Alternatives to h5py
Compare h5py alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to h5py in 2026. Compare features, ratings, user reviews, pricing, and more from h5py competitors and alternatives in order to make an informed decision for your business.
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1
NumPy
NumPy
Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today. NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries. The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code. NumPy’s high level syntax makes it accessible and productive for programmers from any background or experience level. NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. With this power comes simplicity: a solution in NumPy is often clear and elegant.Starting Price: Free -
2
broot
broot
The ROOT data analysis framework is used much in High Energy Physics (HEP) and has its own output format (.root). ROOT can be easily interfaced with software written in C++. For software tools in Python there exists pyROOT. Unfortunately, pyROOT does not work well with python3.4. broot is a small library that converts data in python numpy ndarrays to ROOT files containing trees with a branch for each array. The goal of this library is to provide a generic way of writing python numpy datastructures to ROOT files. The library should be portable and supports both python2, python3, ROOT v5 and ROOT v6 (requiring no modifications on the ROOT part, just the default installation). Installation of the library should only require a user to compile to library once or install it as a python package.Starting Price: Free -
3
Cython
Cython
Cython is an optimizing static compiler for both the Python programming language and the extended Cython programming language (based on Pyrex). It makes writing C extensions for Python as easy as Python itself. Cython gives you the combined power of Python and C to let you write Python code that calls back and forth from and to C or C++ code natively at any point. Easily tune readable Python code into plain C performance by adding static type declarations, also in Python syntax. Use combined source code level debugging to find bugs in your Python, Cython, and C code. Interact efficiently with large data sets, e.g. using multi-dimensional NumPy arrays. Quickly build your applications within the large, mature, and widely used CPython ecosystem. The Cython language is a superset of the Python language that additionally supports calling C functions and declaring C types on variables and class attributes.Starting Price: Free -
4
Bokeh
Bokeh
Bokeh makes it simple to create common plots, but also can handle custom or specialized use-cases. Plots, dashboards, and apps can be published in web pages or Jupyter notebooks. Python has an incredible ecosystem of powerful analytics tools: NumPy, Scipy, Pandas, Dask, Scikit-Learn, OpenCV, and more. With a wide array of widgets, plot tools, and UI events that can trigger real Python callbacks, the Bokeh server is the bridge that lets you connect these tools to rich, interactive visualizations in the browser. Microscopium is a project maintained by researchers at Monash University. It allows researchers to discover new gene or drug functions by exploring large image datasets with Bokeh’s interactive tools. Panel is a tool for polished data presentation that utilizes the Bokeh server. It is created and supported by Anaconda. Panel makes it simple to create custom interactive web apps and dashboards by connecting user-defined widgets to plots, images, tables, or text.Starting Price: Free -
5
PyQtGraph
PyQtGraph
PyQtGraph is a pure-python graphics and GUI library built on PyQt/PySide and NumPy. It is intended for use in mathematics/scientific/engineering applications. Despite being written entirely in python, the library is very fast due to its heavy leverage of NumPy for number crunching and Qt's GraphicsView framework for fast display. PyQtGraph is distributed under the MIT open-source license. Basic 2D plotting in interactive view boxes. Line and scatter plots. Data can be panned/scaled by mouse. Fast drawing for real-time data display and interaction. Displays most data types (int or float; any bit depth; RGB, RGBA, or luminance). Functions for slicing multidimensional images at arbitrary angles (great for MRI data). Rapid update for video display or real-time interaction. Image display with interactive lookup tables and level control. Mesh rendering with isosurface generation. Interactive viewports rotate/zoom with mouse. Basic 3D scenegraph for easier programming.Starting Price: Free -
6
imageio
imageio
Imageio is a Python library that provides an easy interface to read and write a wide range of image data, including animated images, volumetric data, and scientific formats. It is cross-platform, runs on Python 3.5+, and is easy to install. Imageio is written in pure Python, so installation is easy. Imageio works on Python 3.5+. It also works on Pypy. Imageio depends on Numpy and Pillow. For some formats, imageio needs additional libraries/executables (e.g. ffmpeg), which imageio helps you to download/install. If something doesn’t work as it should, you need to know where to search for causes. The overview on this page aims to help you in this regard by giving you an idea of how things work, and - hence - where things may go sideways.Starting Price: Free -
7
statsmodels
statsmodels
statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests and statistical data exploration. An extensive list of result statistics is available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open-source Modified BSD (3-clause) license. statsmodels supports specifying models using R-style formulas and pandas DataFrames. Have a look at dir(results) to see available results. Attributes are described in results.__doc__ and results methods have their own docstrings. You can also use numpy arrays instead of formulas. The easiest way to install statsmodels is to install it as part of the Anaconda distribution, a cross-platform distribution for data analysis and scientific computing. This is the recommended installation method for most users.Starting Price: Free -
8
Dask
Dask
Dask is open source and freely available. It is developed in coordination with other community projects like NumPy, pandas, and scikit-learn. Dask uses existing Python APIs and data structures to make it easy to switch between NumPy, pandas, scikit-learn to their Dask-powered equivalents. Dask's schedulers scale to thousand-node clusters and its algorithms have been tested on some of the largest supercomputers in the world. But you don't need a massive cluster to get started. Dask ships with schedulers designed for use on personal machines. Many people use Dask today to scale computations on their laptop, using multiple cores for computation and their disk for excess storage. Dask exposes lower-level APIs letting you build custom systems for in-house applications. This helps open source leaders parallelize their own packages and helps business leaders scale custom business logic. -
9
scikit-learn
scikit-learn
Scikit-learn provides simple and efficient tools for predictive data analysis. Scikit-learn is a robust, open source machine learning library for the Python programming language, designed to provide simple and efficient tools for data analysis and modeling. Built on the foundations of popular scientific libraries like NumPy, SciPy, and Matplotlib, scikit-learn offers a wide range of supervised and unsupervised learning algorithms, making it an essential toolkit for data scientists, machine learning engineers, and researchers. The library is organized into a consistent and flexible framework, where various components can be combined and customized to suit specific needs. This modularity makes it easy for users to build complex pipelines, automate repetitive tasks, and integrate scikit-learn into larger machine-learning workflows. Additionally, the library’s emphasis on interoperability ensures that it works seamlessly with other Python libraries, facilitating smooth data processing.Starting Price: Free -
10
JAX
JAX
JAX is a Python library designed for high-performance numerical computing and machine learning research. It offers a NumPy-like API, facilitating seamless adoption for those familiar with NumPy. Key features of JAX include automatic differentiation, just-in-time compilation, vectorization, and parallelization, all optimized for execution on CPUs, GPUs, and TPUs. These capabilities enable efficient computation for complex mathematical functions and large-scale machine-learning models. JAX also integrates with various libraries within its ecosystem, such as Flax for neural networks and Optax for optimization tasks. Comprehensive documentation, including tutorials and user guides, is available to assist users in leveraging JAX's full potential. -
11
Avanzai
Avanzai
Avanzai helps accelerate your financial data analysis by letting you use natural language to output production-ready Python code. Avanzai speeds up financial data analysis for both beginners and experts using plain English. Plot times series data, equity index members, and even stock performance data using natural prompts. Skip the boring parts of financial analysis by leveraging AI to generate code with relevant Python packages already installed. Further edit the code if you wish, once you're ready copy and paste the code into your local environment and get straight to business. Leverage commonly used Python packages for quant analysis such as Pandas, Numpy, etc using plain English. Take financial analysis to the next level, quickly pull fundamental data and calculate the performance of nearly all US stocks. Enhance your investment decisions with accurate and up-to-date information. Avanzai empowers you to write the same Python code that quants use to analyze complex financial data. -
12
RunMat
RunMat
RunMat (by Dystr) is a fast, free, open-source alternative for running MATLAB code. Users can run their existing .m files with complete MATLAB language grammar and core semantics. No license fees, no lock-in. 300+ built-in functions supported. RunMat is built with a modern Rust runtime featuring a tiered execution model: an interpreter (Ignition) for instant 5ms startup and a JIT compiler (Turbine/Cranelift) for hot paths. GPU acceleration is automatic via a fusion engine that detects elementwise operation chains and dispatches them as optimized GPU kernels across NVIDIA, AMD, Apple Silicon, and Intel GPUs through Metal, DirectX 12, Vulkan, and WebGPU. Up to 131x faster than NumPy and 7x faster than PyTorch on dense numerical workloads. Runs everywhere: CLI, NPM package, Homebrew, Jupyter kernel, or instantly in the browser via WebAssembly + WebGPU. Single portable binary. MIT licensed.Starting Price: $0 -
13
CVXOPT
CVXOPT
