Merge branch 'master' into master

Author: kernc

.coveragerc

@@ -17,8 +17,16 @@
 2.
 3.
 
+```python
+
+python code goes here
+
+```
+
 ### Additional info
 
 <!-- screenshots, code snippets, ... -->
 
 - Backtesting version: 0.?.?   <!-- From backtesting.__version__ -->
+- `bokeh.__version__`:
+- OS:

.flake8

@@ -8,62 +8,49 @@ jobs:
   build:
     name: Build
     runs-on: ubuntu-18.04
-
     strategy:
       matrix:
-        python-version: [3.6, 3.7]
+        python-version: [3.7, '3.10']
         include:
-          - python-version: 3.8
+          - python-version: 3.9
             test-type: lint
-          - python-version: 3.8
+          - python-version: 3.9
             test-type: docs
 
     steps:
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
+      - uses: actions/setup-python@v4
         with:
           python-version: ${{ matrix.python-version }}
-
-      - uses: actions/cache@v2
-        name: Set up caches
+      - uses: actions/cache@v3
         with:
           path: ~/.cache/pip
           key: ${{ runner.os }}-py${{ matrix.python-version }}
-
-      - name: Checkout repo
-        uses: actions/checkout@v2
+      - uses: actions/checkout@v3
         with:
           fetch-depth: 3
       - name: Fetch tags
         run: git fetch --depth=1 origin +refs/tags/*:refs/tags/*
 
-      - name: Install dependencies
-        run: |
-          pip install -U pip setuptools wheel
-          pip install -U --pre .[test]
-
-      - name: Install lint dependencies
-        if: matrix.test-type == 'lint'
-        run: pip install -U .[dev]
-
-      - name: Install docs dependencies
-        if: matrix.test-type == 'docs'
-        run: pip install -e .[doc,test]  # -e provides _version.py for pdoc
-
-      - name: Test w/ Coverage, Lint
-        if: matrix.test-type == 'lint'
+      - run: pip install -U pip setuptools wheel
+      - if: matrix.test-type == 'lint'
+        run: pip install -U --pre bokeh pandas 'numpy<1.24' && pip install -U .[dev]
+      - if: matrix.test-type == 'docs'
+        run: pip install -e .[doc]  # -e provides _version.py for pdoc
+      - run: pip install -U .[test]
+
+      - if: matrix.test-type == 'lint'
+        run: ruff backtesting
+      - if: matrix.test-type == 'lint'
+        run: mypy backtesting
+      - if: matrix.test-type == 'lint'
         env: { BOKEH_BROWSER: none }
-        run: |
-          flake8
-          mypy backtesting
-          time catchsegv coverage run -m backtesting.test
-          bash <(curl -s https://codecov.io/bash)
+        run: time catchsegv coverage run -m backtesting.test
+      - if: matrix.test-type == 'lint'
+        run: bash <(curl -s https://codecov.io/bash)
 
-      - name: Test
-        if: '! matrix.test-type'
+      - if: '! matrix.test-type'
         env: { BOKEH_BROWSER: none }
         run: time catchsegv python -m backtesting.test
 
-      - name: Test docs
-        if: matrix.test-type == 'docs'
+      - if: matrix.test-type == 'docs'
         run: time catchsegv doc/build.sh

.github/issue_template.md

@@ -3,10 +3,35 @@ What's New
 
 These were the major changes contributing to each release:
 
-
 ### 0.x.x
 
 
+### 0.3.3
+(2021-12-13)
+
+* Fix random generation with recent NumPy.
+* Fix Pandas deprecation warnings.
+* Replace Bokeh 3.0 deprecations.
+
+
+### 0.3.2
+(2021-08-03)
+
+* New strategy performance method [`backtesting.lib.compute_stats`](https://kernc.github.io/backtesting.py/doc/backtesting/lib.html#backtesting.lib.compute_stats) (#281)
+* Improve plotting speed (#329) and optimization performance (#295) on large datasets.
+* Commission constraints now allow for market-maker's rebates.
+* [`Backtest.plot`](https://kernc.github.io/backtesting.py/doc/backtesting/backtesting.html#backtesting.backtesting.Backtest.plot)
+  now returns the bokeh figure object for further processing.
+* Other small bugs and fixes.
+
+
+### 0.3.1
+(2021-01-25)
+
+* Avoid some `pandas.Index` deprecations
+* Fix `Backtest.plot(show_legend=False)` for recent Bokeh
+
+
 ### 0.3.0
 (2020-11-24)
 

.github/workflows/ci.yml

@@ -10,13 +10,19 @@ have been fixed already.
 To have your issue dealt with promptly, it's best to construct a
 [minimal working example] that exposes the issue in a clear and
 reproducible manner. Make sure to understand
-[how to report bugs effectively][bugs].
+[how to report bugs effectively][bugs] and how to
+[craft useful bug reports][bugs2] in Python.
 
