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2021-11-18 20:20:01 +01:00
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3
docs/configuration.md
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@@ -104,6 +104,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
| `unfilledtimeout.buy` | **Required.** How long (in minutes or seconds) the bot will wait for an unfilled buy order to complete, after which the order will be cancelled and repeated at current (new) price, as long as there is a signal. [Strategy Override](#parameters-in-the-strategy).<br> **Datatype:** Integer
| `unfilledtimeout.sell` | **Required.** How long (in minutes or seconds) the bot will wait for an unfilled sell order to complete, after which the order will be cancelled and repeated at current (new) price, as long as there is a signal. [Strategy Override](#parameters-in-the-strategy).<br> **Datatype:** Integer
| `unfilledtimeout.unit` | Unit to use in unfilledtimeout setting. Note: If you set unfilledtimeout.unit to "seconds", "internals.process_throttle_secs" must be inferior or equal to timeout [Strategy Override](#parameters-in-the-strategy). <br> *Defaults to `minutes`.* <br> **Datatype:** String
| `unfilledtimeout.exit_timeout_count` | How many times can exit orders time out. Once this number of timeouts is reached, an emergency sell is triggered. 0 to disable and allow unlimited order cancels. [Strategy Override](#parameters-in-the-strategy).<br>*Defaults to `0`.* <br> **Datatype:** Integer
| `bid_strategy.price_side` | Select the side of the spread the bot should look at to get the buy rate. [More information below](#buy-price-side).<br> *Defaults to `bid`.* <br> **Datatype:** String (either `ask` or `bid`).
| `bid_strategy.ask_last_balance` | **Required.** Interpolate the bidding price. More information [below](#buy-price-without-orderbook-enabled).
| `bid_strategy.use_order_book` | Enable buying using the rates in [Order Book Bids](#buy-price-with-orderbook-enabled). <br> **Datatype:** Boolean
@@ -215,7 +216,7 @@ With a reserve of 5%, the minimum stake amount would be ~12.6$ (`12 * (1 + 0.05)
To limit this calculation in case of large stoploss values, the calculated minimum stake-limit will never be more than 50% above the real limit.
!!! Warning
Since the limits on exchanges are usually stable and are not updated often, some pairs can show pretty high minimum limits, simply because the price increased a lot since the last limit adjustment by the exchange.
Since the limits on exchanges are usually stable and are not updated often, some pairs can show pretty high minimum limits, simply because the price increased a lot since the last limit adjustment by the exchange. Freqtrade adjusts the stake-amount to this value, unless it's > 30% more than the calculated/desired stake-amount - in which case the trade is rejected.
#### Tradable balance

2
docs/developer.md
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@@ -26,6 +26,8 @@ Alternatively (e.g. if your system is not supported by the setup.sh script), fol
This will install all required tools for development, including `pytest`, `flake8`, `mypy`, and `coveralls`.
Before opening a pull request, please familiarize yourself with our [Contributing Guidelines](https://github.com/freqtrade/freqtrade/blob/develop/CONTRIBUTING.md).
### Devcontainer setup
The fastest and easiest way to get started is to use [VSCode](https://code.visualstudio.com/) with the Remote container extension.

4
docs/includes/pairlists.md
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@@ -198,7 +198,7 @@ Not defining this parameter (or setting it to 0) will use all-time performance.
The optional `min_profit` parameter defines the minimum profit a pair must have to be considered.
Pairs below this level will be filtered out.
Using this parameter without `minutes` is highly discouraged, as it can lead to an empty pairlist without without a way to recover.
Using this parameter without `minutes` is highly discouraged, as it can lead to an empty pairlist without a way to recover.
```json
"pairlists": [
@@ -211,6 +211,8 @@ Using this parameter without `minutes` is highly discouraged, as it can lead to
],
```
As this Filter uses past performance of the bot, it'll have some startup-period - and should only be used after the bot has a few 100 trades in the database.
!!! Warning "Backtesting"
`PerformanceFilter` does not support backtesting mode.