CVXOPT is a free software package for convex optimization based on the Python programming language. It can be used with the interactive Python interpreter, on the command line by executing Python scripts, or integrated in other software via Python extension modules. Its main purpose is to make the development of software for convex optimization applications straightforward by building on Python’s extensive standard library and on the strengths of Python as a high-level programming language. Efficient Python classes for dense and sparse matrices (real and complex), with Python indexing and slicing and overloaded operations for matrix arithmetic. Interfaces to the linear programming solver in GLPK, the semidefinite programming solver in DSDP5, and the linear, quadratic and second-order cone programming solvers in MOSEK.Starting Price: Free -
14
PyTorch
PyTorch
Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies. -
15
gTTS
gTTS
gTTS (Google Text-to-Speech), a Python library and CLI tool to interface with Google Translate's text-to-speech API. Write spoken mp3 data to a file, a file-like object (bytestring) for further audio manipulation, or stdout. Or simply pre-generate Google Translate TTS request URLs to feed to an external program. Customizable speech-specific sentence tokenizer that allows for unlimited lengths of text to be read, all while keeping proper intonation, abbreviations, decimals and more. Customizable text pre-processors which can, for example, provide pronunciation corrections.Starting Price: Free -
16
Mako
Mako
It provides a familiar, non-XML syntax that compiles into Python modules for maximum performance. Mako's syntax and API borrows from the best ideas of many others, including Django and Jinja2 templates, Cheetah, Myghty, and Genshi. Conceptually, Mako is an embedded Python (i.e. Python Server Page) language, which refines the familiar ideas of componentized layout and inheritance to produce one of the most straightforward and flexible models available, while also maintaining close ties to Python calling and scoping semantics. As templates are ultimately compiled into Python bytecode, Mako's approach is extremely efficient and was originally written to be just as fast as Cheetah. Today, Mako is very close in speed to Jinja2, which uses a similar approach and for which Mako was an inspiration. Can access variables from their enclosing scope as well as the template's request contextStarting Price: Free -
17
Tomviz
Kitware
Tomviz is an open source, cross-platform application designed for the processing, visualization, and analysis of 3D tomographic data, with a particular focus on electron tomography. It provides a robust graphical interface that allows users to render objects as shaded contours or volumetric projections, facilitating the manipulation and analysis of large 3D tomograms. Users can work with multiple datasets simultaneously, applying various colormaps and visualization settings to rotate, slice, animate, and save visualizations as images or video files. The platform supports advanced data analysis through histograms, multicorrelative statistics, multiple filters, and user-customized Python scripts. Additionally, Tomviz enables tomographic reconstructions of experimental data, offering a comprehensive suite of Python tools for 3D analysis to accommodate custom algorithms. It is compatible with 64-bit Windows, macOS, and Linux operating systems.Starting Price: Free -
18
Gensim
Radim Řehůřek
Gensim is a free, open source Python library designed for unsupervised topic modeling and natural language processing, focusing on large-scale semantic modeling. It enables the training of models like Word2Vec, FastText, Latent Semantic Analysis (LSA), and Latent Dirichlet Allocation (LDA), facilitating the representation of documents as semantic vectors and the discovery of semantically related documents. Gensim is optimized for performance with highly efficient implementations in Python and Cython, allowing it to process arbitrarily large corpora using data streaming and incremental algorithms without loading the entire dataset into RAM. It is platform-independent, running on Linux, Windows, and macOS, and is licensed under the GNU LGPL, promoting both personal and commercial use. The library is widely adopted, with thousands of companies utilizing it daily, over 2,600 academic citations, and more than 1 million downloads per week.Starting Price: Free -
19
yarl
Python Software Foundation
All URL parts, scheme, user, password, host, port, path, query, and fragment are accessible by properties. All URL manipulations produce a new URL object. Strings passed to constructor and modification methods are automatically encoded giving canonical representation as result. Regular properties are percent-decoded, use raw_ versions for getting encoded strings. Human-readable representation of URL is available as .human_repr(). PyPI contains binary wheels for Linux, Windows and MacOS. If you want to install yarl on another operating system (like Alpine Linux, which is not manylinux-compliant because of the missing glibc and therefore, cannot be used with our wheels) the tarball will be used to compile the library from the source code. It requires a C compiler and Python headers installed. Please note that the pure-Python (uncompiled) version is much slower. However, PyPy always uses a pure-Python implementation, and, as such, it is unaffected by this variable.Starting Price: Free -
20
CZ CELLxGENE Discover
CZ CELLxGENE
