diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index f4b550855..d187e650b 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -461,7 +461,7 @@ jobs: python setup.py sdist bdist_wheel - name: Publish to PyPI (Test) - uses: pypa/gh-action-pypi-publish@v1.8.8 + uses: pypa/gh-action-pypi-publish@v1.8.10 if: (github.event_name == 'release') with: user: __token__ @@ -469,7 +469,7 @@ jobs: repository_url: https://test.pypi.org/legacy/ - name: Publish to PyPI - uses: pypa/gh-action-pypi-publish@v1.8.8 + uses: pypa/gh-action-pypi-publish@v1.8.10 if: (github.event_name == 'release') with: user: __token__ diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 6e4919763..8fea99cd1 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -8,7 +8,7 @@ repos: # stages: [push] - repo: https://github.com/pre-commit/mirrors-mypy - rev: "v1.3.0" + rev: "v1.5.0" hooks: - id: mypy exclude: build_helpers diff --git a/build_helpers/install_ta-lib.sh b/build_helpers/install_ta-lib.sh index 005d9abca..0315c7025 100755 --- a/build_helpers/install_ta-lib.sh +++ b/build_helpers/install_ta-lib.sh @@ -8,8 +8,9 @@ if [ -n "$2" ] || [ ! -f "${INSTALL_LOC}/lib/libta_lib.a" ]; then tar zxvf ta-lib-0.4.0-src.tar.gz cd ta-lib \ && sed -i.bak "s|0.00000001|0.000000000000000001 |g" src/ta_func/ta_utility.h \ - && curl 'https://raw.githubusercontent.com/gcc-mirror/gcc/master/config.guess' -o config.guess \ - && curl 'https://raw.githubusercontent.com/gcc-mirror/gcc/master/config.sub' -o config.sub \ + && echo "Downloading gcc config.guess and config.sub" \ + && curl -s 'https://raw.githubusercontent.com/gcc-mirror/gcc/master/config.guess' -o config.guess \ + && curl -s 'https://raw.githubusercontent.com/gcc-mirror/gcc/master/config.sub' -o config.sub \ && ./configure --prefix=${INSTALL_LOC}/ \ && make if [ $? -ne 0 ]; then diff --git a/config_examples/config_full.example.json b/config_examples/config_full.example.json index 42c05eaf5..4681ec7df 100644 --- a/config_examples/config_full.example.json +++ b/config_examples/config_full.example.json @@ -89,7 +89,6 @@ ], "exchange": { "name": "binance", - "sandbox": false, "key": "your_exchange_key", "secret": "your_exchange_secret", "password": "", diff --git a/docs/assets/pycharm_debug.png b/docs/assets/pycharm_debug.png new file mode 100644 index 000000000..b1c19ca93 Binary files /dev/null and b/docs/assets/pycharm_debug.png differ diff --git a/docs/bot-usage.md b/docs/bot-usage.md index c6a7f6103..7aeda0c42 100644 --- a/docs/bot-usage.md +++ b/docs/bot-usage.md @@ -3,7 +3,7 @@ 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. diff --git a/docs/configuration.md b/docs/configuration.md index e05d1b450..6c0795c67 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -188,7 +188,6 @@ Mandatory parameters are marked as **Required**, which means that they are requi | `max_entry_position_adjustment` | Maximum additional order(s) for each open trade on top of the first entry Order. Set it to `-1` for unlimited additional orders. [More information here](strategy-callbacks.md#adjust-trade-position).
[Strategy Override](#parameters-in-the-strategy).
*Defaults to `-1`.*
**Datatype:** Positive Integer or -1 | | **Exchange** | `exchange.name` | **Required.** Name of the exchange class to use. [List below](#user-content-what-values-for-exchangename).
**Datatype:** String -| `exchange.sandbox` | Use the 'sandbox' version of the exchange, where the exchange provides a sandbox for risk-free integration. See [here](sandbox-testing.md) in more details.
**Datatype:** Boolean | `exchange.key` | API key to use for the exchange. Only required when you are in production mode.
**Keep it in secret, do not disclose publicly.**
**Datatype:** String | `exchange.secret` | API secret to use for the exchange. Only required when you are in production mode.
**Keep it in secret, do not disclose publicly.**
**Datatype:** String | `exchange.password` | API password to use for the exchange. Only required when you are in production mode and for exchanges that use password for API requests.
**Keep it in secret, do not disclose publicly.**
**Datatype:** String diff --git a/docs/data-analysis.md b/docs/data-analysis.md index afee9049f..7f5637dd0 100644 --- a/docs/data-analysis.md +++ b/docs/data-analysis.md @@ -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 diff --git a/docs/developer.md b/docs/developer.md index 4784e5352..23f4a9b26 100644 --- a/docs/developer.md +++ b/docs/developer.md @@ -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). diff --git a/docs/docker_quickstart.md b/docs/docker_quickstart.md index 89f737d71..0c9e8001a 100644 --- a/docs/docker_quickstart.md +++ b/docs/docker_quickstart.md @@ -14,6 +14,9 @@ Start by downloading and installing Docker / Docker Desktop for your platform: Freqtrade documentation assumes the use of Docker desktop (or the docker compose plugin). While the docker-compose standalone installation still works, it will require changing all `docker compose` commands from `docker compose` to `docker-compose` to work (e.g. `docker compose up -d` will become `docker-compose up -d`). +??? Warning "Docker on windows" + If you just installed docker on a windows system, make sure to reboot your system, otherwise you might encounter unexplainable Problems related to network connectivity to docker containers. + ## Freqtrade with docker Freqtrade provides an official Docker image on [Dockerhub](https://hub.docker.com/r/freqtradeorg/freqtrade/), as well as a [docker compose file](https://github.com/freqtrade/freqtrade/blob/stable/docker-compose.yml) ready for usage. @@ -78,7 +81,7 @@ If you've selected to enable FreqUI in the `new-config` step, you will have freq You can now access the UI by typing localhost:8080 in your browser. -??? Note "UI Access on a remote servers" +??? Note "UI Access on a remote server" If you're running on a VPS, you should consider using either a ssh tunnel, or setup a VPN (openVPN, wireguard) to connect to your bot. This will ensure that freqUI is not directly exposed to the internet, which is not recommended for security reasons (freqUI does not support https out of the box). Setup of these tools is not part of this tutorial, however many good tutorials can be found on the internet. @@ -128,7 +131,7 @@ All freqtrade arguments will be available by running `docker compose run --rm fr !!! Note "`docker compose run --rm`" Including `--rm` will remove the container after completion, and is highly recommended for all modes except trading mode (running with `freqtrade trade` command). -??? Note "Using docker without docker" +??? Note "Using docker without docker compose" "`docker compose run --rm`" will require a compose file to be provided. Some freqtrade commands that don't require authentication such as `list-pairs` can be run with "`docker run --rm`" instead. For example `docker run --rm freqtradeorg/freqtrade:stable list-pairs --exchange binance --quote BTC --print-json`. @@ -172,7 +175,7 @@ You can then run `docker compose build --pull` to build the docker image, and ru ### Plotting with docker -Commands `freqtrade plot-profit` and `freqtrade plot-dataframe` ([Documentation](plotting.md)) are available by changing the image to `*_plot` in your docker-compose.yml file. +Commands `freqtrade plot-profit` and `freqtrade plot-dataframe` ([Documentation](plotting.md)) are available by changing the image to `*_plot` in your `docker-compose.yml` file. You can then use these commands as follows: ``` bash @@ -203,16 +206,20 @@ docker compose -f docker/docker-compose-jupyter.yml build --no-cache ### Docker on Windows -* Error: `"Timestamp for this request is outside of the recvWindow."` - * The market api requests require a synchronized clock but the time in the docker container shifts a bit over time into the past. - To fix this issue temporarily you need to run `wsl --shutdown` and restart docker again (a popup on windows 10 will ask you to do so). - A permanent solution is either to host the docker container on a linux host or restart the wsl from time to time with the scheduler. +* Error: `"Timestamp for this request is outside of the recvWindow."` + The market api requests require a synchronized clock but the time in the docker container shifts a bit over time into the past. + To fix this issue temporarily you need to run `wsl --shutdown` and restart docker again (a popup on windows 10 will ask you to do so). + A permanent solution is either to host the docker container on a linux host or restart the wsl from time to time with the scheduler. - ``` bash - taskkill /IM "Docker Desktop.exe" /F - wsl --shutdown - start "" "C:\Program Files\Docker\Docker\Docker Desktop.exe" - ``` + ``` bash + taskkill /IM "Docker Desktop.exe" /F + wsl --shutdown + start "" "C:\Program Files\Docker\Docker\Docker Desktop.exe" + ``` + +* Cannot connect to the API (Windows) + If you're on windows and just installed Docker (desktop), make sure to reboot your System. Docker can have problems with network connectivity without a restart. + You should obviously also make sure to have your [settings](#accessing-the-ui) accordingly. !!! Warning Due to the above, we do not recommend the usage of docker on windows for production setups, but only for experimentation, datadownload and backtesting. diff --git a/docs/faq.md b/docs/faq.md index 7b8cc2580..50aaa03a3 100644 --- a/docs/faq.md +++ b/docs/faq.md @@ -20,7 +20,7 @@ Futures trading is supported for selected exchanges. Please refer to the [docume * When you work with your strategy & hyperopt file you should use a proper code editor like VSCode or PyCharm. A good code editor will provide syntax highlighting as well as line numbers, making it easy to find syntax errors (most likely pointed out by Freqtrade during startup). -## Freqtrade common issues +## Freqtrade common questions ### Can freqtrade open multiple positions on the same pair in parallel? @@ -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). @@ -78,6 +78,14 @@ Where possible (e.g. on binance), the use of the exchange's dedicated fee curren On binance, it's sufficient to have BNB in your account, and have "Pay fees in BNB" enabled in your profile. Your BNB balance will slowly decline (as it's used to pay fees) - but you'll no longer encounter dust (Freqtrade will include the fees in the profit calculations). Other exchanges don't offer such possibilities, where it's simply something you'll have to accept or move to a different exchange. +### I deposited more funds to the exchange, but my bot doesn't recognize this + +Freqtrade will update the exchange balance when necessary (Before placing an order). +RPC calls (Telegram's `/balance`, API calls to `/balance`) can trigger an update at max. once per hour. + +If `adjust_trade_position` is enabled (and the bot has open trades eligible for position adjustments) - then the wallets will be refreshed once per hour. +To force an immediate update, you can use `/reload_config` - which will restart the bot. + ### I want to use incomplete candles Freqtrade will not provide incomplete candles to strategies. Using incomplete candles will lead to repainting and consequently to strategies with "ghost" buys, which are impossible to both backtest, and verify after they happened. diff --git a/docs/freqai-parameter-table.md b/docs/freqai-parameter-table.md index 5e60d2a07..95687c7ab 100644 --- a/docs/freqai-parameter-table.md +++ b/docs/freqai-parameter-table.md @@ -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.
**Datatype:** int.
Default: `100`. -| `batch_size` | The size of the batches to use during training..
**Datatype:** int.
Default: `64`. -| `max_n_eval_batches` | The maximum number batches to use for evaluation..
**Datatype:** int, optional.
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.

**Datatype:** int. optional.
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:

n_epochs = n_steps / (n_obs / batch_size)

The motivation here is that `n_steps` is easier to optimize and keep stable across different n_obs - the number of data points.

**Datatype:** int. optional.
Default: `None`. +| `batch_size` | The size of the batches to use during training.

**Datatype:** int.
Default: `64`. ### Additional parameters diff --git a/docs/freqai-reinforcement-learning.md b/docs/freqai-reinforcement-learning.md index 1c95409ae..df4508c86 100644 --- a/docs/freqai-reinforcement-learning.md +++ b/docs/freqai-reinforcement-learning.md @@ -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. """ diff --git a/docs/hyperopt.md b/docs/hyperopt.md index b0920f9c4..3fbbee7f6 100644 --- a/docs/hyperopt.md +++ b/docs/hyperopt.md @@ -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 ``` diff --git a/docs/installation.md b/docs/installation.md index a06968dba..a89c83d28 100644 --- a/docs/installation.md +++ b/docs/installation.md @@ -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 @@ -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 diff --git a/docs/lookahead-analysis.md b/docs/lookahead-analysis.md index 9d57de779..e998b1b77 100644 --- a/docs/lookahead-analysis.md +++ b/docs/lookahead-analysis.md @@ -21,7 +21,10 @@ It also supports the lookahead-analysis of freqai strategies. - `--cache` is forced to "none". - `--max-open-trades` is forced to be at least equal to the number of pairs. -- `--dry-run-wallet` is forced to be basically infinite. +- `--dry-run-wallet` is forced to be basically infinite (1 billion). +- `--stake-amount` is forced to be a static 10000 (10k). + +Those are set to avoid users accidentally generating false positives. ## Lookahead-analysis command reference diff --git a/docs/sandbox-testing.md b/docs/sandbox-testing.md deleted file mode 100644 index 2c0f306cf..000000000 --- a/docs/sandbox-testing.md +++ /dev/null @@ -1,121 +0,0 @@ -# Sandbox API testing - -Some exchanges provide sandboxes or testbeds for risk-free testing, while running the bot against a real exchange. -With some configuration, freqtrade (in combination with ccxt) provides access to these. - -This document is an overview to configure Freqtrade to be used with sandboxes. -This can be useful to developers and trader alike. - -!!! Warning - Sandboxes usually have very low volume, and either a very wide spread, or no orders available at all. - Therefore, sandboxes will usually not do a good job of showing you how a strategy would work in real trading. - -## Exchanges known to have a sandbox / testnet - -* [binance](https://testnet.binance.vision/) -* [coinbasepro](https://public.sandbox.pro.coinbase.com) -* [gemini](https://exchange.sandbox.gemini.com/) -* [huobipro](https://www.testnet.huobi.pro/) -* [kucoin](https://sandbox.kucoin.com/) -* [phemex](https://testnet.phemex.com/) - -!!! Note - We did not test correct functioning of all of the above testnets. Please report your experiences with each sandbox. - ---- - -## Configure a Sandbox account - -When testing your API connectivity, make sure to use the appropriate sandbox / testnet URL. - -In general, you should follow these steps to enable an exchange's sandbox: - -* Figure out if an exchange has a sandbox (most likely by using google or the exchange's support documents) -* Create a sandbox account (often the sandbox-account requires separate registration) -* [Add some test assets to account](#add-test-funds) -* Create API keys - -### Add test funds - -Usually, sandbox exchanges allow depositing funds directly via web-interface. -You should make sure to have a realistic amount of funds available to your test-account, so results are representable of your real account funds. - -!!! Warning - Test exchanges will **NEVER** require your real credit card or banking details! - -## Configure freqtrade to use a exchange's sandbox - -### Sandbox URLs - -Freqtrade makes use of CCXT which in turn provides a list of URLs to Freqtrade. -These include `['test']` and `['api']`. - -* `[Test]` if available will point to an Exchanges sandbox. -* `[Api]` normally used, and resolves to live API target on the exchange. - -To make use of sandbox / test add "sandbox": true, to your config.json - -```json - "exchange": { - "name": "coinbasepro", - "sandbox": true, - "key": "5wowfxemogxeowo;heiohgmd", - "secret": "/ZMH1P62rCVmwefewrgcewX8nh4gob+lywxfwfxwwfxwfNsH1ySgvWCUR/w==", - "password": "1bkjfkhfhfu6sr", - "outdated_offset": 5 - "pair_whitelist": [ - "BTC/USD" - ] - }, - "datadir": "user_data/data/coinbasepro_sandbox" -``` - -Also the following information: - -* api-key (created for the sandbox webpage) -* api-secret (noted earlier) -* password (the passphrase - noted earlier) - -!!! Tip "Different data directory" - We also recommend to set `datadir` to something identifying downloaded data as sandbox data, to avoid having sandbox data mixed with data from the real exchange. - This can be done by adding the `"datadir"` key to the configuration. - Now, whenever you use this configuration, your data directory will be set to this directory. - ---- - -## You should now be ready to test your sandbox - -Ensure Freqtrade logs show the sandbox URL, and trades made are shown in sandbox. Also make sure to select a pair which shows at least some decent value (which very often is BTC/). - -## Common problems with sandbox exchanges - -Sandbox exchange instances often have very low volume, which can cause some problems which usually are not seen on a real exchange instance. - -### Old Candles problem - -Since Sandboxes often have low volume, candles can be quite old and show no volume. -To disable the error "Outdated history for pair ...", best increase the parameter `"outdated_offset"` to a number that seems realistic for the sandbox you're using. - -### Unfilled orders - -Sandboxes often have very low volumes - which means that many trades can go unfilled, or can go unfilled for a very long time. - -To mitigate this, you can try to match the first order on the opposite orderbook side using the following configuration: - -``` jsonc - "order_types": { - "entry": "limit", - "exit": "limit" - // ... - }, - "entry_pricing": { - "price_side": "other", - // ... - }, - "exit_pricing":{ - "price_side": "other", - // ... - }, - ``` - - The configuration is similar to the suggested configuration for market orders - however by using limit-orders you can avoid moving the price too much, and you can set the worst price you might get. diff --git a/docs/utils.md b/docs/utils.md index 900856af4..65ab50b9e 100644 --- a/docs/utils.md +++ b/docs/utils.md @@ -967,7 +967,7 @@ Print trades with id 2 and 3 as json freqtrade show-trades --db-url sqlite:///tradesv3.sqlite --trade-ids 2 3 --print-json ``` -### Strategy-Updater +## Strategy-Updater Updates listed strategies or all strategies within the strategies folder to be v3 compliant. If the command runs without --strategy-list then all strategies inside the strategies folder will be converted. diff --git a/docs/windows_installation.md b/docs/windows_installation.md index 0327f21e5..db785a1fc 100644 --- a/docs/windows_installation.md +++ b/docs/windows_installation.md @@ -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 diff --git a/freqtrade/commands/build_config_commands.py b/freqtrade/commands/build_config_commands.py index 311622458..3b0c39921 100644 --- a/freqtrade/commands/build_config_commands.py +++ b/freqtrade/commands/build_config_commands.py @@ -10,7 +10,7 @@ from freqtrade.configuration.directory_operations import chown_user_directory from freqtrade.constants import UNLIMITED_STAKE_AMOUNT from freqtrade.exceptions import OperationalException from freqtrade.exchange import MAP_EXCHANGE_CHILDCLASS, available_exchanges -from freqtrade.misc import render_template +from freqtrade.util import render_template logger = logging.getLogger(__name__) diff --git a/freqtrade/commands/deploy_commands.py b/freqtrade/commands/deploy_commands.py index 9ec33eac4..75da2552e 100644 --- a/freqtrade/commands/deploy_commands.py +++ b/freqtrade/commands/deploy_commands.py @@ -10,7 +10,7 @@ from freqtrade.configuration.directory_operations import