2
docs/index.md
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@@ -36,7 +36,7 @@ Freqtrade is a crypto-currency algorithmic trading software developed in python
Please read the [exchange specific notes](exchanges.md) to learn about eventual, special configurations needed for each exchange.
- [X] [Binance](https://www.binance.com/) ([*Note for binance users](docs/exchanges.md#binance-blacklist))
- [X] [Binance](https://www.binance.com/) ([*Note for binance users](exchanges.md#binance-blacklist))
- [X] [Bittrex](https://bittrex.com/)
- [X] [FTX](https://ftx.com)
- [X] [Gate.io](https://www.gate.io/ref/6266643)

4
docs/installation.md
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@@ -60,7 +60,7 @@ OS Specific steps are listed first, the [Common](#common) section below is neces
sudo apt-get update
# install packages
sudo apt install -y python3-pip python3-venv python3-dev python3-pandas git
sudo apt install -y python3-pip python3-venv python3-dev python3-pandas git curl
```
=== "RaspberryPi/Raspbian"
@@ -71,7 +71,7 @@ OS Specific steps are listed first, the [Common](#common) section below is neces
```bash
sudo apt-get install python3-venv libatlas-base-dev cmake
sudo apt-get install python3-venv libatlas-base-dev cmake curl
# Use pywheels.org to speed up installation
sudo echo "[global]\nextra-index-url=https://www.piwheels.org/simple" > tee /etc/pip.conf

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docs/requirements-docs.txt
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@@ -1,4 +1,4 @@
mkdocs==1.2.3
mkdocs-material==7.3.6
mdx_truly_sane_lists==1.2
pymdown-extensions==9.0
pymdown-extensions==9.1

72
docs/strategy-advanced.md
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@@ -143,6 +143,52 @@ def custom_sell(self, pair: str, trade: Trade, current_time: datetime, current_r
!!! Note
`buy_tag` is limited to 100 characters, remaining data will be truncated.
## Exit tag
Similar to [Buy Tagging](#buy-tag), you can also specify a sell tag.
``` python
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['rsi'] > 70) &
(dataframe['volume'] > 0)
),
['sell', 'exit_tag']] = (1, 'exit_rsi')
return dataframe
```
The provided exit-tag is then used as sell-reason - and shown as such in backtest results.
!!! Note
`sell_reason` is limited to 100 characters, remaining data will be truncated.
## Bot loop start callback
A simple callback which is called once at the start of every bot throttling iteration.
This can be used to perform calculations which are pair independent (apply to all pairs), loading of external data, etc.
``` python
import requests
class AwesomeStrategy(IStrategy):
# ... populate_* methods
def bot_loop_start(self, **kwargs) -> None:
"""
Called at the start of the bot iteration (one loop).
Might be used to perform pair-independent tasks
(e.g. gather some remote resource for comparison)
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
"""
if self.config['runmode'].value in ('live', 'dry_run'):
# Assign this to the class by using self.*
# can then be used by populate_* methods
self.remote_data = requests.get('https://some_remote_source.example.com')
```
## Custom stoploss
@@ -501,32 +547,6 @@ class AwesomeStrategy(IStrategy):
---
## Bot loop start callback
A simple callback which is called once at the start of every bot throttling iteration.
This can be used to perform calculations which are pair independent (apply to all pairs), loading of external data, etc.
``` python
import requests
class AwesomeStrategy(IStrategy):
# ... populate_* methods
def bot_loop_start(self, **kwargs) -> None:
"""
Called at the start of the bot iteration (one loop).
Might be used to perform pair-independent tasks
(e.g. gather some remote resource for comparison)
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
"""
if self.config['runmode'].value in ('live', 'dry_run'):
# Assign this to the class by using self.*
# can then be used by populate_* methods
self.remote_data = requests.get('https://some_remote_source.example.com')
```
## Bot order confirmation
### Trade entry (buy order) confirmation