Select two custom cell groups based on metadata to find their top differentially expressed genes. Leverage millions of cells from the integrated CZ CELLxGENE corpus for powerful analysis. Execute interactive analyses on a dataset to explore how patterns of gene expression are determined by spatial, environmental, and genetic factors using an interactive speed no-code UI. Understand published datasets or use them as a launchpad to identify new cell sub-types and states. Census provides access to any custom slice of standardized cell data available on CZ CELLxGENE Discover in R and Python. Explore an interactive encyclopedia of 700+ cell types that provides detailed definitions, marker genes, lineage, and relevant datasets in one place. Browse and download hundreds of standardized data collections and 1,000+ datasets characterizing the functionality of healthy mouse and human tissues. -
21
websockets
Python Software Foundation
An implementation of the WebSocket Protocol (RFC 6455 & 7692). websockets is a library for building WebSocket servers and clients in Python with a focus on correctness, simplicity, robustness, and performance. Built on top of asyncio, Python’s standard asynchronous I/O framework, it provides an elegant coroutine-based API. websockets is heavily tested for compliance with RFC 6455. Continuous integration fails under 100% branch coverage. websockets is built for production. For example, it was the only library to handle backpressure correctly before the issue became widely known in the Python community. Memory usage is optimized and configurable. A C extension accelerates expensive operations. It’s pre-compiled for Linux, macOS, and Windows and packaged in the wheel format for each system and Python version. websockets takes care of everything under the hood so you can focus on your application!Starting Price: Free -
22
Pillow
Pillow
The Python Imaging Library adds image processing capabilities to your Python interpreter. This library provides extensive file format support, an efficient internal representation, and fairly powerful image processing capabilities. The core image library is designed for fast access to data stored in a few basic pixel formats. It should provide a solid foundation for a general image processing tool. Pillow for enterprise is available via the Tidelift subscription. The Python Imaging Library is ideal for image archival and batch processing applications. You can use the library to create thumbnails, convert between file formats, print images, etc. The current version identifies and reads a large number of formats. Write support is intentionally restricted to the most commonly used interchange and presentation formats. The library contains basic image processing functionality, including point operations, filtering with a set of built-in convolution kernels, and color space conversions.Starting Price: Free -
23
DataChain
iterative.ai
DataChain connects unstructured data in cloud storage with AI models and APIs, enabling instant data insights by leveraging foundational models and API calls to quickly understand your unstructured files in storage. Its Pythonic stack accelerates development tenfold by switching to Python-based data wrangling without SQL data islands. DataChain ensures dataset versioning, guaranteeing traceability and full reproducibility for every dataset to streamline team collaboration and ensure data integrity. It allows you to analyze your data where it lives, keeping raw data in storage (S3, GCP, Azure, or local) while storing metadata in inefficient data warehouses. DataChain offers tools and integrations that are cloud-agnostic for both storage and computing. With DataChain, you can query your unstructured multi-modal data, apply intelligent AI filters to curate data for training and snapshot your unstructured data, the code for data selection, and any stored or computed metadata.Starting Price: Free -
24
NetworkX
NetworkX
NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. Generators for classic graphs, random graphs, and synthetic networks. Additional benefits from Python include fast prototyping, easy to teach, and multi-platform. Network structure and analysis measures.Starting Price: Free -
25
AG Grid
AG Grid
AG Grid is a high-performance, feature-rich JavaScript Data Grid library used to display, manipulate, and interact with large tabular datasets in modern web applications, offering core features such as sorting, filtering, editing, grouping, aggregation, pivoting, pagination, and responsive performance that scales to hundreds of thousands of rows with minimal overhead. It is framework-agnostic with official support for major frameworks, including React, Angular, Vue, and plain JavaScript, while maintaining a single consistent API and zero third-party dependencies, making it simple to integrate into existing applications and customize deeply with user-defined components, theming, and modules that allow fine control over bundle size and capabilities. AG Grid is available in a free open source Community edition with essential grid functionality under the MIT license, as well as a commercial Enterprise edition that adds advanced features.Starting Price: $999 per developer -
26
ruffus
ruffus
