quantstats - pypi Package Compare versions

Comparing version 0.0.78 to 0.0.79

CHANGELOG.md

 Changelog
 ===========
 
+0.0.79
+------
+
+**Hotfix Release**
+
+- Fixed critical circular import error that broke `import quantstats` (#499):
+  - Root cause: `utils.py` imported `stats` at module level, creating circular dependency
+  - Fix: Deferred `stats` import inside `to_prices()` and `group_returns()` functions
+  - Import now works correctly on fresh installations
+
 0.0.78
@@ -5,0 +15,0 @@ ------

PKG-INFO

 Metadata-Version: 2.4
 Name: quantstats
-Version: 0.0.78
+Version: 0.0.79
 Summary: Portfolio analytics for quants
@@ -49,6 +49,7 @@ Project-URL: Homepage, https://github.com/ranaroussi/quantstats
 
-[![Python version](https://img.shields.io/badge/python-3.6+-blue.svg?style=flat)](https://pypi.python.org/pypi/quantstats)
+[![Python version](https://img.shields.io/badge/python-3.10+-blue.svg?style=flat)](https://pypi.python.org/pypi/quantstats)
 [![PyPi version](https://img.shields.io/pypi/v/quantstats.svg?maxAge=60)](https://pypi.python.org/pypi/quantstats)
 [![PyPi status](https://img.shields.io/pypi/status/quantstats.svg?maxAge=60)](https://pypi.python.org/pypi/quantstats)
 [![PyPi downloads](https://img.shields.io/pypi/dm/quantstats.svg?maxAge=2592000&label=installs&color=%2327B1FF)](https://pypi.python.org/pypi/quantstats)
+[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/ranaroussi/quantstats)
 [![Star this repo](https://img.shields.io/github/stars/ranaroussi/quantstats.svg?style=social&label=Star&maxAge=60)](https://github.com/ranaroussi/quantstats)
@@ -249,2 +250,22 @@ [![Follow me on twitter](https://img.shields.io/twitter/follow/aroussi.svg?style=social&label=Follow&maxAge=60)](https://twitter.com/aroussi)
 
+### Important: Period-Based vs Trade-Based Metrics
+
+QuantStats analyzes **return series** (daily, weekly, monthly returns), not discrete trade data. This means:
+
+- **Win Rate** = percentage of periods with positive returns
+- **Consecutive Wins/Losses** = consecutive positive/negative return periods
+- **Payoff Ratio** = average winning period return / average losing period return
+- **Profit Factor** = sum of positive returns / sum of negative returns
+
+These metrics are **valid and useful** for:
+- Systematic/algorithmic strategies with regular rebalancing
+- Analyzing return-series behavior over time
+- Comparing strategies on a period-by-period basis
+
+For **discretionary traders** with multi-day trades, these period-based metrics may differ from trade-level statistics. A single 5-day trade might span 3 positive days and 2 negative days - QuantStats would count these as 3 "wins" and 2 "losses" at the daily level.
+
+This is consistent with how all return-based analytics work (Sharpe ratio, Sortino ratio, drawdown analysis, etc.) - they operate on return periods, not discrete trade entries/exits.
+
+---
+
 In the meantime, you can get insights as to optional parameters for each method, by using Python's `help` method:
@@ -280,11 +301,11 @@
 
-* [Python](https://www.python.org) >= 3.5+
-* [pandas](https://github.com/pydata/pandas) (tested to work with >=0.24.0)
-* [numpy](http://www.numpy.org) >= 1.15.0
-* [scipy](https://www.scipy.org) >= 1.2.0
-* [matplotlib](https://matplotlib.org) >= 3.0.0
-* [seaborn](https://seaborn.pydata.org) >= 0.9.0
-* [tabulate](https://bitbucket.org/astanin/python-tabulate) >= 0.8.0
-* [yfinance](https://github.com/ranaroussi/yfinance) >= 0.1.38
-* [plotly](https://plot.ly/) >= 3.4.1 (optional, for using `plots.to_plotly()`)
+* [Python](https://www.python.org) >= 3.10
+* [pandas](https://github.com/pydata/pandas) >= 1.5.0
+* [numpy](http://www.numpy.org) >= 1.24.0
+* [scipy](https://www.scipy.org) >= 1.11.0
+* [matplotlib](https://matplotlib.org) >= 3.7.0
+* [seaborn](https://seaborn.pydata.org) >= 0.13.0
+* [tabulate](https://bitbucket.org/astanin/python-tabulate) >= 0.9.0
+* [yfinance](https://github.com/ranaroussi/yfinance) >= 0.2.40
+* [plotly](https://plot.ly/) >= 5.0.0 (optional, for using `plots.to_plotly()`)
 
@@ -291,0 +312,0 @@ ## Questions?