copy_sample_files, crea from freqtrade.constants import USERPATH_STRATEGIES from freqtrade.enums import RunMode from freqtrade.exceptions import OperationalException -from freqtrade.misc import render_template, render_template_with_fallback +from freqtrade.util import render_template, render_template_with_fallback logger = logging.getLogger(__name__) @@ -35,6 +35,10 @@ def deploy_new_strategy(strategy_name: str, strategy_path: Path, subtemplate: st Deploy new strategy from template to strategy_path """ fallback = 'full' + attributes = render_template_with_fallback( + templatefile=f"strategy_subtemplates/strategy_attributes_{subtemplate}.j2", + templatefallbackfile=f"strategy_subtemplates/strategy_attributes_{fallback}.j2", + ) indicators = render_template_with_fallback( templatefile=f"strategy_subtemplates/indicators_{subtemplate}.j2", templatefallbackfile=f"strategy_subtemplates/indicators_{fallback}.j2", @@ -58,6 +62,7 @@ def deploy_new_strategy(strategy_name: str, strategy_path: Path, subtemplate: st strategy_text = render_template(templatefile='base_strategy.py.j2', arguments={"strategy": strategy_name, + "attributes": attributes, "indicators": indicators, "buy_trend": buy_trend, "sell_trend": sell_trend, diff --git a/freqtrade/commands/webserver_commands.py b/freqtrade/commands/webserver_commands.py index 9a5975227..2fd7fe75c 100644 --- a/freqtrade/commands/webserver_commands.py +++ b/freqtrade/commands/webserver_commands.py @@ -7,9 +7,10 @@ def start_webserver(args: Dict[str, Any]) -> None: """ Main entry point for webserver mode """ - from freqtrade.configuration import Configuration + from freqtrade.configuration import setup_utils_configuration from freqtrade.rpc.api_server import ApiServer # Initialize configuration - config = Configuration(args, RunMode.WEBSERVER).get_config() + + config = setup_utils_configuration(args, RunMode.WEBSERVER) ApiServer(config, standalone=True) diff --git a/freqtrade/configuration/config_validation.py b/freqtrade/configuration/config_validation.py index f1745df61..395826557 100644 --- a/freqtrade/configuration/config_validation.py +++ b/freqtrade/configuration/config_validation.py @@ -51,6 +51,8 @@ def validate_config_schema(conf: Dict[str, Any], preliminary: bool = False) -> D conf_schema['required'] = constants.SCHEMA_BACKTEST_REQUIRED else: conf_schema['required'] = constants.SCHEMA_BACKTEST_REQUIRED_FINAL + elif conf.get('runmode', RunMode.OTHER) == RunMode.WEBSERVER: + conf_schema['required'] = constants.SCHEMA_MINIMAL_WEBSERVER else: conf_schema['required'] = constants.SCHEMA_MINIMAL_REQUIRED try: diff --git a/freqtrade/constants.py b/freqtrade/constants.py index 4b3cff7a1..9a8d17909 100644 --- a/freqtrade/constants.py +++ b/freqtrade/constants.py @@ -461,7 +461,6 @@ CONF_SCHEMA = { 'type': 'object', 'properties': { 'name': {'type': 'string'}, - 'sandbox': {'type': 'boolean', 'default': False}, 'key': {'type': 'string', 'default': ''}, 'secret': {'type': 'string', 'default': ''}, 'password': {'type': 'string', 'default': ''}, @@ -668,6 +667,9 @@ SCHEMA_MINIMAL_REQUIRED = [ 'dataformat_ohlcv', 'dataformat_trades', ] +SCHEMA_MINIMAL_WEBSERVER = SCHEMA_MINIMAL_REQUIRED + [ + 'api_server', +] CANCEL_REASON = { "TIMEOUT": "cancelled due to timeout", diff --git a/freqtrade/data/btanalysis.py b/freqtrade/data/btanalysis.py index 206588d37..96ab4927e 100644 --- a/freqtrade/data/btanalysis.py +++ b/freqtrade/data/btanalysis.py @@ -12,7 +12,7 @@ import pandas as pd from freqtrade.constants import LAST_BT_RESULT_FN, IntOrInf from freqtrade.exceptions import OperationalException -from freqtrade.misc import json_load +from freqtrade.misc import file_dump_json, json_load from freqtrade.optimize.backtest_caching import get_backtest_metadata_filename from freqtrade.persistence import LocalTrade, Trade, init_db from freqtrade.types import BacktestHistoryEntryType, BacktestResultType @@ -175,6 +175,21 @@ def _get_backtest_files(dirname: Path) -> List[Path]: return list(reversed(sorted(dirname.glob('backtest-result-*-[0-9][0-9].json')))) +def get_backtest_result(filename: Path) -> List[BacktestHistoryEntryType]: + """ + Get backtest result read from metadata file + """ + return [ + { + 'filename': filename.stem, + 'strategy': s, + 'notes': v.get('notes', ''), + 'run_id': v['run_id'], + 'backtest_start_time': v['backtest_start_time'], + } for s, v in load_backtest_metadata(filename).items() + ] + + def get_backtest_resultlist(dirname: Path) -> List[BacktestHistoryEntryType]: """ Get list of backtest results read from metadata files @@ -184,6 +199,7 @@ def get_backtest_resultlist(dirname: Path) -> List[BacktestHistoryEntryType]: 'filename': filename.stem, 'strategy': s, 'run_id': v['run_id'], + 'notes': v.get('notes', ''), 'backtest_start_time': v['backtest_start_time'], } for filename in _get_backtest_files(dirname) @@ -203,6 +219,21 @@ def delete_backtest_result(file_abs: Path): file_abs_meta.unlink() +def update_backtest_metadata(filename: Path, strategy: str, content: Dict[str, Any]): + """ + Updates backtest metadata file with new content. + :raises: ValueError if metadata file does not exist, or strategy is not in this file. + """ + metadata = load_backtest_metadata(filename) + if not metadata: + raise ValueError("File does not exist.") + if strategy not in metadata: + raise ValueError("Strategy not in metadata.") + metadata[strategy].update(content) + # Write data again. + file_dump_json(get_backtest_metadata_filename(filename), metadata) + + def find_existing_backtest_stats(dirname: Union[Path, str], run_ids: Dict[str, str], min_backtest_date: Optional[datetime] = None) -> Dict[str, Any]: """ diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py index e7ba20c44..11cbd7934 100644 --- a/freqtrade/data/dataprovider.py +++ b/freqtrade/data/dataprovider.py @@ -17,7 +17,7 @@ from freqtrade.constants import (FULL_DATAFRAME_THRESHOLD, Config, ListPairsWith from freqtrade.data.history import load_pair_history from freqtrade.enums import CandleType, RPCMessageType, RunMode from freqtrade.exceptions import ExchangeError, OperationalException -from freqtrade.exchange import Exchange, timeframe_to_seconds +from freqtrade.exchange import Exchange, timeframe_to_prev_date, timeframe_to_seconds from freqtrade.exchange.types import OrderBook from freqtrade.misc import append_candles_to_dataframe from freqtrade.rpc import RPCManager @@ -46,6 +46,8 @@ class DataProvider: self.__rpc = rpc self.__cached_pairs: Dict[PairWithTimeframe, Tuple[DataFrame, datetime]] = {} self.__slice_index: Optional[int] = None + self.__slice_date: Optional[datetime] = None + self.__cached_pairs_backtesting: Dict[PairWithTimeframe, DataFrame] = {} self.__producer_pairs_df: Dict[str, Dict[PairWithTimeframe, Tuple[DataFrame, datetime]]] = {} @@ -64,10 +66,19 @@ class DataProvider: def _set_dataframe_max_index(self, limit_index: int): """ Limit analyzed dataframe to max specified index. + Only relevant in backtesting. :param limit_index: dataframe index. """ self.__slice_index = limit_index + def _set_dataframe_max_date(self, limit_date: datetime): + """ + Limit infomrative dataframe to max specified index. + Only relevant in backtesting. + :param limit_date: "current date" + """ + self.__slice_date = limit_date + def _set_cached_df( self, pair: str, @@ -284,7 +295,7 @@ class DataProvider: def historic_ohlcv( self, pair: str, - timeframe: Optional[str] = None, + timeframe: str, candle_type: str = '' ) -> DataFrame: """ @@ -307,7 +318,7 @@ class DataProvider: timerange.subtract_start(tf_seconds * startup_candles) self.__cached_pairs_backtesting[saved_pair] = load_pair_history( pair=pair, - timeframe=timeframe or self._config['timeframe'], + timeframe=timeframe, datadir=self._config['datadir'], timerange=timerange, data_format=self._config['dataformat_ohlcv'], @@ -354,7 +365,13 @@ class DataProvider: data = self.ohlcv(pair=pair, timeframe=timeframe, candle_type=candle_type) else: # Get historical OHLCV data (cached on disk). + timeframe = timeframe or self._config['timeframe'] data = self.historic_ohlcv(pair=pair, timeframe=timeframe, candle_type=candle_type) + # Cut date to timeframe-specific date. + # This is necessary to prevent lookahead bias in callbacks through informative pairs. + if self.__slice_date: + cutoff_date = timeframe_to_prev_date(timeframe, self.__slice_date) + data = data.loc[data['date'] < cutoff_date] if len(data) == 0: logger.warning(f"No data found for ({pair}, {timeframe}, {candle_type}).") return data diff --git a/freqtrade/exchange/binance_leverage_tiers.json b/freqtrade/exchange/binance_leverage_tiers.json index 7be7a9d29..a4a81abb3 100644 --- a/freqtrade/exchange/binance_leverage_tiers.json +++ b/freqtrade/exchange/binance_leverage_tiers.json @@ -590,13 +590,13 @@ "tier": 3.0, "currency": "USDT", "minNotional": 25000.0, - "maxNotional": 100000.0, + "maxNotional": 150000.0, "maintenanceMarginRate": 0.01, "maxLeverage": 25.0, "info": { "bracket": "3", "initialLeverage": "25", - "notionalCap": "100000", + "notionalCap": "150000", "notionalFloor": "25000", "maintMarginRatio": "0.01", "cum": "67.5" @@ -605,87 +605,87 @@ { "tier": 4.0, "currency": "USDT", - "minNotional": 100000.0, - "maxNotional": 300000.0, + "minNotional": 150000.0, + "maxNotional": 600000.0, "maintenanceMarginRate": 0.025, "maxLeverage": 20.0, "info": { "bracket": "4", "initialLeverage": "20", - "notionalCap": "300000", - "notionalFloor": "100000", + "notionalCap": "600000", + "notionalFloor": "150000", "maintMarginRatio": "0.025", - "cum": "1567.5" + "cum": "2317.5" } }, { "tier": 5.0, "currency": "USDT", - "minNotional": 300000.0, - "maxNotional": 750000.0, + "minNotional": 600000.0, + "maxNotional": 1500000.0, "maintenanceMarginRate": 0.05, "maxLeverage": 10.0, "info": { "bracket": "5", "initialLeverage": "10", - "notionalCap": "750000", - "notionalFloor": "300000", + "notionalCap": "1500000", + "notionalFloor": "600000", "maintMarginRatio": "0.05", - "cum": "9067.5" + "cum": "17317.5" } }, { "tier": 6.0, "currency": "USDT", - "minNotional": 750000.0, - "maxNotional": 1500000.0, + "minNotional": 1500000.0, + "maxNotional": 3000000.0, "maintenanceMarginRate": 0.1, "maxLeverage": 5.0, "info": { "bracket": "6", "initialLeverage": "5", - "notionalCap": "1500000", - "notionalFloor": "750000", + "notionalCap": "3000000", + "notionalFloor": "1500000", "maintMarginRatio": "0.1", - "cum": "46567.5" + "cum": "92317.5" } }, { "tier": 7.0, "currency": "USDT", - "minNotional": 1500000.0, - "maxNotional": 3000000.0, + "minNotional": 3000000.0, + "maxNotional": 5000000.0, "maintenanceMarginRate": 0.125, "maxLeverage": 4.0, "info": { "bracket": "7", "initialLeverage": "4", - "notionalCap": "3000000", - "notionalFloor": "1500000", + "notionalCap": "5000000", + "notionalFloor": "3000000", "maintMarginRatio": "0.125", - "cum": "84067.5" + "cum": "167317.5" } }, { "tier": 8.0, "currency": "USDT", - "minNotional": 3000000.0, - "maxNotional": 6000000.0, + "minNotional": 5000000.0, + "maxNotional": 9000000.0, "maintenanceMarginRate": 0.25, "maxLeverage": 2.0, "info": { "bracket": "8", "initialLeverage": "2", - "notionalCap": "6000000", - "notionalFloor": "3000000", + "notionalCap": "9000000", + "notionalFloor": "5000000", "maintMarginRatio": "0.25", - "cum": "459067.5" + "cum": "792317.5" } }, { "tier": 9.0, "currency": "USDT", - "minNotional": 6000000.0, + "minNotional": 9000000.0, "maxNotional": 30000000.0, "maintenanceMarginRate": 0.5, "maxLeverage": 1.0, @@ -693,9 +693,9 @@ "bracket": "9", "initialLeverage": "1", "notionalCap": "30000000", - "notionalFloor": "6000000", + "notionalFloor": "9000000", "maintMarginRatio": "0.5", - "cum": "1959067.5" + "cum": "3042317.5" } } ], @@ -1114,10 +1114,10 @@ "minNotional": 0.0, "maxNotional": 100000.0, "maintenanceMarginRate": 0.025, - "maxLeverage": 20.0, + "maxLeverage": 10.0, "info": { "bracket": "1", - "initialLeverage": "20", + "initialLeverage": "10", "notionalCap": "100000", "notionalFloor": "0", "maintMarginRatio": "0.025", @@ -1130,10 +1130,10 @@ "minNotional": 100000.0, "maxNotional": 500000.0, "maintenanceMarginRate": 0.05, - "maxLeverage": 10.0, + "maxLeverage": 8.0, "info": { "bracket": "2", - "initialLeverage": "10", + "initialLeverage": "8", "notionalCap": "500000", "notionalFloor": "100000", "maintMarginRatio": "0.05", @@ -1192,13 +1192,13 @@ "tier": 6.0, "currency": "BUSD", "minNotional": 5000000.0, - "maxNotional": 8000000.0, + "maxNotional": 5500000.0, "maintenanceMarginRate": 0.5, "maxLeverage": 1.0, "info": { "bracket": "6", "initialLeverage": "1", - "notionalCap": "8000000", + "notionalCap": "5500000", "notionalFloor": "5000000", "maintMarginRatio": "0.5", "cum": "1527500.0" @@ -2759,14 +2759,14 @@ "currency": "USDT", "minNotional": 0.0, "maxNotional": 5000.0, - "maintenanceMarginRate": 0.02, - "maxLeverage": 25.0, + "maintenanceMarginRate": 0.025, + "maxLeverage": 20.0, "info": { "bracket": "1", - "initialLeverage": "25", + "initialLeverage": "20", "notionalCap": "5000", "notionalFloor": "0", - "maintMarginRatio": "0.02", + "maintMarginRatio": "0.025", "cum": "0.0" } }, @@ -2775,37 +2775,37 @@ "currency": "USDT", "minNotional": 5000.0, "maxNotional": 25000.0, - "maintenanceMarginRate": 0.025, - "maxLeverage": 20.0, + "maintenanceMarginRate": 0.05, + "maxLeverage": 10.0, "info": { "bracket": "2", - "initialLeverage": "20", + "initialLeverage": "10", "notionalCap": "25000", "notionalFloor": "5000", - "maintMarginRatio": "0.025", - "cum": "25.0" + "maintMarginRatio": "0.05", + "cum": "125.0" } }, { "tier": 3.0, "currency": "USDT", "minNotional": 25000.0, - "maxNotional": 600000.0, - "maintenanceMarginRate": 0.05, - "maxLeverage": 10.0, + "maxNotional": 500000.0, + "maintenanceMarginRate": 0.06, + "maxLeverage": 8.0, "info": { "bracket": "3", - "initialLeverage": "10", - "notionalCap": "600000", + "initialLeverage": "8", + "notionalCap": "500000", "notionalFloor": "25000", - "maintMarginRatio": "0.05", - "cum": "650.0" + "maintMarginRatio": "0.06", + "cum": "375.0" } }, { "tier": 4.0, "currency": "USDT", - "minNotional": 600000.0, + "minNotional": 500000.0, "maxNotional": 1600000.0, "maintenanceMarginRate": 0.1, "maxLeverage": 5.0, @@ -2813,9 +2813,9 @@ "bracket": "4", "initialLeverage": "5", "notionalCap": "1600000", - "notionalFloor": "600000", + "notionalFloor": "500000", "maintMarginRatio": "0.1", - "cum": "30650.0" + "cum": "20375.0" } }, { @@ -2831,39 +2831,39 @@ "notionalCap": "2000000", "notionalFloor": "1600000", "maintMarginRatio": "0.125", - "cum": "70650.0" + "cum": "60375.0" } }, { "tier": 6.0, "currency": "USDT", "minNotional": 2000000.0, - "maxNotional": 6000000.0, + "maxNotional": 3000000.0, "maintenanceMarginRate": 0.25, "maxLeverage": 2.0, "info": { "bracket": "6", "initialLeverage": "2", - "notionalCap": "6000000", + "notionalCap": "3000000", "notionalFloor": "2000000", "maintMarginRatio": "0.25", - "cum": "320650.0" + "cum": "310375.0" } }, { "tier": 7.0, "currency": "USDT", - "minNotional": 6000000.0, - "maxNotional": 10000000.0, + "minNotional": 3000000.0, + "maxNotional": 4000000.0, "maintenanceMarginRate": 0.5, "maxLeverage": 1.0, "info": { "bracket": "7", "initialLeverage": "1", - "notionalCap": "10000000", - "notionalFloor": "6000000", + "notionalCap": "4000000", + "notionalFloor": "3000000", "maintMarginRatio": "0.5", - "cum": "1820650.0" + "cum": "1060375.0" } } ], @@ -5413,14 +5413,14 @@ "currency": "USDT", "minNotional": 0.0, "maxNotional": 5000.0, - "maintenanceMarginRate": 0.02, - "maxLeverage": 20.0, + "maintenanceMarginRate": 0.025, + "maxLeverage": 8.0, "info": { "bracket": "1", - "initialLeverage": "20", + "initialLeverage": "8", "notionalCap": "5000", "notionalFloor": "0", - "maintMarginRatio": "0.02", + "maintMarginRatio": "0.025", "cum": "0.0" } }, @@ -5428,80 +5428,64 @@ "tier": 2.0, "currency": "USDT", "minNotional": 5000.0, - "maxNotional": 25000.0, - "maintenanceMarginRate": 0.025, - "maxLeverage": 10.0, + "maxNotional": 100000.0, + "maintenanceMarginRate": 0.05, + "maxLeverage": 6.0, "info": { "bracket": "2", - "initialLeverage": "10", - "notionalCap": "25000", + "initialLeverage": "6", + "notionalCap": "100000", "notionalFloor": "5000", - "maintMarginRatio": "0.025", - "cum": "25.0" + "maintMarginRatio": "0.05", + "cum": "125.0" } }, { "tier": 3.0, "currency": "USDT", - "minNotional": 25000.0, - "maxNotional": 100000.0, - "maintenanceMarginRate": 0.05, - "maxLeverage": 8.0, - "info": { - "bracket": "3", - "initialLeverage": "8", - "notionalCap": "100000", - "notionalFloor": "25000", - "maintMarginRatio": "0.05", - "cum": "650.0" - } - }, - { - "tier": 4.0, - "currency": "USDT", "minNotional": 100000.0, "maxNotional": 250000.0, "maintenanceMarginRate": 0.1, "maxLeverage": 5.0, "info": { - "bracket": "4", + "bracket": "3", "initialLeverage": "5", "notionalCap": "250000", "notionalFloor": "100000", "maintMarginRatio": "0.1", - "cum": "5650.0" + "cum": "5125.0" } }, { - "tier": 5.0, + "tier": 4.0, "currency": "USDT", "minNotional": 250000.0, "maxNotional": 1000000.0, "maintenanceMarginRate": 0.125, "maxLeverage": 2.0, "info": { - "bracket": "5", + "bracket": "4", "initialLeverage": "2", "notionalCap": "1000000", "notionalFloor": "250000", "maintMarginRatio": "0.125", - "cum": "11900.0" + "cum": "11375.0" } }, { - "tier": 6.0, + "tier": 5.0, "currency": "USDT", "minNotional": 1000000.0, - "maxNotional": 2000000.0, + "maxNotional": 1200000.0, "maintenanceMarginRate": 0.5, "maxLeverage": 1.0, "info": { - "bracket": "6", + "bracket": "5", "initialLeverage": "1", - "notionalCap": "2000000", + "notionalCap": "1200000", "notionalFloor": "1000000", "maintMarginRatio": "0.5", - "cum": "386900.0" + "cum": "386375.0" } } ], @@ -5765,6 +5749,120 @@ } } ], + "BNT/USDT:USDT": [ + { + "tier": 1.0, + "currency": "USDT", + "minNotional": 0.0, + "maxNotional": 5000.0, + "maintenanceMarginRate": 0.02, + "maxLeverage": 20.0, + "info": { + "bracket": "1", + "initialLeverage": "20", + "notionalCap": "5000", + "notionalFloor": "0", + "maintMarginRatio": "0.02", + "cum": "0.0" + } + }, + { + "tier": 2.0, + "currency": "USDT", + "minNotional": 5000.0, + "maxNotional": 25000.0, + "maintenanceMarginRate": 0.025, + "maxLeverage": 15.0, + "info": { + "bracket": "2", + "initialLeverage": "15", + "notionalCap": "25000", + "notionalFloor": "5000", + "maintMarginRatio": "0.025", + "cum": "25.0" + } + }, + { + "tier": 3.0, + "currency": "USDT", + "minNotional": 25000.0, + "maxNotional": 200000.0, + "maintenanceMarginRate": 0.05, + "maxLeverage": 10.0, + "info": { + "bracket": "3", + "initialLeverage": "10", + "notionalCap": "200000", + "notionalFloor": "25000", + "maintMarginRatio": "0.05", + "cum": "650.0" + } + }, + { + "tier": 4.0, + "currency": "USDT", + "minNotional": 200000.0, + "maxNotional": 500000.0, + "maintenanceMarginRate": 0.1, + "maxLeverage": 5.0, + "info": { + "bracket": "4", + "initialLeverage": "5", + "notionalCap": "500000", + "notionalFloor": "200000", + "maintMarginRatio": "0.1", + "cum": "10650.0" + } + }, + { + "tier": 5.0, + "currency": "USDT", + "minNotional": 500000.0, + "maxNotional": 1000000.0, + "maintenanceMarginRate": 0.125, + "maxLeverage": 4.0, + "info": { + "bracket": "5", + "initialLeverage": "4", + "notionalCap": "1000000", + "notionalFloor": "500000", + "maintMarginRatio": "0.125", + "cum": "23150.0" + } + }, + { + "tier": 6.0, + "currency": "USDT", + "minNotional": 1000000.0, + "maxNotional": 3000000.0, + "maintenanceMarginRate": 0.25, + "maxLeverage": 2.0, + "info": { + "bracket": "6", + "initialLeverage": "2", + "notionalCap": "3000000", + "notionalFloor": "1000000", + "maintMarginRatio": "0.25", + "cum": "148150.0" + } + }, + { + "tier": 7.0, + "currency": "USDT", + "minNotional": 3000000.0, + "maxNotional": 5000000.0, + "maintenanceMarginRate": 0.5, + "maxLeverage": 1.0, + "info": { + "bracket": "7", + "initialLeverage": "1", + "notionalCap": "5000000", + "notionalFloor": "3000000", + "maintMarginRatio": "0.5", + "cum": "898150.0" + } + } + ], "BNX/USDT:USDT": [ { "tier": 1.0, @@ -7626,13 +7724,13 @@ "tier": 3.0, "currency": "USDT", "minNotional": 50000.0, - "maxNotional": 