Bottleneck Alternatives

Similar projects and alternatives to bottleneck based on common topics and language

cupy

21 7,774 9.9 Python bottleneck VS cupy

NumPy & SciPy for GPU
NumPy

272 26,360 10.0 Python bottleneck VS NumPy

The fundamental package for scientific computing with Python.
WorkOS

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The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
pyxirr

0 144 8.3 Python bottleneck VS pyxirr

Rust-powered collection of financial functions.
segyio

1 460 5.6 Python bottleneck VS segyio

Fast Python library for SEGY files.
jdupes

44 1,681 0.0 C bottleneck VS jdupes

Discontinued A powerful duplicate file finder and an enhanced fork of 'fdupes'.
trusted-traveler-scheduler

2 34 7.2 Python bottleneck VS trusted-traveler-scheduler

Python script for periodically fetching appointment dates from the Trusted Traveler Program API for Global Entry, Nexus, SENTRI, and FAST, with notifications to the user when new appointments are discovered.
numpy-stl

1 594 6.6 Python bottleneck VS numpy-stl

Simple library to make working with STL files (and 3D objects in general) fast and easy.
InfluxDB

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NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better bottleneck alternative or higher similarity.

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bottleneck reviews and mentions

Posts with mentions or reviews of bottleneck. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-10-29.

Update on my Python, C++ and Rust Library
2 projects | /r/Python | 29 Oct 2021

Fast Array Manipulation in Python: Since Numpy is the de facto standard for storing multi-dimensional data, any performance gain you see using librapid math kernels will need to be realized on data which probably started its life as a numpy array, and needs to be passed to another tool as a numpy array. Hopefully there will be (or already is?) a way to build a librapid array out of a numpy array without copying the data and vice versa. In fact I might suggest that librapid focus on the fast math operations and simply become an accelerator for numpy arrays. For instance, look at CuPy which provides GPU-implemented operations within a numpy-compatible API, and Bottleneck which simply provides fast C-based implementations of some otherwise slow parts of Numpy. Also note that numpy *can* be multi-threaded depending on the operation and some environment variables. Single-threaded to Single-threaded I think you will be hard-pressed to beat Numpy on general math operations, but that doesn't mean there aren't specific "kernels" that are more specialized that can be greatly improved with a C++ back-end.