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docs/strategy-customization.md
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@@ -4,33 +4,23 @@ This page explains how to customize your strategies, add new indicators and set
Please familiarize yourself with [Freqtrade basics](bot-basics.md) first, which provides overall info on how the bot operates.
## Install a custom strategy file
This is very simple. Copy paste your strategy file into the directory `user_data/strategies`.
Let assume you have a class called `AwesomeStrategy` in the file `AwesomeStrategy.py`:
1. Move your file into `user_data/strategies` (you should have `user_data/strategies/AwesomeStrategy.py`
2. Start the bot with the param `--strategy AwesomeStrategy` (the parameter is the class name)
```bash
freqtrade trade --strategy AwesomeStrategy
```
## Develop your own strategy
The bot includes a default strategy file.
Also, several other strategies are available in the [strategy repository](https://github.com/freqtrade/freqtrade-strategies).
You will however most likely have your own idea for a strategy.
This document intends to help you develop one for yourself.
This document intends to help you convert your strategy idea into your own strategy.
To get started, use `freqtrade new-strategy --strategy AwesomeStrategy`.
To get started, use `freqtrade new-strategy --strategy AwesomeStrategy` (you can obviously use your own naming for your strategy).
This will create a new strategy file from a template, which will be located under `user_data/strategies/AwesomeStrategy.py`.
!!! Note
This is just a template file, which will most likely not be profitable out of the box.
??? Hint "Different template levels"
`freqtrade new-strategy` has an additional parameter, `--template`, which controls the amount of pre-build information you get in the created strategy. Use `--template minimal` to get an empty strategy without any indicator examples, or `--template advanced` to get a template with most callbacks defined.
### Anatomy of a strategy
A strategy file contains all the information needed to build a good strategy:
@@ -67,6 +57,46 @@ file as reference.**
needs to take care to avoid having the strategy utilize data from the future.
Some common patterns for this are listed in the [Common Mistakes](#common-mistakes-when-developing-strategies) section of this document.
### Dataframe
Freqtrade uses [pandas](https://pandas.pydata.org/) to store/provide the candlestick (OHLCV) data.
Pandas is a great library developed for processing large amounts of data.
Each row in a dataframe corresponds to one candle on a chart, with the latest candle always being the last in the dataframe (sorted by date).
``` output
> dataframe.head()
date open high low close volume
0 2021-11-09 23:25:00+00:00 67279.67 67321.84 67255.01 67300.97 44.62253
1 2021-11-09 23:30:00+00:00 67300.97 67301.34 67183.03 67187.01 61.38076
2 2021-11-09 23:35:00+00:00 67187.02 67187.02 67031.93 67123.81 113.42728
3 2021-11-09 23:40:00+00:00 67123.80 67222.40 67080.33 67160.48 78.96008
4 2021-11-09 23:45:00+00:00 67160.48 67160.48 66901.26 66943.37 111.39292
```
Pandas provides fast ways to calculate metrics. To benefit from this speed, it's advised to not use loops, but use vectorized methods instead.
Vectorized operations perform calculations across the whole range of data and are therefore, compared to looping through each row, a lot faster when calculating indicators.
As a dataframe is a table, simple python comparisons like the following will not work
``` python
if dataframe['rsi'] > 30:
dataframe['buy'] = 1
```
The above section will fail with `The truth value of a Series is ambiguous. [...]`.
This must instead be written in a pandas-compatible way, so the operation is performed across the whole dataframe.
``` python
dataframe.loc[
(dataframe['rsi'] > 30)
, 'buy'] = 1
```
With this section, you have a new column in your dataframe, which has `1` assigned whenever RSI is above 30.
### Customize Indicators
Buy and sell strategies need indicators. You can add more indicators by extending the list contained in the method `populate_indicators()` from your strategy file.
@@ -134,7 +164,7 @@ Additional technical libraries can be installed as necessary, or custom indicato
### Strategy startup period
Most indicators have an instable startup period, in which they are either not available, or the calculation is incorrect. This can lead to inconsistencies, since Freqtrade does not know how long this instable period should be.
Most indicators have an instable startup period, in which they are either not available (NaN), or the calculation is incorrect. This can lead to inconsistencies, since Freqtrade does not know how long this instable period should be.
To account for this, the strategy can be assigned the `startup_candle_count` attribute.
This should be set to the maximum number of candles that the strategy requires to calculate stable indicators.
@@ -146,8 +176,14 @@ In this example strategy, this should be set to 100 (`startup_candle_count = 100
By letting the bot know how much history is needed, backtest trades can start at the specified timerange during backtesting and hyperopt.
!!! Warning "Using x calls to get OHLCV"
If you receive a warning like `WARNING - Using 3 calls to get OHLCV. This can result in slower operations for the bot. Please check if you really need 1500 candles for your strategy` - you should consider if you really need this much historic data for your signals.
Having this will cause Freqtrade to make multiple calls for the same pair, which will obviously be slower than one network request.
As a consequence, Freqtrade will take longer to refresh candles - and should therefore be avoided if possible.
This is capped to 5 total calls to avoid overloading the exchange, or make freqtrade too slow.
!!! Warning
`startup_candle_count` should be below `ohlcv_candle_limit` (which is 500 for most exchanges) - since only this amount of candles will be available during Dry-Run/Live Trade operations.
`startup_candle_count` should be below `ohlcv_candle_limit * 5` (which is 500 * 5 for most exchanges) - since only this amount of candles will be available during Dry-Run/Live Trade operations.
#### Example
@@ -312,6 +348,19 @@ Currently this is `pair`, which can be accessed using `metadata['pair']` - and w
The Metadata-dict should not be modified and does not persist information across multiple calls.
Instead, have a look at the section [Storing information](strategy-advanced.md#Storing-information)
## Strategy file loading
By default, freqtrade will attempt to load strategies from all `.py` files within `user_data/strategies`.
Assuming your strategy is called `AwesomeStrategy`, stored in the file `user_data/strategies/AwesomeStrategy.py`, then you can start freqtrade with `freqtrade trade --strategy AwesomeStrategy`.
Note that we're using the class-name, not the file name.
You can use `freqtrade list-strategies` to see a list of all strategies Freqtrade is able to load (all strategies in the correct folder).
It will also include a "status" field, highlighting potential problems.
??? Hint "Customize strategy directory"
You can use a different directory by using `--strategy-path user_data/otherPath`. This parameter is available to all commands that require a strategy.
## Informative Pairs
### Get data for non-tradeable pairs

