 2017-11-02 18:58:55 +01:00
gcarq
465c91b9a9 telegram.cleanup: fix NoneType issue when telegram is deactivated 2017-11-02 18:56:57 +01:00
Sebastien Moreau
60249af04c Removes long format + pylint fixes 2017-11-02 13:25:19 -04:00
gcarq
c3653dc417 Merge branch 'master' of https://github.com/gcarq/freqtrade into develop 2017-11-01 18:37:27 +01:00
gcarq
3d61095ba4 modify header font size 2017-11-01 18:36:22 +01:00
gcarq
7a0be94cde adapt README 2017-11-01 18:32:27 +01:00
gcarq
fad6427078 coverage: omit vendor folder 2017-11-01 01:43:15 +01:00
gcarq
4dfde7f9a2 Merge tag '0.13.0' into develop
0.13.0
2017-11-01 01:15:35 +01:00
gcarq
e2eceaa904 Merge branch 'release/0.13.0' 2017-11-01 01:15:31 +01:00
gcarq
f34af0ad67 version bump 2017-11-01 01:15:06 +01:00
gcarq
e07904d436 PEP8 linting 2017-10-31 00:36:35 +01:00
gcarq
26468bef83 balance: filter currencies with 0.0 balances 2017-10-31 00:29:22 +01:00
Michael Egger
ea1b1e11ea Merge pull request #88 from gcarq/reduce_memory_use
Reduce memory use in backtesting
2017-10-31 00:28:38 +01:00
Janne Sinivirta
e68e6c0a1a reuse mock in hyperopt also 2017-10-30 22:31:28 +02:00
Janne Sinivirta
7190226c84 reuse same mock for get_ticker_history, just change return_value 2017-10-30 22:06:09 +02:00
gcarq
6f2915e25e move qtpylib to vendor folder
This is necessary to distribute qtpylib with
freqtrade when you install it globally.
2017-10-30 20:41:36 +01:00
gcarq
6f7ac0720b add qtpylib to manifest 2017-10-30 20:24:58 +01:00
gcarq
b76554a487 add __init__ file for qtpylib 2017-10-30 20:23:19 +01:00
Janne Sinivirta
8da55c3742 move patching of arrow.utcnow to remove 500 unnecessary mock objects 2017-10-30 19:56:53 +02:00
Michael Egger
05111edd04 Merge pull request #87 from gcarq/more_triggers
More triggers and guards to hyperopt
2017-10-30 14:43:18 +01:00
Sebastien Moreau
361bdd20d3 Updates README 2017-10-29 20:55:14 -04:00
Sebastien Moreau
8bdace68f6 Adds options for /status command 2017-10-29 20:51:38 -04:00
Sebastien Moreau
0e1eb20781 Adds /count command
Adds /count command

Adds /count command
2017-10-29 18:47:42 -04:00
Michael Egger
4c2dea83c5 Merge pull request #84 from gcarq/telegram/show-balance
Telegram command: /show balance
2017-10-29 22:05:10 +01:00
Janne Sinivirta
d066817d0b removed below_sma and over_sma to wait for better implementation 2017-10-29 21:33:57 +02:00
Janne Sinivirta
a632121368 add macd cross signal trigger to hyperopt 2017-10-29 21:33:57 +02:00
Janne Sinivirta
473d09b5cd add ema50 and ema100. add long uptrend ema guard to hyperopt 2017-10-29 21:33:57 +02:00
Janne Sinivirta
893738d6f0 add MACD to analyze 2017-10-29 21:33:57 +02:00
Janne Sinivirta
22cfef7d36 add ema5 cross ema10 trigger to hyperopt 2017-10-29 21:33:57 +02:00
Janne Sinivirta
e1bbe1d9a9 adjust indicator ranges in hyperopt 2017-10-29 21:33:57 +02:00
Janne Sinivirta
ec981b415a add RSI to hyperopt 2017-10-29 21:33:57 +02:00
Janne Sinivirta
57a17697a0 add RSI, MOM, EMA5 and EMA10 to analyze 2017-10-29 21:33:57 +02:00
Samuel Husso
f4fe09ffbf added get_balances as a abstract method to the interface baseclass 2017-10-29 17:57:57 +02:00
Michael Egger
871b5e17ee Merge pull request #85 from gcarq/datetime_fixes
Performance improvements for backtesting
2017-10-29 15:56:20 +01:00
Janne Sinivirta
9b00fc3474 use .ix instead of .loc for small perf boost 2017-10-29 16:28:55 +02:00
Janne Sinivirta
3b1dc36d8a switch to using itertuples instead of iterrows as it's a lot faster 2017-10-29 16:28:55 +02:00
Janne Sinivirta
4edf8f2079 copy only needed columns before iterating over them 2017-10-29 16:28:55 +02:00
Janne Sinivirta
54987fd9ca do date parsing while loading json, not later 2017-10-29 16:28:55 +02:00
Janne Sinivirta
da9c3e7d7d remove leftover dates from removing date filtering 2017-10-29 16:28:55 +02:00
Michael Egger
a948142ef5 Merge pull request #83 from gcarq/better-hyperopt-objective
Better hyperopt objective
2017-10-29 14:13:44 +01:00
Samuel Husso
4f6c3f94e0 added tests to /balance, minor cleanup 2017-10-29 10:10:00 +02:00
Janne Sinivirta
25d6d6bbe5 remove unused imports from test_hyperopt 2017-10-28 15:32:29 +03:00
Janne Sinivirta
649781d823 store result strings, display best result in summary. switch to a lot better objective algo 2017-10-28 15:26:22 +03:00
Janne Sinivirta
08ca7a8166 change print to format so result can be used in hyperopt Trials 2017-10-28 15:26:22 +03:00
Samuel Husso
dd78c62c3d added new command to return balance across all currencies 2017-10-28 08:59:43 +03:00
Samuel Husso
29de1645fe Merge pull request #82 from gcarq/feature/handle-process-signals
handle SIGINT, SIGTERM and SIGABRT process signals
2017-10-28 08:49:42 +03:00
gcarq
4139b0b0c7 add signal handler for SIGINT, SIGTERM and SIGABRT 2017-10-27 15:52:14 +02:00
Samuel Husso
0c33e917d5 Merge pull request #79 from gcarq/qtpylib
Include new indicators from qtpylib
2017-10-27 12:11:04 +03:00
Janne Sinivirta
e401a016f5 change analyze tests to use full json dump from bittrex 2017-10-26 16:50:31 +03:00
Janne Sinivirta
e0fde8665c Merge pull request #80 from gcarq/fix-testdate-dl-path
download testdata to correct folder when running from project root
2017-10-26 10:37:38 +03:00
Samuel Husso
752520c823 When running from project root download the files to the testdata folder instead of cwd 2017-10-26 10:24:22 +03:00
Janne Sinivirta
6ba2492360 add Awesome Oscillator and try it in hyperopt 2017-10-25 18:37:20 +03:00
Janne Sinivirta
d5d798f6fa pull in new indicators from QTPYLib 2017-10-25 18:37:20 +03:00
Janne Sinivirta
9c9cf76a0d Merge pull request #78 from gcarq/refactor-backtest
Refactor backtest functionality
2017-10-25 18:19:44 +03:00
Samuel Husso
041e201713 remove duplicated backtesting from hyperopt 2017-10-25 08:17:17 +03:00
gcarq
e09505b22d Merge tag '0.12.0' into develop
0.12.0
2017-10-24 18:14:41 +02:00
Samuel Husso
f43ba44b15 refactor backtesting to its own method as we use it also in hyperopt 2017-10-24 07:58:42 +03:00
42 changed files with 2651 additions and 831 deletions

View File

@@ -1,2 +1,5 @@
[run]
omit = freqtrade/tests/*
omit =
scripts/*
freqtrade/tests/*
freqtrade/vendor/*

View File

@@ -1,2 +1,3 @@
[BASIC]
good-names=logger
ignore=vendor

View File

@@ -4,6 +4,9 @@ os:
language: python
python:
- 3.6
env:
- BACKTEST=
- BACKTEST=true
addons:
apt:
packages:

View File

@@ -1,7 +1,5 @@
include LICENSE
include README.md
include config.json.example
include freqtrade/exchange/*.py
include freqtrade/rpc/*.py
include freqtrade/tests/*.py
recursive-include freqtrade *.py
include freqtrade/tests/testdata/*.json

View File

@@ -16,15 +16,19 @@ and enter the telegram `token` and your `chat_id` in `config.json`
Persistence is achieved through sqlite.
#### Telegram RPC commands:
### Telegram RPC commands:
* /start: Starts the trader
* /stop: Stops the trader
* /status: Lists all open trades
* /status [table]: Lists all open trades
* /count: Displays number of open trades
* /profit: Lists cumulative profit from all finished trades
* /forcesell <trade_id>: Instantly sells the given trade (Ignoring `minimum_roi`).
* /forcesell <trade_id>|all: Instantly sells the given trade (Ignoring `minimum_roi`).
* /performance: Show performance of each finished trade grouped by pair
* /balance: Show account balance per currency
* /help: Show help message
* /version: Show version
#### Config
### Config
`minimal_roi` is a JSON object where the key is a duration
in minutes and the value is the minimum ROI in percent.
See the example below:
@@ -53,12 +57,18 @@ end up paying more then would probably have been necessary.
The other values should be self-explanatory,
if not feel free to raise a github issue.
#### Prerequisites
### Prerequisites
* python3.6
* sqlite
* [TA-lib](https://github.com/mrjbq7/ta-lib#dependencies) binaries
#### Install
### Install
#### Arch Linux
Use your favorite AUR helper and install `python-freqtrade-git`.
#### Manually
`master` branch contains the latest stable release.
@@ -75,18 +85,9 @@ $ pip install -e .
$ ./freqtrade/main.py
```
There is also an [article](https://www.sales4k.com/blockchain/high-frequency-trading-bot-tutorial/) about how to setup the bot (thanks [@gurghet](https://github.com/gurghet)).
There is also an [article](https://www.sales4k.com/blockchain/high-frequency-trading-bot-tutorial/) about how to setup the bot (thanks [@gurghet](https://github.com/gurghet)).*
#### Execute tests
```
$ pytest
```
This will by default skip the slow running backtest set. To run backtest set:
```
$ BACKTEST=true pytest -s freqtrade/tests/test_backtesting.py
```
\* *Note:* that article was written for an earlier version, so it may be outdated
#### Docker
@@ -114,14 +115,14 @@ filesystem):
```
$ cd ~/.freq
$ touch tradesv2.sqlite
$ touch tradesv3.sqlite
$ docker run -d \
--name freqtrade \
-v ~/.freq/config.json:/freqtrade/config.json \
-v ~/.freq/tradesv2.sqlite:/freqtrade/tradesv2.sqlite \
-v ~/.freq/tradesv3.sqlite:/freqtrade/tradesv3.sqlite \
freqtrade
```
If you are using `dry_run=True` you need to bind `tradesv2.dry_run.sqlite` instead of `tradesv2.sqlite`.
If you are using `dry_run=True` it's not necessary to mount `tradesv3.sqlite`.
You can then use the following commands to monitor and manage your container:
@@ -136,7 +137,18 @@ $ docker start freqtrade
You do not need to rebuild the image for configuration
changes, it will suffice to edit `config.json` and restart the container.
#### Contributing
### Execute tests
```
$ pytest
```
This will by default skip the slow running backtest set. To run backtest set:
```
$ BACKTEST=true pytest -s freqtrade/tests/test_backtesting.py
```
### Contributing
Feel like our bot is missing a feature? We welcome your pull requests! Few pointers for contributions:

View File

@@ -1,4 +1,4 @@
#!/usr/bin/env python
#!/usr/bin/env python3
from freqtrade.main import main
main()

View File

@@ -34,5 +34,8 @@
"token": "token",
"chat_id": "chat_id"
},
"initial_state": "running"
"initial_state": "running",
"internals": {
"process_throttle_secs": 5
}
}

View File

@@ -1,3 +1,3 @@
__version__ = '0.12.0'
__version__ = '0.14.2'
from . import main

View File

@@ -1,30 +1,29 @@
import logging
import time
from datetime import timedelta
import arrow
import talib.abstract as ta
from pandas import DataFrame
from pandas import DataFrame, to_datetime
from freqtrade import exchange
from freqtrade.exchange import Bittrex, get_ticker_history
from freqtrade.exchange import get_ticker_history
from freqtrade.vendor.qtpylib.indicators import awesome_oscillator
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
def parse_ticker_dataframe(ticker: list, minimum_date: arrow.Arrow) -> DataFrame:
def parse_ticker_dataframe(ticker: list) -> DataFrame:
"""
Analyses the trend for the given pair
:param pair: pair as str in format BTC_ETH or BTC-ETH
Analyses the trend for the given ticker history
:param ticker: See exchange.get_ticker_history
:return: DataFrame
"""
df = DataFrame(ticker) \
columns = {'C': 'close', 'V': 'volume', 'O': 'open', 'H': 'high', 'L': 'low', 'T': 'date'}
frame = DataFrame(ticker) \
.drop('BV', 1) \
.rename(columns={'C':'close', 'V':'volume', 'O':'open', 'H':'high', 'L':'low', 'T':'date'}) \
.sort_values('date')
return df
.rename(columns=columns)
frame['date'] = to_datetime(frame['date'], utc=True, infer_datetime_format=True)
frame.sort_values('date', inplace=True)
return frame
def populate_indicators(dataframe: DataFrame) -> DataFrame:
@@ -40,7 +39,19 @@ def populate_indicators(dataframe: DataFrame) -> DataFrame:
dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
dataframe['mfi'] = ta.MFI(dataframe)
dataframe['cci'] = ta.CCI(dataframe)
dataframe['rsi'] = ta.RSI(dataframe)
dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
dataframe['ao'] = awesome_oscillator(dataframe)
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal']
dataframe['macdhist'] = macd['macdhist']
hilbert = ta.HT_SINE(dataframe)
dataframe['htsine'] = hilbert['sine']
dataframe['htleadsine'] = hilbert['leadsine']
return dataframe
@@ -50,14 +61,14 @@ def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
dataframe.loc[
dataframe.ix[
(dataframe['close'] < dataframe['sma']) &
(dataframe['tema'] <= dataframe['blower']) &
(dataframe['mfi'] < 25) &
(dataframe['fastd'] < 25) &
(dataframe['adx'] > 30),
'buy'] = 1
dataframe.loc[dataframe['buy'] == 1, 'buy_price'] = dataframe['close']
dataframe.ix[dataframe['buy'] == 1, 'buy_price'] = dataframe['close']
return dataframe
@@ -68,14 +79,12 @@ def analyze_ticker(pair: str) -> DataFrame:
add several TA indicators and buy signal to it
:return DataFrame with ticker data and indicator data
"""
minimum_date = arrow.utcnow().shift(hours=-24)
data = get_ticker_history(pair, minimum_date)
dataframe = parse_ticker_dataframe(data['result'], minimum_date)
if dataframe.empty:
logger.warning('Empty dataframe for pair %s', pair)
return dataframe
ticker_hist = get_ticker_history(pair)
if not ticker_hist:
logger.warning('Empty ticker history for pair %s', pair)
return DataFrame()
dataframe = parse_ticker_dataframe(ticker_hist)
dataframe = populate_indicators(dataframe)
dataframe = populate_buy_trend(dataframe)
return dataframe
@@ -88,7 +97,6 @@ def get_buy_signal(pair: str) -> bool:
:return: True if pair is good for buying, False otherwise
"""
dataframe = analyze_ticker(pair)
if dataframe.empty:
return False
@@ -102,55 +110,3 @@ def get_buy_signal(pair: str) -> bool:
signal = latest['buy'] == 1
logger.debug('buy_trigger: %s (pair=%s, signal=%s)', latest['date'], pair, signal)
return signal
def plot_dataframe(dataframe: DataFrame, pair: str) -> None:
"""
Plots the given dataframe
:param dataframe: DataFrame
:param pair: pair as str
:return: None
"""
import matplotlib
matplotlib.use("Qt5Agg")
import matplotlib.pyplot as plt
# Two subplots sharing x axis
fig, (ax1, ax2, ax3) = plt.subplots(3, sharex=True)
fig.suptitle(pair, fontsize=14, fontweight='bold')
ax1.plot(dataframe.index.values, dataframe['close'], label='close')
# ax1.plot(dataframe.index.values, dataframe['sell'], 'ro', label='sell')
ax1.plot(dataframe.index.values, dataframe['sma'], '--', label='SMA')
ax1.plot(dataframe.index.values, dataframe['tema'], ':', label='TEMA')
ax1.plot(dataframe.index.values, dataframe['blower'], '-.', label='BB low')
ax1.plot(dataframe.index.values, dataframe['buy_price'], 'bo', label='buy')
ax1.legend()
ax2.plot(dataframe.index.values, dataframe['adx'], label='ADX')
ax2.plot(dataframe.index.values, dataframe['mfi'], label='MFI')
# ax2.plot(dataframe.index.values, [25] * len(dataframe.index.values))
ax2.legend()
ax3.plot(dataframe.index.values, dataframe['fastk'], label='k')
ax3.plot(dataframe.index.values, dataframe['fastd'], label='d')
ax3.plot(dataframe.index.values, [20] * len(dataframe.index.values))
ax3.legend()
# Fine-tune figure; make subplots close to each other and hide x ticks for
# all but bottom plot.
fig.subplots_adjust(hspace=0)
plt.setp([a.get_xticklabels() for a in fig.axes[:-1]], visible=False)
plt.show()
if __name__ == '__main__':
# Install PYQT5==5.9 manually if you want to test this helper function
while True:
exchange.EXCHANGE = Bittrex({'key': '', 'secret': ''})
test_pair = 'BTC_ETH'
# for pair in ['BTC_ANT', 'BTC_ETH', 'BTC_GNT', 'BTC_ETC']:
# get_buy_signal(pair)
plot_dataframe(analyze_ticker(test_pair), test_pair)
time.sleep(60)

View File

@@ -1,8 +1,10 @@
import enum
import logging
from typing import List
from random import randint
from typing import List, Dict, Any, Optional
import arrow
from cachetools import cached, TTLCache
from freqtrade.exchange.bittrex import Bittrex
from freqtrade.exchange.interface import Exchange
@@ -10,9 +12,12 @@ from freqtrade.exchange.interface import Exchange
logger = logging.getLogger(__name__)
# Current selected exchange
EXCHANGE: Exchange = None
_API: Exchange = None
_CONF: dict = {}
# Holds all open sell orders for dry_run
_DRY_RUN_OPEN_ORDERS: Dict[str, Any] = {}
class Exchanges(enum.Enum):
"""
@@ -29,7 +34,7 @@ def init(config: dict) -> None:
:param config: config to use
:return: None
"""
global _CONF, EXCHANGE
global _CONF, _API
_CONF.update(config)
@@ -45,7 +50,7 @@ def init(config: dict) -> None:
except KeyError:
raise RuntimeError('Exchange {} is not supported'.format(name))
EXCHANGE = exchange_class(exchange_config)
_API = exchange_class(exchange_config)
# Check if all pairs are available
validate_pairs(config['exchange']['pair_whitelist'])
@@ -58,58 +63,113 @@ def validate_pairs(pairs: List[str]) -> None:
:param pairs: list of pairs
:return: None
"""
markets = EXCHANGE.get_markets()
markets = _API.get_markets()
stake_cur = _CONF['stake_currency']
for pair in pairs:
if not pair.startswith(stake_cur):
raise RuntimeError(
'Pair {} not compatible with stake_currency: {}'.format(pair, stake_cur)
)
if pair not in markets:
raise RuntimeError('Pair {} is not available at {}'.format(pair, EXCHANGE.name.lower()))
raise RuntimeError('Pair {} is not available at {}'.format(pair, _API.name.lower()))
def buy(pair: str, rate: float, amount: float) -> str:
if _CONF['dry_run']:
return 'dry_run'
global _DRY_RUN_OPEN_ORDERS
order_id = 'dry_run_buy_{}'.format(randint(0, 1e6))
_DRY_RUN_OPEN_ORDERS[order_id] = {
'pair': pair,
'rate': rate,
'amount': amount,
'type': 'LIMIT_BUY',
'remaining': 0.0,
'opened': arrow.utcnow().datetime,
'closed': arrow.utcnow().datetime,
}
return order_id
return EXCHANGE.buy(pair, rate, amount)
return _API.buy(pair, rate, amount)
def sell(pair: str, rate: float, amount: float) -> str:
if _CONF['dry_run']:
return 'dry_run'
global _DRY_RUN_OPEN_ORDERS
order_id = 'dry_run_sell_{}'.format(randint(0, 1e6))
_DRY_RUN_OPEN_ORDERS[order_id] = {
'pair': pair,
'rate': rate,
'amount': amount,
'type': 'LIMIT_SELL',
'remaining': 0.0,
'opened': arrow.utcnow().datetime,
'closed': arrow.utcnow().datetime,
}
return order_id
return EXCHANGE.sell(pair, rate, amount)
return _API.sell(pair, rate, amount)
def get_balance(currency: str) -> float:
if _CONF['dry_run']:
return 999.9
return EXCHANGE.get_balance(currency)
return _API.get_balance(currency)
def get_balances():
if _CONF['dry_run']:
return []
return _API.get_balances()
def get_ticker(pair: str) -> dict:
return EXCHANGE.get_ticker(pair)
return _API.get_ticker(pair)
def get_ticker_history(pair: str, minimum_date: arrow.Arrow):
return EXCHANGE.get_ticker_history(pair, minimum_date)
@cached(TTLCache(maxsize=100, ttl=30))
def get_ticker_history(pair: str, tick_interval: Optional[int] = 5) -> List[Dict]:
return _API.get_ticker_history(pair, tick_interval)
def cancel_order(order_id: str) -> None:
if _CONF['dry_run']:
return
return EXCHANGE.cancel_order(order_id)
return _API.cancel_order(order_id)
def get_open_orders(pair: str) -> List[dict]:
def get_order(order_id: str) -> Dict:
if _CONF['dry_run']:
return []
order = _DRY_RUN_OPEN_ORDERS[order_id]
order.update({
'id': order_id
})
return order
return EXCHANGE.get_open_orders(pair)
return _API.get_order(order_id)
def get_pair_detail_url(pair: str) -> str:
return EXCHANGE.get_pair_detail_url(pair)
return _API.get_pair_detail_url(pair)
def get_markets() -> List[str]:
return EXCHANGE.get_markets()
return _API.get_markets()
def get_market_summaries() -> List[Dict]:
return _API.get_market_summaries()
def get_name() -> str:
return _API.name
def get_fee() -> float:
return _API.fee
def get_wallet_health() -> List[Dict]:
return _API.get_wallet_health()

View File

@@ -1,15 +1,14 @@
import logging
from typing import List, Optional
from typing import List, Dict
import arrow
import requests
from bittrex.bittrex import Bittrex as _Bittrex
from bittrex.bittrex import Bittrex as _Bittrex, API_V2_0, API_V1_1
from freqtrade.exchange.interface import Exchange
logger = logging.getLogger(__name__)
_API: _Bittrex = None
_API_V2: _Bittrex = None
_EXCHANGE_CONF: dict = {}
@@ -19,85 +18,131 @@ class Bittrex(Exchange):
"""
# Base URL and API endpoints
BASE_URL: str = 'https://www.bittrex.com'
TICKER_METHOD: str = BASE_URL + '/Api/v2.0/pub/market/GetTicks'
PAIR_DETAIL_METHOD: str = BASE_URL + '/Market/Index'
# Ticker inveral
TICKER_INTERVAL: str = 'fiveMin'
# Sleep time to avoid rate limits, used in the main loop
SLEEP_TIME: float = 25
@property
def sleep_time(self) -> float:
return self.SLEEP_TIME
def __init__(self, config: dict) -> None:
global _API, _EXCHANGE_CONF
global _API, _API_V2, _EXCHANGE_CONF
_EXCHANGE_CONF.update(config)
_API = _Bittrex(api_key=_EXCHANGE_CONF['key'], api_secret=_EXCHANGE_CONF['secret'])
_API = _Bittrex(
api_key=_EXCHANGE_CONF['key'],
api_secret=_EXCHANGE_CONF['secret'],
calls_per_second=1,
api_version=API_V1_1,
)
_API_V2 = _Bittrex(
api_key=_EXCHANGE_CONF['key'],
api_secret=_EXCHANGE_CONF['secret'],
calls_per_second=1,
api_version=API_V2_0,
)
@property
def fee(self) -> float:
# See https://bittrex.com/fees
return 0.0025
def buy(self, pair: str, rate: float, amount: float) -> str:
data = _API.buy_limit(pair.replace('_', '-'), amount, rate)
if not data['success']:
raise RuntimeError('{}: {}'.format(self.name.upper(), data['message']))
raise RuntimeError('{message} params=({pair}, {rate}, {amount})'.format(
message=data['message'],
pair=pair,
rate=rate,
amount=amount))
return data['result']['uuid']
def sell(self, pair: str, rate: float, amount: float) -> str:
data = _API.sell_limit(pair.replace('_', '-'), amount, rate)
if not data['success']:
raise RuntimeError('{}: {}'.format(self.name.upper(), data['message']))
raise RuntimeError('{message} params=({pair}, {rate}, {amount})'.format(
message=data['message'],
pair=pair,
rate=rate,
amount=amount))
return data['result']['uuid']
def get_balance(self, currency: str) -> float:
data = _API.get_balance(currency)
if not data['success']:
raise RuntimeError('{}: {}'.format(self.name.upper(), data['message']))
raise RuntimeError('{message} params=({currency})'.format(
message=data['message'],
currency=currency))
return float(data['result']['Balance'] or 0.0)
def get_balances(self):
data = _API.get_balances()
if not data['success']:
raise RuntimeError('{message}'.format(message=data['message']))
return data['result']
def get_ticker(self, pair: str) -> dict:
data = _API.get_ticker(pair.replace('_', '-'))
if not data['success']:
raise RuntimeError('{}: {}'.format(self.name.upper(), data['message']))
raise RuntimeError('{message} params=({pair})'.format(
message=data['message'],
pair=pair))
if not data['result']['Bid'] or not data['result']['Ask'] or not data['result']['Last']:
raise RuntimeError('{message} params=({pair})'.format(
message=data['message'],
pair=pair))
return {
'bid': float(data['result']['Bid']),
'ask': float(data['result']['Ask']),
'last': float(data['result']['Last']),
}
def get_ticker_history(self, pair: str, minimum_date: Optional[arrow.Arrow] = None):
url = self.TICKER_METHOD
headers = {
# TODO: Set as global setting
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/61.0.3163.100 Safari/537.36'
}
params = {
'marketName': pair.replace('_', '-'),
'tickInterval': self.TICKER_INTERVAL,
# TODO: Timestamp has no effect on API response
'_': minimum_date.timestamp * 1000
}
data = requests.get(url, params=params, headers=headers).json()
def get_ticker_history(self, pair: str, tick_interval: int) -> List[Dict]:
if tick_interval == 1:
interval = 'oneMin'
elif tick_interval == 5:
interval = 'fiveMin'
else:
raise ValueError('Cannot parse tick_interval: {}'.format(tick_interval))
data = _API_V2.get_candles(pair.replace('_', '-'), interval)
# These sanity check are necessary because bittrex cannot keep their API stable.
if not data.get('result'):
return []
for prop in ['C', 'V', 'O', 'H', 'L', 'T']:
for tick in data['result']:
if prop not in tick.keys():
logger.warning('Required property %s not present in response', prop)
return []
if not data['success']:
raise RuntimeError('{}: {}'.format(self.name.upper(), data['message']))
return data
raise RuntimeError('{message} params=({pair})'.format(
message=data['message'],
pair=pair))
return data['result']
def get_order(self, order_id: str) -> Dict:
data = _API.get_order(order_id)
if not data['success']:
raise RuntimeError('{message} params=({order_id})'.format(
message=data['message'],
order_id=order_id))
data = data['result']
return {
'id': data['OrderUuid'],
'type': data['Type'],
'pair': data['Exchange'].replace('-', '_'),
'opened': data['Opened'],
'rate': data['PricePerUnit'],
'amount': data['Quantity'],
'remaining': data['QuantityRemaining'],
'closed': data['Closed'],
}
def cancel_order(self, order_id: str) -> None:
data = _API.cancel(order_id)
if not data['success']:
raise RuntimeError('{}: {}'.format(self.name.upper(), data['message']))
def get_open_orders(self, pair: str) -> List[dict]:
data = _API.get_open_orders(pair.replace('_', '-'))
if not data['success']:
raise RuntimeError('{}: {}'.format(self.name.upper(), data['message']))
return [{
'id': entry['OrderUuid'],
'type': entry['OrderType'],
'opened': entry['Opened'],
'rate': entry['PricePerUnit'],
'amount': entry['Quantity'],
'remaining': entry['QuantityRemaining'],
} for entry in data['result']]
raise RuntimeError('{message} params=({order_id})'.format(
message=data['message'],
order_id=order_id))
def get_pair_detail_url(self, pair: str) -> str:
return self.PAIR_DETAIL_METHOD + '?MarketName={}'.format(pair.replace('_', '-'))
@@ -105,5 +150,22 @@ class Bittrex(Exchange):
def get_markets(self) -> List[str]:
data = _API.get_markets()
if not data['success']:
raise RuntimeError('{}: {}'.format(self.name.upper(), data['message']))
raise RuntimeError('{message}'.format(message=data['message']))
return [m['MarketName'].replace('-', '_') for m in data['result']]
def get_market_summaries(self) -> List[Dict]:
data = _API.get_market_summaries()
if not data['success']:
raise RuntimeError('{message}'.format(message=data['message']))
return data['result']
def get_wallet_health(self) -> List[Dict]:
data = _API_V2.get_wallet_health()
if not data['success']:
raise RuntimeError('{message}'.format(message=data['message']))
return [{
'Currency': entry['Health']['Currency'],
'IsActive': entry['Health']['IsActive'],
'LastChecked': entry['Health']['LastChecked'],
'Notice': entry['Currency'].get('Notice'),
} for entry in data['result']]

View File

@@ -1,7 +1,5 @@
from abc import ABC, abstractmethod
from typing import List, Optional
import arrow
from typing import List, Dict
class Exchange(ABC):
@@ -14,11 +12,10 @@ class Exchange(ABC):
return self.__class__.__name__
@property
@abstractmethod
def sleep_time(self) -> float:
def fee(self) -> float:
"""
Sleep time in seconds for the main loop to avoid API rate limits.
:return: float
Fee for placing an order
:return: percentage in float
"""
@abstractmethod
@@ -49,6 +46,21 @@ class Exchange(ABC):
:return: float
"""
@abstractmethod
def get_balances(self) -> List[dict]:
"""
Gets account balances across currencies
:return: List of dicts, format: [
{
'Currency': str,
'Balance': float,
'Available': float,
'Pending': float,
}
...
]
"""
@abstractmethod
def get_ticker(self, pair: str) -> dict:
"""
@@ -62,26 +74,38 @@ class Exchange(ABC):
"""
@abstractmethod
def get_ticker_history(self, pair: str, minimum_date: Optional[arrow.Arrow] = None) -> dict:
def get_ticker_history(self, pair: str, tick_interval: int) -> List[Dict]:
"""
Gets ticker history for given pair.
:param pair: Pair as str, format: BTC_ETC
:param minimum_date: Minimum date (optional)
:param tick_interval: ticker interval in minutes
:return: list, format: [
{
'O': float, (Open)
'H': float, (High)
'L': float, (Low)
'C': float, (Close)
'V': float, (Volume)
'T': datetime, (Time)
'BV': float, (Base Volume)
},
...
]
"""
def get_order(self, order_id: str) -> Dict:
"""
Get order details for the given order_id.
:param order_id: ID as str
:return: dict, format: {
'success': bool,
'message': str,
'result': [
{
'O': float, (Open)
'H': float, (High)
'L': float, (Low)
'C': float, (Close)
'V': float, (Volume)
'T': datetime, (Time)
'BV': float, (Base Volume)
},
...
]
'id': str,
'type': str,
'pair': str,
'opened': str ISO 8601 datetime,
'closed': str ISO 8601 datetime,
'rate': float,
'amount': float,
'remaining': int
}
"""
@@ -93,24 +117,6 @@ class Exchange(ABC):
:return: None
"""
@abstractmethod
def get_open_orders(self, pair: str) -> List[dict]:
"""
Gets all open orders for given pair.
:param pair: Pair as str, format: BTC_ETC
:return: List of dicts, format: [
{
'id': str,
'type': str,
'opened': datetime,
'rate': float,
'amount': float,
'remaining': int,
},
...
]
"""
@abstractmethod
def get_pair_detail_url(self, pair: str) -> str:
"""
@@ -125,3 +131,41 @@ class Exchange(ABC):
Returns all available markets.
:return: List of all available pairs
"""
@abstractmethod
def get_market_summaries(self) -> List[Dict]:
"""
Returns a 24h market summary for all available markets
:return: list, format: [
{
'MarketName': str,
'High': float,
'Low': float,
'Volume': float,
'Last': float,
'TimeStamp': datetime,
'BaseVolume': float,
'Bid': float,
'Ask': float,
'OpenBuyOrders': int,
'OpenSellOrders': int,
'PrevDay': float,
'Created': datetime
},
...
]
"""
@abstractmethod
def get_wallet_health(self) -> List[Dict]:
"""
Returns a list of all wallet health information
:return: list, format: [
{
'Currency': str,
'IsActive': bool,
'LastChecked': str,
'Notice': str
},
...
"""

View File

@@ -1,34 +1,67 @@
#!/usr/bin/env python
#!/usr/bin/env python3
import copy
import json
import logging
import time
import traceback
from datetime import datetime
from typing import Dict, Optional
from signal import signal, SIGINT, SIGABRT, SIGTERM
from typing import Dict, Optional, List
import requests
from cachetools import cached, TTLCache
from jsonschema import validate
from freqtrade import __version__, exchange, persistence
from freqtrade.analyze import get_buy_signal
from freqtrade.misc import CONF_SCHEMA, State, get_state, update_state
from freqtrade.misc import CONF_SCHEMA, State, get_state, update_state, build_arg_parser, throttle
from freqtrade.persistence import Trade
from freqtrade.rpc import telegram
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
logger = logging.getLogger('freqtrade')
_CONF = {}
def _process() -> None:
def refresh_whitelist(whitelist: Optional[List[str]] = None) -> None:
"""
Check wallet health and remove pair from whitelist if necessary
:param whitelist: a new whitelist (optional)
:return: None
"""
whitelist = whitelist or _CONF['exchange']['pair_whitelist']
sanitized_whitelist = []
health = exchange.get_wallet_health()
for status in health:
pair = '{}_{}'.format(_CONF['stake_currency'], status['Currency'])
if pair not in whitelist:
continue
if status['IsActive']:
sanitized_whitelist.append(pair)
else:
logger.info(
'Ignoring %s from whitelist (reason: %s).',
pair, status.get('Notice') or 'wallet is not active'
)
if _CONF['exchange']['pair_whitelist'] != sanitized_whitelist:
logger.debug('Using refreshed pair whitelist: %s ...', sanitized_whitelist)
_CONF['exchange']['pair_whitelist'] = sanitized_whitelist
def _process(dynamic_whitelist: Optional[bool] = False) -> bool:
"""
Queries the persistence layer for open trades and handles them,
otherwise a new trade is created.
