Skip to main content

Portfolio analytics for quants — a modern rebuild of QuantStats with a fast pandas+Numba core and an optional web UI

Project description

OpenStatz

OpenStatz is a modern rebuild of QuantStats. It gives you the same portfolio analytics and the same numbers, plus an optional web tearsheet you can open in a browser.

OpenStatz tearsheet

What you can do

  • Use it in Python as a drop-in for QuantStats.
  • Generate the modern web tearsheet as a single offline HTML file. It works on a plain pip install openstatz, with no server and no Node.js.
  • Or run the same dashboard as a live server (openstatz serve) to type tickers and upload CSVs.
  • Send your backtest returns (a CSV file or a pandas Series) and get a full report.
  • Compare several strategies side by side and see which one is better on each metric.

Install

pip install openstatz          # the library
pip install "openstatz[app]"   # also installs the web app and API

Use it in Python

It works like QuantStats. You only change the import.

import openstatz as os

returns = my_backtest.returns                 # a pandas Series of daily returns
benchmark = os.utils.download_returns("SPY")

os.reports.html(returns, benchmark=benchmark, output="tearsheet.html")
os.reports.metrics(returns, mode="full", display=True)

os.extend_pandas()
returns.sharpe()

The qs alias also works. Note that the os alias hides Python's built-in os inside files that use it, so write import os as _os if you need both.

Two ways to make a tearsheet

Both work on a plain pip install openstatz, with no [app] extra, no server, and no Node.js.

Modern tearsheet. The same dashboard as openstatz serve, written to a single self-contained HTML file with the analysis baked in (charts, heatmaps, metrics, light and dark themes, PDF export):

import openstatz as os

os.dashboard(returns, benchmark=benchmark, output="report.html")

The file embeds the data and inlines the JS/CSS, so you can email it or commit it and it just opens.

Classic tearsheet. The original QuantStats-style report (matplotlib charts in a static HTML template). Use this when you want the familiar QuantStats look or exact upstream parity:

import openstatz as os

os.reports.html(returns, benchmark=benchmark, output="tearsheet.html")
os.reports.metrics(returns, mode="full", display=True)

Examples for traders

US market (a stock vs the market).

import openstatz as os

aapl = os.utils.download_returns("AAPL")     # or NVDA, MSFT, TSLA, ...
spy  = os.utils.download_returns("SPY")

os.dashboard(aapl, benchmark=spy, output="aapl.html")      # modern tearsheet
os.reports.html(aapl, benchmark=spy, output="aapl_classic.html")   # classic tearsheet

Indian market (a stock vs the Nifty 50).

import openstatz as os

reliance = os.utils.download_returns("RELIANCE.NS")   # NSE tickers end in .NS
nifty    = os.utils.download_returns("^NSEI")          # Nifty 50 index

os.dashboard(reliance, benchmark=nifty, output="reliance.html")

Your own backtest strategy. Feed a pandas Series of daily returns straight from your backtest.

import openstatz as os

returns = my_backtest.returns          # pd.Series of daily returns
bench   = os.utils.download_returns("SPY")

os.dashboard(returns, benchmark=bench, output="strategy.html")
os.reports.metrics(returns, benchmark=bench, mode="full", display=True)

CSV works too: a date, return file (with an optional third benchmark column). Load it with pandas and pass the Series, or drop it into the web app (see below).

Compare strategies

See which of several strategies is better, at a glance. Start the server and open the Compare tab, or call the API. Best value per metric is green, worst is red, and the leader wins the most key metrics.