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docs/telegram-usage.md
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@@ -58,6 +58,8 @@ For the Freqtrade configuration, you can then use the the full value (including
```json
"chat_id": "-1001332619709"
```
!!! Warning "Using telegram groups"
When using telegram groups, you're giving every member of the telegram group access to your freqtrade bot and to all commands possible via telegram. Please make sure that you can trust everyone in the telegram group to avoid unpleasent surprises.
## Control telegram noise
@@ -175,6 +177,8 @@ official commands. You can ask at any moment for help with `/help`.
| `/performance` | Show performance of each finished trade grouped by pair
| `/balance` | Show account balance per currency
| `/daily <n>` | Shows profit or loss per day, over the last n days (n defaults to 7)
| `/weekly <n>` | Shows profit or loss per week, over the last n weeks (n defaults to 8)
| `/monthly <n>` | Shows profit or loss per month, over the last n months (n defaults to 6)
| `/stats` | Shows Wins / losses by Sell reason as well as Avg. holding durations for buys and sells
| `/whitelist` | Show the current whitelist
| `/blacklist [pair]` | Show the current blacklist, or adds a pair to the blacklist.
@@ -307,8 +311,7 @@ Return the balance of all crypto-currency your have on the exchange.
### /daily <n>
Per default `/daily` will return the 7 last days.
The example below if for `/daily 3`:
Per default `/daily` will return the 7 last days. The example below if for `/daily 3`:
> **Daily Profit over the last 3 days:**
```
@@ -319,6 +322,34 @@ Day Profit BTC Profit USD
2018-01-01 0.00269130 BTC 34.986 USD
```
### /weekly <n>
Per default `/weekly` will return the 8 last weeks, including the current week. Each week starts
from Monday. The example below if for `/weekly 3`:
> **Weekly Profit over the last 3 weeks (starting from Monday):**
```
Monday Profit BTC Profit USD
---------- -------------- ------------
2018-01-03 0.00224175 BTC 29,142 USD
2017-12-27 0.00033131 BTC 4,307 USD
2017-12-20 0.00269130 BTC 34.986 USD
```
### /monthly <n>
Per default `/monthly` will return the 6 last months, including the current month. The example below
if for `/monthly 3`:
> **Monthly Profit over the last 3 months:**
```
Month Profit BTC Profit USD
---------- -------------- ------------
2018-01 0.00224175 BTC 29,142 USD
2017-12 0.00033131 BTC 4,307 USD
2017-11 0.00269130 BTC 34.986 USD
```
### /whitelist
Shows the current whitelist