:return: None
:param: dynamic_whitelist: True is a dynamic whitelist should be generated (optional)
:return: True if a trade has been created or closed, False otherwise
"""
state_changed = False
try:
# Refresh whitelist based on wallet maintenance
refresh_whitelist(
gen_pair_whitelist(_CONF['stake_currency']) if dynamic_whitelist else None
)
# Query trades from persistence layer
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
if len(trades) < _CONF['max_open_trades']:
@@ -37,28 +70,39 @@ def _process() -> None:
trade = create_trade(float(_CONF['stake_amount']))
if trade:
Trade.session.add(trade)
state_changed = True
else:
logging.info('Got no buy signal...')
logger.info(
'Checked all whitelisted currencies. '
'Found no suitable entry positions for buying. Will keep looking ...'
)
except ValueError:
logger.exception('Unable to create trade')
for trade in trades:
# Check if there is already an open order for this trade
orders = exchange.get_open_orders(trade.pair)
orders = [o for o in orders if o['id'] == trade.open_order_id]
if orders:
logger.info('There is an open order for: %s', orders[0])
else:
# Update state
trade.open_order_id = None
# Check if this trade can be closed
if not close_trade_if_fulfilled(trade):
# Check if we can sell our current pair
handle_trade(trade)
Trade.session.flush()
except (ConnectionError, json.JSONDecodeError) as error:
msg = 'Got {} in _process()'.format(error.__class__.__name__)
# Get order details for actual price per unit
if trade.open_order_id:
# Update trade with order values
logger.info('Got open order for %s', trade)
trade.update(exchange.get_order(trade.open_order_id))
if not close_trade_if_fulfilled(trade):
# Check if we can sell our current pair
state_changed = handle_trade(trade) or state_changed
Trade.session.flush()
except (requests.exceptions.RequestException, json.JSONDecodeError) as error:
msg = 'Got {} in _process(), retrying in 30 seconds...'.format(error.__class__.__name__)
logger.exception(msg)
time.sleep(30)
except RuntimeError:
telegram.send_msg('*Status:* Got RuntimeError:\n```\n{traceback}```{hint}'.format(
traceback=traceback.format_exc(),
hint='Issue `/start` if you think it is safe to restart.'
))
logger.exception('Got RuntimeError. Stopping trader ...')
update_state(State.STOPPED)
return state_changed
def close_trade_if_fulfilled(trade: Trade) -> bool:
@@ -74,28 +118,32 @@ def close_trade_if_fulfilled(trade: Trade) -> bool:
and trade.close_rate is not None \
and trade.open_order_id is None:
trade.is_open = False
logger.info('No open orders found and trade is fulfilled. Marking %s as closed ...', trade)
logger.info(
'Marking %s as closed as the trade is fulfilled and found no open orders for it.',
trade
)
return True
return False
def execute_sell(trade: Trade, current_rate: float) -> None:
def execute_sell(trade: Trade, limit: float) -> None:
"""
Executes a sell for the given trade and current rate
Executes a limit sell for the given trade and limit
:param trade: Trade instance
:param current_rate: current rate
:param limit: limit rate for the sell order
:return: None
"""
# Get available balance
currency = trade.pair.split('_')[1]
balance = exchange.get_balance(currency)
profit = trade.exec_sell_order(current_rate, balance)
message = '*{}:* Selling [{}]({}) at rate `{:f} (profit: {}%)`'.format(
# Execute sell and update trade record
order_id = exchange.sell(str(trade.pair), limit, trade.amount)
trade.open_order_id = order_id
fmt_exp_profit = round(trade.calc_profit(limit) * 100, 2)
message = '*{}:* Selling [{}]({}) with limit `{:.8f} (profit: ~{:.2f}%)`'.format(
trade.exchange,
trade.pair.replace('_', '/'),
exchange.get_pair_detail_url(trade.pair),
trade.close_rate,
round(profit, 2)
limit,
fmt_exp_profit
)
logger.info(message)
telegram.send_msg(message)
@@ -106,41 +154,35 @@ def should_sell(trade: Trade, current_rate: float, current_time: datetime) -> bo
Based an earlier trade and current price and configuration, decides whether bot should sell
:return True if bot should sell at current rate
"""
current_profit = (current_rate - trade.open_rate) / trade.open_rate
current_profit = trade.calc_profit(current_rate)
if 'stoploss' in _CONF and current_profit < float(_CONF['stoploss']):
logger.debug('Stop loss hit.')
return True
for duration, threshold in sorted(_CONF['minimal_roi'].items()):
duration, threshold = float(duration), float(threshold)
# Check if time matches and current rate is above threshold
time_diff = (current_time - trade.open_date).total_seconds() / 60
if time_diff > duration and current_profit > threshold:
if time_diff > float(duration) and current_profit > threshold:
return True
logger.debug('Threshold not reached. (cur_profit: %1.2f%%)', current_profit * 100.0)
return False
def handle_trade(trade: Trade) -> None:
def handle_trade(trade: Trade) -> bool:
"""
Sells the current pair if the threshold is reached and updates the trade record.
:return: None
:return: True if trade has been sold, False otherwise
"""
try:
if not trade.is_open:
raise ValueError('attempt to handle closed trade: {}'.format(trade))
if not trade.is_open:
raise ValueError('attempt to handle closed trade: {}'.format(trade))
logger.debug('Handling open trade %s ...', trade)
current_rate = exchange.get_ticker(trade.pair)['bid']
if should_sell(trade, current_rate, datetime.utcnow()):
execute_sell(trade, current_rate)
return
except ValueError:
logger.exception('Unable to handle open order')
logger.debug('Handling %s ...', trade)
current_rate = exchange.get_ticker(trade.pair)['bid']
if should_sell(trade, current_rate, datetime.utcnow()):
execute_sell(trade, current_rate)
return True
return False
def get_target_bid(ticker: Dict[str, float]) -> float:
@@ -157,12 +199,15 @@ def create_trade(stake_amount: float) -> Optional[Trade]:
if one pair triggers the buy_signal a new trade record gets created
:param stake_amount: amount of btc to spend
"""
logger.info('Creating new trade with stake_amount: %f ...', stake_amount)
logger.info(
'Checking buy signals to create a new trade with stake_amount: %f ...',
stake_amount
)
whitelist = copy.deepcopy(_CONF['exchange']['pair_whitelist'])
# Check if stake_amount is fulfilled
if exchange.get_balance(_CONF['stake_currency']) < stake_amount:
raise ValueError(
'stake amount is not fulfilled (currency={}'.format(_CONF['stake_currency'])
'stake amount is not fulfilled (currency={})'.format(_CONF['stake_currency'])
)
# Remove currently opened and latest pairs from whitelist
@@ -181,27 +226,30 @@ def create_trade(stake_amount: float) -> Optional[Trade]:
else:
return None
open_rate = get_target_bid(exchange.get_ticker(pair))
amount = stake_amount / open_rate
order_id = exchange.buy(pair, open_rate, amount)
# Calculate amount and subtract fee
fee = exchange.get_fee()
buy_limit = get_target_bid(exchange.get_ticker(pair))
amount = (1 - fee) * stake_amount / buy_limit
order_id = exchange.buy(pair, buy_limit, amount)
# Create trade entity and return
message = '*{}:* Buying [{}]({}) at rate `{:f}`'.format(
exchange.EXCHANGE.name.upper(),
message = '*{}:* Buying [{}]({}) with limit `{:.8f}`'.format(
exchange.get_name().upper(),
pair.replace('_', '/'),
exchange.get_pair_detail_url(pair),
open_rate
buy_limit
)
logger.info(message)
telegram.send_msg(message)
# Fee is applied twice because we make a LIMIT_BUY and LIMIT_SELL
return Trade(pair=pair,
stake_amount=stake_amount,
open_rate=open_rate,
open_date=datetime.utcnow(),
amount=amount,
exchange=exchange.EXCHANGE.name.upper(),
open_order_id=order_id,
is_open=True)
fee=fee * 2,
open_rate=buy_limit,
open_date=datetime.utcnow(),
exchange=exchange.get_name().upper(),
open_order_id=order_id)
def init(config: dict, db_url: Optional[str] = None) -> None:
@@ -223,50 +271,90 @@ def init(config: dict, db_url: Optional[str] = None) -> None:
else:
update_state(State.STOPPED)
# Register signal handlers
for sig in (SIGINT, SIGTERM, SIGABRT):
signal(sig, cleanup)
def app(config: dict) -> None:
@cached(TTLCache(maxsize=1, ttl=1800))
def gen_pair_whitelist(base_currency: str, topn: int = 20, key: str = 'BaseVolume') -> List[str]:
"""
Main loop which handles the application state
:param config: config as dict
Updates the whitelist with with a dynamically generated list
:param base_currency: base currency as str
:param topn: maximum number of returned results
:param key: sort key (defaults to 'BaseVolume')
:return: List of pairs
"""
summaries = sorted(
(s for s in exchange.get_market_summaries() if s['MarketName'].startswith(base_currency)),
key=lambda s: s.get(key) or 0.0,
reverse=True
)
return [s['MarketName'].replace('-', '_') for s in summaries[:topn]]
def cleanup(*args, **kwargs) -> None:
"""
Cleanup the application state und finish all pending tasks
:return: None
"""
logger.info('Starting freqtrade %s', __version__)
init(config)
try:
old_state = get_state()
logger.info('Initial State: %s', old_state)
telegram.send_msg('*Status:* `{}`'.format(old_state.name.lower()))
while True:
new_state = get_state()
# Log state transition
if new_state != old_state:
telegram.send_msg('*Status:* `{}`'.format(new_state.name.lower()))
logging.info('Changing state to: %s', new_state.name)
if new_state == State.STOPPED:
time.sleep(1)
elif new_state == State.RUNNING:
_process()
# We need to sleep here because otherwise we would run into bittrex rate limit
time.sleep(exchange.EXCHANGE.sleep_time)
old_state = new_state
except RuntimeError:
telegram.send_msg('*Status:* Got RuntimeError: ```\n{}\n```'.format(traceback.format_exc()))
logger.exception('RuntimeError. Trader stopped!')
finally:
telegram.send_msg('*Status:* `Trader has stopped`')
telegram.send_msg('*Status:* `Stopping trader...`')
logger.info('Stopping trader and cleaning up modules...')
update_state(State.STOPPED)
persistence.cleanup()
telegram.cleanup()
exit(0)
def main():
"""
Loads and validates the config and starts the main loop
Loads and validates the config and handles the main loop
:return: None
"""
global _CONF
with open('config.json') as file:
args = build_arg_parser().parse_args()
# Initialize logger
logging.basicConfig(
level=args.loglevel,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
)
logger.info(
'Starting freqtrade %s (loglevel=%s)',
__version__,
logging.getLevelName(args.loglevel)
)
# Load and validate configuration
with open(args.config) as file:
_CONF = json.load(file)
validate(_CONF, CONF_SCHEMA)
app(_CONF)
if 'internals' not in _CONF:
_CONF['internals'] = {}
logger.info('Validating configuration ...')
validate(_CONF, CONF_SCHEMA)
# Initialize all modules and start main loop
if args.dynamic_whitelist:
logger.info('Using dynamically generated whitelist. (--dynamic-whitelist detected)')
init(_CONF)
old_state = None
while True:
new_state = get_state()
# Log state transition
if new_state != old_state:
telegram.send_msg('*Status:* `{}`'.format(new_state.name.lower()))
logger.info('Changing state to: %s', new_state.name)
if new_state == State.STOPPED:
time.sleep(1)
elif new_state == State.RUNNING:
throttle(
_process,
min_secs=_CONF['internals'].get('process_throttle_secs', 10),
dynamic_whitelist=args.dynamic_whitelist,
)
old_state = new_state
if __name__ == '__main__':

View File

@@ -1,7 +1,15 @@
import argparse
import enum
import logging
from typing import Any, Callable
import time
from wrapt import synchronized
from freqtrade import __version__
logger = logging.getLogger(__name__)
class State(enum.Enum):
RUNNING = 0
@@ -32,6 +40,57 @@ def get_state() -> State:
return _STATE
def throttle(func: Callable[..., Any], min_secs: float, *args, **kwargs) -> Any:
"""
Throttles the given callable that it
takes at least `min_secs` to finish execution.
:param func: Any callable
:param min_secs: minimum execution time in seconds
:return: Any
"""
start = time.time()
result = func(*args, **kwargs)
end = time.time()
duration = max(min_secs - (end - start), 0.0)
logger.debug('Throttling %s for %.2f seconds', func.__name__, duration)
time.sleep(duration)
return result
def build_arg_parser() -> argparse.ArgumentParser:
""" Builds and returns an ArgumentParser instance """
parser = argparse.ArgumentParser(
description='Simple High Frequency Trading Bot for crypto currencies'
)
parser.add_argument(
'-c', '--config',
help='specify configuration file (default: config.json)',
dest='config',
default='config.json',
type=str,
metavar='PATH',
)
parser.add_argument(
'-v', '--verbose',
help='be verbose',
action='store_const',
dest='loglevel',
const=logging.DEBUG,
default=logging.INFO,
)
parser.add_argument(
'--version',
action='version',
version='%(prog)s {}'.format(__version__),
)
parser.add_argument(
'--dynamic-whitelist',
help='dynamically generate and update whitelist based on 24h BaseVolume',
action='store_true',
)
return parser
# Required json-schema for user specified config
CONF_SCHEMA = {
'type': 'object',
@@ -71,6 +130,12 @@ CONF_SCHEMA = {
'required': ['enabled', 'token', 'chat_id']
},
'initial_state': {'type': 'string', 'enum': ['running', 'stopped']},
'internals': {
'type': 'object',
'properties': {
'process_throttle_secs': {'type': 'number'}
}
}
},
'definitions': {
'exchange': {

View File

@@ -1,87 +1,112 @@
import logging
from datetime import datetime
from typing import Optional
from decimal import Decimal, getcontext
from typing import Optional, Dict
import arrow
from sqlalchemy import Boolean, Column, DateTime, Float, Integer, String, create_engine
from sqlalchemy.engine import Engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm.scoping import scoped_session
from sqlalchemy.orm.session import sessionmaker
from sqlalchemy.types import Enum
from sqlalchemy.pool import StaticPool
from freqtrade import exchange
logger = logging.getLogger(__name__)
_CONF = {}
Base = declarative_base()
_DECL_BASE = declarative_base()
def init(config: dict, db_url: Optional[str] = None) -> None:
def init(config: dict, engine: Optional[Engine] = None) -> None:
"""
Initializes this module with the given config,
registers all known command handlers
and starts polling for message updates
:param config: config to use
:param db_url: database connector string for sqlalchemy (Optional)
:param engine: database engine for sqlalchemy (Optional)
:return: None
"""
_CONF.update(config)
if not db_url:
if not engine:
if _CONF.get('dry_run', False):
db_url = 'sqlite:///tradesv2.dry_run.sqlite'
engine = create_engine('sqlite://',
connect_args={'check_same_thread': False},
poolclass=StaticPool,
echo=False)
else:
db_url = 'sqlite:///tradesv2.sqlite'
engine = create_engine('sqlite:///tradesv3.sqlite')
engine = create_engine(db_url, echo=False)
session = scoped_session(sessionmaker(bind=engine, autoflush=True, autocommit=True))
Trade.session = session()
Trade.query = session.query_property()
Base.metadata.create_all(engine)
_DECL_BASE.metadata.create_all(engine)
class Trade(Base):
def cleanup() -> None:
"""
Flushes all pending operations to disk.
:return: None
"""
Trade.session.flush()
class Trade(_DECL_BASE):
__tablename__ = 'trades'
id = Column(Integer, primary_key=True)
exchange = Column(String, nullable=False)
pair = Column(String, nullable=False)
is_open = Column(Boolean, nullable=False, default=True)
open_rate = Column(Float, nullable=False)
fee = Column(Float, nullable=False, default=0.0)
open_rate = Column(Float)
close_rate = Column(Float)
close_profit = Column(Float)
stake_amount = Column(Float, name='btc_amount', nullable=False)
amount = Column(Float, nullable=False)
stake_amount = Column(Float, nullable=False)
amount = Column(Float)
open_date = Column(DateTime, nullable=False, default=datetime.utcnow)
close_date = Column(DateTime)
open_order_id = Column(String)
def __repr__(self):
if self.is_open:
open_since = 'closed'
else:
open_since = round((datetime.utcnow() - self.open_date).total_seconds() / 60, 2)
return 'Trade(id={}, pair={}, amount={}, open_rate={}, open_since={})'.format(
self.id,
self.pair,
self.amount,
self.open_rate,
open_since
arrow.get(self.open_date).humanize() if self.is_open else 'closed'
)
def exec_sell_order(self, rate: float, amount: float) -> float:
def update(self, order: Dict) -> None:
"""
Executes a sell for the given trade and updated the entity.
:param rate: rate to sell for
:param amount: amount to sell
:return: current profit as percentage
Updates this entity with amount and actual open/close rates.