-Show verbatim code in [fenced code blocks], and use the
-preview function!
+In case of bugs, please submit full tracebacks
+
+Wrap verbatim example code/traceback in [fenced code blocks],
+and use the preview function!
+
+Many thanks from the maintainers!
 
 [minimal working example]: https://en.wikipedia.org/wiki/Minimal_working_example
 [bugs]: https://www.chiark.greenend.org.uk/~sgtatham/bugs.html
+[bugs2]: https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports
 [fenced code blocks]: https://www.markdownguide.org/extended-syntax/#fenced-code-blocks
 
 
@@ -62,4 +68,4 @@ Please use explicit commit messages. See [NumPy's development workflow]
 for inspiration.
 
 [code-review]: https://mtlynch.io/code-review-love/
-[NumPy's development workflow]: https://docs.scipy.org/doc/numpy/dev/gitwash/development_workflow.html
+[NumPy's development workflow]: https://numpy.org/doc/stable/dev/development_workflow.html

CHANGELOG.md

@@ -10,11 +10,8 @@ Backtesting.py
 
 Backtest trading strategies with Python.
 
-[**Project website**][website]
+[**Project website**](https://kernc.github.io/backtesting.py) + [Documentation]
 
-[Documentation]
-
-[website]: https://kernc.github.io/backtesting.py/
 [Documentation]: https://kernc.github.io/backtesting.py/doc/backtesting/
 
 
@@ -82,6 +79,7 @@ Avg. Trade Duration          32 days 00:00:00
 Profit Factor                            2.13
 Expectancy [%]                           6.91
 SQN                                      1.78
+Kelly Criterion                        0.6134
 _strategy              SmaCross(n1=10, n2=20)
 _equity_curve                          Equ...
 _trades                       Size  EntryB...
@@ -91,6 +89,7 @@ dtype: object
 
 Find more usage examples in the [documentation].
 
+
 Features
 --------
 * Simple, well-documented API
@@ -102,101 +101,20 @@ Features
 * Detailed results
 * Interactive visualizations
 
+![xkcd.com/1570](https://imgs.xkcd.com/comics/engineer_syllogism.png)
+
+
+Bugs
+----
+Before reporting bugs or posting to the
+[discussion board](https://github.com/kernc/backtesting.py/discussions),
+please read [contributing guidelines](CONTRIBUTING.md), particularly the section
+about crafting useful bug reports and ```` ``` ````-fencing your code. We thank you!
 
