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Merge branch 'develop' into feat/stoploss_adjust

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Matthias
2023-08-29 07:04:08 +02:00
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docs/bot-basics.md
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@@ -7,7 +7,7 @@ This page provides you some basic concepts on how Freqtrade works and operates.
* **Strategy**: Your trading strategy, telling the bot what to do.
* **Trade**: Open position.
* **Open Order**: Order which is currently placed on the exchange, and is not yet complete.
* **Pair**: Tradable pair, usually in the format of Base/Quote (e.g. XRP/USDT).
* **Pair**: Tradable pair, usually in the format of Base/Quote (e.g. `XRP/USDT` for spot, `XRP/USDT:USDT` for futures).
* **Timeframe**: Candle length to use (e.g. `"5m"`, `"1h"`, ...).
* **Indicators**: Technical indicators (SMA, EMA, RSI, ...).
* **Limit order**: Limit orders which execute at the defined limit price or better.
@@ -20,6 +20,20 @@ This page provides you some basic concepts on how Freqtrade works and operates.
All profit calculations of Freqtrade include fees. For Backtesting / Hyperopt / Dry-run modes, the exchange default fee is used (lowest tier on the exchange). For live operations, fees are used as applied by the exchange (this includes BNB rebates etc.).
## Pair naming
Freqtrade follows the [ccxt naming convention](https://docs.ccxt.com/#/README?id=consistency-of-base-and-quote-currencies) for currencies.
Using the wrong naming convention in the wrong market will usually result in the bot not recognizing the pair, usually resulting in errors like "this pair is not available".
### Spot pair naming
For spot pairs, naming will be `base/quote` (e.g. `ETH/USDT`).
### Futures pair naming
For futures pairs, naming will be `base/quote:settle` (e.g. `ETH/USDT:USDT`).
## Bot execution logic
Starting freqtrade in dry-run or live mode (using `freqtrade trade`) will start the bot and start the bot iteration loop.
docs/bot-usage.md
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This page explains the different parameters of the bot and how to run it.
!!! Note
If you've used `setup.sh`, don't forget to activate your virtual environment (`source .env/bin/activate`) before running freqtrade commands.
If you've used `setup.sh`, don't forget to activate your virtual environment (`source .venv/bin/activate`) before running freqtrade commands.
!!! Warning "Up-to-date clock"
The clock on the system running the bot must be accurate, synchronized to a NTP server frequently enough to avoid problems with communication to the exchanges.
docs/data-analysis.md
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@@ -27,7 +27,7 @@ For this to work, first activate your virtual environment and run the following
``` bash
# Activate virtual environment
source .env/bin/activate
source .venv/bin/activate
pip install ipykernel
ipython kernel install --user --name=freqtrade
docs/developer.md
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@@ -77,7 +77,7 @@ def test_method_to_test(caplog):
### Debug configuration
To debug freqtrade, we recommend VSCode with the following launch configuration (located in `.vscode/launch.json`).
To debug freqtrade, we recommend VSCode (with the Python extension) with the following launch configuration (located in `.vscode/launch.json`).
Details will obviously vary between setups - but this should work to get you started.
``` json
@@ -102,6 +102,19 @@ This method can also be used to debug a strategy, by setting the breakpoints wit
A similar setup can also be taken for Pycharm - using `freqtrade` as module name, and setting the command line arguments as "parameters".
??? Tip "Correct venv usage"
When using a virtual environment (which you should), make sure that your Editor is using the correct virtual environment to avoid problems or "unknown import" errors.
#### Vscode
You can select the correct environment in VSCode with the command "Python: Select Interpreter" - which will show you environments the extension detected.
If your environment has not been detected, you can also pick a path manually.
#### Pycharm
In pycharm, you can select the appropriate Environment in the "Run/Debug Configurations" window.
![Pycharm debug configuration](assets/pycharm_debug.png)
!!! Note "Startup directory"
This assumes that you have the repository checked out, and the editor is started at the repository root level (so setup.py is at the top level of your repository).
docs/edge.md
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The `Edge Positioning` module uses probability to calculate your win rate and risk reward ratio. It will use these statistics to control your strategy trade entry points, position size and, stoploss.
!!! Danger "Deprecated functionality"
`Edge positioning` (or short Edge) is currently in maintenance mode only (we keep existing functionality alive) and should be considered as deprecated.