200000.0, + "maxNotional": 400000.0, "maintenanceMarginRate": 0.05, "maxLeverage": 10.0, "info": { "bracket": "3", "initialLeverage": "10", - "notionalCap": "200000", + "notionalCap": "400000", "notionalFloor": "50000", "maintMarginRatio": "0.05", "cum": "1325.0" @@ -7641,49 +7739,65 @@ { "tier": 4.0, "currency": "USDT", - "minNotional": 200000.0, - "maxNotional": 500000.0, + "minNotional": 400000.0, + "maxNotional": 1000000.0, "maintenanceMarginRate": 0.1, "maxLeverage": 5.0, "info": { "bracket": "4", "initialLeverage": "5", - "notionalCap": "500000", - "notionalFloor": "200000", + "notionalCap": "1000000", + "notionalFloor": "400000", "maintMarginRatio": "0.1", - "cum": "11325.0" + "cum": "21325.0" } }, { "tier": 5.0, "currency": "USDT", - "minNotional": 500000.0, - "maxNotional": 1000000.0, + "minNotional": 1000000.0, + "maxNotional": 1200000.0, "maintenanceMarginRate": 0.125, - "maxLeverage": 2.0, + "maxLeverage": 4.0, "info": { "bracket": "5", - "initialLeverage": "2", - "notionalCap": "1000000", - "notionalFloor": "500000", + "initialLeverage": "4", + "notionalCap": "1200000", + "notionalFloor": "1000000", "maintMarginRatio": "0.125", - "cum": "23825.0" + "cum": "46325.0" } }, { "tier": 6.0, "currency": "USDT", - "minNotional": 1000000.0, + "minNotional": 1200000.0, + "maxNotional": 2000000.0, + "maintenanceMarginRate": 0.25, + "maxLeverage": 2.0, + "info": { + "bracket": "6", + "initialLeverage": "2", + "notionalCap": "2000000", + "notionalFloor": "1200000", + "maintMarginRatio": "0.25", + "cum": "196325.0" + } + }, + { + "tier": 7.0, + "currency": "USDT", + "minNotional": 2000000.0, "maxNotional": 5000000.0, "maintenanceMarginRate": 0.5, "maxLeverage": 1.0, "info": { - "bracket": "6", + "bracket": "7", "initialLeverage": "1", "notionalCap": "5000000", - "notionalFloor": "1000000", + "notionalFloor": "2000000", "maintMarginRatio": "0.5", - "cum": "398825.0" + "cum": "696325.0" } } ], @@ -8900,6 +9014,88 @@ "tier": 1.0, "currency": "BUSD", "minNotional": 0.0, + "maxNotional": 25000.0, + "maintenanceMarginRate": 0.025, + "maxLeverage": 8.0, + "info": { + "bracket": "1", + "initialLeverage": "8", + "notionalCap": "25000", + "notionalFloor": "0", + "maintMarginRatio": "0.025", + "cum": "0.0" + } + }, + { + "tier": 2.0, + "currency": "BUSD", + "minNotional": 25000.0, + "maxNotional": 100000.0, + "maintenanceMarginRate": 0.05, + "maxLeverage": 6.0, + "info": { + "bracket": "2", + "initialLeverage": "6", + "notionalCap": "100000", + "notionalFloor": "25000", + "maintMarginRatio": "0.05", + "cum": "625.0" + } + }, + { + "tier": 3.0, + "currency": "BUSD", + "minNotional": 100000.0, + "maxNotional": 250000.0, + "maintenanceMarginRate": 0.1, + "maxLeverage": 5.0, + "info": { + "bracket": "3", + "initialLeverage": "5", + "notionalCap": "250000", + "notionalFloor": "100000", + "maintMarginRatio": "0.1", + "cum": "5625.0" + } + }, + { + "tier": 4.0, + "currency": "BUSD", + "minNotional": 250000.0, + "maxNotional": 1000000.0, + "maintenanceMarginRate": 0.125, + "maxLeverage": 2.0, + "info": { + "bracket": "4", + "initialLeverage": "2", + "notionalCap": "1000000", + "notionalFloor": "250000", + "maintMarginRatio": "0.125", + "cum": "11875.0" + } + }, + { + "tier": 5.0, + "currency": "BUSD", + "minNotional": 1000000.0, + "maxNotional": 1200000.0, + "maintenanceMarginRate": 0.5, + "maxLeverage": 1.0, + "info": { + "bracket": "5", + "initialLeverage": "1", + "notionalCap": "1200000", + "notionalFloor": "1000000", + "maintMarginRatio": "0.5", + "cum": "386875.0" + } + } + ], + "DODOX/USDT:USDT": [ + { + "tier": 1.0, + "currency": "USDT", + "minNotional": 0.0, "maxNotional": 5000.0, "maintenanceMarginRate": 0.02, "maxLeverage": 20.0, @@ -8914,14 +9110,14 @@ }, { "tier": 2.0, - "currency": "BUSD", + "currency": "USDT", "minNotional": 5000.0, "maxNotional": 25000.0, "maintenanceMarginRate": 0.025, - "maxLeverage": 10.0, + "maxLeverage": 15.0, "info": { "bracket": "2", - "initialLeverage": "10", + "initialLeverage": "15", "notionalCap": "25000", "notionalFloor": "5000", "maintMarginRatio": "0.025", @@ -8930,15 +9126,15 @@ }, { "tier": 3.0, - "currency": "BUSD", + "currency": "USDT", "minNotional": 25000.0, - "maxNotional": 100000.0, + "maxNotional": 200000.0, "maintenanceMarginRate": 0.05, - "maxLeverage": 8.0, + "maxLeverage": 10.0, "info": { "bracket": "3", - "initialLeverage": "8", - "notionalCap": "100000", + "initialLeverage": "10", + "notionalCap": "200000", "notionalFloor": "25000", "maintMarginRatio": "0.05", "cum": "650.0" @@ -8946,50 +9142,66 @@ }, { "tier": 4.0, - "currency": "BUSD", - "minNotional": 100000.0, - "maxNotional": 250000.0, + "currency": "USDT", + "minNotional": 200000.0, + "maxNotional": 500000.0, "maintenanceMarginRate": 0.1, "maxLeverage": 5.0, "info": { "bracket": "4", "initialLeverage": "5", - "notionalCap": "250000", - "notionalFloor": "100000", + "notionalCap": "500000", + "notionalFloor": "200000", "maintMarginRatio": "0.1", - "cum": "5650.0" + "cum": "10650.0" } }, { "tier": 5.0, - "currency": "BUSD", - "minNotional": 250000.0, + "currency": "USDT", + "minNotional": 500000.0, "maxNotional": 1000000.0, "maintenanceMarginRate": 0.125, - "maxLeverage": 2.0, + "maxLeverage": 4.0, "info": { "bracket": "5", - "initialLeverage": "2", + "initialLeverage": "4", "notionalCap": "1000000", - "notionalFloor": "250000", + "notionalFloor": "500000", "maintMarginRatio": "0.125", - "cum": "11900.0" + "cum": "23150.0" } }, { "tier": 6.0, - "currency": "BUSD", + "currency": "USDT", "minNotional": 1000000.0, "maxNotional": 3000000.0, + "maintenanceMarginRate": 0.25, + "maxLeverage": 2.0, + "info": { + "bracket": "6", + "initialLeverage": "2", + "notionalCap": "3000000", + "notionalFloor": "1000000", + "maintMarginRatio": "0.25", + "cum": "148150.0" + } + }, + { + "tier": 7.0, + "currency": "USDT", + "minNotional": 3000000.0, + "maxNotional": 5000000.0, "maintenanceMarginRate": 0.5, "maxLeverage": 1.0, "info": { - "bracket": "6", + "bracket": "7", "initialLeverage": "1", - "notionalCap": "3000000", - "notionalFloor": "1000000", + "notionalCap": "5000000", + "notionalFloor": "3000000", "maintMarginRatio": "0.5", - "cum": "386900.0" + "cum": "898150.0" } } ], @@ -16652,96 +16864,80 @@ "tier": 1.0, "currency": "USDT", "minNotional": 0.0, - "maxNotional": 5000.0, - "maintenanceMarginRate": 0.01, - "maxLeverage": 20.0, + "maxNotional": 25000.0, + "maintenanceMarginRate": 0.025, + "maxLeverage": 10.0, "info": { "bracket": "1", - "initialLeverage": "20", - "notionalCap": "5000", + "initialLeverage": "10", + "notionalCap": "25000", "notionalFloor": "0", - "maintMarginRatio": "0.01", + "maintMarginRatio": "0.025", "cum": "0.0" } }, { "tier": 2.0, "currency": "USDT", - "minNotional": 5000.0, - "maxNotional": 25000.0, - "maintenanceMarginRate": 0.025, - "maxLeverage": 10.0, - "info": { - "bracket": "2", - "initialLeverage": "10", - "notionalCap": "25000", - "notionalFloor": "5000", - "maintMarginRatio": "0.025", - "cum": "75.0" - } - }, - { - "tier": 3.0, - "currency": "USDT", "minNotional": 25000.0, "maxNotional": 100000.0, "maintenanceMarginRate": 0.05, "maxLeverage": 8.0, "info": { - "bracket": "3", + "bracket": "2", "initialLeverage": "8", "notionalCap": "100000", "notionalFloor": "25000", "maintMarginRatio": "0.05", - "cum": "700.0" + "cum": "625.0" } }, { - "tier": 4.0, + "tier": 3.0, "currency": "USDT", "minNotional": 100000.0, "maxNotional": 250000.0, "maintenanceMarginRate": 0.1, "maxLeverage": 5.0, "info": { - "bracket": "4", + "bracket": "3", "initialLeverage": "5", "notionalCap": "250000", "notionalFloor": "100000", "maintMarginRatio": "0.1", - "cum": "5700.0" + "cum": "5625.0" } }, { - "tier": 5.0, + "tier": 4.0, "currency": "USDT", "minNotional": 250000.0, "maxNotional": 1000000.0, "maintenanceMarginRate": 0.125, "maxLeverage": 2.0, "info": { - "bracket": "5", + "bracket": "4", "initialLeverage": "2", "notionalCap": "1000000", "notionalFloor": "250000", "maintMarginRatio": "0.125", - "cum": "11950.0" + "cum": "11875.0" } }, { - "tier": 6.0, + "tier": 5.0, "currency": "USDT", "minNotional": 1000000.0, - "maxNotional": 5000000.0, + "maxNotional": 3000000.0, "maintenanceMarginRate": 0.5, "maxLeverage": 1.0, "info": { - "bracket": "6", + "bracket": "5", "initialLeverage": "1", - "notionalCap": "5000000", + "notionalCap": "3000000", "notionalFloor": "1000000", "maintMarginRatio": "0.5", - "cum": "386950.0" + "cum": "386875.0" } } ], @@ -17712,10 +17908,10 @@ "minNotional": 0.0, "maxNotional": 5000.0, "maintenanceMarginRate": 0.02, - "maxLeverage": 25.0, + "maxLeverage": 10.0, "info": { "bracket": "1", - "initialLeverage": "25", + "initialLeverage": "10", "notionalCap": "5000", "notionalFloor": "0", "maintMarginRatio": "0.02", @@ -17728,10 +17924,10 @@ "minNotional": 5000.0, "maxNotional": 25000.0, "maintenanceMarginRate": 0.025, - "maxLeverage": 15.0, + "maxLeverage": 8.0, "info": { "bracket": "2", - "initialLeverage": "15", + "initialLeverage": "8", "notionalCap": "25000", "notionalFloor": "5000", "maintMarginRatio": "0.025", @@ -17744,10 +17940,10 @@ "minNotional": 25000.0, "maxNotional": 100000.0, "maintenanceMarginRate": 0.05, - "maxLeverage": 10.0, + "maxLeverage": 6.0, "info": { "bracket": "3", - "initialLeverage": "10", + "initialLeverage": "6", "notionalCap": "100000", "notionalFloor": "25000", "maintMarginRatio": "0.05", @@ -17806,13 +18002,13 @@ "tier": 7.0, "currency": "BUSD", "minNotional": 3000000.0, - "maxNotional": 8000000.0, + "maxNotional": 3500000.0, "maintenanceMarginRate": 0.5, "maxLeverage": 1.0, "info": { "bracket": "7", "initialLeverage": "1", - "notionalCap": "8000000", + "notionalCap": "3500000", "notionalFloor": "3000000", "maintMarginRatio": "0.5", "cum": "949400.0" @@ -19757,6 +19953,120 @@ } } ], + "OXT/USDT:USDT": [ + { + "tier": 1.0, + "currency": "USDT", + "minNotional": 0.0, + "maxNotional": 5000.0, + "maintenanceMarginRate": 0.02, + "maxLeverage": 20.0, + "info": { + "bracket": "1", + "initialLeverage": "20", + "notionalCap": "5000", + "notionalFloor": "0", + "maintMarginRatio": "0.02", + "cum": "0.0" + } + }, + { + "tier": 2.0, + "currency": "USDT", + "minNotional": 5000.0, + "maxNotional": 25000.0, + "maintenanceMarginRate": 0.025, + "maxLeverage": 15.0, + "info": { + "bracket": "2", + "initialLeverage": "15", + "notionalCap": "25000", + "notionalFloor": "5000", + "maintMarginRatio": "0.025", + "cum": "25.0" + } + }, + { + "tier": 3.0, + "currency": "USDT", + "minNotional": 25000.0, + "maxNotional": 200000.0, + "maintenanceMarginRate": 0.05, + "maxLeverage": 10.0, + "info": { + "bracket": "3", + "initialLeverage": "10", + "notionalCap": "200000", + "notionalFloor": "25000", + "maintMarginRatio": "0.05", + "cum": "650.0" + } + }, + { + "tier": 4.0, + "currency": "USDT", + "minNotional": 200000.0, + "maxNotional": 500000.0, + "maintenanceMarginRate": 0.1, + "maxLeverage": 5.0, + "info": { + "bracket": "4", + "initialLeverage": "5", + "notionalCap": "500000", + "notionalFloor": "200000", + "maintMarginRatio": "0.1", + "cum": "10650.0" + } + }, + { + "tier": 5.0, + "currency": "USDT", + "minNotional": 500000.0, + "maxNotional": 1000000.0, + "maintenanceMarginRate": 0.125, + "maxLeverage": 4.0, + "info": { + "bracket": "5", + "initialLeverage": "4", + "notionalCap": "1000000", + "notionalFloor": "500000", + "maintMarginRatio": "0.125", + "cum": "23150.0" + } + }, + { + "tier": 6.0, + "currency": "USDT", + "minNotional": 1000000.0, + "maxNotional": 3000000.0, + "maintenanceMarginRate": 0.25, + "maxLeverage": 2.0, + "info": { + "bracket": "6", + "initialLeverage": "2", + "notionalCap": "3000000", + "notionalFloor": "1000000", + "maintMarginRatio": "0.25", + "cum": "148150.0" + } + }, + { + "tier": 7.0, + "currency": "USDT", + "minNotional": 3000000.0, + "maxNotional": 5000000.0, + "maintenanceMarginRate": 0.5, + "maxLeverage": 1.0, + "info": { + "bracket": "7", + "initialLeverage": "1", + "notionalCap": "5000000", + "notionalFloor": "3000000", + "maintMarginRatio": "0.5", + "cum": "898150.0" + } + } + ], "PENDLE/USDT:USDT": [ { "tier": 1.0, @@ -24442,10 +24752,10 @@ "minNotional": 0.0, "maxNotional": 5000.0, "maintenanceMarginRate": 0.02, - "maxLeverage": 25.0, + "maxLeverage": 10.0, "info": { "bracket": "1", - "initialLeverage": "25", + "initialLeverage": "10", "notionalCap": "5000", "notionalFloor": "0", "maintMarginRatio": "0.02", @@ -24458,10 +24768,10 @@ "minNotional": 5000.0, "maxNotional": 25000.0, "maintenanceMarginRate": 0.025, - "maxLeverage": 15.0, + "maxLeverage": 8.0, "info": { "bracket": "2", - "initialLeverage": "15", + "initialLeverage": "8", "notionalCap": "25000", "notionalFloor": "5000", "maintMarginRatio": "0.025", @@ -24474,10 +24784,10 @@ "minNotional": 25000.0, "maxNotional": 100000.0, "maintenanceMarginRate": 0.05, - "maxLeverage": 10.0, + "maxLeverage": 6.0, "info": { "bracket": "3", - "initialLeverage": "10", + "initialLeverage": "6", "notionalCap": "100000", "notionalFloor": "25000", "maintMarginRatio": "0.05", @@ -24536,13 +24846,13 @@ "tier": 7.0, "currency": "BUSD", "minNotional": 3000000.0, - "maxNotional": 8000000.0, + "maxNotional": 4000000.0, "maintenanceMarginRate": 0.5, "maxLeverage": 1.0, "info": { "bracket": "7", "initialLeverage": "1", - "notionalCap": "8000000", + "notionalCap": "4000000", "notionalFloor": "3000000", "maintMarginRatio": "0.5", "cum": "949400.0" @@ -25613,14 +25923,14 @@ "currency": "USDT", "minNotional": 0.0, "maxNotional": 5000.0, - "maintenanceMarginRate": 0.02, - "maxLeverage": 20.0, + "maintenanceMarginRate": 0.01, + "maxLeverage": 50.0, "info": { "bracket": "1", - "initialLeverage": "20", + "initialLeverage": "50", "notionalCap": "5000", "notionalFloor": "0", - "maintMarginRatio": "0.02", + "maintMarginRatio": "0.01", "cum": "0.0" } }, @@ -25629,95 +25939,111 @@ "currency": "USDT", "minNotional": 5000.0, "maxNotional": 25000.0, - "maintenanceMarginRate": 0.025, - "maxLeverage": 15.0, + "maintenanceMarginRate": 0.02, + "maxLeverage": 25.0, "info": { "bracket": "2", - "initialLeverage": "15", + "initialLeverage": "25", "notionalCap": "25000", "notionalFloor": "5000", - "maintMarginRatio": "0.025", - "cum": "25.0" + "maintMarginRatio": "0.02", + "cum": "50.0" } }, { "tier": 3.0, "currency": "USDT", "minNotional": 25000.0, - "maxNotional": 200000.0, - "maintenanceMarginRate": 0.05, - "maxLeverage": 10.0, + "maxNotional": 50000.0, + "maintenanceMarginRate": 0.025, + "maxLeverage": 20.0, "info": { "bracket": "3", - "initialLeverage": "10", - "notionalCap": "200000", + "initialLeverage": "20", + "notionalCap": "50000", "notionalFloor": "25000", - "maintMarginRatio": "0.05", - "cum": "650.0" + "maintMarginRatio": "0.025", + "cum": "175.0" } }, { "tier": 4.0, "currency": "USDT", - "minNotional": 200000.0, - "maxNotional": 500000.0, - "maintenanceMarginRate": 0.1, - "maxLeverage": 5.0, + "minNotional": 50000.0, + "maxNotional": 400000.0, + "maintenanceMarginRate": 0.05, + "maxLeverage": 10.0, "info": { "bracket": "4", - "initialLeverage": "5", - "notionalCap": "500000", - "notionalFloor": "200000", - "maintMarginRatio": "0.1", - "cum": "10650.0" + "initialLeverage": "10", + "notionalCap": "400000", + "notionalFloor": "50000", + "maintMarginRatio": "0.05", + "cum": "1425.0" } }, { "tier": 5.0, "currency": "USDT", - "minNotional": 500000.0, + "minNotional": 400000.0, "maxNotional": 1000000.0, - "maintenanceMarginRate": 0.125, - "maxLeverage": 4.0, + "maintenanceMarginRate": 0.1, + "maxLeverage": 5.0, "info": { "bracket": "5", - "initialLeverage": "4", + "initialLeverage": "5", "notionalCap": "1000000", - "notionalFloor": "500000", - "maintMarginRatio": "0.125", - "cum": "23150.0" + "notionalFloor": "400000", + "maintMarginRatio": "0.1", + "cum": "21425.0" } }, { "tier": 6.0, "currency": "USDT", "minNotional": 1000000.0, - "maxNotional": 3000000.0, - "maintenanceMarginRate": 0.25, - "maxLeverage": 2.0, + "maxNotional": 2000000.0, + "maintenanceMarginRate": 0.125, + "maxLeverage": 4.0, "info": { "bracket": "6", - "initialLeverage": "2", - "notionalCap": "3000000", + "initialLeverage": "4", + "notionalCap": "2000000", "notionalFloor": "1000000", - "maintMarginRatio": "0.25", - "cum": "148150.0" + "maintMarginRatio": "0.125", + "cum": "46425.0" } }, { "tier": 7.0, "currency": "USDT", - "minNotional": 3000000.0, + "minNotional": 2000000.0, "maxNotional": 5000000.0, + "maintenanceMarginRate": 0.25, + "maxLeverage": 2.0, + "info": { + "bracket": "7", + "initialLeverage": "2", + "notionalCap": "5000000", + "notionalFloor": "2000000", + "maintMarginRatio": "0.25", + "cum": "296425.0" + } + }, + { + "tier": 8.0, + "currency": "USDT", + "minNotional": 5000000.0, + "maxNotional": 10000000.0, "maintenanceMarginRate": 0.5, "maxLeverage": 1.0, "info": { - "bracket": "7", + "bracket": "8", "initialLeverage": "1", - "notionalCap": "5000000", - "notionalFloor": "3000000", + "notionalCap": "10000000", + "notionalFloor": "5000000", "maintMarginRatio": "0.5", - "cum": "898150.0" + "cum": "1546425.0" } } ], @@ -26861,6 +27187,120 @@ } } ], + "YGG/USDT:USDT": [ + { + "tier": 1.0, + "currency": "USDT", + "minNotional": 0.0, + "maxNotional": 5000.0, + "maintenanceMarginRate": 0.02, + "maxLeverage": 20.0, + "info": { + "bracket": "1", + "initialLeverage": "20", + "notionalCap": "5000", + "notionalFloor": "0", + "maintMarginRatio": "0.02", + "cum": "0.0" + } + }, + { + "tier": 2.0, + "currency": "USDT", + "minNotional": 5000.0, + "maxNotional": 25000.0, + "maintenanceMarginRate": 0.025, + "maxLeverage": 15.0, + "info": { + "bracket": "2", + "initialLeverage": "15", + "notionalCap": "25000", + "notionalFloor": "5000", + "maintMarginRatio": "0.025", + "cum": "25.0" + } + }, + { + "tier": 3.0, + "currency": "USDT", + "minNotional": 25000.0, + "maxNotional": 200000.0, + "maintenanceMarginRate": 0.05, + "maxLeverage": 10.0, + "info": { + "bracket": "3", + "initialLeverage": "10", + "notionalCap": "200000", + "notionalFloor": "25000", + "maintMarginRatio": "0.05", + "cum": "650.0" + } + }, + { + "tier": 4.0, + "currency": "USDT", + "minNotional": 200000.0, + "maxNotional": 500000.0, + "maintenanceMarginRate": 0.1, + "maxLeverage": 5.0, + "info": { + "bracket": "4", + "initialLeverage": "5", + "notionalCap": "500000", + "notionalFloor": "200000", + "maintMarginRatio": "0.1", + "cum": "10650.0" + } + }, + { + "tier": 5.0, + "currency": "USDT", + "minNotional": 500000.0, + "maxNotional": 1000000.0, + "maintenanceMarginRate": 0.125, + "maxLeverage": 4.0, + "info": { + "bracket": "5", + "initialLeverage": "4", + "notionalCap": "1000000", + "notionalFloor": "500000", + "maintMarginRatio": "0.125", + "cum": "23150.0" + } + }, + { + "tier": 6.0, + "currency": "USDT", + "minNotional": 1000000.0, + "maxNotional": 3000000.0, + "maintenanceMarginRate": 0.25, + "maxLeverage": 2.0, + "info": { + "bracket": "6", + "initialLeverage": "2", + "notionalCap": "3000000", + "notionalFloor": "1000000", + "maintMarginRatio": "0.25", + "cum": "148150.0" + } + }, + { + "tier": 7.0, + "currency": "USDT", + "minNotional": 3000000.0, + "maxNotional": 5000000.0, + "maintenanceMarginRate": 0.5, + "maxLeverage": 1.0, + "info": { + "bracket": "7", + "initialLeverage": "1", + "notionalCap": "5000000", + "notionalFloor": "3000000", + "maintMarginRatio": "0.5", + "cum": "898150.0" + } + } + ], "ZEC/USDT:USDT": [ { "tier": 1.0, diff --git a/freqtrade/exchange/bybit.py b/freqtrade/exchange/bybit.py index 145a501c9..626643d06 100644 --- a/freqtrade/exchange/bybit.py +++ b/freqtrade/exchange/bybit.py @@ -7,10 +7,10 @@ import ccxt from freqtrade.constants import BuySell from freqtrade.enums import MarginMode, PriceType, TradingMode +from freqtrade.enums.candletype import CandleType from freqtrade.exceptions import DDosProtection, OperationalException, TemporaryError from freqtrade.exchange import Exchange from freqtrade.exchange.common import retrier -from freqtrade.exchange.exchange_utils import timeframe_to_msecs logger = logging.getLogger(__name__) @@ -27,7 +27,7 @@ class Bybit(Exchange): """ _ft_has: Dict = { - "ohlcv_candle_limit": 200, + "ohlcv_candle_limit": 1000, "ohlcv_has_history": True, } _ft_has_futures: Dict = { @@ -91,28 +91,13 @@ class Bybit(Exchange): except ccxt.BaseError as e: raise OperationalException(e) from e - async def _fetch_funding_rate_history( - self, - pair: str, - timeframe: str, - limit: int, - since_ms: Optional[int] = None, - ) -> List[List]: - """ - Fetch funding rate history - Necessary workaround until https://github.com/ccxt/ccxt/issues/15990 is fixed. - """ - params = {} - if since_ms: - until = since_ms + (timeframe_to_msecs(timeframe) * self._ft_has['ohlcv_candle_limit']) - params.update({'until': until}) - # Funding rate - data = await self._api_async.fetch_funding_rate_history( - pair, since=since_ms, - params=params) - # Convert funding rate to candle pattern - data = [[x['timestamp'], x['fundingRate'], 0, 0, 0, 0] for x in data] - return data + def ohlcv_candle_limit( + self, timeframe: str, candle_type: CandleType, since_ms: Optional[int] = None) -> int: + + if candle_type in (CandleType.FUNDING_RATE): + return 200 + + return super().ohlcv_candle_limit(timeframe, candle_type, since_ms) def _lev_prep(self, pair: str, leverage: float, side: BuySell, accept_fail: bool = False): if self.trading_mode != TradingMode.SPOT: diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py index 5f2530431..3f36bd16c 100644 --- a/freqtrade/exchange/exchange.py +++ b/freqtrade/exchange/exchange.py @@ -263,8 +263,6 @@ class Exchange: except ccxt.BaseError as e: raise OperationalException(f"Initialization of ccxt failed. Reason: {e}") from e - self.set_sandbox(api, exchange_config, name) - return api @property @@ -465,16 +463,6 @@ class Exchange: return amount_to_contract_precision(amount, self.get_precision_amount(pair), self.precisionMode, contract_size) - def set_sandbox(self, api: ccxt.Exchange, exchange_config: dict, name: str) -> None: - if exchange_config.get('sandbox'): - if api.urls.get('test'): - api.urls['api'] = api.urls['test'] - logger.info("Enabled Sandbox API on %s", name) - else: - logger.warning( - f"No Sandbox URL in CCXT for {name}, exiting. Please check your config.json") - raise OperationalException(f'Exchange {name} does not provide a sandbox api') - def _load_async_markets(self, reload: bool = False) -> None: try: if self._api_async: @@ -580,7 +568,7 @@ class Exchange: for pair in [f"{curr_1}/{curr_2}", f"{curr_2}/{curr_1}"]: if pair in self.markets and self.markets[pair].get('active'): return pair - raise ExchangeError(f"Could not combine {curr_1} and {curr_2} to get a valid pair.") + raise ValueError(f"Could not combine {curr_1} and {curr_2} to get a valid pair.") def validate_timeframes(self, timeframe: Optional[str]) -> None: """ @@ -1876,7 +1864,7 @@ class Exchange: tick = self.fetch_ticker(comb) fee_to_quote_rate = safe_value_fallback2(tick, tick, 'last', 'ask') - except ExchangeError: + except (ValueError, ExchangeError): fee_to_quote_rate = self._config['exchange'].get('unknown_fee_rate', None) if not fee_to_quote_rate: return None diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py index b9854919d..b6ded83b1 100644 --- a/freqtrade/freqai/data_drawer.py +++ b/freqtrade/freqai/data_drawer.py @@ -375,7 +375,7 @@ class FreqaiDataDrawer: num_keep = self.freqai_info["purge_old_models"] if not num_keep: return - elif type(num_keep) == bool: + elif isinstance(num_keep, bool): num_keep = 2 model_folders = [x for x in self.full_path.iterdir() if x.is_dir()] diff --git a/freqtrade/freqai/prediction_models/PyTorchMLPClassifier.py b/freqtrade/freqai/prediction_models/PyTorchMLPClassifier.py index 71279dba9..9aabdf7ad 100644 --- a/freqtrade/freqai/prediction_models/PyTorchMLPClassifier.py +++ b/freqtrade/freqai/prediction_models/PyTorchMLPClassifier.py @@ -26,9 +26,9 @@ class PyTorchMLPClassifier(BasePyTorchClassifier): "model_training_parameters" : { "learning_rate": 3e-4, "trainer_kwargs": { - "max_iters": 5000, + "n_steps": 5000, "batch_size": 64, - "max_n_eval_batches": null, + "n_epochs": null, }, "model_kwargs": { "hidden_dim": 512, diff --git a/freqtrade/freqai/prediction_models/PyTorchMLPRegressor.py b/freqtrade/freqai/prediction_models/PyTorchMLPRegressor.py index 9f4534487..dc8dc4b61 100644 --- a/freqtrade/freqai/prediction_models/PyTorchMLPRegressor.py +++ b/freqtrade/freqai/prediction_models/PyTorchMLPRegressor.py @@ -27,9 +27,9 @@ class PyTorchMLPRegressor(BasePyTorchRegressor): "model_training_parameters" : { "learning_rate": 3e-4, "trainer_kwargs": { - "max_iters": 5000, + "n_steps": 5000, "batch_size": 64, - "max_n_eval_batches": null, + "n_epochs": null, }, "model_kwargs": { "hidden_dim": 512, diff --git a/freqtrade/freqai/prediction_models/PyTorchTransformerRegressor.py b/freqtrade/freqai/prediction_models/PyTorchTransformerRegressor.py index a76bab05c..846d6df2e 100644 --- a/freqtrade/freqai/prediction_models/PyTorchTransformerRegressor.py +++ b/freqtrade/freqai/prediction_models/PyTorchTransformerRegressor.py @@ -30,9 +30,9 @@ class PyTorchTransformerRegressor(BasePyTorchRegressor): "model_training_parameters" : { "learning_rate": 3e-4, "trainer_kwargs": { - "max_iters": 5000, + "n_steps": 5000, "batch_size": 64, - "max_n_eval_batches": null + "n_epochs": null }, "model_kwargs": { "hidden_dim": 512, diff --git a/freqtrade/freqai/torch/PyTorchDataConvertor.py b/freqtrade/freqai/torch/PyTorchDataConvertor.py index e6b815373..0af14dd14 100644 --- a/freqtrade/freqai/torch/PyTorchDataConvertor.py +++ b/freqtrade/freqai/torch/PyTorchDataConvertor.py @@ -1,5 +1,4 @@ from abc import ABC, abstractmethod -from typing import Optional import pandas as pd import torch @@ -12,14 +11,14 @@ class PyTorchDataConvertor(ABC): """ @abstractmethod - def convert_x(self, df: pd.DataFrame, device: Optional[str] = None) -> torch.Tensor: + def convert_x(self, df: pd.DataFrame, device: str) -> torch.Tensor: """ :param df: "*_features" dataframe. :param device: The device to use for training (e.g. 'cpu', 'cuda'). """ @abstractmethod - def convert_y(self, df: pd.DataFrame, device: Optional[str] = None) -> torch.Tensor: + def convert_y(self, df: pd.DataFrame, device: str) -> torch.Tensor: """ :param df: "*_labels" dataframe. :param device: The device to use for training (e.g. 'cpu', 'cuda'). @@ -33,8 +32,8 @@ class DefaultPyTorchDataConvertor(PyTorchDataConvertor): def __init__( self, - target_tensor_type: Optional[torch.dtype] = None, - squeeze_target_tensor: bool = False + target_tensor_type: torch.dtype = torch.float32, + squeeze_target_tensor: bool = False, ): """ :param target_tensor_type: type of target tensor, for classification use @@ -45,23 +44,14 @@ class DefaultPyTorchDataConvertor(PyTorchDataConvertor): self._target_tensor_type = target_tensor_type self._squeeze_target_tensor = squeeze_target_tensor - def convert_x(self, df: pd.DataFrame, device: Optional[str] = None) -> torch.Tensor: - x = torch.from_numpy(df.values).float() - if device: - x = x.to(device) - + def convert_x(self, df: pd.DataFrame, device: str) -> torch.Tensor: + numpy_arrays = df.values + x = torch.tensor(numpy_arrays, device=device, dtype=torch.float32) return x - def convert_y(self, df: pd.DataFrame, device: Optional[str] = None) -> torch.Tensor: - y = torch.from_numpy(df.values) - - if self._target_tensor_type: - y = y.to(self._target_tensor_type) - + def convert_y(self, df: pd.DataFrame, device: str) -> torch.Tensor: + numpy_arrays = df.values + y = torch.tensor(numpy_arrays, device=device, dtype=self._target_tensor_type) if self._squeeze_target_tensor: y = y.squeeze() - - if device: - y = y.to(device) - return y diff --git a/freqtrade/freqai/torch/PyTorchModelTrainer.py b/freqtrade/freqai/torch/PyTorchModelTrainer.py index 603e7ac12..371a953e7 100644 --- a/freqtrade/freqai/torch/PyTorchModelTrainer.py +++ b/freqtrade/freqai/torch/PyTorchModelTrainer.py @@ -1,5 +1,4 @@ import logging -import math from pathlib import Path from typing import Any, Dict, List, Optional @@ -40,23 +39,27 @@ class PyTorchModelTrainer(PyTorchTrainerInterface): state_dict and model_meta_data saved by self.save() method. :param model_meta_data: Additional metadata about the model (optional). :param data_convertor: convertor from pd.DataFrame to torch.tensor. - :param 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. + :param n_steps: used to calculate n_epochs. The number of training iterations to run. + iteration here refers to the number of times optimizer.step() is called. + ignored if n_epochs is set. + :param n_epochs: The maximum number batches to use for evaluation. :param batch_size: The size of the batches to use during training. - :param max_n_eval_batches: The maximum number batches to use for evaluation. """ self.model = model self.optimizer = optimizer self.criterion = criterion self.model_meta_data = model_meta_data self.device = device - self.max_iters: int = kwargs.get("max_iters", 100) + self.n_epochs: Optional[int] = kwargs.get("n_epochs", 10) + self.n_steps: Optional[int] = kwargs.get("n_steps", None) + if self.n_steps is None and not self.n_epochs: + raise Exception("Either `n_steps` or `n_epochs` should be set.") + self.batch_size: int = kwargs.get("batch_size", 64) - self.max_n_eval_batches: Optional[int] = kwargs.get("max_n_eval_batches", None) self.data_convertor = data_convertor self.window_size: int = window_size self.tb_logger = tb_logger + self.test_batch_counter = 0 def fit(self, data_dictionary: Dict[str, pd.DataFrame], splits: List[str]): """ @@ -72,55 +75,46 @@ class PyTorchModelTrainer(PyTorchTrainerInterface): backpropagation. - Updates the model's parameters using an optimizer. """ - data_loaders_dictionary = self.create_data_loaders_dictionary(data_dictionary, splits) - epochs = self.calc_n_epochs( - n_obs=len(data_dictionary["train_features"]), - batch_size=self.batch_size, - n_iters=self.max_iters - ) self.model.train() - for epoch in range(1, epochs + 1): - for i, batch_data in enumerate(data_loaders_dictionary["train"]): + data_loaders_dictionary = self.create_data_loaders_dictionary(data_dictionary, splits) + n_obs = len(data_dictionary["train_features"]) + n_epochs = self.n_epochs or self.calc_n_epochs(n_obs=n_obs) + batch_counter = 0 + for _ in range(n_epochs): + for _, batch_data in enumerate(data_loaders_dictionary["train"]): xb, yb = batch_data - xb.to(self.device) - yb.to(self.device) + xb = xb.to(self.device) + yb = yb.to(self.device) yb_pred = self.model(xb) loss = self.criterion(yb_pred, yb) self.optimizer.zero_grad(set_to_none=True) loss.backward() self.optimizer.step() - self.tb_logger.log_scalar("train_loss", loss.item(), i) + self.tb_logger.log_scalar("train_loss", loss.item(), batch_counter) + batch_counter += 1 # evaluation if "test" in splits: - self.estimate_loss( - data_loaders_dictionary, - self.max_n_eval_batches, - "test" - ) + self.estimate_loss(data_loaders_dictionary, "test") @torch.no_grad() def estimate_loss( self, data_loader_dictionary: Dict[str, DataLoader], - max_n_eval_batches: Optional[int], split: str, ) -> None: self.model.eval() - n_batches = 0 - for i, batch_data in enumerate(data_loader_dictionary[split]): - if max_n_eval_batches and i > max_n_eval_batches: - n_batches += 1 - break + for _, batch_data in enumerate(data_loader_dictionary[split]): xb, yb = batch_data - xb.to(self.device) - yb.to(self.device) + xb = xb.to(self.device) + yb = yb.to(self.device) yb_pred = self.model(xb) loss = self.criterion(yb_pred, yb) - self.tb_logger.log_scalar(f"{split}_loss", loss.item(), i) + self.tb_logger.log_scalar(f"{split}_loss", loss.item(), self.test_batch_counter) + self.test_batch_counter += 1 self.model.train() @@ -148,31 +142,30 @@ class PyTorchModelTrainer(PyTorchTrainerInterface): return data_loader_dictionary - @staticmethod - def calc_n_epochs(n_obs: int, batch_size: int, n_iters: int) -> int: + def calc_n_epochs(self, n_obs: int) -> int: """ Calculates the number of epochs required to reach the maximum number of iterations specified in the model training parameters. - the motivation here is that `max_iters` is easier to optimize and keep stable, + the motivation here is that `n_steps` is easier to optimize and keep stable, across different n_obs - the number of data points. """ + assert isinstance(self.n_steps, int), "Either `n_steps` or `n_epochs` should be set." + n_batches = n_obs // self.batch_size + n_epochs = min(self.n_steps // n_batches, 1) + if n_epochs <= 10: + logger.warning( + f"Setting low n_epochs: {n_epochs}. " + f"Please consider increasing `n_steps` hyper-parameter." + ) - n_batches = math.ceil(n_obs // batch_size) - epochs = math.ceil(n_iters // n_batches) - if epochs <= 10: - logger.warning("User set `max_iters` in such a way that the trainer will only perform " - f" {epochs} epochs. Please consider increasing this value accordingly") - if epochs <= 1: - logger.warning("Epochs set to 1. Please review your `max_iters` value") - epochs = 1 - return epochs + return n_epochs def save(self, path: Path): """ - Saving any nn.Module state_dict - Saving model_meta_data, this dict should contain any additional data that the - user needs to store. e.g class_names for classification models. + user needs to store. e.g. class_names for classification models. """ torch.save({ diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py index 9d35aee0f..beca1f09c 100644 --- a/freqtrade/freqtradebot.py +++ b/freqtrade/freqtradebot.py @@ -613,6 +613,8 @@ class FreqtradeBot(LoggingMixin): for trade in Trade.get_open_trades(): # If there is any open orders, wait for them to finish. if trade.open_order_id is None: + # Do a wallets update (will be ratelimited to once per hour) + self.wallets.update(False) try: self.check_and_call_adjust_trade_position(trade) except DependencyException as exception: diff --git a/freqtrade/misc.py b/freqtrade/misc.py index e715c280a..f8d730fae 100644 --- a/freqtrade/misc.py +++ b/freqtrade/misc.py @@ -192,30 +192,6 @@ def plural(num: float, singular: str, plural: Optional[str] = None) -> str: return singular if (num == 1 or num == -1) else plural or singular + 's' -def render_template(templatefile: str, arguments: dict = {}) -> str: - - from jinja2 import Environment, PackageLoader, select_autoescape - - env = Environment( - loader=PackageLoader('freqtrade', 'templates'), - autoescape=select_autoescape(['html', 'xml']) - ) - template = env.get_template(templatefile) - return template.render(**arguments) - - -def render_template_with_fallback(templatefile: str, templatefallbackfile: str, - arguments: dict = {}) -> str: - """ - Use templatefile if possible, otherwise fall back to templatefallbackfile - """ - from jinja2.exceptions import TemplateNotFound - try: - return render_template(templatefile, arguments) - except TemplateNotFound: - return render_template(templatefallbackfile, arguments) - - def chunks(lst: List[Any], n: int) -> Iterator[List[Any]]: """ Split lst into chunks of the size n. diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py index ce20d2178..21390489e 100644 --- a/freqtrade/optimize/backtesting.py +++ b/freqtrade/optimize/backtesting.py @@ -369,13 +369,14 @@ class Backtesting: # Cleanup from prior runs pair_data.drop(HEADERS[5:] + ['buy', 'sell'], axis=1, errors='ignore') df_analyzed = self.strategy.ft_advise_signals(pair_data, {'pair': pair}) - # Trim startup period from analyzed dataframe - df_analyzed = processed[pair] = pair_data = trim_dataframe( - df_analyzed, self.timerange, startup_candles=self.required_startup) # Update dataprovider cache self.dataprovider._set_cached_df( pair, self.timeframe, df_analyzed, self.config['candle_type_def']) + # Trim startup period from analyzed dataframe + df_analyzed = processed[pair] = pair_data = trim_dataframe( + df_analyzed, self.timerange, startup_candles=self.required_startup) + # Create a copy of the dataframe before shifting, that way the entry signal/tag # remains on the correct candle for callbacks. df_analyzed = df_analyzed.copy() @@ -567,8 +568,7 @@ class Backtesting: pos_trade = self._get_exit_for_signal(trade, row, exit_, amount) if pos_trade is not None: order = pos_trade.orders[-1] - if self._get_order_filled(order.ft_price, row): - order.close_bt_order(current_date, trade) + if self._try_close_open_order(order, trade, current_date, row): trade.recalc_trade_from_orders() self.wallets.update() return pos_trade @@ -579,6 +579,19 @@ class Backtesting: """ Rate is within candle, therefore filled""" return row[LOW_IDX] <= rate <= row[HIGH_IDX] + def _try_close_open_order( + self, order: Optional[Order], trade: LocalTrade, current_date: datetime, + row: Tuple) -> bool: + """ + Check if an order is open and if it should've filled. + :return: True if the order filled. + """ + if order and self._get_order_filled(order.ft_price, row): + order.close_bt_order(current_date, trade) + trade.open_order_id = None + return True + return False + def _get_exit_for_signal( self, trade: LocalTrade, row: Tuple, exit_: ExitCheckTuple, amount: Optional[float] = None) -> Optional[LocalTrade]: @@ -903,9 +916,7 @@ class Backtesting: ) order._trade_bt = trade trade.orders.append(order) - if pos_adjust and self._get_order_filled(order.ft_price, row): - order.close_bt_order(current_time, trade) - else: + if not self._try_close_open_order(order, trade, current_time, row): trade.open_order_id = str(self.order_id_counter) trade.recalc_trade_from_orders() @@ -1121,23 +1132,18 @@ class Backtesting: for trade in list(LocalTrade.bt_trades_open_pp[pair]): # 3. Process entry orders. order = trade.select_order(trade.entry_side, is_open=True) - if order and self._get_order_filled(order.ft_price, row): - order.close_bt_order(current_time, trade) - trade.open_order_id = None + if self._try_close_open_order(order, trade, current_time, row): self.wallets.update() - # 4. Create exit orders (if any) + # 4. Create exit orders (if any) if not trade.open_order_id: self._check_trade_exit(trade, row) # Place exit order if necessary - # 5. Process exit orders. + # 5. Process exit orders. order = trade.select_order(trade.exit_side, is_open=True) - if order and self._get_order_filled(order.ft_price, row): - order.close_bt_order(current_time, trade) - trade.open_order_id = None + if order and self._try_close_open_order(order, trade, current_time, row): sub_trade = order.safe_amount_after_fee != trade.amount if sub_trade: - order.close_bt_order(current_time, trade) trade.recalc_trade_from_orders() else: trade.close_date = current_time @@ -1191,7 +1197,8 @@ class Backtesting: row_index += 1 indexes[pair] = row_index - self.dataprovider._set_dataframe_max_index(row_index) + self.dataprovider._set_dataframe_max_index(self.required_startup + row_index) + self.dataprovider._set_dataframe_max_date(current_time) current_detail_time: datetime = row[DATE_IDX].to_pydatetime() trade_dir: Optional[LongShort] = self.check_for_trade_entry(row) @@ -1224,12 +1231,14 @@ class Backtesting: is_first = True current_time_det = current_time for det_row in detail_data[HEADERS].values.tolist(): + self.dataprovider._set_dataframe_max_date(current_time_det) open_trade_count_start = self.backtest_loop( det_row, pair, current_time_det, end_date, open_trade_count_start, trade_dir, is_first) current_time_det += timedelta(minutes=self.timeframe_detail_min) is_first = False else: + self.dataprovider._set_dataframe_max_date(current_time) open_trade_count_start = self.backtest_loop( row, pair, current_time, end_date, open_trade_count_start, trade_dir) diff --git a/freqtrade/optimize/lookahead_analysis.py b/freqtrade/optimize/lookahead_analysis.py index dcc1088b3..80418da95 100755 --- a/freqtrade/optimize/lookahead_analysis.py +++ b/freqtrade/optimize/lookahead_analysis.py @@ -48,6 +48,7 @@ class LookaheadAnalysis: self.entry_varHolders: List[VarHolder] = [] self.exit_varHolders: List[VarHolder] = [] self.exchange: Optional[Any] = None + self._fee = None # pull variables the scope of the lookahead_analysis-instance self.local_config = deepcopy(config) @@ -145,8 +146,13 @@ class LookaheadAnalysis: str(self.dt_to_timestamp(varholder.to_dt))) prepare_data_config['exchange']['pair_whitelist'] = pairs_to_load + if self._fee is not None: + # Don't re-calculate fee per pair, as fee might differ per pair. + prepare_data_config['fee'] = self._fee + backtesting = Backtesting(prepare_data_config, self.exchange) self.exchange = backtesting.exchange + self._fee = backtesting.fee backtesting._set_strategy(backtesting.strategylist[0]) varholder.data, varholder.timerange = backtesting.load_bt_data() @@ -198,7 +204,7 @@ class LookaheadAnalysis: self.prepare_data(exit_varHolder, [result_row['pair']]) # now we analyze a full trade of full_varholder and look for analyze its bias - def analyze_row(self, idx, result_row): + def analyze_row(self, idx: int, result_row): # if force-sold, ignore this signal since here it will unconditionally exit. if result_row.close_date == self.dt_to_timestamp(self.full_varHolder.to_dt): return @@ -209,12 +215,16 @@ class LookaheadAnalysis: # fill entry_varHolder and exit_varHolder self.fill_entry_and_exit_varHolders(result_row) + # this will trigger a logger-message + buy_or_sell_biased: bool = False + # register if buy signal is broken if not self.report_signal( self.entry_varHolders[idx].result, "open_date", self.entry_varHolders[idx].compared_dt): self.current_analysis.false_entry_signals += 1 + buy_or_sell_biased = True # register if buy or sell signal is broken if not self.report_signal( @@ -222,6 +232,13 @@ class LookaheadAnalysis: "close_date", self.exit_varHolders[idx].compared_dt): self.current_analysis.false_exit_signals += 1 + buy_or_sell_biased = True + + if buy_or_sell_biased: + logger.info(f"found lookahead-bias in trade " + f"pair: {result_row['pair']}, " + f"timerange:{result_row['open_date']} - {result_row['close_date']}, " + f"idx: {idx}") # check if the indicators themselves contain biased data self.analyze_indicators(self.full_varHolder, self.entry_varHolders[idx], result_row['pair']) @@ -251,9 +268,33 @@ class LookaheadAnalysis: # starting from the same datetime to avoid miss-reports of bias for idx, result_row in self.full_varHolder.result['results'].iterrows(): if self.current_analysis.total_signals == self.targeted_trade_amount: + logger.info(f"Found targeted trade amount = {self.targeted_trade_amount} signals.") break + if found_signals < self.minimum_trade_amount: + logger.info(f"only found {found_signals} " + f"which is smaller than " + f"minimum trade amount = {self.minimum_trade_amount}. " + f"Exiting this lookahead-analysis") + return None + if "force_exit" in result_row['exit_reason']: + logger.info("found force-exit in pair: {result_row['pair']}, " + f"timerange:{result_row['open_date']}-{result_row['close_date']}, " + f"idx: {idx}, skipping this one to avoid a false-positive.") + + # just to keep the IDs of both full, entry and exit varholders the same + # to achieve a better debugging experience + self.entry_varHolders.append(VarHolder()) + self.exit_varHolders.append(VarHolder()) + continue + self.analyze_row(idx, result_row) + if len(self.entry_varHolders) < self.minimum_trade_amount: + logger.info(f"only found {found_signals} after skipping forced exits " + f"which is smaller than " + f"minimum trade amount = {self.minimum_trade_amount}. " + f"Exiting this lookahead-analysis") + # Restore verbosity, so it's not too quiet for the next strategy restore_verbosity_for_bias_tester() # check and report signals diff --git a/freqtrade/optimize/lookahead_analysis_helpers.py b/freqtrade/optimize/lookahead_analysis_helpers.py index 702eee774..422026780 100644 --- a/freqtrade/optimize/lookahead_analysis_helpers.py +++ b/freqtrade/optimize/lookahead_analysis_helpers.py @@ -137,6 +137,19 @@ class LookaheadAnalysisSubFunctions: 'just to avoid false positives') config['dry_run_wallet'] = min_dry_run_wallet + if 'timerange' not in config: + # setting a timerange is enforced here + raise OperationalException( + "Please set a timerange. " + "Usually a few months are enough depending on your needs and strategy." + ) + # fix stake_amount to 10k. + # in a combination with a wallet size of 1 billion it should always be able to trade + # no matter if they use custom_stake_amount as a small percentage of wallet size + # or fixate custom_stake_amount to a certain value. + logger.info('fixing stake_amount to 10k') + config['stake_amount'] = 10000 + # enforce cache to be 'none', shift it to 'none' if not already # (since the default value is 'day') if config.get('backtest_cache') is None: diff --git a/freqtrade/optimize/optimize_reports/bt_storage.py b/freqtrade/optimize/optimize_reports/bt_storage.py index 71c6dc130..6b50412b3 100644 --- a/freqtrade/optimize/optimize_reports/bt_storage.py +++ b/freqtrade/optimize/optimize_reports/bt_storage.py @@ -12,7 +12,7 @@ logger = logging.getLogger(__name__) def store_backtest_stats( - recordfilename: Path, stats: BacktestResultType, dtappendix: str) -> None: + recordfilename: Path, stats: BacktestResultType, dtappendix: str) -> Path: """ Stores backtest results :param recordfilename: Path object, which can either be a filename or a directory. @@ -41,6 +41,8 @@ def store_backtest_stats( latest_filename = Path.joinpath(filename.parent, LAST_BT_RESULT_FN) file_dump_json(latest_filename, {'latest_backtest': str(filename.name)}) + return filename + def _store_backtest_analysis_data( recordfilename: Path, data: Dict[str, Dict], diff --git a/freqtrade/persistence/trade_model.py b/freqtrade/persistence/trade_model.py index f686e4f8c..7b17bef8d 100644 --- a/freqtrade/persistence/trade_model.py +++ b/freqtrade/persistence/trade_model.py @@ -48,7 +48,7 @@ class Order(ModelBase): id: Mapped[int] = mapped_column(Integer, primary_key=True) ft_trade_id: Mapped[int] = mapped_column(Integer, ForeignKey('trades.id'), index=True) - _trade_live: Mapped["Trade"] = relationship("Trade", back_populates="orders") + _trade_live: Mapped["Trade"] = relationship("Trade", back_populates="orders", lazy="immediate") _trade_bt: "LocalTrade" = None # type: ignore # order_side can only be 'buy', 'sell' or 'stoploss' @@ -614,11 +614,9 @@ class LocalTrade: """ Method used internally to set self.stop_loss. """ - stop_loss_norm = price_to_precision(stop_loss, self.price_precision, self.precision_mode, - rounding_mode=ROUND_DOWN if self.is_short else ROUND_UP) if not self.stop_loss: - self.initial_stop_loss = stop_loss_norm - self.stop_loss = stop_loss_norm + self.initial_stop_loss = stop_loss + self.stop_loss = stop_loss self.stop_loss_pct = -1 * abs(percent) @@ -642,26 +640,27 @@ class LocalTrade: else: new_loss = float(current_price * (1 - abs(stoploss / leverage))) + stop_loss_norm = price_to_precision(new_loss, self.price_precision, self.precision_mode, + rounding_mode=ROUND_DOWN if self.is_short else ROUND_UP) # no stop loss assigned yet if self.initial_stop_loss_pct is None or refresh: - self.__set_stop_loss(new_loss, stoploss) + self.__set_stop_loss(stop_loss_norm, stoploss) self.initial_stop_loss = price_to_precision( - new_loss, self.price_precision, self.precision_mode, + stop_loss_norm, self.price_precision, self.precision_mode, rounding_mode=ROUND_DOWN if self.is_short else ROUND_UP) self.initial_stop_loss_pct = -1 * abs(stoploss) # evaluate if the stop loss needs to be updated else: - - higher_stop = new_loss > self.stop_loss - lower_stop = new_loss < self.stop_loss + higher_stop = stop_loss_norm > self.stop_loss + lower_stop = stop_loss_norm < self.stop_loss # stop losses only walk up, never down!, # ? But adding more to a leveraged trade would create a lower liquidation price, # ? decreasing the minimum stoploss if (higher_stop and not self.is_short) or (lower_stop and self.is_short): logger.debug(f"{self.pair} - Adjusting stoploss...") - self.__set_stop_loss(new_loss, stoploss) + self.__set_stop_loss(stop_loss_norm, stoploss) else: logger.debug(f"{self.pair} - Keeping current stoploss...") @@ -746,10 +745,8 @@ class LocalTrade: self.open_order_id = None self.recalc_trade_from_orders(is_closing=True) if show_msg: - logger.info( - 'Marking %s as closed as the trade is fulfilled and found no open orders for it.', - self - ) + logger.info(f"Marking {self} as closed as the trade is fulfilled " + "and found no open orders for it.") def update_fee(self, fee_cost: float, fee_currency: Optional[str], fee_rate: Optional[float], side: str) -> None: @@ -1187,12 +1184,13 @@ class LocalTrade: return LocalTrade.bt_open_open_trade_count @staticmethod - def stoploss_reinitialization(desired_stoploss): + def stoploss_reinitialization(desired_stoploss: float): """ Adjust initial Stoploss to desired stoploss for all open trades. """ + trade: Trade for trade in Trade.get_open_trades(): - logger.info("Found open trade: %s", trade) + logger.info(f"Found open trade: {trade}") # skip case if trailing-stop changed the stoploss already. if (trade.stop_loss == trade.initial_stop_loss @@ -1201,7 +1199,7 @@ class LocalTrade: logger.info(f"Stoploss for {trade} needs adjustment...") # Force reset of stoploss - trade.stop_loss = None + trade.stop_loss = 0.0 trade.initial_stop_loss_pct = None trade.adjust_stop_loss(trade.open_rate, desired_stoploss) logger.info(f"New stoploss: {trade.stop_loss}.") diff --git a/freqtrade/rpc/api_server/api_backtest.py b/freqtrade/rpc/api_server/api_backtest.py index 6d3174a5a..f387a9ac8 100644 --- a/freqtrade/rpc/api_server/api_backtest.py +++ b/freqtrade/rpc/api_server/api_backtest.py @@ -10,14 +10,15 @@ from fastapi.exceptions import HTTPException from freqtrade.configuration.config_validation import validate_config_consistency from freqtrade.constants import Config -from freqtrade.data.btanalysis import (delete_backtest_result, get_backtest_resultlist, - load_and_merge_backtest_result) +from freqtrade.data.btanalysis import (delete_backtest_result, get_backtest_result, + get_backtest_resultlist, load_and_merge_backtest_result, + update_backtest_metadata) from freqtrade.enums import BacktestState from freqtrade.exceptions import DependencyException, OperationalException from freqtrade.exchange.common import remove_exchange_credentials from freqtrade.misc import deep_merge_dicts, is_file_in_dir -from freqtrade.rpc.api_server.api_schemas import (BacktestHistoryEntry, BacktestRequest, - BacktestResponse) +from freqtrade.rpc.api_server.api_schemas import (BacktestHistoryEntry, BacktestMetadataUpdate, + BacktestRequest, BacktestResponse) from freqtrade.rpc.api_server.deps import get_config from freqtrade.rpc.api_server.webserver_bgwork import ApiBG from freqtrade.rpc.rpc import RPCException @@ -74,10 +75,11 @@ def __run_backtest_bg(btconfig: Config): ApiBG.bt['bt'].load_prior_backtest() ApiBG.bt['bt'].abort = False + strategy_name = strat.get_strategy_name() if (ApiBG.bt['bt'].results and - strat.get_strategy_name() in ApiBG.bt['bt'].results['strategy']): + strategy_name in ApiBG.bt['bt'].results['strategy']): # When previous result hash matches - reuse that result and skip backtesting. - logger.info(f'Reusing result of previous backtest for {strat.get_strategy_name()}') + logger.info(f'Reusing result of previous backtest for {strategy_name}') else: min_date, max_date = ApiBG.bt['bt'].backtest_one_strategy( strat, ApiBG.bt['data'], ApiBG.bt['timerange']) @@ -87,10 +89,12 @@ def __run_backtest_bg(btconfig: Config): min_date=min_date, max_date=max_date) if btconfig.get('export', 'none') == 'trades': - store_backtest_stats( + fn = store_backtest_stats( btconfig['exportfilename'], ApiBG.bt['bt'].results, datetime.now().strftime("%Y-%m-%d_%H-%M-%S") ) + ApiBG.bt['bt'].results['metadata'][strategy_name]['filename'] = str(fn.name) + ApiBG.bt['bt'].results['metadata'][strategy_name]['strategy'] = strategy_name logger.info("Backtest finished.") @@ -281,3 +285,24 @@ def api_delete_backtest_history_entry(file: str, config=Depends(get_config)): delete_backtest_result(file_abs) return get_backtest_resultlist(config['user_data_dir'] / 'backtest_results') + + +@router.patch('/backtest/history/{file}', response_model=List[BacktestHistoryEntry], + tags=['webserver', 'backtest']) +def api_update_backtest_history_entry(file: str, body: BacktestMetadataUpdate, + config=Depends(get_config)): + # Get backtest result history, read from metadata files + bt_results_base: Path = config['user_data_dir'] / 'backtest_results' + file_abs = (bt_results_base / file).with_suffix('.json') + # Ensure file is in backtest_results directory + if not is_file_in_dir(file_abs, bt_results_base): + raise HTTPException(status_code=404, detail="File not found.") + content = { + 'notes': body.notes + } + try: + update_backtest_metadata(file_abs, body.strategy, content) + except ValueError as e: + raise HTTPException(status_code=400, detail=str(e)) + + return get_backtest_result(file_abs) diff --git a/freqtrade/rpc/api_server/api_schemas.py b/freqtrade/rpc/api_server/api_schemas.py index b16a2c661..892865d43 100644 --- a/freqtrade/rpc/api_server/api_schemas.py +++ b/freqtrade/rpc/api_server/api_schemas.py @@ -524,6 +524,12 @@ class BacktestHistoryEntry(BaseModel): strategy: str run_id: str backtest_start_time: int + notes: Optional[str] = '' + + +class BacktestMetadataUpdate(BaseModel): + strategy: str + notes: str = '' class SysInfo(BaseModel): diff --git a/freqtrade/rpc/api_server/api_v1.py b/freqtrade/rpc/api_server/api_v1.py index 08c26c59b..2e2d57edc 100644 --- a/freqtrade/rpc/api_server/api_v1.py +++ b/freqtrade/rpc/api_server/api_v1.py @@ -50,7 +50,8 @@ logger = logging.getLogger(__name__) # 2.29: Add /exchanges endpoint # 2.30: new /pairlists endpoint # 2.31: new /backtest/history/ delete endpoint -API_VERSION = 2.31 +# 2.32: new /backtest/history/ patch endpoint +API_VERSION = 2.32 # Public API, requires no auth. router_public = APIRouter() diff --git a/freqtrade/rpc/discord.py b/freqtrade/rpc/discord.py index 8be0eab68..36ef37d01 100644 --- a/freqtrade/rpc/discord.py +++ b/freqtrade/rpc/discord.py @@ -20,6 +20,7 @@ class Discord(Webhook): self._format = 'json' self._retries = 1 self._retry_delay = 0.1 + self._timeout = self._config['discord'].get('timeout', 10) def cleanup(self) -> None: """ diff --git a/freqtrade/rpc/fiat_convert.py b/freqtrade/rpc/fiat_convert.py index ea13209c4..d790c4b48 100644 --- a/freqtrade/rpc/fiat_convert.py +++ b/freqtrade/rpc/fiat_convert.py @@ -26,6 +26,7 @@ coingecko_mapping = { 'sol': 'solana', 'usdt': 'tether', 'busd': 'binance-usd', + 'tusd': 'true-usd', } diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py index 466c99aa1..61f4384b7 100644 --- a/freqtrade/rpc/rpc.py +++ b/freqtrade/rpc/rpc.py @@ -605,17 +605,13 @@ class RPC: est_stake = balance.free est_bot_stake = amount else: - try: - pair = self._freqtrade.exchange.get_valid_pair_combination(coin, stake_currency) - rate: Optional[float] = tickers.get(pair, {}).get('last', None) - if rate: - if pair.startswith(stake_currency) and not pair.endswith(stake_currency): - rate = 1.0 / rate - est_stake = rate * balance.total - est_bot_stake = rate * amount - except (ExchangeError): - logger.warning(f"Could not get rate for pair {coin}.") - raise ValueError() + pair = self._freqtrade.exchange.get_valid_pair_combination(coin, stake_currency) + rate: Optional[float] = tickers.get(pair, {}).get('last', None) + if rate: + if pair.startswith(stake_currency) and not pair.endswith(stake_currency): + rate = 1.0 / rate + est_stake = rate * balance.total + est_bot_stake = rate * amount return est_stake, est_bot_stake diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py index 0f848130f..eca3e3ede 100644 --- a/freqtrade/strategy/interface.py +++ b/freqtrade/strategy/interface.py @@ -381,7 +381,7 @@ class IStrategy(ABC, HyperStrategyMixin): For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/ - When not implemented by a strategy, returns the initial stoploss value + When not implemented by a strategy, returns the initial stoploss value. Only called when use_custom_stoploss is set to True. :param pair: Pair that's currently analyzed @@ -1181,7 +1181,8 @@ class IStrategy(ABC, HyperStrategyMixin): bound = (low if trade.is_short else high) bound_profit = current_profit if not bound else trade.calc_profit_ratio(bound) if self.use_custom_stoploss and dir_correct: - stop_loss_value = strategy_safe_wrapper(self.custom_stoploss, default_retval=None + stop_loss_value = strategy_safe_wrapper(self.custom_stoploss, default_retval=None, + supress_error=True )(pair=trade.pair, trade=trade, current_time=current_time, current_rate=(bound or current_rate), diff --git a/freqtrade/templates/base_strategy.py.j2 b/freqtrade/templates/base_strategy.py.j2 index 53426b211..a4e0a2b24 100644 --- a/freqtrade/templates/base_strategy.py.j2 +++ b/freqtrade/templates/base_strategy.py.j2 @@ -78,19 +78,7 @@ class {{ strategy }}(IStrategy): buy_rsi = IntParameter(10, 40, default=30, space="buy") sell_rsi = IntParameter(60, 90, default=70, space="sell") - # Optional order type mapping. - order_types = { - 'entry': 'limit', - 'exit': 'limit', - 'stoploss': 'market', - 'stoploss_on_exchange': False - } - - # Optional order time in force. - order_time_in_force = { - 'entry': 'GTC', - 'exit': 'GTC' - } + {{ attributes | indent(4) }} {{ plot_config | indent(4) }} def informative_pairs(self): diff --git a/freqtrade/templates/strategy_subtemplates/strategy_attributes_full.j2 b/freqtrade/templates/strategy_subtemplates/strategy_attributes_full.j2 new file mode 100644 index 000000000..86445510d --- /dev/null +++ b/freqtrade/templates/strategy_subtemplates/strategy_attributes_full.j2 @@ -0,0 +1,13 @@ +# Optional order type mapping. +order_types = { + 'entry': 'limit', + 'exit': 'limit', + 'stoploss': 'market', + 'stoploss_on_exchange': False +} + +# Optional order time in force. +order_time_in_force = { + 'entry': 'GTC', + 'exit': 'GTC' +} diff --git a/freqtrade/templates/strategy_subtemplates/strategy_attributes_minimal.j2 b/freqtrade/templates/strategy_subtemplates/strategy_attributes_minimal.j2 new file mode 100644 index 000000000..e69de29bb diff --git a/freqtrade/types/backtest_result_type.py b/freqtrade/types/backtest_result_type.py index bc53097ab..1043899f7 100644 --- a/freqtrade/types/backtest_result_type.py +++ b/freqtrade/types/backtest_result_type.py @@ -25,3 +25,4 @@ def get_BacktestResultType_default() -> BacktestResultType: class BacktestHistoryEntryType(BacktestMetadataType): filename: str strategy: str + notes: str diff --git a/freqtrade/util/__init__.py b/freqtrade/util/__init__.py index 92c79b899..af09624ac 100644 --- a/freqtrade/util/__init__.py +++ b/freqtrade/util/__init__.py @@ -2,6 +2,7 @@ from freqtrade.util.datetime_helpers import (dt_floor_day, dt_from_ts, dt_humani dt_utc, format_ms_time, shorten_date) from freqtrade.util.ft_precise import FtPrecise from freqtrade.util.periodic_cache import PeriodicCache +from freqtrade.util.template_renderer import render_template, render_template_with_fallback # noqa __all__ = [ diff --git a/freqtrade/util/template_renderer.py b/freqtrade/util/template_renderer.py new file mode 100644 index 000000000..362d0f875 --- /dev/null +++ b/freqtrade/util/template_renderer.py @@ -0,0 +1,27 @@ +""" +Jinja2 rendering utils, used to generate new strategy and configurations. +""" + + +def render_template(templatefile: str, arguments: dict = {}) -> str: + + from jinja2 import Environment, PackageLoader, select_autoescape + + env = Environment( + loader=PackageLoader('freqtrade', 'templates'), + autoescape=select_autoescape(['html', 'xml']) + ) + template = env.get_template(templatefile) + return template.render(**arguments) + + +def render_template_with_fallback(templatefile: str, templatefallbackfile: str, + arguments: dict = {}) -> str: + """ + Use templatefile if possible, otherwise fall back to templatefallbackfile + """ + from jinja2.exceptions import TemplateNotFound + try: + return render_template(templatefile, arguments) + except TemplateNotFound: + return render_template(templatefallbackfile, arguments) diff --git a/mkdocs.yml b/mkdocs.yml index 815a10419..bb5ae0010 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -47,7 +47,6 @@ nav: - Advanced Hyperopt: advanced-hyperopt.md - Producer/Consumer mode: producer-consumer.md - Edge Positioning: edge.md - - Sandbox Testing: sandbox-testing.md - FAQ: faq.md - SQL Cheat-sheet: