Derivative Python Packages

autograd

Efficiently computes derivatives of NumPy code.

autograd-gamma

NotImplementedError: VJP of gammainc wrt argnum 0 not defined

findiff

Python package for numerical derivatives and partial differential equations in any number of dimensions.

smt

SMT: The Surrogate Modeling Toolbox

nsepy

Python Library to get publicly available data on NSE website ie. stock quotes, historical data, live indices

aperiodic

Python client library for Aperiodic.io — institutional-grade market microstructure, liquidity and order flow metrics with full exchange universe coverage. Turn flow dynamics into alpha in hours, not months. No tick infrastructure to build or maintain.

incline

Estimate Trend at a Particular Point in a Noisy Time Series

autograd-latest

Efficiently computes derivatives of numpy code.

thoad

**thoad** (Torch High Order Automatic Differentiation) is a lightweight reverse-mode autodifferentiation engine written entirely in Python that works over PyTorch’s computational graph to compute **high order partial derivatives**. Unlike PyTorch’s native autograd - which is limited to first-order native partial derivatives - **thoad** is able to performantly propagate arbitray-order derivatives throughout the graph, enabling more advanced gradient-based computations.