It will currently not receive new features until either someone stepped forward to take up ownership of that module - or we'll decide to remove edge from freqtrade.
!!! Warning
When using `Edge positioning` with a dynamic whitelist (VolumePairList), make sure to also use `AgeFilter` and set it to at least `calculate_since_number_of_days` to avoid problems with missing data.
docs/faq.md
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@@ -36,7 +36,7 @@ Running the bot with `freqtrade trade --config config.json` shows the output `fr
This could be caused by the following reasons:
* The virtual environment is not active.
* Run `source .env/bin/activate` to activate the virtual environment.
* Run `source .venv/bin/activate` to activate the virtual environment.
* The installation did not complete successfully.
* Please check the [Installation documentation](installation.md).
docs/freqai-parameter-table.md
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@@ -100,12 +100,12 @@ Mandatory parameters are marked as **Required** and have to be set in one of the
#### trainer_kwargs
| Parameter | Description |
|------------|-------------|
| | **Model training parameters within the `freqai.model_training_parameters.model_kwargs` sub dictionary**
| `max_iters` | The number of training iterations to run. iteration here refers to the number of times we call self.optimizer.step(). used to calculate n_epochs. <br> **Datatype:** int. <br> Default: `100`.
| `batch_size` | The size of the batches to use during training.. <br> **Datatype:** int. <br> Default: `64`.
| `max_n_eval_batches` | The maximum number batches to use for evaluation.. <br> **Datatype:** int, optional. <br> Default: `None`.
| Parameter | Description |
|--------------|-------------|
| | **Model training parameters within the `freqai.model_training_parameters.model_kwargs` sub dictionary**
| `n_epochs` | The `n_epochs` parameter is a crucial setting in the PyTorch training loop that determines the number of times the entire training dataset will be used to update the model's parameters. An epoch represents one full pass through the entire training dataset. Overrides `n_steps`. Either `n_epochs` or `n_steps` must be set. <br><br> **Datatype:** int. optional. <br> Default: `10`.
| `n_steps` | An alternative way of setting `n_epochs` - the number of training iterations to run. Iteration here refer to the number of times we call `optimizer.step()`. Ignored if `n_epochs` is set. A simplified version of the function: <br><br> n_epochs = n_steps / (n_obs / batch_size) <br><br> The motivation here is that `n_steps` is easier to optimize and keep stable across different n_obs - the number of data points. <br> <br> **Datatype:** int. optional. <br> Default: `None`.
| `batch_size` | The size of the batches to use during training. <br><br> **Datatype:** int. <br> Default: `64`.
### Additional parameters
docs/freqai-reinforcement-learning.md
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@@ -20,7 +20,7 @@ With the current framework, we aim to expose the training environment via the co
We envision the majority of users focusing their effort on creative design of the `calculate_reward()` function [details here](#creating-a-custom-reward-function), while leaving the rest of the environment untouched. Other users may not touch the environment at all, and they will only play with the configuration settings and the powerful feature engineering that already exists in FreqAI. Meanwhile, we enable advanced users to create their own model classes entirely.
The framework is built on stable_baselines3 (torch) and OpenAI gym for the base environment class. But generally speaking, the model class is well isolated. Thus, the addition of competing libraries can be easily integrated into the existing framework. For the environment, it is inheriting from `gym.env` which means that it is necessary to write an entirely new environment in order to switch to a different library.
The framework is built on stable_baselines3 (torch) and OpenAI gym for the base environment class. But generally speaking, the model class is well isolated. Thus, the addition of competing libraries can be easily integrated into the existing framework. For the environment, it is inheriting from `gym.Env` which means that it is necessary to write an entirely new environment in order to switch to a different library.
### Important considerations
@@ -173,7 +173,7 @@ class MyCoolRLModel(ReinforcementLearner):
"""
class MyRLEnv(Base5ActionRLEnv):
"""
User made custom environment. This class inherits from BaseEnvironment and gym.env.
User made custom environment. This class inherits from BaseEnvironment and gym.Env.
Users can override any functions from those parent classes. Here is an example
of a user customized `calculate_reward()` function.
@@ -254,7 +254,7 @@ FreqAI also provides a built in episodic summary logger called `self.tensorboard
```python
class MyRLEnv(Base5ActionRLEnv):
"""
User made custom environment. This class inherits from BaseEnvironment and gym.env.