:param order: order retrieved by exchange.get_order()
:return: None
"""
profit = 100 * ((rate - self.open_rate) / self.open_rate)
if not order['closed']:
return
# Execute sell and update trade record
order_id = exchange.sell(str(self.pair), rate, amount)
self.close_rate = rate
self.close_profit = profit
self.close_date = datetime.utcnow()
self.open_order_id = order_id
logger.debug('Updating trade (id=%d) ...', self.id)
if order['type'] == 'LIMIT_BUY':
# Update open rate and actual amount
self.open_rate = order['rate']
self.amount = order['amount']
elif order['type'] == 'LIMIT_SELL':
# Set close rate and set actual profit
self.close_rate = order['rate']
self.close_profit = self.calc_profit()
self.close_date = datetime.utcnow()
else:
raise ValueError('Unknown order type: {}'.format(order['type']))
# Flush changes
Trade.session.flush()
return profit
self.open_order_id = None
def calc_profit(self, rate: Optional[float] = None) -> float:
"""
Calculates the profit in percentage (including fee).
:param rate: rate to compare with (optional).
If rate is not set self.close_rate will be used
:return: profit in percentage as float
"""
getcontext().prec = 8
return float((Decimal(rate or self.close_rate) - Decimal(self.open_rate))
/ Decimal(self.open_rate) - Decimal(self.fee))

View File

@@ -1,6 +1,9 @@
import logging
import re
from datetime import timedelta
from typing import Callable, Any
from pandas import DataFrame
from tabulate import tabulate
import arrow
from sqlalchemy import and_, func, text
@@ -8,7 +11,7 @@ from telegram import ParseMode, Bot, Update
from telegram.error import NetworkError
from telegram.ext import CommandHandler, Updater
from freqtrade import exchange
from freqtrade import exchange, __version__
from freqtrade.misc import get_state, State, update_state
from freqtrade.persistence import Trade
@@ -17,7 +20,7 @@ logging.getLogger('requests.packages.urllib3').setLevel(logging.INFO)
logging.getLogger('telegram').setLevel(logging.INFO)
logger = logging.getLogger(__name__)
_updater = None
_UPDATER: Updater = None
_CONF = {}
@@ -29,27 +32,30 @@ def init(config: dict) -> None:
:param config: config to use
:return: None
"""
global _updater
global _UPDATER
_CONF.update(config)
if not _CONF['telegram']['enabled']:
if not is_enabled():
return
_updater = Updater(token=config['telegram']['token'], workers=0)
_UPDATER = Updater(token=config['telegram']['token'], workers=0)
# Register command handler and start telegram message polling
handles = [
CommandHandler('status', _status),
CommandHandler('profit', _profit),
CommandHandler('balance', _balance),
CommandHandler('start', _start),
CommandHandler('stop', _stop),
CommandHandler('forcesell', _forcesell),
CommandHandler('performance', _performance),
CommandHandler('count', _count),
CommandHandler('help', _help),
CommandHandler('version', _version),
]
for handle in handles:
_updater.dispatcher.add_handler(handle)
_updater.start_polling(
_UPDATER.dispatcher.add_handler(handle)
_UPDATER.start_polling(
clean=True,
bootstrap_retries=3,
timeout=30,
@@ -61,6 +67,23 @@ def init(config: dict) -> None:
)
def cleanup() -> None:
"""
Stops all running telegram threads.
:return: None
"""
if not is_enabled():
return
_UPDATER.stop()
def is_enabled() -> bool:
"""
Returns True if the telegram module is activated, False otherwise
"""
return bool(_CONF['telegram'].get('enabled', False))
def authorized_only(command_handler: Callable[[Bot, Update], None]) -> Callable[..., Any]:
"""
Decorator to check if the message comes from the correct chat_id
@@ -70,15 +93,17 @@ def authorized_only(command_handler: Callable[[Bot, Update], None]) -> Callable[
def wrapper(*args, **kwargs):
bot, update = kwargs.get('bot') or args[0], kwargs.get('update') or args[1]
if not isinstance(bot, Bot) or not isinstance(update, Update):
raise ValueError('Received invalid Arguments: {}'.format(*args))
# Reject unauthorized messages
chat_id = int(_CONF['telegram']['chat_id'])
if int(update.message.chat_id) == chat_id:
logger.info('Executing handler: %s for chat_id: %s', command_handler.__name__, chat_id)
return command_handler(*args, **kwargs)
else:
if int(update.message.chat_id) != chat_id:
logger.info('Rejected unauthorized message from: %s', update.message.chat_id)
return wrapper
logger.info('Executing handler: %s for chat_id: %s', command_handler.__name__, chat_id)
try:
return command_handler(*args, **kwargs)
except BaseException:
logger.exception('Exception occurred within Telegram module')
return wrapper
@@ -91,32 +116,39 @@ def _status(bot: Bot, update: Update) -> None:
:param update: message update
:return: None
"""
# Check if additional parameters are passed
params = update.message.text.replace('/status', '').split(' ') \
if update.message.text else []
if 'table' in params:
_status_table(bot, update)
return
# Fetch open trade
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
if get_state() != State.RUNNING:
send_msg('*Status:* `trader is not running`', bot=bot)
elif not trades:
send_msg('*Status:* `no active order`', bot=bot)
send_msg('*Status:* `no active trade`', bot=bot)
else:
for trade in trades:
order = None
if trade.open_order_id:
order = exchange.get_order(trade.open_order_id)
# calculate profit and send message to user
current_rate = exchange.get_ticker(trade.pair)['bid']
current_profit = 100 * ((current_rate - trade.open_rate) / trade.open_rate)
orders = exchange.get_open_orders(trade.pair)
orders = [o for o in orders if o['id'] == trade.open_order_id]
order = orders[0] if orders else None
current_profit = trade.calc_profit(current_rate)
fmt_close_profit = '{:.2f}%'.format(
round(trade.close_profit, 2)
round(trade.close_profit * 100, 2)
) if trade.close_profit else None
message = """
*Trade ID:* `{trade_id}`
*Current Pair:* [{pair}]({market_url})
*Open Since:* `{date}`
*Amount:* `{amount}`
*Open Rate:* `{open_rate}`
*Open Rate:* `{open_rate:.8f}`
*Close Rate:* `{close_rate}`
*Current Rate:* `{current_rate}`
*Current Rate:* `{current_rate:.8f}`
*Close Profit:* `{close_profit}`
*Current Profit:* `{current_profit:.2f}%`
*Open Order:* `{open_order}`
@@ -130,12 +162,51 @@ def _status(bot: Bot, update: Update) -> None:
current_rate=current_rate,
amount=round(trade.amount, 8),
close_profit=fmt_close_profit,
current_profit=round(current_profit, 2),
open_order='{} ({})'.format(order['remaining'], order['type']) if order else None,
current_profit=round(current_profit * 100, 2),
open_order='{} ({})'.format(
order['remaining'], order['type']
) if order else None,
)
send_msg(message, bot=bot)
@authorized_only
def _status_table(bot: Bot, update: Update) -> None:
"""
Handler for /status table.
Returns the current TradeThread status in table format
:param bot: telegram bot
:param update: message update
:return: None
"""
# Fetch open trade
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
if get_state() != State.RUNNING:
send_msg('*Status:* `trader is not running`', bot=bot)
elif not trades:
send_msg('*Status:* `no active order`', bot=bot)
else:
trades_list = []
for trade in trades:
# calculate profit and send message to user
current_rate = exchange.get_ticker(trade.pair)['bid']
trades_list.append([
trade.id,
trade.pair,
shorten_date(arrow.get(trade.open_date).humanize(only_distance=True)),
'{:.2f}'.format(100 * trade.calc_profit(current_rate))
])
columns = ['ID', 'Pair', 'Since', 'Profit']
df_statuses = DataFrame.from_records(trades_list, columns=columns)
df_statuses = df_statuses.set_index(columns[0])
message = tabulate(df_statuses, headers='keys', tablefmt='simple')
message = "<pre>{}</pre>".format(message)
send_msg(message, parse_mode=ParseMode.HTML)
@authorized_only
def _profit(bot: Bot, update: Update) -> None:
"""
@@ -151,6 +222,8 @@ def _profit(bot: Bot, update: Update) -> None:
profits = []
durations = []
for trade in trades:
if not trade.open_rate:
continue
if trade.close_date:
durations.append((trade.close_date - trade.open_date).total_seconds())
if trade.close_profit:
@@ -158,9 +231,9 @@ def _profit(bot: Bot, update: Update) -> None:
else:
# Get current rate
current_rate = exchange.get_ticker(trade.pair)['bid']
profit = 100 * ((current_rate - trade.open_rate) / trade.open_rate)
profit = trade.calc_profit(current_rate)
profit_amounts.append((profit / 100) * trade.stake_amount)
profit_amounts.append(profit * trade.stake_amount)
profits.append(profit)
best_pair = Trade.session.query(Trade.pair, func.sum(Trade.close_profit).label('profit_sum')) \
@@ -175,7 +248,7 @@ def _profit(bot: Bot, update: Update) -> None:
bp_pair, bp_rate = best_pair
markdown_msg = """
*ROI:* `{profit_btc:.2f} ({profit:.2f}%)`
*ROI:* `{profit_btc:.8f} ({profit:.2f}%)`
*Trade Count:* `{trade_count}`
*First Trade opened:* `{first_trade_date}`
*Latest Trade opened:* `{latest_trade_date}`
@@ -183,17 +256,41 @@ def _profit(bot: Bot, update: Update) -> None:
*Best Performing:* `{best_pair}: {best_rate:.2f}%`
""".format(
profit_btc=round(sum(profit_amounts), 8),
profit=round(sum(profits), 2),
profit=round(sum(profits) * 100, 2),
trade_count=len(trades),
first_trade_date=arrow.get(trades[0].open_date).humanize(),
latest_trade_date=arrow.get(trades[-1].open_date).humanize(),
avg_duration=str(timedelta(seconds=sum(durations) / float(len(durations)))).split('.')[0],
best_pair=bp_pair,
best_rate=round(bp_rate, 2),
best_rate=round(bp_rate * 100, 2),
)
send_msg(markdown_msg, bot=bot)
@authorized_only
def _balance(bot: Bot, update: Update) -> None:
"""
Handler for /balance
Returns current account balance per crypto
"""
output = ''
balances = [
c for c in exchange.get_balances()
if c['Balance'] or c['Available'] or c['Pending']
]
if not balances:
output = '`All balances are zero.`'
for currency in balances:
output += """*Currency*: {Currency}
*Available*: {Available}
*Balance*: {Balance}
*Pending*: {Pending}
""".format(**currency)
send_msg(output)
@authorized_only
def _start(bot: Bot, update: Update) -> None:
"""
@@ -238,38 +335,29 @@ def _forcesell(bot: Bot, update: Update) -> None:
send_msg('`trader is not running`', bot=bot)
return
try:
trade_id = int(update.message.text
.replace('/forcesell', '')
.strip())
# Query for trade
trade = Trade.query.filter(and_(
Trade.id == trade_id,
Trade.is_open.is_(True)
)).first()
if not trade:
send_msg('There is no open trade with ID: `{}`'.format(trade_id))
return
# Get current rate
current_rate = exchange.get_ticker(trade.pair)['bid']
# Get available balance
currency = trade.pair.split('_')[1]
balance = exchange.get_balance(currency)
# Execute sell
profit = trade.exec_sell_order(current_rate, balance)
message = '*{}:* Selling [{}]({}) at rate `{:f} (profit: {}%)`'.format(
trade.exchange,
trade.pair.replace('_', '/'),
exchange.get_pair_detail_url(trade.pair),
trade.close_rate,
round(profit, 2)
)
logger.info(message)
send_msg(message)
trade_id = update.message.text.replace('/forcesell', '').strip()
if trade_id == 'all':
# Execute sell for all open orders
for trade in Trade.query.filter(Trade.is_open.is_(True)).all():
# Get current rate
current_rate = exchange.get_ticker(trade.pair)['bid']
from freqtrade.main import execute_sell
execute_sell(trade, current_rate)
return
except ValueError:
send_msg('Invalid argument. Usage: `/forcesell <trade_id>`')
# Query for trade
trade = Trade.query.filter(and_(
Trade.id == trade_id,
Trade.is_open.is_(True)
)).first()
if not trade:
send_msg('Invalid argument. See `/help` to view usage')
logger.warning('/forcesell: Invalid argument received')
return
# Get current rate
current_rate = exchange.get_ticker(trade.pair)['bid']
from freqtrade.main import execute_sell
execute_sell(trade, current_rate)
@authorized_only
@@ -291,13 +379,37 @@ def _performance(bot: Bot, update: Update) -> None:
.order_by(text('profit_sum DESC')) \
.all()
stats = '\n'.join('{index}. <code>{pair}\t{profit:.2f}%</code>'.format(
stats = '\n'.join('{index}.\t<code>{pair}\t{profit:.2f}%</code>'.format(
index=i + 1,
pair=pair,
profit=round(rate, 2)
profit=round(rate * 100, 2)
) for i, (pair, rate) in enumerate(pair_rates))
message = '<b>Performance:</b>\n{}\n'.format(stats)
message = '<b>Performance:</b>\n{}'.format(stats)
logger.debug(message)
send_msg(message, parse_mode=ParseMode.HTML)
@authorized_only
def _count(bot: Bot, update: Update) -> None:
"""
Handler for /count.
Returns the number of trades running
:param bot: telegram bot
:param update: message update
:return: None
"""
if get_state() != State.RUNNING:
send_msg('`trader is not running`', bot=bot)
return
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
message = tabulate({
'current': [len(trades)],
'max': [_CONF['max_open_trades']]
}, headers=['current', 'max'], tablefmt='simple')
message = "<pre>{}</pre>".format(message)
logger.debug(message)
send_msg(message, parse_mode=ParseMode.HTML)
@@ -314,15 +426,43 @@ def _help(bot: Bot, update: Update) -> None:
message = """
*/start:* `Starts the trader`
*/stop:* `Stops the trader`
*/status:* `Lists all open trades`
*/status [table]:* `Lists all open trades`
*table :* `will display trades in a table`
*/profit:* `Lists cumulative profit from all finished trades`
*/forcesell <trade_id>:* `Instantly sells the given trade, regardless of profit`
*/forcesell <trade_id>|all:* `Instantly sells the given trade or all trades, regardless of profit`
*/performance:* `Show performance of each finished trade grouped by pair`
*/count:* `Show number of trades running compared to allowed number of trades`
*/balance:* `Show account balance per currency`
*/help:* `This help message`
*/version:* `Show version`
"""
send_msg(message, bot=bot)
@authorized_only
def _version(bot: Bot, update: Update) -> None:
"""
Handler for /version.
Show version information
:param bot: telegram bot
:param update: message update
:return: None
"""
send_msg('*Version:* `{}`'.format(__version__), bot=bot)
def shorten_date(date):
"""
Trim the date so it fits on small screens
"""
new_date = re.sub('seconds?', 'sec', date)
new_date = re.sub('minutes?', 'min', new_date)
new_date = re.sub('hours?', 'h', new_date)
new_date = re.sub('days?', 'd', new_date)
new_date = re.sub('^an?', '1', new_date)
return new_date
def send_msg(msg: str, bot: Bot = None, parse_mode: ParseMode = ParseMode.MARKDOWN) -> None:
"""
Send given markdown message
@@ -331,18 +471,17 @@ def send_msg(msg: str, bot: Bot = None, parse_mode: ParseMode = ParseMode.MARKDO
:param parse_mode: telegram parse mode
:return: None
"""
if _CONF['telegram'].get('enabled', False):
try:
bot = bot or _updater.bot
try:
bot.send_message(_CONF['telegram']['chat_id'], msg, parse_mode=parse_mode)
except NetworkError as error:
# Sometimes the telegram server resets the current connection,
# if this is the case we send the message again.
logger.warning(
'Got Telegram NetworkError: %s! Trying one more time.',
error.message
)
bot.send_message(_CONF['telegram']['chat_id'], msg, parse_mode=parse_mode)
except Exception:
logger.exception('Exception occurred within Telegram API')
if not is_enabled():
return
bot = bot or _UPDATER.bot
try:
bot.send_message(_CONF['telegram']['chat_id'], msg, parse_mode=parse_mode)
except NetworkError as error:
# Sometimes the telegram server resets the current connection,
# if this is the case we send the message again.
logger.warning(
'Got Telegram NetworkError: %s! Trying one more time.',
error.message
)
bot.send_message(_CONF['telegram']['chat_id'], msg, parse_mode=parse_mode)

149
freqtrade/tests/conftest.py Normal file
View File

@@ -0,0 +1,149 @@
# pragma pylint: disable=missing-docstring
import json
from datetime import datetime
from unittest.mock import MagicMock
import pytest
from jsonschema import validate
from telegram import Message, Chat, Update
from freqtrade.misc import CONF_SCHEMA
@pytest.fixture(scope="module")
def default_conf():
""" Returns validated configuration suitable for most tests """
configuration = {
"max_open_trades": 1,
"stake_currency": "BTC",
"stake_amount": 0.05,
"dry_run": True,
"minimal_roi": {
"40": 0.0,
"30": 0.01,
"20": 0.02,
"0": 0.04
},
"stoploss": -0.05,
"bid_strategy": {
"ask_last_balance": 0.0
},
"exchange": {
"name": "bittrex",
"enabled": True,
"key": "key",
"secret": "secret",
"pair_whitelist": [
"BTC_ETH",
"BTC_TKN",
"BTC_TRST",
"BTC_SWT",
"BTC_BCC"
]
},
"telegram": {
"enabled": True,
"token": "token",
"chat_id": "0"
},
"initial_state": "running"
}
validate(configuration, CONF_SCHEMA)
return configuration
@pytest.fixture(scope="module")
def backtest_conf():
return {
"minimal_roi": {
"40": 0.0,
"30": 0.01,
"20": 0.02,
"0": 0.04
},
"stoploss": -0.05
}
@pytest.fixture(scope="module")
def backdata():
result = {}
for pair in ['btc-neo', 'btc-eth', 'btc-omg', 'btc-edg', 'btc-pay',
'btc-pivx', 'btc-qtum', 'btc-mtl', 'btc-etc', 'btc-ltc']:
with open('freqtrade/tests/testdata/' + pair + '.json') as data_file:
result[pair] = json.load(data_file)
return result
@pytest.fixture
def update():
_update = Update(0)
_update.message = Message(0, 0, datetime.utcnow(), Chat(0, 0))
return _update
@pytest.fixture
def ticker():
return MagicMock(return_value={
'bid': 0.07256061,
'ask': 0.072661,
'last': 0.07256061,
})
@pytest.fixture
def health():
return MagicMock(return_value=[{
'Currency': 'BTC',
'IsActive': True,
'LastChecked': '2017-11-13T20:15:00.00',
'Notice': None
}, {
'Currency': 'ETH',
'IsActive': True,
'LastChecked': '2017-11-13T20:15:00.00',
'Notice': None
}, {
'Currency': 'TRST',
'IsActive': True,
'LastChecked': '2017-11-13T20:15:00.00',
'Notice': None
}, {
'Currency': 'SWT',
'IsActive': True,
'LastChecked': '2017-11-13T20:15:00.00',
'Notice': None
}, {
'Currency': 'BCC',
'IsActive': False,
'LastChecked': '2017-11-13T20:15:00.00',
'Notice': None
}])
@pytest.fixture
def limit_buy_order():
return {
'id': 'mocked_limit_buy',
'type': 'LIMIT_BUY',
'pair': 'mocked',
'opened': datetime.utcnow(),
'rate': 0.07256061,
'amount': 206.43811673387373,
'remaining': 0.0,
'closed': datetime.utcnow(),
}
@pytest.fixture
def limit_sell_order():
return {
'id': 'mocked_limit_sell',
'type': 'LIMIT_SELL',
'pair': 'mocked',
'opened': datetime.utcnow(),
'rate': 0.0802134,
'amount': 206.43811673387373,
'remaining': 0.0,
'closed': datetime.utcnow(),
}

View File

@@ -1,47 +1,39 @@
# pragma pylint: disable=missing-docstring
from datetime import datetime
import json
import pytest
import arrow
from pandas import DataFrame
from freqtrade.analyze import parse_ticker_dataframe, populate_buy_trend, populate_indicators, \
get_buy_signal
RESULT_BITTREX = {
'success': True,
'message': '',
'result': [
{'O': 0.00065311, 'H': 0.00065311, 'L': 0.00065311, 'C': 0.00065311, 'V': 22.17210568, 'T': '2017-08-30T10:40:00', 'BV': 0.01448082},
{'O': 0.00066194, 'H': 0.00066195, 'L': 0.00066194, 'C': 0.00066195, 'V': 33.4727437, 'T': '2017-08-30T10:34:00', 'BV': 0.02215696},
{'O': 0.00065311, 'H': 0.00065311, 'L': 0.00065311, 'C': 0.00065311, 'V': 53.85127609, 'T': '2017-08-30T10:37:00', 'BV': 0.0351708},
{'O': 0.00066194, 'H': 0.00066194, 'L': 0.00065311, 'C': 0.00065311, 'V': 46.29210665, 'T': '2017-08-30T10:42:00', 'BV': 0.03063118},
]
}
@pytest.fixture
def result():
return parse_ticker_dataframe(RESULT_BITTREX['result'], arrow.get('2017-08-30T10:00:00'))
with open('freqtrade/tests/testdata/btc-eth.json') as data_file:
return parse_ticker_dataframe(json.load(data_file))
def test_dataframe_has_correct_columns(result):
def test_dataframe_correct_columns(result):
assert result.columns.tolist() == \
['close', 'high', 'low', 'open', 'date', 'volume']
['close', 'high', 'low', 'open', 'date', 'volume']
def test_dataframe_correct_length(result):
assert len(result.index) == 5751
def test_orders_by_date(result):
assert result['date'].tolist() == \
['2017-08-30T10:34:00',
'2017-08-30T10:37:00',
'2017-08-30T10:40:00',
'2017-08-30T10:42:00']
def test_populates_buy_trend(result):
dataframe = populate_buy_trend(populate_indicators(result))
assert 'buy' in dataframe.columns
assert 'buy_price' in dataframe.columns
def test_returns_latest_buy_signal(mocker):
buydf = DataFrame([{'buy': 1, 'date': arrow.utcnow()}])
buydf = DataFrame([{'buy': 1, 'date': datetime.today()}])
mocker.patch('freqtrade.analyze.analyze_ticker', return_value=buydf)
assert get_buy_signal('BTC-ETH')
buydf = DataFrame([{'buy': 0, 'date': arrow.utcnow()}])
buydf = DataFrame([{'buy': 0, 'date': datetime.today()}])
mocker.patch('freqtrade.analyze.analyze_ticker', return_value=buydf)
assert not get_buy_signal('BTC-ETH')

View File

@@ -1,5 +1,4 @@
# pragma pylint: disable=missing-docstring
import json
import logging
import os
@@ -7,71 +6,60 @@ import pytest
import arrow
from pandas import DataFrame
from freqtrade import exchange
from freqtrade.analyze import analyze_ticker
from freqtrade.exchange import Bittrex
from freqtrade.main import should_sell
from freqtrade.persistence import Trade
logging.disable(logging.DEBUG) # disable debug logs that slow backtesting a lot
logging.disable(logging.DEBUG) # disable debug logs that slow backtesting a lot
def print_results(results):
print('Made {} buys. Average profit {:.2f}%. Total profit was {:.3f}. Average duration {:.1f} mins.'.format(
len(results.index),
results.profit.mean() * 100.0,
results.profit.sum(),
results.duration.mean() * 5
))
@pytest.fixture
def pairs():
return ['btc-neo', 'btc-eth', 'btc-omg', 'btc-edg', 'btc-pay',
'btc-pivx', 'btc-qtum', 'btc-mtl', 'btc-etc', 'btc-ltc']
def format_results(results):
return 'Made {} buys. Average profit {:.2f}%. Total profit was {:.3f}. Average duration {:.1f} mins.'.format(
len(results.index), results.profit.mean() * 100.0, results.profit.sum(), results.duration.mean() * 5)
@pytest.fixture
def conf():
return {
"minimal_roi": {
"50": 0.0,
"40": 0.01,
"30": 0.02,
"0": 0.045
},
"stoploss": -0.40
}
def print_pair_results(pair, results):
print('For currency {}:'.format(pair))
print(format_results(results[results.currency == pair]))
def backtest(backtest_conf, backdata, mocker):
trades = []
exchange._API = Bittrex({'key': '', 'secret': ''})
mocked_history = mocker.patch('freqtrade.analyze.get_ticker_history')
mocker.patch.dict('freqtrade.main._CONF', backtest_conf)
mocker.patch('arrow.utcnow', return_value=arrow.get('2017-08-20T14:50:00'))
for pair, pair_data in backdata.items():
mocked_history.return_value = pair_data
ticker = analyze_ticker(pair)[['close', 'date', 'buy']].copy()
# for each buy point
for row in ticker[ticker.buy == 1].itertuples(index=True):
trade = Trade(
open_rate=row.close,
open_date=row.date,
amount=1,
fee=exchange.get_fee() * 2
)
# calculate win/lose forwards from buy point
for row2 in ticker[row.Index:].itertuples(index=True):
if should_sell(trade, row2.close, row2.date):
current_profit = trade.calc_profit(row2.close)
trades.append((pair, current_profit, row2.Index - row.Index))
break
labels = ['currency', 'profit', 'duration']
results = DataFrame.from_records(trades, columns=labels)
return results
@pytest.mark.skipif(not os.environ.get('BACKTEST', False), reason="BACKTEST not set")
def test_backtest(conf, pairs, mocker):
trades = []
mocker.patch.dict('freqtrade.main._CONF', conf)
for pair in pairs:
with open('freqtrade/tests/testdata/'+pair+'.json') as data_file:
data = json.load(data_file)
mocker.patch('freqtrade.analyze.get_ticker_history', return_value=data)
mocker.patch('arrow.utcnow', return_value=arrow.get('2017-08-20T14:50:00'))
ticker = analyze_ticker(pair)
# for each buy point
for index, row in ticker[ticker.buy == 1].iterrows():
trade = Trade(
open_rate=row['close'],
open_date=arrow.get(row['date']).datetime,
amount=1,
)
# calculate win/lose forwards from buy point
for index2, row2 in ticker[index:].iterrows():
if should_sell(trade, row2['close'], arrow.get(row2['date']).datetime):
current_profit = (row2['close'] - trade.open_rate) / trade.open_rate
trades.append((pair, current_profit, index2 - index))
break
labels = ['currency', 'profit', 'duration']
results = DataFrame.from_records(trades, columns=labels)
def test_backtest(backtest_conf, backdata, mocker, report=True):
results = backtest(backtest_conf, backdata, mocker)
print('====================== BACKTESTING REPORT ================================')
for pair in pairs:
print('For currency {}:'.format(pair))
print_results(results[results.currency == pair])
for pair in backdata:
print_pair_results(pair, results)
print('TOTAL OVER ALL TRADES:')
print_results(results)
print(format_results(results))

View File

@@ -0,0 +1,36 @@
# pragma pylint: disable=missing-docstring
from unittest.mock import MagicMock
import pytest
from freqtrade.exchange import validate_pairs
def test_validate_pairs(default_conf, mocker):
api_mock = MagicMock()
api_mock.get_markets = MagicMock(return_value=[
'BTC_ETH', 'BTC_TKN', 'BTC_TRST', 'BTC_SWT', 'BTC_BCC',
])
mocker.patch('freqtrade.exchange._API', api_mock)
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
validate_pairs(default_conf['exchange']['pair_whitelist'])
def test_validate_pairs_not_available(default_conf, mocker):
api_mock = MagicMock()
api_mock.get_markets = MagicMock(return_value=[])
mocker.patch('freqtrade.exchange._API', api_mock)
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
with pytest.raises(RuntimeError, match=r'not available'):
validate_pairs(default_conf['exchange']['pair_whitelist'])
def test_validate_pairs_not_compatible(default_conf, mocker):
api_mock = MagicMock()
api_mock.get_markets = MagicMock(return_value=['BTC_ETH', 'BTC_TKN', 'BTC_TRST', 'BTC_SWT'])
default_conf['stake_currency'] = 'ETH'
mocker.patch('freqtrade.exchange._API', api_mock)
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
with pytest.raises(RuntimeError, match=r'not compatible'):
validate_pairs(default_conf['exchange']['pair_whitelist'])

View File

@@ -1,112 +1,58 @@
# pragma pylint: disable=missing-docstring
import json
import logging
import os
from functools import reduce
from math import exp
from operator import itemgetter
import pytest
import arrow
from hyperopt import fmin, tpe, hp, Trials, STATUS_OK
from pandas import DataFrame
from hyperopt import fmin, tpe, hp
from freqtrade.tests.test_backtesting import backtest, format_results
from freqtrade.vendor.qtpylib.indicators import crossed_above
from freqtrade.analyze import analyze_ticker
from freqtrade.main import should_sell
from freqtrade.persistence import Trade
logging.disable(logging.DEBUG) # disable debug logs that slow backtesting a lot
logging.disable(logging.DEBUG) # disable debug logs that slow backtesting a lot
def print_results(results):
print('Made {} buys. Average profit {:.2f}%. Total profit was {:.3f}. Average duration {:.1f} mins.'.format(
len(results.index),
results.profit.mean() * 100.0,
results.profit.sum(),
results.duration.mean() * 5
))
@pytest.fixture
def pairs():
return ['btc-neo', 'btc-eth', 'btc-omg', 'btc-edg', 'btc-pay',
'btc-pivx', 'btc-qtum', 'btc-mtl', 'btc-etc', 'btc-ltc']
@pytest.fixture
def conf():
return {
"minimal_roi": {
"40": 0.0,
"30": 0.01,
"20": 0.02,
"0": 0.04
},
"stoploss": -0.05
}
def backtest(conf, pairs, mocker, buy_strategy):
trades = []
mocker.patch.dict('freqtrade.main._CONF', conf)
for pair in pairs:
with open('freqtrade/tests/testdata/'+pair+'.json') as data_file:
data = json.load(data_file)
mocker.patch('freqtrade.analyze.get_ticker_history', return_value=data)
mocker.patch('arrow.utcnow', return_value=arrow.get('2017-08-20T14:50:00'))
mocker.patch('freqtrade.analyze.populate_buy_trend', side_effect=buy_strategy)
ticker = analyze_ticker(pair)
# for each buy point
for index, row in ticker[ticker.buy == 1].iterrows():
trade = Trade(
open_rate=row['close'],
open_date=arrow.get(row['date']).datetime,
amount=1,
)
# calculate win/lose forwards from buy point
for index2, row2 in ticker[index:].iterrows():
if should_sell(trade, row2['close'], arrow.get(row2['date']).datetime):
current_profit = (row2['close'] - trade.open_rate) / trade.open_rate
trades.append((pair, current_profit, index2 - index))
break
labels = ['currency', 'profit', 'duration']
results = DataFrame.from_records(trades, columns=labels)
print_results(results)
# set the value below to suit your number concurrent trades so its realistic to 20days of data
TARGET_TRADES = 1200
if results.profit.sum() == 0 or results.profit.mean() == 0:
return 49999999999 # avoid division by zero, return huge value to discard result
return abs(len(results.index) - 1200.1) / (results.profit.sum() ** 2) * results.duration.mean() # the smaller the better
# set TARGET_TRADES to suit your number concurrent trades so its realistic to 20days of data
TARGET_TRADES = 1300
TOTAL_TRIES = 4
current_tries = 0
def buy_strategy_generator(params):
print(params)
def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
conditions = []
# GUARDS AND TRENDS
if params['below_sma']['enabled']:
conditions.append(dataframe['close'] < dataframe['sma'])
if params['over_sma']['enabled']:
conditions.append(dataframe['close'] > dataframe['sma'])
if params['uptrend_long_ema']['enabled']:
conditions.append(dataframe['ema50'] > dataframe['ema100'])
if params['uptrend_short_ema']['enabled']:
conditions.append(dataframe['ema5'] > dataframe['ema10'])
if params['mfi']['enabled']:
conditions.append(dataframe['mfi'] < params['mfi']['value'])
if params['fastd']['enabled']:
conditions.append(dataframe['fastd'] < params['fastd']['value'])
if params['adx']['enabled']:
conditions.append(dataframe['adx'] > params['adx']['value'])
if params['cci']['enabled']:
conditions.append(dataframe['cci'] < params['cci']['value'])
if params['rsi']['enabled']:
conditions.append(dataframe['rsi'] < params['rsi']['value'])
if params['over_sar']['enabled']:
conditions.append(dataframe['close'] > dataframe['sar'])
if params['green_candle']['enabled']:
conditions.append(dataframe['close'] > dataframe['open'])
if params['uptrend_sma']['enabled']:
prevsma = dataframe['sma'].shift(1)
conditions.append(dataframe['sma'] > prevsma)
prev_fastd = dataframe['fastd'].shift(1)
# TRIGGERS
triggers = {
'lower_bb': dataframe['tema'] <= dataframe['blower'],
'faststoch10': (dataframe['fastd'] >= 10) & (prev_fastd < 10),
'faststoch10': (crossed_above(dataframe['fastd'], 10.0)),
'ao_cross_zero': (crossed_above(dataframe['ao'], 0.0)),
'ema5_cross_ema10': (crossed_above(dataframe['ema5'], dataframe['ema10'])),
'macd_cross_signal': (crossed_above(dataframe['macd'], dataframe['macdsignal'])),
'sar_reversal': (crossed_above(dataframe['close'], dataframe['sar'])),
'stochf_cross': (crossed_above(dataframe['fastk'], dataframe['fastd'])),
'ht_sine': (crossed_above(dataframe['htleadsine'], dataframe['htsine'])),
}
conditions.append(triggers.get(params['trigger']['type']))
@@ -118,34 +64,56 @@ def buy_strategy_generator(params):
return dataframe
return populate_buy_trend
@pytest.mark.skipif(not os.environ.get('BACKTEST', False), reason="BACKTEST not set")
def test_hyperopt(conf, pairs, mocker):
def test_hyperopt(backtest_conf, backdata, mocker):
mocked_buy_trend = mocker.patch('freqtrade.analyze.populate_buy_trend')
def optimizer(params):
return backtest(conf, pairs, mocker, buy_strategy_generator(params))
mocked_buy_trend.side_effect = buy_strategy_generator(params)
results = backtest(backtest_conf, backdata, mocker)
result = format_results(results)
total_profit = results.profit.sum() * 1000
trade_count = len(results.index)
trade_loss = 1 - 0.4 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.2)
profit_loss = max(0, 1 - total_profit / 15000) # max profit 15000
global current_tries
current_tries += 1
print('{}/{}: {}'.format(current_tries, TOTAL_TRIES, result))
return {
'loss': trade_loss + profit_loss,
'status': STATUS_OK,
'result': result
}
space = {
'mfi': hp.choice('mfi', [
{'enabled': False},
{'enabled': True, 'value': hp.uniform('mfi-value', 2, 40)}
{'enabled': True, 'value': hp.quniform('mfi-value', 5, 25, 1)}
]),
'fastd': hp.choice('fastd', [
{'enabled': False},
{'enabled': True, 'value': hp.uniform('fastd-value', 2, 40)}
{'enabled': True, 'value': hp.quniform('fastd-value', 10, 50, 1)}
]),
'adx': hp.choice('adx', [
{'enabled': False},
{'enabled': True, 'value': hp.uniform('adx-value', 2, 40)}
{'enabled': True, 'value': hp.quniform('adx-value', 15, 50, 1)}
]),
'cci': hp.choice('cci', [
'rsi': hp.choice('rsi', [
{'enabled': False},
{'enabled': True, 'value': hp.uniform('cci-value', -200, -100)}
{'enabled': True, 'value': hp.quniform('rsi-value', 20, 40, 1)}
]),
'below_sma': hp.choice('below_sma', [