--------------------------------------------------
 
 Alternatives
 ------------
-The thing with backtesting is, unless you dug into the dirty details yourself,
-you can't rely on execution correctness, and you risk losing your house.
-In addition, everyone has their own preconveived ideas about how a mechanical
-trading strategy should be conducted, so everyone (and their brother)
-just rolls their own backtesting frameworks.
-
-If after reviewing the docs and exmples perchance you find
-[_Backtesting.py_][website] not your cup of tea,
-kindly have a look at some similar alternative Python backtesting frameworks:
-
-- [bt](http://pmorissette.github.io/bt/) -
-  a framework based on reusable and flexible blocks of
-  strategy logic that support multiple instruments and
-  output detailed statistics and useful charts.
-- [vectorbt](https://polakowo.io/vectorbt/) -
-  a pandas-based library for quickly analyzing trading strategies at scale.
-- [Backtrader](https://www.backtrader.com/) -
-  a pure-python feature-rich framework for backtesting
-  and live algotrading with a few brokers.
-- [PyAlgoTrade](https://gbeced.github.io/pyalgotrade/) -
-  event-driven algorithmic trading library with focus on
-  backtesting and support for live trading.
-- [Zipline](https://www.zipline.io/) -
-  the backtesting and live-trading engine powering Quantopian — the
-  community-centered, hosted platform for building and executing strategies.
-- [Pinkfish](http://fja05680.github.io/pinkfish/) -
-  a lightweight backtester for intraday strategies on daily data.
-- [finmarketpy](https://github.com/cuemacro/finmarketpy) -
-  a library for analyzing financial market data.
-- [QuantStart QSTrader](https://github.com/mhallsmoore/qstrader/) -
-  a modular schedule-driven backtesting framework for long-short equities
-  and ETF-based systematic trading strategies.
-- [pysystemtrade](https://github.com/robcarver17/pysystemtrade) -
-  the open-source version of Robert Carver's backtesting engine that
-  implements systems according to his book _Systematic Trading:
-  A unique new method for designing trading and investing systems_.
-- [QTPyLib](https://github.com/ranaroussi/qtpylib) -
-  a versatile, event-driven algorithmic trading library.
-- [Gemini](https://github.com/anfederico/Gemini) -
-  a backtester namely focusing on cryptocurrency markets.
-- [Quantdom](https://github.com/constverum/Quantdom) -
-  a Qt-based framework that lets you focus on modeling financial strategies,
-  portfolio management, and analyzing backtests.
-- [Clairvoyant](https://github.com/anfederico/Clairvoyant) -
-  software for identifying and monitoring social / historical cues
-  for short-term stock movement.
-- [optopsy](https://github.com/michaelchu/optopsy) -
-  a nimble backtesting library for options trading.
-- [RQalpha](https://github.com/ricequant/rqalpha) -
-  a complete solution for programmatic traders from data acquisition,
-  algorithmic trading, backtesting, real-time simulation, live trading
-  to mere data analysis. Documentation in Chinese.
-- [zvt](https://github.com/zvtvz/zvt) -
-  a quant trading platform which includes data recorder, factor calculation,
-  stock picking, backtesting, and unified visualization. Documentation in Chinese.
-- [AwesomeQuant](https://github.com/wilsonfreitas/awesome-quant#trading--backtesting) -
-  A somewhat curated list of libraries, packages, and resources for quants.
-
-#### Obsolete / Unmaintained
-
-The following projects are mainly old, stale, incomplete, incompatible,
-abandoned, and here for posterity reference only:
-
-- [AlephNull](https://github.com/CarterBain/AlephNull) -
-  extends the features of Zipline, for use within an institutional environment.
-- [ProfitPy](https://code.google.com/p/profitpy/) -
-  a set of libraries and tools for the development, testing, and execution of
-  automated stock trading systems.
-- [prophet](https://github.com/Emsu/prophet) -
-  a microframework for financial markets, focusing on modeling
-  strategies and portfolio management.
-- [pybacktest](https://github.com/ematvey/pybacktest) -
-  a vectorized pandas-based backtesting framework,
-  designed to make backtesting compact, simple and fast.
-- [quant](https://github.com/maihde/quant) -
-  a technical analysis tool for trading strategies with a particularily
-  simplistic view of the market.
-- [QuantSoftware Toolkit](https://github.com/QuantSoftware/QuantSoftwareToolkit) -
-  a toolkit by the guys that soon after went to form Lucena Research.
-- [QuantStart QSForex](https://github.com/mhallsmoore/qsforex) -
-  an event-driven backtesting and live-trading platform for use in
-  the foreign exchange markets,
-- [tia: Toolkit for integration and analysis](https://github.com/PaulMest/tia/) -
-  a toolkit providing Bloomberg data access, PDF generation,
-  technical analysis and backtesting functionality.
-- [TradingWithPython](https://github.com/sjev/trading-with-python) -
-  boiler-plate code for the (no longer active) course _Trading With Python_.
-- [Ultra-Finance](https://github.com/panpanpandas/ultrafinance) -
-  real-time financial data collection, analyzing and backtesting trading strategies.
-- [visualize-wealth](https://github.com/benjaminmgross/visualize-wealth) -
-  a library to construct, backtest, analyze, and evaluate portfolios
-  and their benchmarks, with comprehensive documentation illustrating
-  all underlying methodologies and statistics.
+See [alternatives.md] for a list of alternative Python
+backtesting frameworks and related packages.
+
+[alternatives.md]: https://github.com/kernc/backtesting.py/blob/master/doc/alternatives.md

CONTRIBUTING.md

@@ -1,4 +1,7 @@
 """
+
+![xkcd.com/1570](https://imgs.xkcd.com/comics/engineer_syllogism.png)
+
 ## Manuals
 
 * [**Quick Start User Guide**](../examples/Quick Start User Guide.html)
@@ -12,7 +15,7 @@
 
 These tutorials are also available as live Jupyter notebooks:
 [![Binder](https://mybinder.org/badge_logo.svg)][binder]
-[![Google Colab](https://colab.research.google.com/assets/colab-badge.svg)][colab]
+[![Google Colab](https://colab.research.google.com/assets/colab-badge.png)][colab]
 <br>In Colab, you might have to `!pip install backtesting`.
 
 [binder]: \
@@ -50,10 +53,10 @@
 # API Reference Documentation
 """
 try:
-    from ._version import version as __version__  # noqa: F401
+    from ._version import version as __version__
 except ImportError:
     __version__ = '?.?.?'  # Package not installed
 
-from .backtesting import Backtest, Strategy  # noqa: F401
 from . import lib  # noqa: F401
 from ._plotting import set_bokeh_output  # noqa: F401
+from .backtesting import Backtest, Strategy  # noqa: F401