sql_cheatsheet.md - Strategy migration: strategy_migration.md diff --git a/pyproject.toml b/pyproject.toml index 17f91c7b2..40c0e2005 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -63,7 +63,7 @@ ignore = ["freqtrade/vendor/**"] [tool.ruff] line-length = 100 -extend-exclude = [".env"] +extend-exclude = [".env", ".venv"] target-version = "py38" extend-select = [ "C90", # mccabe diff --git a/requirements-dev.txt b/requirements-dev.txt index 9d1873f2e..f00a84b55 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -7,8 +7,8 @@ -r docs/requirements-docs.txt coveralls==3.3.1 -ruff==0.0.282 -mypy==1.4.1 +ruff==0.0.284 +mypy==1.5.0 pre-commit==3.3.3 pytest==7.4.0 pytest-asyncio==0.21.1 diff --git a/requirements-freqai-rl.txt b/requirements-freqai-rl.txt index 74c6d4ebe..3a49eed05 100644 --- a/requirements-freqai-rl.txt +++ b/requirements-freqai-rl.txt @@ -8,4 +8,4 @@ gymnasium==0.28.1 stable_baselines3==2.0.0 sb3_contrib>=2.0.0a9 # Progress bar for stable-baselines3 and sb3-contrib -tqdm==4.65.0 +tqdm==4.66.1 diff --git a/requirements-freqai.txt b/requirements-freqai.txt index 325b92544..d8421e968 100644 --- a/requirements-freqai.txt +++ b/requirements-freqai.txt @@ -4,9 +4,9 @@ # Required for freqai scikit-learn==1.1.3 -joblib==1.3.1 +joblib==1.3.2 catboost==1.2; 'arm' not in platform_machine lightgbm==4.0.0 xgboost==1.7.6 -tensorboard==2.13.0 +tensorboard==2.14.0 datasieve==0.1.7 diff --git a/requirements-plot.txt b/requirements-plot.txt index 72303efcb..f7d979814 100644 --- a/requirements-plot.txt +++ b/requirements-plot.txt @@ -1,4 +1,4 @@ # Include all requirements to run the bot. -r requirements.txt -plotly==5.15.0 +plotly==5.16.0 diff --git a/requirements.txt b/requirements.txt index 5ac592a3b..922daf80b 100644 --- a/requirements.txt +++ b/requirements.txt @@ -3,7 +3,7 @@ numpy==1.24.3; python_version <= '3.8' pandas==2.0.3 pandas-ta==0.3.14b -ccxt==4.0.47 +ccxt==4.0.59 cryptography==41.0.3; platform_machine != 'armv7l' cryptography==40.0.1; platform_machine == 'armv7l' aiohttp==3.8.5 @@ -15,7 +15,7 @@ arrow==1.2.3 cachetools==5.3.1 requests==2.31.0 urllib3==2.0.4 -jsonschema==4.18.4 +jsonschema==4.19.0 TA-Lib==0.4.27 technical==1.4.0 tabulate==0.9.0 @@ -23,7 +23,7 @@ pycoingecko==3.1.0 jinja2==3.1.2 tables==3.8.0 blosc==1.11.1 -joblib==1.3.1 +joblib==1.3.2 rich==13.5.2 pyarrow==12.0.1; platform_machine != 'armv7l' @@ -33,24 +33,24 @@ py_find_1st==1.1.5 # Load ticker files 30% faster python-rapidjson==1.10 # Properly format api responses -orjson==3.9.2 +orjson==3.9.4 # Notify systemd sdnotify==0.3.2 # API Server -fastapi==0.100.1 +fastapi==0.101.0 pydantic==2.1.1 uvicorn==0.23.2 pyjwt==2.8.0 -aiofiles==23.1.0 +aiofiles==23.2.1 psutil==5.9.5 # Support for colorized terminal output colorama==0.4.6 # Building config files interactively -questionary==1.10.0 -prompt-toolkit==3.0.39 +questionary==2.0.0 +prompt-toolkit==3.0.36 # Extensions to datetime library python-dateutil==2.8.2 diff --git a/setup.sh b/setup.sh index 84f804021..a53be205b 100755 --- a/setup.sh +++ b/setup.sh @@ -11,7 +11,7 @@ function check_installed_pip() { ${PYTHON} -m pip > /dev/null if [ $? -ne 0 ]; then echo_block "Installing Pip for ${PYTHON}" - curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py + curl https://bootstrap.pypa.io/get-pip.py -s -o get-pip.py ${PYTHON} get-pip.py rm get-pip.py fi @@ -41,12 +41,12 @@ function check_installed_python() { } function updateenv() { - echo_block "Updating your virtual env" - if [ ! -f .env/bin/activate ]; then + echo_block "Updating your virtual environment" + if [ ! -f .venv/bin/activate ]; then echo "Something went wrong, no virtual environment found." exit 1 fi - source .env/bin/activate + source .venv/bin/activate SYS_ARCH=$(uname -m) echo "pip install in-progress. Please wait..." ${PYTHON} -m pip install --upgrade pip wheel setuptools @@ -186,7 +186,14 @@ function install_redhat() { # Upgrade the bot function update() { git pull + if [ -f .env/bin/activate ]; then + # Old environment found - updating to new environment. + recreate_environments + fi updateenv + echo "Update completed." + echo_block "Don't forget to activate your virtual enviorment with 'source .venv/bin/activate'!" + } function check_git_changes() { @@ -199,6 +206,27 @@ function check_git_changes() { fi } +function recreate_environments() { + if [ -d ".env" ]; then + # Remove old virtual env + echo "- Deleting your previous virtual env" + echo "Warning: Your new environment will be at .venv!" + rm -rf .env + fi + if [ -d ".venv" ]; then + echo "- Deleting your previous virtual env" + rm -rf .venv + fi + + echo + ${PYTHON} -m venv .venv + if [ $? -ne 0 ]; then + echo "Could not create virtual environment. Leaving now" + exit 1 + fi + +} + # Reset Develop or Stable branch function reset() { echo_block "Resetting branch and virtual env" @@ -225,17 +253,8 @@ function reset() { else echo "Reset ignored because you are not on 'stable' or 'develop'." fi + recreate_environments - if [ -d ".env" ]; then - echo "- Deleting your previous virtual env" - rm -rf .env - fi - echo - ${PYTHON} -m venv .env - if [ $? -ne 0 ]; then - echo "Could not create virtual environment. Leaving now" - exit 1 - fi updateenv } @@ -266,9 +285,9 @@ function install() { reset config echo_block "Run the bot !" - echo "You can now use the bot by executing 'source .env/bin/activate; freqtrade '." - echo "You can see the list of available bot sub-commands by executing 'source .env/bin/activate; freqtrade --help'." - echo "You verify that freqtrade is installed successfully by running 'source .env/bin/activate; freqtrade --version'." + echo "You can now use the bot by executing 'source .venv/bin/activate; freqtrade '." + echo "You can see the list of available bot sub-commands by executing 'source .venv/bin/activate; freqtrade --help'." + echo "You verify that freqtrade is installed successfully by running 'source .venv/bin/activate; freqtrade --version'." } function plot() { diff --git a/tests/data/test_converter.py b/tests/data/test_converter.py index 6a2cb5638..f23a85501 100644 --- a/tests/data/test_converter.py +++ b/tests/data/test_converter.py @@ -34,26 +34,21 @@ def test_ohlcv_to_dataframe(ohlcv_history_list, caplog): assert log_has('Converting candle (OHLCV) data to dataframe for pair UNITTEST/BTC.', caplog) -def test_trades_to_ohlcv(ohlcv_history_list, caplog): +def test_trades_to_ohlcv(trades_history, caplog): caplog.set_level(logging.DEBUG) with pytest.raises(ValueError, match="Trade-list empty."): trades_to_ohlcv([], '1m') - trades = [ - [1570752011620, "13519807", None, "sell", 0.00141342, 23.0, 0.03250866], - [1570752011620, "13519808", None, "sell", 0.00141266, 54.0, 0.07628364], - [1570752017964, "13519809", None, "sell", 0.00141266, 8.0, 0.01130128]] - - df = trades_to_ohlcv(trades, '1m') + df = trades_to_ohlcv(trades_history, '1m') assert not df.empty assert len(df) == 1 assert 'open' in df.columns assert 'high' in df.columns assert 'low' in df.columns assert 'close' in df.columns - assert df.loc[:, 'high'][0] == 0.00141342 - assert df.loc[:, 'low'][0] == 0.00141266 + assert df.loc[:, 'high'][0] == 0.019627 + assert df.loc[:, 'low'][0] == 0.019626 def test_ohlcv_fill_up_missing_data(testdatadir, caplog): diff --git a/tests/data/test_dataprovider.py b/tests/data/test_dataprovider.py index 4ff4f214b..31c6763bc 100644 --- a/tests/data/test_dataprovider.py +++ b/tests/data/test_dataprovider.py @@ -129,9 +129,14 @@ def test_get_pair_dataframe(mocker, default_conf, ohlcv_history, candle_type): default_conf["runmode"] = RunMode.BACKTEST dp = DataProvider(default_conf, exchange) assert dp.runmode == RunMode.BACKTEST - assert isinstance(dp.get_pair_dataframe( - "UNITTEST/BTC", timeframe, candle_type=candle_type), DataFrame) - # assert dp.get_pair_dataframe("NONESENSE/AAA", timeframe).empty + df = dp.get_pair_dataframe("UNITTEST/BTC", timeframe, candle_type=candle_type) + assert isinstance(df, DataFrame) + assert len(df) == 3 # ohlcv_history mock has just 3 rows + + dp._set_dataframe_max_date(ohlcv_history.iloc[-1]['date']) + df = dp.get_pair_dataframe("UNITTEST/BTC", timeframe, candle_type=candle_type) + assert isinstance(df, DataFrame) + assert len(df) == 2 # ohlcv_history is limited to 2 rows now def test_available_pairs(mocker, default_conf, ohlcv_history): diff --git a/tests/exchange/test_binance.py b/tests/exchange/test_binance.py index 9018d2db9..c4e657ad9 100644 --- a/tests/exchange/test_binance.py +++ b/tests/exchange/test_binance.py @@ -35,7 +35,7 @@ def test__get_params_binance(default_conf, mocker, side, type, time_in_force, ex ]) def test_create_stoploss_order_binance(default_conf, mocker, limitratio, expected, side, trademode): api_mock = MagicMock() - order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6)) + order_id = f'test_prod_buy_{randint(0, 10 ** 6)}' order_type = 'stop_loss_limit' if trademode == TradingMode.SPOT else 'stop' api_mock.create_order = MagicMock(return_value={ diff --git a/tests/exchange/test_bybit.py b/tests/exchange/test_bybit.py index d0d5114a1..7495f543b 100644 --- a/tests/exchange/test_bybit.py +++ b/tests/exchange/test_bybit.py @@ -3,7 +3,6 @@ from unittest.mock import MagicMock from freqtrade.enums.marginmode import MarginMode from freqtrade.enums.tradingmode import TradingMode -from freqtrade.exchange.exchange_utils import timeframe_to_msecs from tests.conftest import get_mock_coro, get_patched_exchange from tests.exchange.test_exchange import ccxt_exceptionhandlers @@ -37,12 +36,10 @@ async def test_bybit_fetch_funding_rate(default_conf, mocker): assert api_mock.fetch_funding_rate_history.call_count == 1 assert api_mock.fetch_funding_rate_history.call_args_list[0][0][0] == 'BTC/USDT:USDT' kwargs = api_mock.fetch_funding_rate_history.call_args_list[0][1] - assert kwargs['params'] == {} assert kwargs['since'] is None api_mock.fetch_funding_rate_history.reset_mock() since_ms = 1610000000000 - since_ms_end = since_ms + (timeframe_to_msecs('4h') * limit) # Test fetch_funding_rate_history (current data) await exchange._fetch_funding_rate_history( pair='BTC/USDT:USDT', @@ -54,7 +51,6 @@ async def test_bybit_fetch_funding_rate(default_conf, mocker): assert api_mock.fetch_funding_rate_history.call_count == 1 assert api_mock.fetch_funding_rate_history.call_args_list[0][0][0] == 'BTC/USDT:USDT' kwargs = api_mock.fetch_funding_rate_history.call_args_list[0][1] - assert kwargs['params'] == {'until': since_ms_end} assert kwargs['since'] == since_ms diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py index 289a67c4a..84b525cff 100644 --- a/tests/exchange/test_exchange.py +++ b/tests/exchange/test_exchange.py @@ -556,41 +556,6 @@ def test_get_min_pair_stake_amount_real_data(mocker, default_conf) -> None: assert result == 4000 -def test_set_sandbox(default_conf, mocker): - """ - Test working scenario - """ - api_mock = MagicMock() - api_mock.load_markets = MagicMock(return_value={ - 'ETH/BTC': '', 'LTC/BTC': '', 'XRP/BTC': '', 'NEO/BTC': '' - }) - url_mock = PropertyMock(return_value={'test': "api-public.sandbox.gdax.com", - 'api': 'https://api.gdax.com'}) - type(api_mock).urls = url_mock - exchange = get_patched_exchange(mocker, default_conf, api_mock) - liveurl = exchange._api.urls['api'] - default_conf['exchange']['sandbox'] = True - exchange.set_sandbox(exchange._api, default_conf['exchange'], 'Logname') - assert exchange._api.urls['api'] != liveurl - - -def test_set_sandbox_exception(default_conf, mocker): - """ - Test Fail scenario - """ - api_mock = MagicMock() - api_mock.load_markets = MagicMock(return_value={ - 'ETH/BTC': '', 'LTC/BTC': '', 'XRP/BTC': '', 'NEO/BTC': '' - }) - url_mock = PropertyMock(return_value={'api': 'https://api.gdax.com'}) - type(api_mock).urls = url_mock - - with pytest.raises(OperationalException, match=r'does not provide a sandbox api'): - exchange = get_patched_exchange(mocker, default_conf, api_mock) - default_conf['exchange']['sandbox'] = True - exchange.set_sandbox(exchange._api, default_conf['exchange'], 'Logname') - - def test__load_async_markets(default_conf, mocker, caplog): mocker.patch(f'{EXMS}._init_ccxt') mocker.patch(f'{EXMS}.validate_pairs') @@ -1372,7 +1337,7 @@ def test_create_dry_run_order_market_fill(default_conf, mocker, side, rate, amou @pytest.mark.parametrize("exchange_name", EXCHANGES) def test_create_order(default_conf, mocker, side, ordertype, rate, marketprice, exchange_name): api_mock = MagicMock() - order_id = 'test_prod_{}_{}'.format(side, randint(0, 10 ** 6)) + order_id = f'test_prod_{side}_{randint(0, 10 ** 6)}' api_mock.options = {} if not marketprice else {"createMarketBuyOrderRequiresPrice": True} api_mock.create_order = MagicMock(return_value={ 'id': order_id, @@ -1452,7 +1417,7 @@ def test_buy_dry_run(default_conf, mocker, exchange_name): @pytest.mark.parametrize("exchange_name", EXCHANGES) def test_buy_prod(default_conf, mocker, exchange_name): api_mock = MagicMock() - order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6)) + order_id = f'test_prod_buy_{randint(0, 10 ** 6)}' order_type = 'market' time_in_force = 'gtc' api_mock.options = {} @@ -1541,7 +1506,7 @@ def test_buy_prod(default_conf, mocker, exchange_name): @pytest.mark.parametrize("exchange_name", EXCHANGES) def test_buy_considers_time_in_force(default_conf, mocker, exchange_name): api_mock = MagicMock() - order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6)) + order_id = f'test_prod_buy_{randint(0, 10 ** 6)}' api_mock.options = {} api_mock.create_order = MagicMock(return_value={ 'id': order_id, @@ -1608,7 +1573,7 @@ def test_sell_dry_run(default_conf, mocker): @pytest.mark.parametrize("exchange_name", EXCHANGES) def test_sell_prod(default_conf, mocker, exchange_name): api_mock = MagicMock() - order_id = 'test_prod_sell_{}'.format(randint(0, 10 ** 6)) + order_id = f'test_prod_sell_{randint(0, 10 ** 6)}' order_type = 'market' api_mock.options = {} api_mock.create_order = MagicMock(return_value={ @@ -1686,7 +1651,7 @@ def test_sell_prod(default_conf, mocker, exchange_name): @pytest.mark.parametrize("exchange_name", EXCHANGES) def test_sell_considers_time_in_force(default_conf, mocker, exchange_name): api_mock = MagicMock() - order_id = 'test_prod_sell_{}'.format(randint(0, 10 ** 6)) + order_id = f'test_prod_sell_{randint(0, 10 ** 6)}' api_mock.create_order = MagicMock(return_value={ 'id': order_id, 'symbol': 'ETH/BTC', @@ -2100,7 +2065,7 @@ def test_get_historic_ohlcv(default_conf, mocker, caplog, exchange_name, candle_ exchange._async_get_candle_history = Mock(wraps=mock_candle_hist) # one_call calculation * 1.8 should do 2 calls - since = 5 * 60 * exchange.ohlcv_candle_limit('5m', CandleType.SPOT) * 1.8 + since = 5 * 60 * exchange.ohlcv_candle_limit('5m', candle_type) * 1.8 ret = exchange.get_historic_ohlcv( pair, "5m", @@ -3557,7 +3522,7 @@ def test_get_valid_pair_combination(default_conf, mocker, markets): assert ex.get_valid_pair_combination("ETH", "BTC") == "ETH/BTC" assert ex.get_valid_pair_combination("BTC", "ETH") == "ETH/BTC" - with pytest.raises(DependencyException, match=r"Could not combine.* to get a valid pair."): + with pytest.raises(ValueError, match=r"Could not combine.* to get a valid pair."): ex.get_valid_pair_combination("NOPAIR", "ETH") @@ -5392,7 +5357,7 @@ def test_get_liquidation_price( ]) def test_stoploss_contract_size(mocker, default_conf, contract_size, order_amount): api_mock = MagicMock() - order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6)) + order_id = f'test_prod_buy_{randint(0, 10 ** 6)}' api_mock.create_order = MagicMock(return_value={ 'id': order_id, diff --git a/tests/exchange/test_huobi.py b/tests/exchange/test_huobi.py index 8be8ef8b3..b3f3c0900 100644 --- a/tests/exchange/test_huobi.py +++ b/tests/exchange/test_huobi.py @@ -16,7 +16,7 @@ from tests.exchange.test_exchange import ccxt_exceptionhandlers ]) def test_create_stoploss_order_huobi(default_conf, mocker, limitratio, expected, side): api_mock = MagicMock() - order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6)) + order_id = f'test_prod_buy_{randint(0, 10 ** 6)}' order_type = 'stop-limit' api_mock.create_order = MagicMock(return_value={ diff --git a/tests/exchange/test_kraken.py b/tests/exchange/test_kraken.py index 8fc23b94e..7db3eeeeb 100644 --- a/tests/exchange/test_kraken.py +++ b/tests/exchange/test_kraken.py @@ -15,7 +15,7 @@ STOPLOSS_LIMIT_ORDERTYPE = 'stop-loss-limit' def test_buy_kraken_trading_agreement(default_conf, mocker): api_mock = MagicMock() - order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6)) + order_id = f'test_prod_buy_{randint(0, 10 ** 6)}' order_type = 'limit' time_in_force = 'ioc' api_mock.options = {} @@ -56,7 +56,7 @@ def test_buy_kraken_trading_agreement(default_conf, mocker): def test_sell_kraken_trading_agreement(default_conf, mocker): api_mock = MagicMock() - order_id = 'test_prod_sell_{}'.format(randint(0, 10 ** 6)) + order_id = f'test_prod_sell_{randint(0, 10 ** 6)}' order_type = 'market' api_mock.options = {} api_mock.create_order = MagicMock(return_value={ @@ -181,7 +181,7 @@ def test_get_balances_prod(default_conf, mocker): ]) def test_create_stoploss_order_kraken(default_conf, mocker, ordertype, side, adjustedprice): api_mock = MagicMock() - order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6)) + order_id = f'test_prod_buy_{randint(0, 10 ** 6)}' api_mock.create_order = MagicMock(return_value={ 'id': order_id, diff --git a/tests/exchange/test_kucoin.py b/tests/exchange/test_kucoin.py index 741ee27be..a74b77859 100644 --- a/tests/exchange/test_kucoin.py +++ b/tests/exchange/test_kucoin.py @@ -17,7 +17,7 @@ from tests.exchange.test_exchange import ccxt_exceptionhandlers ]) def test_create_stoploss_order_kucoin(default_conf, mocker, limitratio, expected, side, order_type): api_mock = MagicMock() - order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6)) + order_id = f'test_prod_buy_{randint(0, 10 ** 6)}' api_mock.create_order = MagicMock(return_value={ 'id': order_id, @@ -136,7 +136,7 @@ def test_stoploss_adjust_kucoin(mocker, default_conf): ]) def test_kucoin_create_order(default_conf, mocker, side, ordertype, rate): api_mock = MagicMock() - order_id = 'test_prod_{}_{}'.format(side, randint(0, 10 ** 6)) + order_id = f'test_prod_{side}_{randint(0, 10 ** 6)}' api_mock.create_order = MagicMock(return_value={ 'id': order_id, 'info': { diff --git a/tests/exchange_online/__init__.py b/tests/exchange_online/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/tests/exchange_online/conftest.py b/tests/exchange_online/conftest.py new file mode 100644 index 000000000..45da16dd5 --- /dev/null +++ b/tests/exchange_online/conftest.py @@ -0,0 +1,334 @@ +from copy import deepcopy +from pathlib import Path +from typing import Tuple + +import pytest + +from freqtrade.constants import Config +from freqtrade.exchange.exchange import Exchange +from freqtrade.resolvers.exchange_resolver import ExchangeResolver +from tests.conftest import EXMS, get_default_conf_usdt + + +EXCHANGE_FIXTURE_TYPE = Tuple[Exchange, str] + +# Exchanges that should be tested online +EXCHANGES = { + 'bittrex': { + 'pair': 'BTC/USDT', + 'stake_currency': 'USDT', + 'hasQuoteVolume': False, + 'timeframe': '1h', + 'leverage_tiers_public': False, + 'leverage_in_spot_market': False, + }, + 'binance': { + 'pair': 'BTC/USDT', + 'stake_currency': 'USDT', + 'use_ci_proxy': True, + 'hasQuoteVolume': True, + 'timeframe': '1h', + 'futures': True, + 'futures_pair': 'BTC/USDT:USDT', + 'hasQuoteVolumeFutures': True, + 'leverage_tiers_public': False, + 'leverage_in_spot_market': False, + 'trades_lookback_hours': 4, + 'private_methods': [ + 'fapiPrivateGetPositionSideDual', + 'fapiPrivateGetMultiAssetsMargin' + ], + 'sample_order': [{ + "symbol": "SOLUSDT", + "orderId": 3551312894, + "orderListId": -1, + "clientOrderId": "x-R4DD3S8297c73a11ccb9dc8f2811ba", + "transactTime": 1674493798550, + "price": "15.50000000", + "origQty": "1.10000000", + "executedQty": "0.00000000", + "cummulativeQuoteQty": "0.00000000", + "status": "NEW", + "timeInForce": "GTC", + "type": "LIMIT", + "side": "BUY", + "workingTime": 