'uptrend_long_ema': hp.choice('uptrend_long_ema', [
{'enabled': False},
{'enabled': True}
]),
'over_sma': hp.choice('over_sma', [
'uptrend_short_ema': hp.choice('uptrend_short_ema', [
{'enabled': False},
{'enabled': True}
]),
@@ -153,14 +121,28 @@ def test_hyperopt(conf, pairs, mocker):
{'enabled': False},
{'enabled': True}
]),
'green_candle': hp.choice('green_candle', [
{'enabled': False},
{'enabled': True}
]),
'uptrend_sma': hp.choice('uptrend_sma', [
{'enabled': False},
{'enabled': True}
]),
'trigger': hp.choice('trigger', [
{'type': 'lower_bb'},
{'type': 'faststoch10'}
{'type': 'faststoch10'},
{'type': 'ao_cross_zero'},
{'type': 'ema5_cross_ema10'},
{'type': 'macd_cross_signal'},
{'type': 'sar_reversal'},
{'type': 'stochf_cross'},
{'type': 'ht_sine'},
]),
}
print('Best parameters {}'.format(fmin(fn=optimizer, space=space, algo=tpe.suggest, max_evals=40)))
trials = Trials()
best = fmin(fn=optimizer, space=space, algo=tpe.suggest, max_evals=TOTAL_TRIES, trials=trials)
print('\n\n\n\n==================== HYPEROPT BACKTESTING REPORT ==============================')
print('Best parameters {}'.format(best))
newlist = sorted(trials.results, key=itemgetter('loss'))
print('Result: {}'.format(newlist[0]['result']))

View File

@@ -1,89 +1,167 @@
# pragma pylint: disable=missing-docstring
import copy
from unittest.mock import MagicMock, call
from unittest.mock import MagicMock
import pytest
from jsonschema import validate
import requests
from sqlalchemy import create_engine
from freqtrade.exchange import Exchanges
from freqtrade.main import create_trade, handle_trade, close_trade_if_fulfilled, init, \
get_target_bid
from freqtrade.misc import CONF_SCHEMA
get_target_bid, _process
from freqtrade.misc import get_state, State
from freqtrade.persistence import Trade
@pytest.fixture
def conf():
configuration = {
"max_open_trades": 3,
"stake_currency": "BTC",
"stake_amount": 0.05,
"dry_run": True,
"minimal_roi": {
"2880": 0.005,
"720": 0.01,
"0": 0.02
},
"bid_strategy": {
"ask_last_balance": 0.0
},
"exchange": {
"name": "bittrex",
"enabled": True,
"key": "key",
"secret": "secret",
"pair_whitelist": [
"BTC_ETH",
"BTC_TKN",
"BTC_TRST",
"BTC_SWT",
]
},
"telegram": {
"enabled": True,
"token": "token",
"chat_id": "chat_id"
}
}
validate(configuration, CONF_SCHEMA)
return configuration
def test_process_trade_creation(default_conf, ticker, health, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch.multiple('freqtrade.main.telegram', init=MagicMock(), send_msg=MagicMock())
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_wallet_health=health,
buy=MagicMock(return_value='mocked_limit_buy'))
init(default_conf, create_engine('sqlite://'))
def test_create_trade(conf, mocker):
mocker.patch.dict('freqtrade.main._CONF', conf)
buy_signal = mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
assert len(trades) == 0
result = _process()
assert result is True
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
assert len(trades) == 1
trade = trades[0]
assert trade is not None
assert trade.stake_amount == default_conf['stake_amount']
assert trade.is_open
assert trade.open_date is not None
assert trade.exchange == Exchanges.BITTREX.name
assert trade.open_rate == 0.072661
assert trade.amount == 0.6864067381401302
def test_process_exchange_failures(default_conf, ticker, health, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch.multiple('freqtrade.main.telegram', init=MagicMock(), send_msg=MagicMock())
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
sleep_mock = mocker.patch('time.sleep', side_effect=lambda _: None)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_wallet_health=health,
buy=MagicMock(side_effect=requests.exceptions.RequestException))
init(default_conf, create_engine('sqlite://'))
result = _process()
assert result is False
assert sleep_mock.has_calls()
def test_process_runtime_error(default_conf, ticker, health, mocker):
msg_mock = MagicMock()
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch.multiple('freqtrade.main.telegram', init=MagicMock(), send_msg=msg_mock)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_wallet_health=health,
buy=MagicMock(side_effect=RuntimeError))
init(default_conf, create_engine('sqlite://'))
assert get_state() == State.RUNNING
result = _process()
assert result is False
assert get_state() == State.STOPPED
assert 'RuntimeError' in msg_mock.call_args_list[-1][0][0]
def test_process_trade_handling(default_conf, ticker, limit_buy_order, health, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch.multiple('freqtrade.main.telegram', init=MagicMock(), send_msg=MagicMock())
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_wallet_health=health,
buy=MagicMock(return_value='mocked_limit_buy'),
get_order=MagicMock(return_value=limit_buy_order))
init(default_conf, create_engine('sqlite://'))
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
assert len(trades) == 0
result = _process()
assert result is True
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
assert len(trades) == 1
result = _process()
assert result is False
def test_create_trade(default_conf, ticker, limit_buy_order, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
mocker.patch.multiple('freqtrade.main.telegram', init=MagicMock(), send_msg=MagicMock())
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=MagicMock(return_value={
'bid': 0.07256061,
'ask': 0.072661,
'last': 0.07256061
}),
buy=MagicMock(return_value='mocked_order_id'))
get_ticker=ticker,
buy=MagicMock(return_value='mocked_limit_buy'))
# Save state of current whitelist
whitelist = copy.deepcopy(conf['exchange']['pair_whitelist'])
whitelist = copy.deepcopy(default_conf['exchange']['pair_whitelist'])
init(conf, 'sqlite://')
for pair in ['BTC_ETH', 'BTC_TKN', 'BTC_TRST', 'BTC_SWT']:
trade = create_trade(15.0)
Trade.session.add(trade)
Trade.session.flush()
assert trade is not None
assert trade.open_rate == 0.072661
assert trade.pair == pair
assert trade.exchange == Exchanges.BITTREX.name
assert trade.amount == 206.43811673387373
assert trade.stake_amount == 15.0
assert trade.is_open
assert trade.open_date is not None
assert whitelist == conf['exchange']['pair_whitelist']
init(default_conf, create_engine('sqlite://'))
trade = create_trade(15.0)
Trade.session.add(trade)
Trade.session.flush()
assert trade is not None
assert trade.stake_amount == 15.0
assert trade.is_open
assert trade.open_date is not None
assert trade.exchange == Exchanges.BITTREX.name
buy_signal.assert_has_calls(
[call('BTC_ETH'), call('BTC_TKN'), call('BTC_TRST'), call('BTC_SWT')]
)
# Simulate fulfilled LIMIT_BUY order for trade
trade.update(limit_buy_order)
def test_handle_trade(conf, mocker):
mocker.patch.dict('freqtrade.main._CONF', conf)
assert trade.open_rate == 0.07256061
assert trade.amount == 206.43811673387373
assert whitelist == default_conf['exchange']['pair_whitelist']
def test_create_trade_no_stake_amount(default_conf, ticker, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
mocker.patch.multiple('freqtrade.main.telegram', init=MagicMock(), send_msg=MagicMock())
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
buy=MagicMock(return_value='mocked_limit_buy'),
get_balance=MagicMock(return_value=default_conf['stake_amount'] * 0.5))
with pytest.raises(ValueError, match=r'.*stake amount.*'):
create_trade(default_conf['stake_amount'])
def test_create_trade_no_pairs(default_conf, ticker, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
mocker.patch.multiple('freqtrade.main.telegram', init=MagicMock(), send_msg=MagicMock())
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
buy=MagicMock(return_value='mocked_limit_buy'))
with pytest.raises(ValueError, match=r'.*No pair in whitelist.*'):
conf = copy.deepcopy(default_conf)
conf['exchange']['pair_whitelist'] = []
mocker.patch.dict('freqtrade.main._CONF', conf)
create_trade(default_conf['stake_amount'])
def test_handle_trade(default_conf, limit_buy_order, limit_sell_order, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
mocker.patch.multiple('freqtrade.main.telegram', init=MagicMock(), send_msg=MagicMock())
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
@@ -92,17 +170,45 @@ def test_handle_trade(conf, mocker):
'ask': 0.172661,
'last': 0.17256061
}),
buy=MagicMock(return_value='mocked_order_id'))
buy=MagicMock(return_value='mocked_limit_buy'),
sell=MagicMock(return_value='mocked_limit_sell'))
init(default_conf, create_engine('sqlite://'))
trade = create_trade(15.0)
trade.update(limit_buy_order)
Trade.session.add(trade)
Trade.session.flush()
trade = Trade.query.filter(Trade.is_open.is_(True)).first()
assert trade
handle_trade(trade)
assert trade.close_rate == 0.17256061
assert trade.close_profit == 137.4872490056564
assert trade.close_date is not None
assert trade.open_order_id == 'dry_run'
def test_close_trade(conf, mocker):
mocker.patch.dict('freqtrade.main._CONF', conf)
handle_trade(trade)
assert trade.open_order_id == 'mocked_limit_sell'
assert close_trade_if_fulfilled(trade) is False
# Simulate fulfilled LIMIT_SELL order for trade
trade.update(limit_sell_order)
assert trade.close_rate == 0.0802134
assert trade.close_profit == 0.10046755
assert trade.close_date is not None
def test_close_trade(default_conf, ticker, limit_buy_order, limit_sell_order, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
mocker.patch.multiple('freqtrade.main.telegram', init=MagicMock(), send_msg=MagicMock())
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
buy=MagicMock(return_value='mocked_limit_buy'))
# Create trade and sell it
init(default_conf, create_engine('sqlite://'))
trade = create_trade(15.0)
trade.update(limit_buy_order)
trade.update(limit_sell_order)
Trade.session.add(trade)
Trade.session.flush()
trade = Trade.query.filter(Trade.is_open.is_(True)).first()
assert trade
@@ -112,15 +218,20 @@ def test_close_trade(conf, mocker):
closed = close_trade_if_fulfilled(trade)
assert closed
assert not trade.is_open
with pytest.raises(ValueError, match=r'.*closed trade.*'):
handle_trade(trade)
def test_balance_fully_ask_side(mocker):
mocker.patch.dict('freqtrade.main._CONF', {'bid_strategy': {'ask_last_balance': 0.0}})
assert get_target_bid({'ask': 20, 'last': 10}) == 20
def test_balance_fully_last_side(mocker):
mocker.patch.dict('freqtrade.main._CONF', {'bid_strategy': {'ask_last_balance': 1.0}})
assert get_target_bid({'ask': 20, 'last': 10}) == 10
def test_balance_when_last_bigger_than_ask(mocker):
def test_balance_bigger_last_ask(mocker):
mocker.patch.dict('freqtrade.main._CONF', {'bid_strategy': {'ask_last_balance': 1.0}})
assert get_target_bid({'ask': 5, 'last': 10}) == 5

View File

@@ -0,0 +1,20 @@
# pragma pylint: disable=missing-docstring
import time
from freqtrade.misc import throttle
def test_throttle():
def func():
return 42
start = time.time()
result = throttle(func, 0.1)
end = time.time()
assert result == 42
assert end - start > 0.1
result = throttle(func, -1)
assert result == 42

View File

@@ -1,20 +1,66 @@
# pragma pylint: disable=missing-docstring
import pytest
from freqtrade.exchange import Exchanges
from freqtrade.persistence import Trade
def test_exec_sell_order(mocker):
api_mock = mocker.patch('freqtrade.main.exchange.sell', side_effect='mocked_order_id')
def test_update(limit_buy_order, limit_sell_order):
trade = Trade(
pair='BTC_ETH',
stake_amount=1.00,
open_rate=0.50,
amount=10.00,
fee=0.1,
exchange=Exchanges.BITTREX,
open_order_id='mocked'
)
profit = trade.exec_sell_order(1.00, 10.00)
api_mock.assert_called_once_with('BTC_ETH', 1.0, 10.0)
assert profit == 100.0
assert trade.close_rate == 1.0
assert trade.close_profit == profit
assert trade.open_order_id is None
assert trade.open_rate is None
assert trade.close_profit is None
assert trade.close_date is None
trade.open_order_id = 'something'
trade.update(limit_buy_order)
assert trade.open_order_id is None
assert trade.open_rate == 0.07256061
assert trade.close_profit is None
assert trade.close_date is None
trade.open_order_id = 'something'
trade.update(limit_sell_order)
assert trade.open_order_id is None
assert trade.open_rate == 0.07256061
assert trade.close_profit == 0.00546755
assert trade.close_date is not None
def test_update_open_order(limit_buy_order):
trade = Trade(
pair='BTC_ETH',
stake_amount=1.00,
fee=0.1,
exchange=Exchanges.BITTREX,
)
assert trade.open_order_id is None
assert trade.open_rate is None
assert trade.close_profit is None
assert trade.close_date is None
limit_buy_order['closed'] = False
trade.update(limit_buy_order)
assert trade.open_order_id is None
assert trade.open_rate is None
assert trade.close_profit is None
assert trade.close_date is None
def test_update_invalid_order(limit_buy_order):
trade = Trade(
pair='BTC_ETH',
stake_amount=1.00,
fee=0.1,
exchange=Exchanges.BITTREX,
)
limit_buy_order['type'] = 'invalid'
with pytest.raises(ValueError, match=r'Unknown order type'):
trade.update(limit_buy_order)

View File

@@ -1,76 +1,106 @@
# pragma pylint: disable=missing-docstring
# pragma pylint: disable=missing-docstring, too-many-arguments, too-many-ancestors
import re
from datetime import datetime
from random import randint
from unittest.mock import MagicMock
import pytest
from jsonschema import validate
from telegram import Bot, Update, Message, Chat
from sqlalchemy import create_engine
from telegram import Update, Message, Chat
from telegram.error import NetworkError
from freqtrade import __version__
from freqtrade.main import init, create_trade
from freqtrade.misc import update_state, State, get_state, CONF_SCHEMA
from freqtrade.misc import update_state, State, get_state
from freqtrade.persistence import Trade
from freqtrade.rpc.telegram import _status, _profit, _forcesell, _performance, _start, _stop
from freqtrade.rpc import telegram
from freqtrade.rpc.telegram import (
_status, _status_table, _profit, _forcesell, _performance, _count, _start, _stop, _balance,
authorized_only, _help, is_enabled, send_msg,
_version)
@pytest.fixture
def conf():
configuration = {
"max_open_trades": 3,
"stake_currency": "BTC",
"stake_amount": 0.05,
"dry_run": True,
"minimal_roi": {
"2880": 0.005,
"720": 0.01,
"0": 0.02
},
"bid_strategy": {
"ask_last_balance": 0.0
},
"exchange": {
"name": "bittrex",
"enabled": True,
"key": "key",
"secret": "secret",
"pair_whitelist": [
"BTC_ETH"
]
},
"telegram": {
"enabled": True,
"token": "token",
"chat_id": "0"
},
"initial_state": "running"
}
validate(configuration, CONF_SCHEMA)
return configuration
@pytest.fixture
def update():
_update = Update(0)
_update.message = Message(0, 0, datetime.utcnow(), Chat(0, 0))
return _update
def test_is_enabled(default_conf, mocker):
mocker.patch.dict('freqtrade.rpc.telegram._CONF', default_conf)
default_conf['telegram']['enabled'] = False
assert is_enabled() is False
class MagicBot(MagicMock, Bot):
pass
def test_init_disabled(default_conf, mocker):
mocker.patch.dict('freqtrade.rpc.telegram._CONF', default_conf)
default_conf['telegram']['enabled'] = False
telegram.init(default_conf)
def test_status_handle(conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', conf)
def test_authorized_only(default_conf, mocker):
mocker.patch.dict('freqtrade.rpc.telegram._CONF', default_conf)
chat = Chat(0, 0)
update = Update(randint(1, 100))
update.message = Message(randint(1, 100), 0, datetime.utcnow(), chat)
state = {'called': False}
@authorized_only
def dummy_handler(*args, **kwargs) -> None:
state['called'] = True
dummy_handler(MagicMock(), update)
assert state['called'] is True
def test_authorized_only_unauthorized(default_conf, mocker):
mocker.patch.dict('freqtrade.rpc.telegram._CONF', default_conf)
chat = Chat(0xdeadbeef, 0)
update = Update(randint(1, 100))
update.message = Message(randint(1, 100), 0, datetime.utcnow(), chat)
state = {'called': False}
@authorized_only
def dummy_handler(*args, **kwargs) -> None:
state['called'] = True
dummy_handler(MagicMock(), update)
assert state['called'] is False
def test_authorized_only_exception(default_conf, mocker):
mocker.patch.dict('freqtrade.rpc.telegram._CONF', default_conf)
update = Update(randint(1, 100))
update.message = Message(randint(1, 100), 0, datetime.utcnow(), Chat(0, 0))
@authorized_only
def dummy_handler(*args, **kwargs) -> None:
raise Exception('test')
dummy_handler(MagicMock(), update)
def test_status_handle(default_conf, update, ticker, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram', _CONF=conf, init=MagicMock(), send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=MagicMock(return_value={
'bid': 0.07256061,
'ask': 0.072661,
'last': 0.07256061
}),
buy=MagicMock(return_value='mocked_order_id'))
init(conf, 'sqlite://')
get_ticker=ticker)
init(default_conf, create_engine('sqlite://'))
update_state(State.STOPPED)
_status(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert 'trader is not running' in msg_mock.call_args_list[0][0][0]
msg_mock.reset_mock()
update_state(State.RUNNING)
_status(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert 'no active trade' in msg_mock.call_args_list[0][0][0]
msg_mock.reset_mock()
# Create some test data
trade = create_trade(15.0)
@@ -78,122 +108,435 @@ def test_status_handle(conf, update, mocker):
Trade.session.add(trade)
Trade.session.flush()
_status(bot=MagicBot(), update=update)