OpenStatz compare view

openstatz serve      # then click "Compare" and enter, e.g., AAPL, NVDA
# Or the API, for tickers or your own strategies:
curl -X POST http://127.0.0.1:8000/api/compare/symbols \
  -H "Content-Type: application/json" \
  -d '{"symbols": ["AAPL", "NVDA", "MSFT"], "period": "5y"}'

Open the web tearsheet (live server)

pip install "openstatz[app]"
openstatz serve        # opens the API and UI at http://127.0.0.1:8000

To run on a different port:

openstatz serve --port 8200            # http://127.0.0.1:8200

# or without installing the command:
python -m openstatz serve --port 8200

In the browser you can:

  • Type a ticker and a benchmark, for example RELIANCE.NS and ^NSEI.
  • Or upload a CSV of your own returns. Columns: date, return, and an optional benchmark. See docs/example_returns.csv for the format.

The page shows the cumulative return, drawdown, monthly and weekly heatmaps, yearly returns, the return distribution, and a full table of metrics. It has light and dark themes and a PDF export.

Send a backtest with the API

curl -X POST http://127.0.0.1:8000/api/analyze \
  -H "Content-Type: application/json" \
  -d '{"dates": ["2024-01-02", "..."], "returns": {"Strategy": [0.001, "..."]}}'

Endpoints:

  • GET /api/health
  • POST /api/analyze for your own returns
  • POST /api/analyze/symbol for a ticker the server fetches for you
  • POST /api/compare/symbols and POST /api/compare to compare several strategies

The same numbers as QuantStats

OpenStatz reuses the QuantStats math without changes, so the results are the same. A test suite checks this on every change. It runs the real QuantStats and OpenStatz side by side and fails if any number, table, or chart differs (to within 1e-9). It has been verified to match exactly, even on live market data.

python tests/parity/generate_fixtures.py   # build the reference output from QuantStats
pytest tests/parity -q                       # run the check

Data sources

openstatz.providers fetches returns for a symbol. yfinance is the default. OpenAlgo is an optional source for users on that platform.

Run old QuantStats code unchanged

import openstatz.compat
openstatz.compat.install_quantstats_shim()

import quantstats as qs        # this is now OpenStatz

Project layout

openstatz/         the library (drop-in for quantstats)
  app/             optional FastAPI server and JSON serializers
  app/static/      the built web UI, shipped inside the package
app/               web UI source (React, Vite, Tailwind)
tests/parity/      the check against QuantStats

Build the web UI (for contributors)

The shipped app is pre-built, so users need no Node.js. To rebuild it from source:

cd app && npm ci && npm run build
cp -r dist/* ../openstatz/app/static/

License

Apache 2.0. See LICENSE.txt and NOTICE.

OpenStatz is built on QuantStats (Copyright 2019 to 2025, Ran Aroussi, Apache 2.0). The portfolio math is reused without changes. Thanks to Ran Aroussi and the QuantStats contributors.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

openstatz-0.3.0.tar.gz (735.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

openstatz-0.3.0-py3-none-any.whl (749.0 kB view details)

Uploaded Python 3

File details

Details for the file openstatz-0.3.0.tar.gz.

File metadata

  • Download URL: openstatz-0.3.0.tar.gz
  • Upload date:
  • Size: 735.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.4

File hashes

Hashes for openstatz-0.3.0.tar.gz
Algorithm Hash digest
SHA256 a308c3d747f6e8c976738fa2a6c195af1d521767e7f10e717b05b84a180ab837
MD5 cafe888797376b0b61c3ca54def4f890
BLAKE2b-256 2f39e6de6df82bf7813d4c016288c436c90b172b7cba5c427417170d1d5e3960

See more details on using hashes here.

File details

Details for the file openstatz-0.3.0-py3-none-any.whl.

File metadata

  • Download URL: openstatz-0.3.0-py3-none-any.whl
  • Upload date:
  • Size: 749.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.4

File hashes

Hashes for openstatz-0.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 8f2d59d036dd4d657f89a522164075bcebee998110521bf3d415ac159918c7cc
MD5 5219ff474753d57903c5b2985be5f5d8
BLAKE2b-256 c7d04dd4b70cd0869361e83975673583972b82f41d66bf21cfc689a234c96186

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page