1674493798550, + "fills": [], + "selfTradePreventionMode": "NONE", + }] + }, + 'binanceus': { + 'pair': 'BTC/USDT', + 'stake_currency': 'USDT', + 'hasQuoteVolume': True, + 'timeframe': '1h', + 'futures': False, + 'sample_order': [{ + "symbol": "SOLUSDT", + "orderId": 3551312894, + "orderListId": -1, + "clientOrderId": "x-R4DD3S8297c73a11ccb9dc8f2811ba", + "transactTime": 1674493798550, + "price": "15.50000000", + "origQty": "1.10000000", + "executedQty": "0.00000000", + "cummulativeQuoteQty": "0.00000000", + "status": "NEW", + "timeInForce": "GTC", + "type": "LIMIT", + "side": "BUY", + "workingTime": 1674493798550, + "fills": [], + "selfTradePreventionMode": "NONE", + }] + }, + 'kraken': { + 'pair': 'BTC/USD', + 'stake_currency': 'USD', + 'hasQuoteVolume': True, + 'timeframe': '1h', + 'leverage_tiers_public': False, + 'leverage_in_spot_market': True, + 'trades_lookback_hours': 12, + }, + 'kucoin': { + 'pair': 'XRP/USDT', + 'stake_currency': 'USDT', + 'hasQuoteVolume': True, + 'timeframe': '1h', + 'leverage_tiers_public': False, + 'leverage_in_spot_market': True, + 'sample_order': [ + {'id': '63d6742d0adc5570001d2bbf7'}, # create order + { + 'id': '63d6742d0adc5570001d2bbf7', + 'symbol': 'SOL-USDT', + 'opType': 'DEAL', + 'type': 'limit', + 'side': 'buy', + 'price': '15.5', + 'size': '1.1', + 'funds': '0', + 'dealFunds': '17.05', + 'dealSize': '1.1', + 'fee': '0.000065252', + 'feeCurrency': 'USDT', + 'stp': '', + 'stop': '', + 'stopTriggered': False, + 'stopPrice': '0', + 'timeInForce': 'GTC', + 'postOnly': False, + 'hidden': False, + 'iceberg': False, + 'visibleSize': '0', + 'cancelAfter': 0, + 'channel': 'API', + 'clientOid': '0a053870-11bf-41e5-be61-b272a4cb62e1', + 'remark': None, + 'tags': 'partner:ccxt', + 'isActive': False, + 'cancelExist': False, + 'createdAt': 1674493798550, + 'tradeType': 'TRADE' + }], + }, + 'gate': { + 'pair': 'BTC/USDT', + 'stake_currency': 'USDT', + 'hasQuoteVolume': True, + 'timeframe': '1h', + 'futures': True, + 'futures_pair': 'BTC/USDT:USDT', + 'hasQuoteVolumeFutures': True, + 'leverage_tiers_public': True, + 'leverage_in_spot_market': True, + 'sample_order': [ + { + "id": "276266139423", + "text": "apiv4", + "create_time": "1674493798", + "update_time": "1674493798", + "create_time_ms": "1674493798550", + "update_time_ms": "1674493798550", + "status": "closed", + "currency_pair": "SOL_USDT", + "type": "limit", + "account": "spot", + "side": "buy", + "amount": "1.1", + "price": "15.5", + "time_in_force": "gtc", + "iceberg": "0", + "left": "0", + "fill_price": "17.05", + "filled_total": "17.05", + "avg_deal_price": "15.5", + "fee": "0.0000018", + "fee_currency": "SOL", + "point_fee": "0", + "gt_fee": "0", + "gt_maker_fee": "0", + "gt_taker_fee": "0.0015", + "gt_discount": True, + "rebated_fee": "0", + "rebated_fee_currency": "USDT" + }, + { + # market order + 'id': '276401180529', + 'text': 'apiv4', + 'create_time': '1674493798', + 'update_time': '1674493798', + 'create_time_ms': '1674493798550', + 'update_time_ms': '1674493798550', + 'status': 'cancelled', + 'currency_pair': 'SOL_USDT', + 'type': 'market', + 'account': 'spot', + 'side': 'buy', + 'amount': '17.05', + 'price': '0', + 'time_in_force': 'ioc', + 'iceberg': '0', + 'left': '0.0000000016228', + 'fill_price': '17.05', + 'filled_total': '17.05', + 'avg_deal_price': '15.5', + 'fee': '0', + 'fee_currency': 'SOL', + 'point_fee': '0.0199999999967544', + 'gt_fee': '0', + 'gt_maker_fee': '0', + 'gt_taker_fee': '0', + 'gt_discount': False, + 'rebated_fee': '0', + 'rebated_fee_currency': 'USDT' + } + ], + }, + 'okx': { + 'pair': 'BTC/USDT', + 'stake_currency': 'USDT', + 'hasQuoteVolume': True, + 'timeframe': '1h', + 'futures': True, + 'futures_pair': 'BTC/USDT:USDT', + 'hasQuoteVolumeFutures': False, + 'leverage_tiers_public': True, + 'leverage_in_spot_market': True, + 'private_methods': ['fetch_accounts'], + }, + 'bybit': { + 'pair': 'BTC/USDT', + 'stake_currency': 'USDT', + 'hasQuoteVolume': True, + 'use_ci_proxy': True, + 'timeframe': '1h', + 'futures_pair': 'BTC/USDT:USDT', + 'futures': True, + 'leverage_tiers_public': True, + 'leverage_in_spot_market': True, + 'sample_order': [ + { + "orderId": "1274754916287346280", + "orderLinkId": "1666798627015730", + "symbol": "SOLUSDT", + "createTime": "1674493798550", + "orderPrice": "15.5", + "orderQty": "1.1", + "orderType": "LIMIT", + "side": "BUY", + "status": "NEW", + "timeInForce": "GTC", + "accountId": "5555555", + "execQty": "0", + "orderCategory": "0" + } + ] + }, + 'huobi': { + 'pair': 'ETH/BTC', + 'stake_currency': 'BTC', + 'hasQuoteVolume': True, + 'timeframe': '1h', + 'futures': False, + }, + 'bitvavo': { + 'pair': 'BTC/EUR', + 'stake_currency': 'EUR', + 'hasQuoteVolume': True, + 'timeframe': '1h', + 'leverage_tiers_public': False, + 'leverage_in_spot_market': False, + }, +} + + +@pytest.fixture(scope="class") +def exchange_conf(): + config = get_default_conf_usdt((Path(__file__).parent / "testdata").resolve()) + config['exchange']['pair_whitelist'] = [] + config['exchange']['key'] = '' + config['exchange']['secret'] = '' + config['dry_run'] = False + config['entry_pricing']['use_order_book'] = True + config['exit_pricing']['use_order_book'] = True + return config + + +def set_test_proxy(config: Config, use_proxy: bool) -> Config: + # Set proxy to test in CI. + import os + if use_proxy and (proxy := os.environ.get('CI_WEB_PROXY')): + config1 = deepcopy(config) + config1['exchange']['ccxt_config'] = { + "httpsProxy": proxy, + } + return config1 + + return config + + +def get_exchange(exchange_name, exchange_conf): + exchange_conf = set_test_proxy( + exchange_conf, EXCHANGES[exchange_name].get('use_ci_proxy', False)) + exchange_conf['exchange']['name'] = exchange_name + exchange_conf['stake_currency'] = EXCHANGES[exchange_name]['stake_currency'] + exchange = ExchangeResolver.load_exchange(exchange_conf, validate=True, + load_leverage_tiers=True) + + yield exchange, exchange_name + + +def get_futures_exchange(exchange_name, exchange_conf, class_mocker): + if EXCHANGES[exchange_name].get('futures') is not True: + pytest.skip(f"Exchange {exchange_name} does not support futures.") + else: + exchange_conf = deepcopy(exchange_conf) + exchange_conf = set_test_proxy( + exchange_conf, EXCHANGES[exchange_name].get('use_ci_proxy', False)) + exchange_conf['trading_mode'] = 'futures' + exchange_conf['margin_mode'] = 'isolated' + + class_mocker.patch( + 'freqtrade.exchange.binance.Binance.fill_leverage_tiers') + class_mocker.patch(f'{EXMS}.fetch_trading_fees') + class_mocker.patch('freqtrade.exchange.okx.Okx.additional_exchange_init') + class_mocker.patch('freqtrade.exchange.binance.Binance.additional_exchange_init') + class_mocker.patch('freqtrade.exchange.bybit.Bybit.additional_exchange_init') + class_mocker.patch(f'{EXMS}.load_cached_leverage_tiers', return_value=None) + class_mocker.patch(f'{EXMS}.cache_leverage_tiers') + + yield from get_exchange(exchange_name, exchange_conf) + + +@pytest.fixture(params=EXCHANGES, scope="class") +def exchange(request, exchange_conf): + yield from get_exchange(request.param, exchange_conf) + + +@pytest.fixture(params=EXCHANGES, scope="class") +def exchange_futures(request, exchange_conf, class_mocker): + + yield from get_futures_exchange(request.param, exchange_conf, class_mocker) diff --git a/tests/exchange/test_ccxt_compat.py b/tests/exchange_online/test_ccxt_compat.py similarity index 57% rename from tests/exchange/test_ccxt_compat.py rename to tests/exchange_online/test_ccxt_compat.py index c57e32633..e33875416 100644 --- a/tests/exchange/test_ccxt_compat.py +++ b/tests/exchange_online/test_ccxt_compat.py @@ -5,338 +5,14 @@ However, these tests should give a good idea to determine if a new exchange is suitable to run with freqtrade. """ -from copy import deepcopy from datetime import datetime, timedelta, timezone -from pathlib import Path -from typing import Tuple import pytest -from freqtrade.constants import Config from freqtrade.enums import CandleType from freqtrade.exchange import timeframe_to_minutes, timeframe_to_prev_date -from freqtrade.exchange.exchange import Exchange, timeframe_to_msecs -from freqtrade.resolvers.exchange_resolver import ExchangeResolver -from tests.conftest import EXMS, get_default_conf_usdt - - -EXCHANGE_FIXTURE_TYPE = Tuple[Exchange, str] - -# Exchanges that should be tested -EXCHANGES = { - 'bittrex': { - 'pair': 'BTC/USDT', - 'stake_currency': 'USDT', - 'hasQuoteVolume': False, - 'timeframe': '1h', - 'leverage_tiers_public': False, - 'leverage_in_spot_market': False, - }, - 'binance': { - 'pair': 'BTC/USDT', - 'stake_currency': 'USDT', - 'use_ci_proxy': True, - 'hasQuoteVolume': True, - 'timeframe': '1h', - 'futures': True, - 'futures_pair': 'BTC/USDT:USDT', - 'hasQuoteVolumeFutures': True, - 'leverage_tiers_public': False, - 'leverage_in_spot_market': False, - 'trades_lookback_hours': 4, - 'private_methods': [ - 'fapiPrivateGetPositionSideDual', - 'fapiPrivateGetMultiAssetsMargin' - ], - 'sample_order': [{ - "symbol": "SOLUSDT", - "orderId": 3551312894, - "orderListId": -1, - "clientOrderId": "x-R4DD3S8297c73a11ccb9dc8f2811ba", - "transactTime": 1674493798550, - "price": "15.50000000", - "origQty": "1.10000000", - "executedQty": "0.00000000", - "cummulativeQuoteQty": "0.00000000", - "status": "NEW", - "timeInForce": "GTC", - "type": "LIMIT", - "side": "BUY", - "workingTime": 1674493798550, - "fills": [], - "selfTradePreventionMode": "NONE", - }] - }, - 'binanceus': { - 'pair': 'BTC/USDT', - 'stake_currency': 'USDT', - 'hasQuoteVolume': True, - 'timeframe': '1h', - 'futures': False, - 'sample_order': [{ - "symbol": "SOLUSDT", - "orderId": 3551312894, - "orderListId": -1, - "clientOrderId": "x-R4DD3S8297c73a11ccb9dc8f2811ba", - "transactTime": 1674493798550, - "price": "15.50000000", - "origQty": "1.10000000", - "executedQty": "0.00000000", - "cummulativeQuoteQty": "0.00000000", - "status": "NEW", - "timeInForce": "GTC", - "type": "LIMIT", - "side": "BUY", - "workingTime": 1674493798550, - "fills": [], - "selfTradePreventionMode": "NONE", - }] - }, - 'kraken': { - 'pair': 'BTC/USD', - 'stake_currency': 'USD', - 'hasQuoteVolume': True, - 'timeframe': '1h', - 'leverage_tiers_public': False, - 'leverage_in_spot_market': True, - 'trades_lookback_hours': 12, - }, - 'kucoin': { - 'pair': 'XRP/USDT', - 'stake_currency': 'USDT', - 'hasQuoteVolume': True, - 'timeframe': '1h', - 'leverage_tiers_public': False, - 'leverage_in_spot_market': True, - 'sample_order': [ - {'id': '63d6742d0adc5570001d2bbf7'}, # create order - { - 'id': '63d6742d0adc5570001d2bbf7', - 'symbol': 'SOL-USDT', - 'opType': 'DEAL', - 'type': 'limit', - 'side': 'buy', - 'price': '15.5', - 'size': '1.1', - 'funds': '0', - 'dealFunds': '17.05', - 'dealSize': '1.1', - 'fee': '0.000065252', - 'feeCurrency': 'USDT', - 'stp': '', - 'stop': '', - 'stopTriggered': False, - 'stopPrice': '0', - 'timeInForce': 'GTC', - 'postOnly': False, - 'hidden': False, - 'iceberg': False, - 'visibleSize': '0', - 'cancelAfter': 0, - 'channel': 'API', - 'clientOid': '0a053870-11bf-41e5-be61-b272a4cb62e1', - 'remark': None, - 'tags': 'partner:ccxt', - 'isActive': False, - 'cancelExist': False, - 'createdAt': 1674493798550, - 'tradeType': 'TRADE' - }], - }, - 'gate': { - 'pair': 'BTC/USDT', - 'stake_currency': 'USDT', - 'hasQuoteVolume': True, - 'timeframe': '1h', - 'futures': True, - 'futures_pair': 'BTC/USDT:USDT', - 'hasQuoteVolumeFutures': True, - 'leverage_tiers_public': True, - 'leverage_in_spot_market': True, - 'sample_order': [ - { - "id": "276266139423", - "text": "apiv4", - "create_time": "1674493798", - "update_time": "1674493798", - "create_time_ms": "1674493798550", - "update_time_ms": "1674493798550", - "status": "closed", - "currency_pair": "SOL_USDT", - "type": "limit", - "account": "spot", - "side": "buy", - "amount": "1.1", - "price": "15.5", - "time_in_force": "gtc", - "iceberg": "0", - "left": "0", - "fill_price": "17.05", - "filled_total": "17.05", - "avg_deal_price": "15.5", - "fee": "0.0000018", - "fee_currency": "SOL", - "point_fee": "0", - "gt_fee": "0", - "gt_maker_fee": "0", - "gt_taker_fee": "0.0015", - "gt_discount": True, - "rebated_fee": "0", - "rebated_fee_currency": "USDT" - }, - { - # market order - 'id': '276401180529', - 'text': 'apiv4', - 'create_time': '1674493798', - 'update_time': '1674493798', - 'create_time_ms': '1674493798550', - 'update_time_ms': '1674493798550', - 'status': 'cancelled', - 'currency_pair': 'SOL_USDT', - 'type': 'market', - 'account': 'spot', - 'side': 'buy', - 'amount': '17.05', - 'price': '0', - 'time_in_force': 'ioc', - 'iceberg': '0', - 'left': '0.0000000016228', - 'fill_price': '17.05', - 'filled_total': '17.05', - 'avg_deal_price': '15.5', - 'fee': '0', - 'fee_currency': 'SOL', - 'point_fee': '0.0199999999967544', - 'gt_fee': '0', - 'gt_maker_fee': '0', - 'gt_taker_fee': '0', - 'gt_discount': False, - 'rebated_fee': '0', - 'rebated_fee_currency': 'USDT' - } - ], - }, - 'okx': { - 'pair': 'BTC/USDT', - 'stake_currency': 'USDT', - 'hasQuoteVolume': True, - 'timeframe': '1h', - 'futures': True, - 'futures_pair': 'BTC/USDT:USDT', - 'hasQuoteVolumeFutures': False, - 'leverage_tiers_public': True, - 'leverage_in_spot_market': True, - 'private_methods': ['fetch_accounts'], - }, - 'bybit': { - 'pair': 'BTC/USDT', - 'stake_currency': 'USDT', - 'hasQuoteVolume': True, - 'use_ci_proxy': True, - 'timeframe': '1h', - 'futures_pair': 'BTC/USDT:USDT', - 'futures': True, - 'leverage_tiers_public': True, - 'leverage_in_spot_market': True, - 'sample_order': [ - { - "orderId": "1274754916287346280", - "orderLinkId": "1666798627015730", - "symbol": "SOLUSDT", - "createTime": "1674493798550", - "orderPrice": "15.5", - "orderQty": "1.1", - "orderType": "LIMIT", - "side": "BUY", - "status": "NEW", - "timeInForce": "GTC", - "accountId": "5555555", - "execQty": "0", - "orderCategory": "0" - } - ] - }, - 'huobi': { - 'pair': 'ETH/BTC', - 'stake_currency': 'BTC', - 'hasQuoteVolume': True, - 'timeframe': '1h', - 'futures': False, - }, - 'bitvavo': { - 'pair': 'BTC/EUR', - 'stake_currency': 'EUR', - 'hasQuoteVolume': True, - 'timeframe': '1h', - 'leverage_tiers_public': False, - 'leverage_in_spot_market': False, - }, -} - - -@pytest.fixture(scope="class") -def exchange_conf(): - config = get_default_conf_usdt((Path(__file__).parent / "testdata").resolve()) - config['exchange']['pair_whitelist'] = [] - config['exchange']['key'] = '' - config['exchange']['secret'] = '' - config['dry_run'] = False - config['entry_pricing']['use_order_book'] = True - config['exit_pricing']['use_order_book'] = True - return config - - -def set_test_proxy(config: Config, use_proxy: bool) -> Config: - # Set proxy to test in CI. - import os - if use_proxy and (proxy := os.environ.get('CI_WEB_PROXY')): - config1 = deepcopy(config) - config1['exchange']['ccxt_config'] = { - "httpsProxy": proxy, - } - return config1 - - return config - - -@pytest.fixture(params=EXCHANGES, scope="class") -def exchange(request, exchange_conf): - exchange_conf = set_test_proxy( - exchange_conf, EXCHANGES[request.param].get('use_ci_proxy', False)) - exchange_conf['exchange']['name'] = request.param - exchange_conf['stake_currency'] = EXCHANGES[request.param]['stake_currency'] - exchange = ExchangeResolver.load_exchange(exchange_conf, validate=True) - - yield exchange, request.param - - -@pytest.fixture(params=EXCHANGES, scope="class") -def exchange_futures(request, exchange_conf, class_mocker): - if EXCHANGES[request.param].get('futures') is not True: - yield None, request.param - else: - exchange_conf = set_test_proxy( - exchange_conf, EXCHANGES[request.param].get('use_ci_proxy', False)) - exchange_conf = deepcopy(exchange_conf) - exchange_conf['exchange']['name'] = request.param - exchange_conf['trading_mode'] = 'futures' - exchange_conf['margin_mode'] = 'isolated' - exchange_conf['stake_currency'] = EXCHANGES[request.param]['stake_currency'] - - class_mocker.patch( - 'freqtrade.exchange.binance.Binance.fill_leverage_tiers') - class_mocker.patch(f'{EXMS}.fetch_trading_fees') - class_mocker.patch('freqtrade.exchange.okx.Okx.additional_exchange_init') - class_mocker.patch('freqtrade.exchange.binance.Binance.additional_exchange_init') - class_mocker.patch('freqtrade.exchange.bybit.Bybit.additional_exchange_init') - class_mocker.patch(f'{EXMS}.load_cached_leverage_tiers', return_value=None) - class_mocker.patch(f'{EXMS}.cache_leverage_tiers') - - exchange = ExchangeResolver.load_exchange( - exchange_conf, validate=True, load_leverage_tiers=True) - - yield exchange, request.param +from freqtrade.exchange.exchange import timeframe_to_msecs +from tests.exchange_online.conftest import EXCHANGE_FIXTURE_TYPE, EXCHANGES @pytest.mark.longrun @@ -371,9 +47,6 @@ class TestCCXTExchange: def test_load_markets_futures(self, exchange_futures: EXCHANGE_FIXTURE_TYPE): exchange, exchangename = exchange_futures - if not exchange: - # exchange_futures only returns values for supported exchanges - return pair = EXCHANGES[exchangename]['pair'] pair = EXCHANGES[exchangename].get('futures_pair', pair) markets = exchange.markets @@ -391,7 +64,7 @@ class TestCCXTExchange: assert po['id'] is not None if len(order.keys()) < 5: # Kucoin case - assert po['status'] == 'closed' + assert po['status'] is None continue assert po['timestamp'] == 1674493798550 assert isinstance(po['datetime'], str) @@ -511,7 +184,8 @@ class TestCCXTExchange: now = datetime.now(timezone.utc) - timedelta(minutes=(timeframe_to_minutes(timeframe) * 2)) assert exch.klines(pair_tf).iloc[-1]['date'] >= timeframe_to_prev_date(timeframe, now) - def ccxt__async_get_candle_history(self, exchange, exchangename, pair, timeframe, candle_type): + def ccxt__async_get_candle_history( + self, exchange, exchangename, pair, timeframe, candle_type, factor=0.9): timeframe_ms = timeframe_to_msecs(timeframe) now = timeframe_to_prev_date( @@ -532,11 +206,11 @@ class TestCCXTExchange: assert res[1] == timeframe assert res[2] == candle_type candles = res[3] - factor = 0.9 candle_count = exchange.ohlcv_candle_limit(timeframe, candle_type, since_ms) * factor candle_count1 = (now.timestamp() * 1000 - since_ms) // timeframe_ms * factor assert len(candles) >= min(candle_count, candle_count1), \ f"{len(candles)} < {candle_count} in {timeframe}, Offset: {offset} {factor}" + # Check if first-timeframe is either the start, or start + 1 assert candles[0][0] == since_ms or (since_ms + timeframe_ms) def test_ccxt__async_get_candle_history(self, exchange: EXCHANGE_FIXTURE_TYPE): @@ -544,8 +218,6 @@ class TestCCXTExchange: if exchangename in ('bittrex'): # For some weired reason, this test returns random lengths for bittrex. pytest.skip("Exchange doesn't provide stable ohlcv history") - if exchangename in ('bitvavo'): - pytest.skip("Exchange Downtime ") if not exc._ft_has['ohlcv_has_history']: pytest.skip("Exchange does not support candle history") @@ -554,21 +226,29 @@ class TestCCXTExchange: self.ccxt__async_get_candle_history( exc, exchangename, pair, timeframe, CandleType.SPOT) - def test_ccxt__async_get_candle_history_futures(self, exchange_futures: EXCHANGE_FIXTURE_TYPE): + @pytest.mark.parametrize('candle_type', [ + CandleType.FUTURES, + CandleType.FUNDING_RATE, + CandleType.MARK, + ]) + def test_ccxt__async_get_candle_history_futures( + self, exchange_futures: EXCHANGE_FIXTURE_TYPE, candle_type): exchange, exchangename = exchange_futures - if not exchange: - # exchange_futures only returns values for supported exchanges - return pair = EXCHANGES[exchangename].get('futures_pair', EXCHANGES[exchangename]['pair']) timeframe = EXCHANGES[exchangename]['timeframe'] + if candle_type == CandleType.FUNDING_RATE: + timeframe = exchange._ft_has.get('funding_fee_timeframe', + exchange._ft_has['mark_ohlcv_timeframe']) self.ccxt__async_get_candle_history( - exchange, exchangename, pair, timeframe, CandleType.FUTURES) + exchange, + exchangename, + pair=pair, + timeframe=timeframe, + candle_type=candle_type, + ) def test_ccxt_fetch_funding_rate_history(self, exchange_futures: EXCHANGE_FIXTURE_TYPE): exchange, exchangename = exchange_futures - if not exchange: - # exchange_futures only returns values for supported exchanges - return pair = EXCHANGES[exchangename].get('futures_pair', EXCHANGES[exchangename]['pair']) since = int((datetime.now(timezone.utc) - timedelta(days=5)).timestamp() * 1000) @@ -604,9 +284,6 @@ class TestCCXTExchange: def test_ccxt_fetch_mark_price_history(self, exchange_futures: EXCHANGE_FIXTURE_TYPE): exchange, exchangename = exchange_futures - if not exchange: - # exchange_futures only returns values for supported exchanges - return pair = EXCHANGES[exchangename].get('futures_pair', EXCHANGES[exchangename]['pair']) since = int((datetime.now(timezone.utc) - timedelta(days=5)).timestamp() * 1000) pair_tf = (pair, '1h', CandleType.MARK) @@ -628,9 +305,6 @@ class TestCCXTExchange: def test_ccxt__calculate_funding_fees(self, exchange_futures: EXCHANGE_FIXTURE_TYPE): exchange, exchangename = exchange_futures - if not exchange: - # exchange_futures only returns values for supported exchanges - return pair = EXCHANGES[exchangename].get('futures_pair', EXCHANGES[exchangename]['pair']) since = datetime.now(timezone.utc) - timedelta(days=5) @@ -677,31 +351,29 @@ class TestCCXTExchange: def test_ccxt_get_max_leverage_futures(self, exchange_futures: EXCHANGE_FIXTURE_TYPE): futures, futures_name = exchange_futures - if futures: - leverage_tiers_public = EXCHANGES[futures_name].get('leverage_tiers_public') - if leverage_tiers_public: - futures_pair = EXCHANGES[futures_name].get( - 'futures_pair', - EXCHANGES[futures_name]['pair'] - ) - futures_leverage = futures.get_max_leverage(futures_pair, 20) - assert (isinstance(futures_leverage, float) or isinstance(futures_leverage, int)) - assert futures_leverage >= 1.0 - - def test_ccxt_get_contract_size(self, exchange_futures: EXCHANGE_FIXTURE_TYPE): - futures, futures_name = exchange_futures - if futures: + leverage_tiers_public = EXCHANGES[futures_name].get('leverage_tiers_public') + if leverage_tiers_public: futures_pair = EXCHANGES[futures_name].get( 'futures_pair', EXCHANGES[futures_name]['pair'] ) - contract_size = futures.get_contract_size(futures_pair) - assert (isinstance(contract_size, float) or isinstance(contract_size, int)) - assert contract_size >= 0.0 + futures_leverage = futures.get_max_leverage(futures_pair, 20) + assert (isinstance(futures_leverage, float) or isinstance(futures_leverage, int)) + assert futures_leverage >= 1.0 + + def test_ccxt_get_contract_size(self, exchange_futures: EXCHANGE_FIXTURE_TYPE): + futures, futures_name = exchange_futures + futures_pair = EXCHANGES[futures_name].get( + 'futures_pair', + EXCHANGES[futures_name]['pair'] + ) + contract_size = futures.get_contract_size(futures_pair) + assert (isinstance(contract_size, float) or isinstance(contract_size, int)) + assert contract_size >= 0.0 def test_ccxt_load_leverage_tiers(self, exchange_futures: EXCHANGE_FIXTURE_TYPE): futures, futures_name = exchange_futures - if futures and EXCHANGES[futures_name].get('leverage_tiers_public'): + if EXCHANGES[futures_name].get('leverage_tiers_public'): leverage_tiers = futures.load_leverage_tiers() futures_pair = EXCHANGES[futures_name].get( 'futures_pair', @@ -734,7 +406,7 @@ class TestCCXTExchange: def test_ccxt_dry_run_liquidation_price(self, exchange_futures: EXCHANGE_FIXTURE_TYPE): futures, futures_name = exchange_futures - if futures and EXCHANGES[futures_name].get('leverage_tiers_public'): + if EXCHANGES[futures_name].get('leverage_tiers_public'): futures_pair = EXCHANGES[futures_name].get( 'futures_pair', @@ -767,14 +439,13 @@ class TestCCXTExchange: def test_ccxt_get_max_pair_stake_amount(self, exchange_futures: EXCHANGE_FIXTURE_TYPE): futures, futures_name = exchange_futures - if futures: - futures_pair = EXCHANGES[futures_name].get( - 'futures_pair', - EXCHANGES[futures_name]['pair'] - ) - max_stake_amount = futures.get_max_pair_stake_amount(futures_pair, 40000) - assert (isinstance(max_stake_amount, float)) - assert max_stake_amount >= 0.0 + futures_pair = EXCHANGES[futures_name].get( + 'futures_pair', + EXCHANGES[futures_name]['pair'] + ) + max_stake_amount = futures.get_max_pair_stake_amount(futures_pair, 40000) + assert (isinstance(max_stake_amount, float)) + assert max_stake_amount >= 0.0 def test_private_method_presence(self, exchange: EXCHANGE_FIXTURE_TYPE): exch, exchangename = exchange diff --git a/tests/freqai/conftest.py b/tests/freqai/conftest.py index 4c4891ceb..9c7a950e7 100644 --- a/tests/freqai/conftest.py +++ b/tests/freqai/conftest.py @@ -97,9 +97,9 @@ def mock_pytorch_mlp_model_training_parameters() -> Dict[str, Any]: return { "learning_rate": 3e-4, "trainer_kwargs": { - "max_iters": 1, + "n_steps": None, "batch_size": 64, - "max_n_eval_batches": 1, + "n_epochs": 1, }, "model_kwargs": { "hidden_dim": 32, diff --git a/tests/optimize/test_backtesting.py b/tests/optimize/test_backtesting.py index f0bd18768..ac409bf71 100644 --- a/tests/optimize/test_backtesting.py +++ b/tests/optimize/test_backtesting.py @@ -20,7 +20,7 @@ from freqtrade.data.dataprovider import DataProvider from freqtrade.data.history import get_timerange from freqtrade.enums import CandleType, ExitType, RunMode from freqtrade.exceptions import DependencyException, OperationalException -from freqtrade.exchange.exchange import timeframe_to_next_date +from freqtrade.exchange import timeframe_to_next_date, timeframe_to_prev_date from freqtrade.optimize.backtest_caching import get_backtest_metadata_filename, get_strategy_run_id from freqtrade.optimize.backtesting import Backtesting from freqtrade.persistence import LocalTrade, Trade @@ -1122,10 +1122,10 @@ def test_backtest_dataprovider_analyzed_df(default_conf, fee, mocker, testdatadi processed = backtesting.strategy.advise_all_indicators(data) min_date, max_date = get_timerange(processed) - global count count = 0 def tmp_confirm_entry(pair, current_time, **kwargs): + nonlocal count dp = backtesting.strategy.dp df, _ = dp.get_analyzed_dataframe(pair, backtesting.strategy.timeframe) current_candle = df.iloc[-1].squeeze() @@ -1135,8 +1135,13 @@ def test_backtest_dataprovider_analyzed_df(default_conf, fee, mocker, testdatadi assert candle_date == current_time # These asserts don't properly raise as they are nested, # therefore we increment count and assert for that. - global count - count = count + 1 + df = dp.get_pair_dataframe(pair, backtesting.strategy.timeframe) + prior_time = timeframe_to_prev_date(backtesting.strategy.timeframe, + candle_date - timedelta(seconds=1)) + assert prior_time == df.iloc[-1].squeeze()['date'] + assert df.iloc[-1].squeeze()['date'] < current_time + + count += 1 backtesting.strategy.confirm_trade_entry = tmp_confirm_entry backtesting.backtest( @@ -1354,11 +1359,11 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir) # Cached data correctly removed amounts offset = 1 if tres == 0 else 0 - removed_candles = len(data[pair]) - offset - backtesting.strategy.startup_candle_count + removed_candles = len(data[pair]) - offset assert len(backtesting.dataprovider.get_analyzed_dataframe(pair, '5m')[0]) == removed_candles assert len( backtesting.dataprovider.get_analyzed_dataframe('NXT/BTC', '5m')[0] - ) == len(data['NXT/BTC']) - 1 - backtesting.strategy.startup_candle_count + ) == len(data['NXT/BTC']) - 1 backtesting.strategy.max_open_trades = 1 backtesting.config.update({'max_open_trades': 1}) diff --git a/tests/optimize/test_lookahead_analysis.py b/tests/optimize/test_lookahead_analysis.py index 3c6a5ad6d..decc4706d 100644 --- a/tests/optimize/test_lookahead_analysis.py +++ b/tests/optimize/test_lookahead_analysis.py @@ -17,6 +17,8 @@ from tests.conftest import EXMS, get_args, log_has_re, patch_exchange def lookahead_conf(default_conf_usdt): default_conf_usdt['minimum_trade_amount'] = 10 default_conf_usdt['targeted_trade_amount'] = 20 + default_conf_usdt['timerange'] = '20220101-20220501' + default_conf_usdt['strategy_path'] = str( Path(__file__).parent.parent / "strategy/strats/lookahead_bias") default_conf_usdt['strategy'] = 'strategy_test_v3_with_lookahead_bias' @@ -43,7 +45,9 @@ def test_start_lookahead_analysis(mocker): "--pairs", "UNITTEST/BTC", "--max-open-trades", - "1" + "1", + "--timerange", + "20220101-20220201" ] pargs = get_args(args) pargs['config'] = None @@ -72,6 +76,24 @@ def test_start_lookahead_analysis(mocker): match=r"Targeted trade amount can't be smaller than minimum trade amount.*"): start_lookahead_analysis(pargs) + # Missing timerange + args = [ + "lookahead-analysis", + "--strategy", + "strategy_test_v3_with_lookahead_bias", + "--strategy-path", + str(Path(__file__).parent.parent / "strategy/strats/lookahead_bias"), + "--pairs", + "UNITTEST/BTC", + "--max-open-trades", + "1", + ] + pargs = get_args(args) + pargs['config'] = None + with pytest.raises(OperationalException, + match=r"Please set a timerange\..*"): + start_lookahead_analysis(pargs) + def test_lookahead_helper_invalid_config(lookahead_conf) -> None: conf = deepcopy(lookahead_conf) diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index 131606aab..f9533e893 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -10,6 +10,7 @@ from unittest.mock import ANY, MagicMock, PropertyMock import pandas as pd import pytest +import rapidjson import uvicorn from fastapi import FastAPI, WebSocketDisconnect from fastapi.exceptions import HTTPException @@ -80,6 +81,16 @@ def client_post(client: TestClient, url, data={}): }) +def client_patch(client: TestClient, url, data={}): + + return client.patch(url, + json=data, + headers={'Authorization': _basic_auth_str(_TEST_USER, _TEST_PASS), + 'Origin': 'http://example.com', + 'content-type': 'application/json' + }) + + def client_get(client: TestClient, url): # Add fake Origin to ensure CORS kicks in return client.get(url, headers={'Authorization': _basic_auth_str(_TEST_USER, _TEST_PASS), @@ -1763,7 +1774,7 @@ def test_api_pairlists_evaluate(botclient, tmpdir, mocker): rc = client_get(client, f"{BASE_URI}/pairlists/evaluate/{job_id}") assert_response(rc) response = rc.json() - assert response['result']['whitelist'] == ['ETH/BTC', 'LTC/BTC', 'XRP/BTC', 'NEO/BTC',] + assert response['result']['whitelist'] == ['ETH/BTC', 'LTC/BTC', 'XRP/BTC', 'NEO/BTC'] assert response['result']['length'] == 4 # Restart with additional filter, reducing the list to 2 @@ -2010,6 +2021,7 @@ def test_api_backtest_history(botclient, mocker, testdatadir): assert len(result) == 3 fn = result[0]['filename'] assert fn == "backtest-result_multistrat" + assert result[0]['notes'] == '' strategy = result[0]['strategy'] rc = client_get(client, f"{BASE_URI}/backtest/history/result?filename={fn}&strategy={strategy}") assert_response(rc) @@ -2023,7 +2035,7 @@ def test_api_backtest_history(botclient, mocker, testdatadir): assert result2['backtest_result']['strategy'][strategy] -def test_api_delete_backtest_history_entry(botclient, mocker, tmp_path: Path): +def test_api_delete_backtest_history_entry(botclient, tmp_path: Path): ftbot, client = botclient # Create a temporary directory and file @@ -2051,6 +2063,75 @@ def test_api_delete_backtest_history_entry(botclient, mocker, tmp_path: Path): assert not meta_path.exists() +def test_api_patch_backtest_history_entry(botclient, tmp_path: Path): + ftbot, client = botclient + + # Create a temporary directory and file + bt_results_base = tmp_path / "backtest_results" + bt_results_base.mkdir() + file_path = bt_results_base / "test.json" + file_path.touch() + meta_path = file_path.with_suffix('.meta.json') + with meta_path.open('w') as metafile: + rapidjson.dump({ + CURRENT_TEST_STRATEGY: { + "run_id": "6e542efc8d5e62cef6e5be0ffbc29be81a6e751d", + "backtest_start_time": 1690176003} + }, metafile) + + def read_metadata(): + with meta_path.open('r') as metafile: + return rapidjson.load(metafile) + + rc = client_patch(client, f"{BASE_URI}/backtest/history/randomFile.json") + assert_response(rc, 503) + + ftbot.config['user_data_dir'] = tmp_path + ftbot.config['runmode'] = RunMode.WEBSERVER + + rc = client_patch(client, f"{BASE_URI}/backtest/history/randomFile.json", { + "strategy": CURRENT_TEST_STRATEGY, + }) + assert rc.status_code == 404 + + # Nonexisting strategy + rc = client_patch(client, f"{BASE_URI}/backtest/history/{file_path.name}", { + "strategy": f"{CURRENT_TEST_STRATEGY}xxx", + }) + assert rc.status_code == 400 + assert rc.json()['detail'] == 'Strategy not in metadata.' + + # no Notes + rc = client_patch(client, f"{BASE_URI}/backtest/history/{file_path.name}", { + "strategy": CURRENT_TEST_STRATEGY, + }) + assert rc.status_code == 200 + res = rc.json() + assert isinstance(res, list) + assert len(res) == 1 + assert res[0]['strategy'] == CURRENT_TEST_STRATEGY + assert res[0]['notes'] == '' + + fileres = read_metadata() + assert fileres[CURRENT_TEST_STRATEGY]['run_id'] == res[0]['run_id'] + assert fileres[CURRENT_TEST_STRATEGY]['notes'] == '' + + rc = client_patch(client, f"{BASE_URI}/backtest/history/{file_path.name}", { + "strategy": CURRENT_TEST_STRATEGY, + "notes": "FooBar", + }) + assert rc.status_code == 200 + res = rc.json() + assert isinstance(res, list) + assert len(res) == 1 + assert res[0]['strategy'] == CURRENT_TEST_STRATEGY + assert res[0]['notes'] == 'FooBar' + + fileres = read_metadata() + assert fileres[CURRENT_TEST_STRATEGY]['run_id'] == res[0]['run_id'] + assert fileres[CURRENT_TEST_STRATEGY]['notes'] == 'FooBar' + + def test_health(botclient): ftbot, client = botclient diff --git a/tests/strategy/strats/strategy_test_v3.py b/tests/strategy/strats/strategy_test_v3.py index 2d5121403..571427fb1 100644 --- a/tests/strategy/strats/strategy_test_v3.py +++ b/tests/strategy/strats/strategy_test_v3.py @@ -197,7 +197,7 @@ class StrategyTestV3(IStrategy): if current_profit < -0.0075: orders = trade.select_filled_orders(trade.entry_side) - return round(orders[0].safe_cost, 0) + return round(orders[0].stake_amount, 0) return None diff --git a/tests/strategy/test_default_strategy.py b/tests/strategy/test_default_strategy.py index 5f41177eb..b5b07e0cd 100644 --- a/tests/strategy/test_default_strategy.py +++ b/tests/strategy/test_default_strategy.py @@ -25,13 +25,13 @@ def test_strategy_test_v3(dataframe_1m, fee, is_short, side): strategy = StrategyTestV3({}) metadata = {'pair': 'ETH/BTC'} - assert type(strategy.minimal_roi) is dict - assert type(strategy.stoploss) is float - assert type(strategy.timeframe) is str + assert isinstance(strategy.minimal_roi, dict) + assert isinstance(strategy.stoploss, float) + assert isinstance(strategy.timeframe, str) indicators = strategy.populate_indicators(dataframe_1m, metadata) - assert type(indicators) is DataFrame - assert type(strategy.populate_buy_trend(indicators, metadata)) is DataFrame - assert type(strategy.populate_sell_trend(indicators, metadata)) is DataFrame + assert isinstance(indicators, DataFrame) + assert isinstance(strategy.populate_buy_trend(indicators, metadata), DataFrame) + assert isinstance(strategy.populate_sell_trend(indicators, metadata), DataFrame) trade = Trade( open_rate=19_000, diff --git a/tests/test_configuration.py b/tests/test_configuration.py index 7808fb5c8..3f2fb0669 100644 --- a/tests/test_configuration.py +++ b/tests/test_configuration.py @@ -1038,8 +1038,7 @@ def test_load_config_stoploss_exchange_limit_ratio(all_conf) -> None: validate_config_schema(all_conf) -@pytest.mark.parametrize("keys", [("exchange", "sandbox", False), - ("exchange", "key", ""), +@pytest.mark.parametrize("keys", [("exchange", "key", ""), ("exchange", "secret", ""), ("exchange", "password", ""), ]) diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py index e533acbb8..f595788dd 100644 --- a/tests/test_freqtradebot.py +++ b/tests/test_freqtradebot.py @@ -1508,15 +1508,15 @@ def test_handle_sle_cancel_cant_recreate(mocker, default_conf_usdt, fee, caplog, @pytest.mark.parametrize("is_short", [False, True]) def test_create_stoploss_order_invalid_order( - mocker, default_conf_usdt, caplog, fee, is_short, limit_order, limit_order_open + mocker, default_conf_usdt, caplog, fee, is_short, limit_order ): - open_order = limit_order_open[entry_side(is_short)] + open_order = limit_order[entry_side(is_short)] order = limit_order[exit_side(is_short)] rpc_mock = patch_RPCManager(mocker) patch_exchange(mocker) create_order_mock = MagicMock(side_effect=[ open_order, - {'id': order['id']} + order, ]) mocker.patch.multiple( EXMS, @@ -1541,6 +1541,7 @@ def test_create_stoploss_order_invalid_order( trade = Trade.session.scalars(select(Trade)).first() trade.is_short = is_short caplog.clear() + rpc_mock.reset_mock() freqtrade.create_stoploss_order(trade, 200) assert trade.stoploss_order_id is None assert trade.exit_reason == ExitType.EMERGENCY_EXIT.value @@ -1554,9 +1555,11 @@ def test_create_stoploss_order_invalid_order( assert create_order_mock.call_args[1]['amount'] == trade.amount # Rpc is sending first buy, then sell - assert rpc_mock.call_count == 3 - assert rpc_mock.call_args_list[2][0][0]['sell_reason'] == ExitType.EMERGENCY_EXIT.value - assert rpc_mock.call_args_list[2][0][0]['order_type'] == 'market' + assert rpc_mock.call_count == 2 + assert rpc_mock.call_args_list[0][0][0]['sell_reason'] == ExitType.EMERGENCY_EXIT.value + assert rpc_mock.call_args_list[0][0][0]['order_type'] == 'market' + assert rpc_mock.call_args_list[0][0][0]['type'] == 'exit' + assert rpc_mock.call_args_list[1][0][0]['type'] == 'exit_fill' @pytest.mark.parametrize("is_short", [False, True]) diff --git a/tests/test_misc.py b/tests/test_misc.py index 3943e7f15..e94e299fd 100644 --- a/tests/test_misc.py +++ b/tests/test_misc.py @@ -9,8 +9,7 @@ import pytest from freqtrade.misc import (dataframe_to_json, decimals_per_coin, deep_merge_dicts, file_dump_json, file_load_json, is_file_in_dir, json_to_dataframe, pair_to_filename, - parse_db_uri_for_logging, plural, render_template, - render_template_with_fallback, round_coin_value, safe_value_fallback, + parse_db_uri_for_logging, plural, round_coin_value, safe_value_fallback, safe_value_fallback2) @@ -177,20 +176,6 @@ def test_plural() -> None: assert plural(-1.5, "ox", "oxen") == "oxen" -def test_render_template_fallback(mocker): - from jinja2.exceptions import TemplateNotFound - with pytest.raises(TemplateNotFound): - val = render_template( - templatefile='subtemplates/indicators_does-not-exist.j2',) - - val = render_template_with_fallback( - templatefile='strategy_subtemplates/indicators_does-not-exist.j2', - templatefallbackfile='strategy_subtemplates/indicators_minimal.j2', - ) - assert isinstance(val, str) - assert 'if self.dp' in val - - @pytest.mark.parametrize('conn_url,expected', [ ("postgresql+psycopg2://scott123:scott123@host:1245/dbname", "postgresql+psycopg2://scott123:*****@host:1245/dbname"), diff --git a/tests/utils/test_datetime_helpers.py b/tests/utils/test_datetime_helpers.py index 222410027..6ce975732 100644 --- a/tests/utils/test_datetime_helpers.py +++ b/tests/utils/test_datetime_helpers.py @@ -63,7 +63,7 @@ def test_format_ms_time() -> None: # Date 2018-04-10 18:02:01 date_in_epoch_ms = 1523383321000 date = format_ms_time(date_in_epoch_ms) - assert type(date) is str + assert isinstance(date, str) res = datetime(2018, 4, 10, 18, 2, 1, tzinfo=timezone.utc) assert date == res.astimezone(None).strftime('%Y-%m-%dT%H:%M:%S') res = datetime(2017, 12, 13, 8, 2, 1, tzinfo=timezone.utc) diff --git a/tests/utils/test_rendering_utils.py b/tests/utils/test_rendering_utils.py new file mode 100644 index 000000000..7d52b4f26 --- /dev/null +++ b/tests/utils/test_rendering_utils.py @@ -0,0 +1,17 @@ +import pytest + +from freqtrade.util import render_template, render_template_with_fallback + + +def test_render_template_fallback(): + from jinja2.exceptions import TemplateNotFound + with pytest.raises(TemplateNotFound): + val = render_template( + templatefile='subtemplates/indicators_does-not-exist.j2',) + + val = render_template_with_fallback( + templatefile='strategy_subtemplates/indicators_does-not-exist.j2', + templatefallbackfile='strategy_subtemplates/indicators_minimal.j2', + ) + assert isinstance(val, str) + assert 'if self.dp' in val