# Trigger status while we have a fulfilled order for the open trade
_status(bot=MagicMock(), update=update)
assert msg_mock.call_count == 2
assert '[BTC_ETH]' in msg_mock.call_args_list[-1][0][0]
def test_profit_handle(conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', conf)
def test_status_table_handle(default_conf, update, ticker, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram', _CONF=conf, init=MagicMock(), send_msg=msg_mock)
mocker.patch.multiple(
'freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=MagicMock(return_value={
'bid': 0.07256061,
'ask': 0.072661,
'last': 0.07256061
}),
get_ticker=ticker,
buy=MagicMock(return_value='mocked_order_id'))
init(conf, 'sqlite://')
init(default_conf, create_engine('sqlite://'))
update_state(State.STOPPED)
_status_table(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert 'trader is not running' in msg_mock.call_args_list[0][0][0]
msg_mock.reset_mock()
update_state(State.RUNNING)
_status_table(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert 'no active order' in msg_mock.call_args_list[0][0][0]
msg_mock.reset_mock()
# Create some test data
trade = create_trade(15.0)
assert trade
trade.close_rate = 0.07256061
trade.close_profit = 100.00
Trade.session.add(trade)
Trade.session.flush()
_status_table(bot=MagicMock(), update=update)
text = re.sub('</?pre>', '', msg_mock.call_args_list[-1][0][0])
line = text.split("\n")
fields = re.sub('[ ]+', ' ', line[2].strip()).split(' ')
assert int(fields[0]) == 1
assert fields[1] == 'BTC_ETH'
assert msg_mock.call_count == 2
def test_profit_handle(default_conf, update, ticker, limit_buy_order, limit_sell_order, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker)
init(default_conf, create_engine('sqlite://'))
_profit(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert 'no closed trade' in msg_mock.call_args_list[0][0][0]
msg_mock.reset_mock()
# Create some test data
trade = create_trade(15.0)
assert trade
# Simulate fulfilled LIMIT_BUY order for trade
trade.update(limit_buy_order)
_profit(bot=MagicMock(), update=update)
assert msg_mock.call_count == 2
assert 'no closed trade' in msg_mock.call_args_list[-1][0][0]
msg_mock.reset_mock()
# Simulate fulfilled LIMIT_SELL order for trade
trade.update(limit_sell_order)
trade.close_date = datetime.utcnow()
trade.open_order_id = None
trade.is_open = False
Trade.session.add(trade)
Trade.session.flush()
_profit(bot=MagicBot(), update=update)
assert msg_mock.call_count == 2
assert '(100.00%)' in msg_mock.call_args_list[-1][0][0]
_profit(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert '*ROI:* `1.50701325 (10.05%)`' in msg_mock.call_args_list[-1][0][0]
assert 'Best Performing:* `BTC_ETH: 10.05%`' in msg_mock.call_args_list[-1][0][0]
def test_forcesell_handle(conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', conf)
def test_forcesell_handle(default_conf, update, ticker, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram', _CONF=conf, init=MagicMock(), send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=MagicMock(return_value={
'bid': 0.07256061,
'ask': 0.072661,
'last': 0.07256061
}),
buy=MagicMock(return_value='mocked_order_id'))
init(conf, 'sqlite://')
get_ticker=ticker)
init(default_conf, create_engine('sqlite://'))
# Create some test data
trade = create_trade(15.0)
assert trade
Trade.session.add(trade)
Trade.session.flush()
update.message.text = '/forcesell 1'
_forcesell(bot=MagicBot(), update=update)
_forcesell(bot=MagicMock(), update=update)
assert msg_mock.call_count == 2
assert 'Selling [BTC/ETH]' in msg_mock.call_args_list[-1][0][0]
assert '0.072561' in msg_mock.call_args_list[-1][0][0]
assert '0.07256061 (profit: ~-0.64%)' in msg_mock.call_args_list[-1][0][0]
def test_performance_handle(conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', conf)
def test_forcesell_all_handle(default_conf, update, ticker, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram', _CONF=conf, init=MagicMock(), send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=MagicMock(return_value={
'bid': 0.07256061,
'ask': 0.072661,
'last': 0.07256061
}),
buy=MagicMock(return_value='mocked_order_id'))
init(conf, 'sqlite://')
get_ticker=ticker)
init(default_conf, create_engine('sqlite://'))
# Create some test data
for _ in range(4):
Trade.session.add(create_trade(15.0))
Trade.session.flush()
msg_mock.reset_mock()
update.message.text = '/forcesell all'
_forcesell(bot=MagicMock(), update=update)
assert msg_mock.call_count == 4
for args in msg_mock.call_args_list:
assert '0.07256061 (profit: ~-0.64%)' in args[0][0]
def test_forcesell_handle_invalid(default_conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock())
init(default_conf, create_engine('sqlite://'))
# Trader is not running
update_state(State.STOPPED)
update.message.text = '/forcesell 1'
_forcesell(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert 'not running' in msg_mock.call_args_list[0][0][0]
# No argument
msg_mock.reset_mock()
update_state(State.RUNNING)
update.message.text = '/forcesell'
_forcesell(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert 'Invalid argument' in msg_mock.call_args_list[0][0][0]
# Invalid argument
msg_mock.reset_mock()
update_state(State.RUNNING)
update.message.text = '/forcesell 123456'
_forcesell(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert 'Invalid argument.' in msg_mock.call_args_list[0][0][0]
def test_performance_handle(
default_conf, update, ticker, limit_buy_order, limit_sell_order, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker)
init(default_conf, create_engine('sqlite://'))
# Create some test data
trade = create_trade(15.0)
assert trade
trade.close_rate = 0.07256061
trade.close_profit = 100.00
# Simulate fulfilled LIMIT_BUY order for trade
trade.update(limit_buy_order)
# Simulate fulfilled LIMIT_SELL order for trade
trade.update(limit_sell_order)
trade.close_date = datetime.utcnow()
trade.open_order_id = None
trade.is_open = False
Trade.session.add(trade)
Trade.session.flush()
_performance(bot=MagicBot(), update=update)
_performance(bot=MagicMock(), update=update)
assert msg_mock.call_count == 2
assert 'Performance' in msg_mock.call_args_list[-1][0][0]
assert 'BTC_ETH 100.00%' in msg_mock.call_args_list[-1][0][0]
assert '<code>BTC_ETH\t10.05%</code>' in msg_mock.call_args_list[-1][0][0]
def test_start_handle(conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', conf)
def test_count_handle(default_conf, update, ticker, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram', _CONF=conf, init=MagicMock(), send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange', _CONF=conf, init=MagicMock())
init(conf, 'sqlite://')
mocker.patch.multiple(
'freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
buy=MagicMock(return_value='mocked_order_id'))
init(default_conf, create_engine('sqlite://'))
update_state(State.STOPPED)
_count(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert 'not running' in msg_mock.call_args_list[0][0][0]
msg_mock.reset_mock()
update_state(State.RUNNING)
# Create some test data
Trade.session.add(create_trade(15.0))
Trade.session.flush()
msg_mock.reset_mock()
_count(bot=MagicMock(), update=update)
msg = '<pre> current max\n--------- -----\n 1 {}</pre>'.format(
default_conf['max_open_trades']
)
assert msg in msg_mock.call_args_list[0][0][0]
def test_performance_handle_invalid(default_conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock())
init(default_conf, create_engine('sqlite://'))
# Trader is not running
update_state(State.STOPPED)
_performance(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert 'not running' in msg_mock.call_args_list[0][0][0]
def test_start_handle(default_conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
_CONF=default_conf,
init=MagicMock())
init(default_conf, create_engine('sqlite://'))
update_state(State.STOPPED)
assert get_state() == State.STOPPED
_start(bot=MagicBot(), update=update)
_start(bot=MagicMock(), update=update)
assert get_state() == State.RUNNING
assert msg_mock.call_count == 0
def test_stop_handle(conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', conf)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram', _CONF=conf, init=MagicMock(), send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange', _CONF=conf, init=MagicMock())
init(conf, 'sqlite://')
def test_start_handle_already_running(default_conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
_CONF=default_conf,
init=MagicMock())
init(default_conf, create_engine('sqlite://'))
update_state(State.RUNNING)
assert get_state() == State.RUNNING
_stop(bot=MagicBot(), update=update)
_start(bot=MagicMock(), update=update)
assert get_state() == State.RUNNING
assert msg_mock.call_count == 1
assert 'already running' in msg_mock.call_args_list[0][0][0]
def test_stop_handle(default_conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
_CONF=default_conf,
init=MagicMock())
init(default_conf, create_engine('sqlite://'))
update_state(State.RUNNING)
assert get_state() == State.RUNNING
_stop(bot=MagicMock(), update=update)
assert get_state() == State.STOPPED
assert msg_mock.call_count == 1
assert 'Stopping trader' in msg_mock.call_args_list[0][0][0]
def test_stop_handle_already_stopped(default_conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
_CONF=default_conf,
init=MagicMock())
init(default_conf, create_engine('sqlite://'))
update_state(State.STOPPED)
assert get_state() == State.STOPPED
_stop(bot=MagicMock(), update=update)
assert get_state() == State.STOPPED
assert msg_mock.call_count == 1
assert 'already stopped' in msg_mock.call_args_list[0][0][0]
def test_balance_handle(default_conf, update, mocker):
mock_balance = [{
'Currency': 'BTC',
'Balance': 10.0,
'Available': 12.0,
'Pending': 0.0,
'CryptoAddress': 'XXXX',
}, {
'Currency': 'ETH',
'Balance': 0.0,
'Available': 0.0,
'Pending': 0.0,
'CryptoAddress': 'XXXX',
}]
mocker.patch.dict('freqtrade.main._CONF', default_conf)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
get_balances=MagicMock(return_value=mock_balance))
_balance(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert '*Currency*: BTC' in msg_mock.call_args_list[0][0][0]
assert 'Balance' in msg_mock.call_args_list[0][0][0]
def test_help_handle(default_conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
_help(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert '*/help:* `This help message`' in msg_mock.call_args_list[0][0][0]
def test_version_handle(default_conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
_version(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert '*Version:* `{}`'.format(__version__) in msg_mock.call_args_list[0][0][0]
def test_send_msg(default_conf, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock())
bot = MagicMock()
send_msg('test', bot)
assert len(bot.method_calls) == 0
bot.reset_mock()
default_conf['telegram']['enabled'] = True
send_msg('test', bot)
assert len(bot.method_calls) == 1
def test_send_msg_network_error(default_conf, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock())
default_conf['telegram']['enabled'] = True
bot = MagicMock()
bot.send_message = MagicMock(side_effect=NetworkError('Oh snap'))
with pytest.raises(NetworkError, match=r'Oh snap'):
send_msg('test', bot)
# Bot should've tried to send it twice
assert len(bot.method_calls) == 2

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28
freqtrade/tests/testdata/download_backtest_data.py vendored Normal file → Executable file
View File

@@ -1,16 +1,24 @@
#!/usr/bin/env python3
"""This script generate json data from bittrex"""
import json
from os import path
from urllib.request import urlopen
from freqtrade import exchange
from freqtrade.exchange import Bittrex
CURRENCIES = ["ok", "neo", "dash", "etc", "eth", "snt"]
PAIRS = ['BTC-OK', 'BTC-NEO', 'BTC-DASH', 'BTC-ETC', 'BTC-ETH', 'BTC-SNT']
TICKER_INTERVAL = 1 # ticker interval in minutes (currently implemented: 1 and 5)
OUTPUT_DIR = path.dirname(path.realpath(__file__))
for cur in CURRENCIES:
url1 = 'https://bittrex.com/Api/v2.0/pub/market/GetTicks?marketName=BTC-'
url = url1+cur+'&tickInterval=fiveMin'
x = urlopen(url)
json_data = x.read()
json_str = str(json_data, 'utf-8')
with open('btc-'+cur+'.json', 'w') as file:
file.write(json_str)
# Init Bittrex exchange
exchange._API = Bittrex({'key': '', 'secret': ''})
for pair in PAIRS:
data = exchange.get_ticker_history(pair, TICKER_INTERVAL)
filename = path.join(OUTPUT_DIR, '{}-{}m.json'.format(
pair.lower(),
TICKER_INTERVAL,
))
with open(filename, 'w') as fp:
json.dump(data, fp)

0
freqtrade/vendor/__init__.py vendored Normal file
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0
freqtrade/vendor/qtpylib/__init__.py vendored Normal file
View File

625
freqtrade/vendor/qtpylib/indicators.py vendored Normal file
View File

@@ -0,0 +1,625 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# QTPyLib: Quantitative Trading Python Library
# https://github.com/ranaroussi/qtpylib
#
# Copyright 2016 Ran Aroussi
#
# Licensed under the GNU Lesser General Public License, v3.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.gnu.org/licenses/lgpl-3.0.en.html
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import numpy as np
import pandas as pd
import warnings
import sys
from datetime import datetime, timedelta
from pandas.core.base import PandasObject
# =============================================
# check min, python version
if sys.version_info < (3, 4):
raise SystemError("QTPyLib requires Python version >= 3.4")
# =============================================
warnings.simplefilter(action="ignore", category=RuntimeWarning)
# =============================================
def numpy_rolling_window(data, window):
shape = data.shape[:-1] + (data.shape[-1] - window + 1, window)
strides = data.strides + (data.strides[-1],)
return np.lib.stride_tricks.as_strided(data, shape=shape, strides=strides)
def numpy_rolling_series(func):
def func_wrapper(data, window, as_source=False):
series = data.values if isinstance(data, pd.Series) else data
new_series = np.empty(len(series)) * np.nan
calculated = func(series, window)
new_series[-len(calculated):] = calculated
if as_source and isinstance(data, pd.Series):
return pd.Series(index=data.index, data=new_series)
return new_series
return func_wrapper
@numpy_rolling_series
def numpy_rolling_mean(data, window, as_source=False):
return np.mean(numpy_rolling_window(data, window), -1)
@numpy_rolling_series
def numpy_rolling_std(data, window, as_source=False):
return np.std(numpy_rolling_window(data, window), -1)
# ---------------------------------------------
def session(df, start='17:00', end='16:00'):
""" remove previous globex day from df """
if len(df) == 0:
return df
# get start/end/now as decimals
int_start = list(map(int, start.split(':')))
int_start = (int_start[0] + int_start[1] - 1 / 100) - 0.0001
int_end = list(map(int, end.split(':')))
int_end = int_end[0] + int_end[1] / 100
int_now = (df[-1:].index.hour[0] + (df[:1].index.minute[0]) / 100)
# same-dat session?
is_same_day = int_end > int_start
# set pointers
curr = prev = df[-1:].index[0].strftime('%Y-%m-%d')
# globex/forex session
if not is_same_day:
prev = (datetime.strptime(curr, '%Y-%m-%d') -
timedelta(1)).strftime('%Y-%m-%d')
# slice
if int_now >= int_start:
df = df[df.index >= curr + ' ' + start]
else:
df = df[df.index >= prev + ' ' + start]
return df.copy()
# ---------------------------------------------
def heikinashi(bars):
bars = bars.copy()
bars['ha_close'] = (bars['open'] + bars['high'] +
bars['low'] + bars['close']) / 4
bars['ha_open'] = (bars['open'].shift(1) + bars['close'].shift(1)) / 2
bars.loc[:1, 'ha_open'] = bars['open'].values[0]
bars.loc[1:, 'ha_open'] = (
(bars['ha_open'].shift(1) + bars['ha_close'].shift(1)) / 2)[1:]
bars['ha_high'] = bars.loc[:, ['high', 'ha_open', 'ha_close']].max(axis=1)
bars['ha_low'] = bars.loc[:, ['low', 'ha_open', 'ha_close']].min(axis=1)
return pd.DataFrame(
index=bars.index,
data={
'open': bars['ha_open'],
'high': bars['ha_high'],
'low': bars['ha_low'],
'close': bars['ha_close']})
# ---------------------------------------------
def tdi(series, rsi_len=13, bollinger_len=34, rsi_smoothing=2,
rsi_signal_len=7, bollinger_std=1.6185):
rsi_series = rsi(series, rsi_len)
bb_series = bollinger_bands(rsi_series, bollinger_len, bollinger_std)
signal = sma(rsi_series, rsi_signal_len)
rsi_series = sma(rsi_series, rsi_smoothing)
return pd.DataFrame(index=series.index, data={
"rsi": rsi_series,
"signal": signal,
"bbupper": bb_series['upper'],
"bblower": bb_series['lower'],
"bbmid": bb_series['mid']
})
# ---------------------------------------------
def awesome_oscillator(df, weighted=False, fast=5, slow=34):
midprice = (df['high'] + df['low']) / 2
if weighted:
ao = (midprice.ewm(fast).mean() - midprice.ewm(slow).mean()).values
else:
ao = numpy_rolling_mean(midprice, fast) - \
numpy_rolling_mean(midprice, slow)
return pd.Series(index=df.index, data=ao)
# ---------------------------------------------
def nans(len=1):
mtx = np.empty(len)
mtx[:] = np.nan
return mtx
# ---------------------------------------------
def typical_price(bars):
res = (bars['high'] + bars['low'] + bars['close']) / 3.