User made custom environment. This class inherits from BaseEnvironment and gym.Env.
Users can override any functions from those parent classes. Here is an example
of a user customized `calculate_reward()` function.
"""
docs/hyperopt.md
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@@ -31,7 +31,7 @@ The docker-image includes hyperopt dependencies, no further action needed.
### Easy installation script (setup.sh) / Manual installation
```bash
source .env/bin/activate
source .venv/bin/activate
pip install -r requirements-hyperopt.txt
```
docs/installation.md
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@@ -143,11 +143,11 @@ If you are on Debian, Ubuntu or MacOS, freqtrade provides the script to install
### Activate your virtual environment
Each time you open a new terminal, you must run `source .env/bin/activate` to activate your virtual environment.
Each time you open a new terminal, you must run `source .venv/bin/activate` to activate your virtual environment.
```bash
# then activate your .env
source ./.env/bin/activate
# activate virtual environment
source ./.venv/bin/activate
```
### Congratulations
@@ -172,7 +172,7 @@ With this option, the script will install the bot and most dependencies:
You will need to have git and python3.8+ installed beforehand for this to work.
* Mandatory software as: `ta-lib`
* Setup your virtualenv under `.env/`
* Setup your virtualenv under `.venv/`
This option is a combination of installation tasks and `--reset`
@@ -225,11 +225,11 @@ rm -rf ./ta-lib*
You will run freqtrade in separated `virtual environment`
```bash
# create virtualenv in directory /freqtrade/.env
python3 -m venv .env
# create virtualenv in directory /freqtrade/.venv
python3 -m venv .venv
# run virtualenv
source .env/bin/activate
source .venv/bin/activate
```
#### Install python dependencies
@@ -286,7 +286,7 @@ cd freqtrade
#### Freqtrade install: Conda Environment
```bash
conda create --name freqtrade python=3.10
conda create --name freqtrade python=3.11
```
!!! Note "Creating Conda Environment"
@@ -383,7 +383,7 @@ You've made it this far, so you have successfully installed freqtrade.
freqtrade create-userdir --userdir user_data
# Step 2 - Create a new configuration file
freqtrade new-config --config config.json
freqtrade new-config --config user_data/config.json
```
You are ready to run, read [Bot Configuration](configuration.md), remember to start with `dry_run: True` and verify that everything is working.
@@ -393,7 +393,7 @@ To learn how to setup your configuration, please refer to the [Bot Configuration
### Start the Bot
```bash
freqtrade trade --config config.json --strategy SampleStrategy
freqtrade trade --config user_data/config.json --strategy SampleStrategy
```
!!! Warning
@@ -411,8 +411,8 @@ If you used (1)`Script` or (2)`Manual` installation, you need to run the bot in
# if:
bash: freqtrade: command not found
# then activate your .env
source ./.env/bin/activate
# then activate your virtual environment
source ./.venv/bin/activate
```
### MacOS installation error
docs/leverage.md
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@@ -64,7 +64,7 @@ You will also have to pick a "margin mode" (explanation below) - with freqtrade
##### Pair namings
Freqtrade follows the [ccxt naming conventions for futures](https://docs.ccxt.com/en/latest/manual.html?#perpetual-swap-perpetual-future).
Freqtrade follows the [ccxt naming conventions for futures](https://docs.ccxt.com/#/README?id=perpetual-swap-perpetual-future).
A futures pair will therefore have the naming of `base/quote:settle` (e.g. `ETH/USDT:USDT`).
### Margin mode
docs/requirements-docs.txt
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markdown==3.4.4
mkdocs==1.5.2
mkdocs-material==9.1.21
mkdocs-material==9.2.5
mdx_truly_sane_lists==1.3
pymdown-extensions==10.1
jinja2==3.1.2
docs/windows_installation.md
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@@ -31,8 +31,8 @@ Other versions must be downloaded from the above link.
``` powershell
cd \path\freqtrade
python -m venv .env
.env\Scripts\activate.ps1
python -m venv .venv
.venv\Scripts\activate.ps1
# optionally install ta-lib from wheel
# Eventually adjust the below filename to match the downloaded wheel
pip install --find-links build_helpers\ TA-Lib -U