quantstats/utils.py

@@ -24,3 +24,2 @@ #!/usr/bin/env python
 from ._compat import safe_yfinance_download
-from . import stats as _stats
 from ._compat import safe_concat, safe_resample
@@ -317,2 +316,4 @@ import inspect
     """
+    from . import stats as _stats  # deferred import to avoid circular dependency
+
     # Clean returns data by filling NaN and replacing infinite values
@@ -436,2 +437,4 @@ returns = returns.copy().fillna(0).replace([_np.inf, -_np.inf], float("NaN"))
     if compounded:
+        from . import stats as _stats  # deferred import to avoid circular dependency
+
         # Use compounded returns calculation
@@ -438,0 +441,0 @@ return returns.groupby(groupby).apply(_stats.comp)

quantstats/version.py

@@ -1,1 +0,1 @@
-version = "0.0.78"
+version = "0.0.79"

README.md

@@ -1,5 +0,6 @@
-[![Python version](https://img.shields.io/badge/python-3.6+-blue.svg?style=flat)](https://pypi.python.org/pypi/quantstats)
+[![Python version](https://img.shields.io/badge/python-3.10+-blue.svg?style=flat)](https://pypi.python.org/pypi/quantstats)
 [![PyPi version](https://img.shields.io/pypi/v/quantstats.svg?maxAge=60)](https://pypi.python.org/pypi/quantstats)
 [![PyPi status](https://img.shields.io/pypi/status/quantstats.svg?maxAge=60)](https://pypi.python.org/pypi/quantstats)
 [![PyPi downloads](https://img.shields.io/pypi/dm/quantstats.svg?maxAge=2592000&label=installs&color=%2327B1FF)](https://pypi.python.org/pypi/quantstats)
+[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/ranaroussi/quantstats)
 [![Star this repo](https://img.shields.io/github/stars/ranaroussi/quantstats.svg?style=social&label=Star&maxAge=60)](https://github.com/ranaroussi/quantstats)
@@ -200,2 +201,22 @@ [![Follow me on twitter](https://img.shields.io/twitter/follow/aroussi.svg?style=social&label=Follow&maxAge=60)](https://twitter.com/aroussi)
 
+### Important: Period-Based vs Trade-Based Metrics
+
+QuantStats analyzes **return series** (daily, weekly, monthly returns), not discrete trade data. This means:
+
+- **Win Rate** = percentage of periods with positive returns
+- **Consecutive Wins/Losses** = consecutive positive/negative return periods
+- **Payoff Ratio** = average winning period return / average losing period return
+- **Profit Factor** = sum of positive returns / sum of negative returns
+
+These metrics are **valid and useful** for:
+- Systematic/algorithmic strategies with regular rebalancing
+- Analyzing return-series behavior over time
+- Comparing strategies on a period-by-period basis
+
+For **discretionary traders** with multi-day trades, these period-based metrics may differ from trade-level statistics. A single 5-day trade might span 3 positive days and 2 negative days - QuantStats would count these as 3 "wins" and 2 "losses" at the daily level.
+
+This is consistent with how all return-based analytics work (Sharpe ratio, Sortino ratio, drawdown analysis, etc.) - they operate on return periods, not discrete trade entries/exits.
+
+---
+
 In the meantime, you can get insights as to optional parameters for each method, by using Python's `help` method:
@@ -231,11 +252,11 @@
 
-* [Python](https://www.python.org) >= 3.5+
-* [pandas](https://github.com/pydata/pandas) (tested to work with >=0.24.0)
-* [numpy](http://www.numpy.org) >= 1.15.0
-* [scipy](https://www.scipy.org) >= 1.2.0
-* [matplotlib](https://matplotlib.org) >= 3.0.0
-* [seaborn](https://seaborn.pydata.org) >= 0.9.0
-* [tabulate](https://bitbucket.org/astanin/python-tabulate) >= 0.8.0
-* [yfinance](https://github.com/ranaroussi/yfinance) >= 0.1.38
-* [plotly](https://plot.ly/) >= 3.4.1 (optional, for using `plots.to_plotly()`)
+* [Python](https://www.python.org) >= 3.10
+* [pandas](https://github.com/pydata/pandas) >= 1.5.0
+* [numpy](http://www.numpy.org) >= 1.24.0
+* [scipy](https://www.scipy.org) >= 1.11.0
+* [matplotlib](https://matplotlib.org) >= 3.7.0
+* [seaborn](https://seaborn.pydata.org) >= 0.13.0
+* [tabulate](https://bitbucket.org/astanin/python-tabulate) >= 0.9.0
+* [yfinance](https://github.com/ranaroussi/yfinance) >= 0.2.40
+* [plotly](https://plot.ly/) >= 5.0.0 (optional, for using `plots.to_plotly()`)
 
@@ -242,0 +263,0 @@ ## Questions?

Alert delta unavailable

Currently unable to show alert delta for PyPI packages.

Improved metrics

Total package byte prevSize

341459

0.84%

Lines of code

7729

0.01%