return pd.Series(index=bars.index, data=res)
# ---------------------------------------------
def mid_price(bars):
res = (bars['high'] + bars['low']) / 2.
return pd.Series(index=bars.index, data=res)
# ---------------------------------------------
def ibs(bars):
""" Internal bar strength """
res = np.round((bars['close'] - bars['low']) /
(bars['high'] - bars['low']), 2)
return pd.Series(index=bars.index, data=res)
# ---------------------------------------------
def true_range(bars):
return pd.DataFrame({
"hl": bars['high'] - bars['low'],
"hc": abs(bars['high'] - bars['close'].shift(1)),
"lc": abs(bars['low'] - bars['close'].shift(1))
}).max(axis=1)
# ---------------------------------------------
def atr(bars, window=14, exp=False):
tr = true_range(bars)
if exp:
res = rolling_weighted_mean(tr, window)
else:
res = rolling_mean(tr, window)
res = pd.Series(res)
return (res.shift(1) * (window - 1) + res) / window
# ---------------------------------------------
def crossed(series1, series2, direction=None):
if isinstance(series1, np.ndarray):
series1 = pd.Series(series1)
if isinstance(series2, int) or isinstance(series2, float) or isinstance(series2, np.ndarray):
series2 = pd.Series(index=series1.index, data=series2)
if direction is None or direction == "above":
above = pd.Series((series1 > series2) & (
series1.shift(1) <= series2.shift(1)))
if direction is None or direction == "below":
below = pd.Series((series1 < series2) & (
series1.shift(1) >= series2.shift(1)))
if direction is None:
return above or below
return above if direction is "above" else below
def crossed_above(series1, series2):
return crossed(series1, series2, "above")
def crossed_below(series1, series2):
return crossed(series1, series2, "below")
# ---------------------------------------------
def rolling_std(series, window=200, min_periods=None):
min_periods = window if min_periods is None else min_periods
try:
if min_periods == window:
return numpy_rolling_std(series, window, True)
else:
try:
return series.rolling(window=window, min_periods=min_periods).std()
except BaseException:
return pd.Series(series).rolling(window=window, min_periods=min_periods).std()
except BaseException:
return pd.rolling_std(series, window=window, min_periods=min_periods)
# ---------------------------------------------
def rolling_mean(series, window=200, min_periods=None):
min_periods = window if min_periods is None else min_periods
try:
if min_periods == window:
return numpy_rolling_mean(series, window, True)
else:
try:
return series.rolling(window=window, min_periods=min_periods).mean()
except BaseException:
return pd.Series(series).rolling(window=window, min_periods=min_periods).mean()
except BaseException:
return pd.rolling_mean(series, window=window, min_periods=min_periods)
# ---------------------------------------------
def rolling_min(series, window=14, min_periods=None):
min_periods = window if min_periods is None else min_periods
try:
try:
return series.rolling(window=window, min_periods=min_periods).min()
except BaseException:
return pd.Series(series).rolling(window=window, min_periods=min_periods).min()
except BaseException:
return pd.rolling_min(series, window=window, min_periods=min_periods)
# ---------------------------------------------
def rolling_max(series, window=14, min_periods=None):
min_periods = window if min_periods is None else min_periods
try:
try:
return series.rolling(window=window, min_periods=min_periods).min()
except BaseException:
return pd.Series(series).rolling(window=window, min_periods=min_periods).min()
except BaseException:
return pd.rolling_min(series, window=window, min_periods=min_periods)
# ---------------------------------------------
def rolling_weighted_mean(series, window=200, min_periods=None):
min_periods = window if min_periods is None else min_periods
try:
return series.ewm(span=window, min_periods=min_periods).mean()
except BaseException:
return pd.ewma(series, span=window, min_periods=min_periods)
# ---------------------------------------------
def hull_moving_average(series, window=200):
wma = (2 * rolling_weighted_mean(series, window=window / 2)) - \
rolling_weighted_mean(series, window=window)
return rolling_weighted_mean(wma, window=np.sqrt(window))
# ---------------------------------------------
def sma(series, window=200, min_periods=None):
return rolling_mean(series, window=window, min_periods=min_periods)
# ---------------------------------------------
def wma(series, window=200, min_periods=None):
return rolling_weighted_mean(series, window=window, min_periods=min_periods)
# ---------------------------------------------
def hma(series, window=200):
return hull_moving_average(series, window=window)
# ---------------------------------------------
def vwap(bars):
"""
calculate vwap of entire time series
(input can be pandas series or numpy array)
bars are usually mid [ (h+l)/2 ] or typical [ (h+l+c)/3 ]
"""
typical = ((bars['high'] + bars['low'] + bars['close']) / 3).values
volume = bars['volume'].values
return pd.Series(index=bars.index,
data=np.cumsum(volume * typical) / np.cumsum(volume))
# ---------------------------------------------
def rolling_vwap(bars, window=200, min_periods=None):
"""
calculate vwap using moving window
(input can be pandas series or numpy array)
bars are usually mid [ (h+l)/2 ] or typical [ (h+l+c)/3 ]
"""
min_periods = window if min_periods is None else min_periods
typical = ((bars['high'] + bars['low'] + bars['close']) / 3)
volume = bars['volume']
left = (volume * typical).rolling(window=window,
min_periods=min_periods).sum()
right = volume.rolling(window=window, min_periods=min_periods).sum()
return pd.Series(index=bars.index, data=(left / right))
# ---------------------------------------------
def rsi(series, window=14):
"""
compute the n period relative strength indicator
"""
# 100-(100/relative_strength)
deltas = np.diff(series)
seed = deltas[:window + 1]
# default values
ups = seed[seed > 0].sum() / window
downs = -seed[seed < 0].sum() / window
rsival = np.zeros_like(series)
rsival[:window] = 100. - 100. / (1. + ups / downs)
# period values
for i in range(window, len(series)):
delta = deltas[i - 1]
if delta > 0:
upval = delta
downval = 0
else:
upval = 0
downval = -delta
ups = (ups * (window - 1) + upval) / window
downs = (downs * (window - 1.) + downval) / window
rsival[i] = 100. - 100. / (1. + ups / downs)
# return rsival
return pd.Series(index=series.index, data=rsival)
# ---------------------------------------------
def macd(series, fast=3, slow=10, smooth=16):
"""
compute the MACD (Moving Average Convergence/Divergence)
using a fast and slow exponential moving avg'
return value is emaslow, emafast, macd which are len(x) arrays
"""
macd = rolling_weighted_mean(series, window=fast) - \
rolling_weighted_mean(series, window=slow)
signal = rolling_weighted_mean(macd, window=smooth)
histogram = macd - signal
# return macd, signal, histogram
return pd.DataFrame(index=series.index, data={
'macd': macd.values,
'signal': signal.values,
'histogram': histogram.values
})
# ---------------------------------------------
def bollinger_bands(series, window=20, stds=2):
sma = rolling_mean(series, window=window)
std = rolling_std(series, window=window)
upper = sma + std * stds
lower = sma - std * stds
return pd.DataFrame(index=series.index, data={
'upper': upper,
'mid': sma,
'lower': lower
})
# ---------------------------------------------
def weighted_bollinger_bands(series, window=20, stds=2):
ema = rolling_weighted_mean(series, window=window)
std = rolling_std(series, window=window)
upper = ema + std * stds
lower = ema - std * stds
return pd.DataFrame(index=series.index, data={
'upper': upper.values,
'mid': ema.values,
'lower': lower.values
})
# ---------------------------------------------
def returns(series):
try:
res = (series / series.shift(1) -
1).replace([np.inf, -np.inf], float('NaN'))
except BaseException:
res = nans(len(series))
return pd.Series(index=series.index, data=res)
# ---------------------------------------------
def log_returns(series):
try:
res = np.log(series / series.shift(1)
).replace([np.inf, -np.inf], float('NaN'))
except BaseException:
res = nans(len(series))
return pd.Series(index=series.index, data=res)
# ---------------------------------------------
def implied_volatility(series, window=252):
try:
logret = np.log(series / series.shift(1)
).replace([np.inf, -np.inf], float('NaN'))
res = numpy_rolling_std(logret, window) * np.sqrt(window)
except BaseException:
res = nans(len(series))
return pd.Series(index=series.index, data=res)
# ---------------------------------------------
def keltner_channel(bars, window=14, atrs=2):
typical_mean = rolling_mean(typical_price(bars), window)
atrval = atr(bars, window) * atrs
upper = typical_mean + atrval
lower = typical_mean - atrval
return pd.DataFrame(index=bars.index, data={
'upper': upper.values,
'mid': typical_mean.values,
'lower': lower.values
})
# ---------------------------------------------
def roc(series, window=14):
"""
compute rate of change
"""
res = (series - series.shift(window)) / series.shift(window)
return pd.Series(index=series.index, data=res)
# ---------------------------------------------
def cci(series, window=14):
"""
compute commodity channel index
"""
price = typical_price(series)
typical_mean = rolling_mean(price, window)
res = (price - typical_mean) / (.015 * np.std(typical_mean))
return pd.Series(index=series.index, data=res)
# ---------------------------------------------
def stoch(df, window=14, d=3, k=3, fast=False):
"""
compute the n period relative strength indicator
http://excelta.blogspot.co.il/2013/09/stochastic-oscillator-technical.html
"""
highs_ma = pd.concat([df['high'].shift(i)
for i in np.arange(window)], 1).apply(list, 1)
highs_ma = highs_ma.T.max().T
lows_ma = pd.concat([df['low'].shift(i)
for i in np.arange(window)], 1).apply(list, 1)
lows_ma = lows_ma.T.min().T
fast_k = ((df['close'] - lows_ma) / (highs_ma - lows_ma)) * 100
fast_d = numpy_rolling_mean(fast_k, d)
if fast:
data = {
'k': fast_k,
'd': fast_d
}
else:
slow_k = numpy_rolling_mean(fast_k, k)
slow_d = numpy_rolling_mean(slow_k, d)
data = {
'k': slow_k,
'd': slow_d
}
return pd.DataFrame(index=df.index, data=data)
# ---------------------------------------------
def zscore(bars, window=20, stds=1, col='close'):
""" get zscore of price """
std = numpy_rolling_std(bars[col], window)
mean = numpy_rolling_mean(bars[col], window)
return (bars[col] - mean) / (std * stds)
# ---------------------------------------------
def pvt(bars):
""" Price Volume Trend """
pvt = ((bars['close'] - bars['close'].shift(1)) /
bars['close'].shift(1)) * bars['volume']
return pvt.cumsum()
# =============================================
PandasObject.session = session
PandasObject.atr = atr
PandasObject.bollinger_bands = bollinger_bands
PandasObject.cci = cci
PandasObject.crossed = crossed
PandasObject.crossed_above = crossed_above
PandasObject.crossed_below = crossed_below
PandasObject.heikinashi = heikinashi
PandasObject.hull_moving_average = hull_moving_average
PandasObject.ibs = ibs
PandasObject.implied_volatility = implied_volatility
PandasObject.keltner_channel = keltner_channel
PandasObject.log_returns = log_returns
PandasObject.macd = macd
PandasObject.returns = returns
PandasObject.roc = roc
PandasObject.rolling_max = rolling_max
PandasObject.rolling_min = rolling_min
PandasObject.rolling_mean = rolling_mean
PandasObject.rolling_std = rolling_std
PandasObject.rsi = rsi
PandasObject.stoch = stoch
PandasObject.zscore = zscore
PandasObject.pvt = pvt
PandasObject.tdi = tdi
PandasObject.true_range = true_range
PandasObject.mid_price = mid_price
PandasObject.typical_price = typical_price
PandasObject.vwap = vwap
PandasObject.rolling_vwap = rolling_vwap
PandasObject.weighted_bollinger_bands = weighted_bollinger_bands
PandasObject.rolling_weighted_mean = rolling_weighted_mean
PandasObject.sma = sma
PandasObject.wma = wma
PandasObject.hma = hma

View File

@@ -1,7 +1,8 @@
-e git+https://github.com/ericsomdahl/python-bittrex.git@d7033d0#egg=python-bittrex
-e git+https://github.com/ericsomdahl/python-bittrex.git@0.2.0#egg=python-bittrex
SQLAlchemy==1.1.14
python-telegram-bot==8.1.1
arrow==0.10.0
cachetools==2.0.1
requests==2.18.4
urllib3==1.22
wrapt==1.10.11
@@ -17,7 +18,8 @@ pytest-cov==2.5.1
hyperopt==0.1
# do not upgrade networkx before this is fixed https://github.com/hyperopt/hyperopt/issues/325
networkx==1.11
tabulate==0.8.1
# Required for plotting data
#matplotlib==2.1.0
#PYQT5==5.9
#PYQT5==5.9

51
scripts/plot_dataframe.py Executable file
View File

@@ -0,0 +1,51 @@
#!/usr/bin/env python3
import matplotlib # Install PYQT5 manually if you want to test this helper function
matplotlib.use("Qt5Agg")
import matplotlib.pyplot as plt
from freqtrade import exchange, analyze
def plot_analyzed_dataframe(pair: str) -> None:
"""
Calls analyze() and plots the returned dataframe
:param pair: pair as str
:return: None
"""
# Init Bittrex to use public API
exchange._API = exchange.Bittrex({'key': '', 'secret': ''})
dataframe = analyze.analyze_ticker(pair)
# Two subplots sharing x axis
fig, (ax1, ax2, ax3) = plt.subplots(3, sharex=True)
fig.suptitle(pair, fontsize=14, fontweight='bold')
ax1.plot(dataframe.index.values, dataframe['close'], label='close')
# ax1.plot(dataframe.index.values, dataframe['sell'], 'ro', label='sell')
ax1.plot(dataframe.index.values, dataframe['sma'], '--', label='SMA')
ax1.plot(dataframe.index.values, dataframe['tema'], ':', label='TEMA')
ax1.plot(dataframe.index.values, dataframe['blower'], '-.', label='BB low')
ax1.plot(dataframe.index.values, dataframe['buy_price'], 'bo', label='buy')
ax1.legend()
ax2.plot(dataframe.index.values, dataframe['adx'], label='ADX')
ax2.plot(dataframe.index.values, dataframe['mfi'], label='MFI')
# ax2.plot(dataframe.index.values, [25] * len(dataframe.index.values))
ax2.legend()
ax3.plot(dataframe.index.values, dataframe['fastk'], label='k')
ax3.plot(dataframe.index.values, dataframe['fastd'], label='d')
ax3.plot(dataframe.index.values, [20] * len(dataframe.index.values))
ax3.legend()
# Fine-tune figure; make subplots close to each other and hide x ticks for
# all but bottom plot.
fig.subplots_adjust(hspace=0)
plt.setp([a.get_xticklabels() for a in fig.axes[:-1]], visible=False)
plt.show()
if __name__ == '__main__':
plot_analyzed_dataframe('BTC_ETH')

View File

@@ -1,5 +1,11 @@
from sys import version_info
from setuptools import setup
if version_info.major == 3 and version_info.minor < 6 or \
version_info.major < 3:
print('Your Python interpreter must be 3.6 or greater!')
exit(1)
from freqtrade import __version__
@@ -15,21 +21,23 @@ setup(name='freqtrade',
setup_requires=['pytest-runner'],
tests_require=['pytest', 'pytest-mock', 'pytest-cov'],
install_requires=[
'python-bittrex==0.1.3',
'SQLAlchemy==1.1.13',
'python-telegram-bot==8.1.1',
'arrow==0.10.0',
'requests==2.18.4',
'urllib3==1.22',
'wrapt==1.10.11',
'pandas==0.20.3',
'scikit-learn==0.19.0',
'scipy==0.19.1',
'jsonschema==2.6.0',
'TA-Lib==0.4.10',
'python-bittrex',
'SQLAlchemy',
'python-telegram-bot',
'arrow',
'requests',
'urllib3',
'wrapt',
'pandas',
'scikit-learn',
'scipy',
'jsonschema',
'TA-Lib',
'tabulate',
'cachetools',
],
dependency_links=[
"git+https://github.com/ericsomdahl/python-bittrex.git@d7033d0#egg=python-bittrex-0.1.3"
"git+https://github.com/ericsomdahl/python-bittrex.git@0.2.0#egg=python-bittrex"
],
include_package_data=True,
zip_safe=False,