Skip to main content

GiQuant

This Python package contain various tools for Quantative Finance and Trading. It should be considered an alpha version but feel free to try it out!

Install from PyPi with: python3 -m pip install giquant

See giquant-examples for examples of how GiQuant can be used!

TimeSeriesLanguage

giquiant.tsl is a DSL (domain specific language) for manipulation of time series.

Show the help with: python3 -m giquant.tsl.run --help

Trading

The trade subpackage has some tools related to trading.

Show the help with:

  • python3 -m giquant.trade.dwnl --help
  • python3 -m giquant.trade.cc --help
  • python3 -m giquant.trade.cf --help
  • python3 -m giquant.trade.cl --help

Web Server

See giquant-examples for details on how to setup the web server.

Metadata

Release files for giquant 2025.0.7

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for giquant 2025.0.7
File Size Uploaded
giquant-2025.0.7.tar.gz 51.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for giquant 2025.0.7
File Interpreter ABI Platform
giquant-2025.0.7-py3-none-any.whl Python 3 none any Details

Total release size: 118.1 kB

Release files / giquant-2025.0.7.tar.gz

Download URL giquant-2025.0.7.tar.gz
Size 51.3 kB
Tags Source
SHA-256 checksum
How to use checksums
2796d0113e5aa8f4715641be65430adcdbf13076614a5bc06723d8fd9c2f8d9d
BLAKE2b-256 checksum
How to use checksums
0b2de77f18d0ea6bfe46bc6e8854693d602ec5fbeb57f4ebe333c34eb37efc92
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.12.8

Release files / giquant-2025.0.7-py3-none-any.whl

Download URL giquant-2025.0.7-py3-none-any.whl
Size 66.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
ee4887a9f58050260ceec20ca5dd7f74e19caa6c705bbf367944bd065235656e
BLAKE2b-256 checksum
How to use checksums
f594eb684916d88e914e38097169a39ed73dab347d0cc082c5464c91706dad3c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.12.8
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page