Development process and tips#
Preface#
In this chapter, we will discuss how to developer tradingstrategy and tradeexecutor Python packages.
Installation for local development#
To install Trading Strategy using pip do:
git clone https://github.com/tradingstrategy-ai/trading-strategy.git
# We have chains submodule
git submodule update --recursive --init
cd tradingstrategy
poetry shell
poetry install -E qstrader
Run tests#
To run tests you need to have a Trading Strategy API key. Tests use the production server.
poetry shell
export TRADING_STRATEGY_API_KEY="secret-token:tradingstrategy-xxx"
pytest
Tests are very slow.
By default, the test run will cache any downloaded blobs. You can force the redownload with:
CLEAR_CACHES=true pytest --log-cli-level=debug -k test_grouped_liquidity
Or manually:
rm -rf /tmp/trading-strategy-tests
Terminal IPython and debugging with ipdb#
You might want to run notebooks in a terminal using ipython command e.g. for better debugging facilities.
You can run example notebooks in a terminal after git checkout and poetry install:
ipython --TerminalIPythonApp.file_to_run=source/programming/strategy-examples/pancakeswap-ema.ipynb
This is especially useful if you want to debug library code with ipdb.
Dataset cache#
The default cache location for the downloaded datasets is ~/.cache/tradingstrategy.
ls -lha ~/.cache/tradingstrategy
total 56M
drwxr-xr-x 5 moo staff 160 Jul 19 23:14 ./
drwx------ 14 moo staff 448 Jul 18 15:49 ../
-rw-r--r-- 1 moo staff 49M Jul 19 23:14 candles-24h.feather
-rw-r--r-- 1 moo staff 95K Jul 18 15:49 exchange-universe.json
-rw-r--r-- 1 moo staff 6.3M Jul 19 21:57 pair-universe.json.zstd
You can clear this out manually from the UNIX shell
rm -rf ~/.cache/tradingstrategy
Making a release#
poetry build
poetry publish
Memory profiling#
Use pytest-monitor for profiling memory usage. We need to ensure large datasets do not cause issues on low-memory environments like WebAsssembly in web browsers.