Ruffus is a computation pipeline library for python. It is open-sourced, powerful and user-friendly, and widely used in science and bioinformatics. Ruffus is designed to allow scientific and other analyses to be automated with the minimum of fuss and the least effort. Suitable for the simplest of tasks. Handles even fiendishly complicated pipelines which would cause make or scons to go cross-eyed and recursive. No "clever magic", no pre-processing. Unambitious, the lightweight syntax which tries to do this one small thing well. Ruffus is available under the permissive MIT free software license. This permits free use and inclusion even within proprietary software. It is good practice to run your pipeline in a temporary, “working” directory away from your original data. Ruffus is a lightweight python module for building computational pipelines. Ruffus requires Python 2.6 or higher or Python 3.0 or higher.Starting Price: Free -
27
Jina Search
Jina AI
With Jina Search, you can search for anything in seconds - faster and more accurately than any traditional search engine. Our AI search captures all the information stored in images and text, providing you with the most comprehensive results. Unlock the power of search and revolutionize the way you find what you're looking for with Jina Search. In this example, not all items on the dataset had the correct label, making it impossible for Classical Search to retrieve relevant results. Since Jina Search doesn't rely on tags, was successful on finding better items. Take full advantage of using state-of-the-art ML models that are optimized to work with multiple modalities of data, such as images and text while maintaining all your Elasticsearch customization. This means you don’t need to annotate each image in your dataset with labels, Jina Search will automatically understand the image and store it accordingly. -
28
Beautiful Soup
Beautiful Soup
Beautiful Soup is a library that makes it easy to scrape information from web pages. It sits atop an HTML or XML parser, providing Pythonic idioms for iterating, searching, and modifying the parse tree. Beautiful Soup's support for Python 2 was discontinued on December 31, 2020: one year after the sunset date for Python 2 itself. From this point onward, new Beautiful Soup development will exclusively target Python 3. The final release of Beautiful Soup 4 to support Python 2 was 4.9.3. Beautiful Soup is licensed under the MIT license, so you can also download the tarball, drop the bs4/ directory into almost any Python application (or into your library path) and start using it immediately.Starting Price: Free -
29
Seaborn
Seaborn
Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. For a brief introduction to the ideas behind the library, you can read the introductory notes or the paper. Visit the installation page to see how you can download the package and get started with it. You can browse the example gallery to see some of the things that you can do with seaborn, and then check out the tutorials or API reference to find out how. To see the code or report a bug, please visit the GitHub repository. General support questions are most at home on StackOverflow, which has a dedicated channel for seaborn. -
30
Oxen.ai
Oxen.ai
Oxen.ai is a collaborative data platform built to help teams manage, version, and operationalize machine learning datasets from initial curation through model deployment. At its core, the system provides a high-performance data version control engine optimized for large and complex datasets, allowing teams to version, branch, and share datasets, model weights, and experiments efficiently. It enables stakeholders across machine learning engineering, data science, product, and legal teams to review, edit, and collaborate on data within a unified workflow. Users can query, modify, and manage datasets through an intuitive web interface, command line tools, or a Python library, making it flexible for different technical workflows. Oxen.ai supports the full AI lifecycle by allowing teams to curate datasets, fine-tune models, and deploy them at scale while maintaining full ownership and traceability.Starting Price: $30 per month -
31
pandas
pandas
pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language. Tools for reading and writing data between in-memory data structures and different formats: CSV and text files, Microsoft Excel, SQL databases, and the fast HDF5 format. Intelligent data alignment and integrated handling of missing data: gain automatic label-based alignment in computations and easily manipulate messy data into an orderly form.Aggregating or transforming data with a powerful group by engine allowing split-apply-combine operations on data sets. Time series-functionality: date range generation and frequency conversion, moving window statistics, date shifting and lagging. Even create domain-specific time offsets and join time series without losing data. -
32
tox
tox
tox aims to automate and standardize testing in Python. It is part of a larger vision of easing the packaging, testing and release process of Python software. tox is a generic virtualenv management and test command-line tool you can use for checking that your package installs correctly with different Python versions and interpreters, running your tests in each of the environments, configuring your test tool of choice, and acting as a frontend to continuous integration servers, greatly reducing boilerplate and merging CI and shell-based testing. First, install tox with pip install tox. Then put basic information about your project and the test environments you want your project to run in into a tox.ini file residing right next to your setup.py file. You can also try generating a tox.ini file automatically, by running tox-quickstart and then answering a few simple questions. Install and test your project against Python2.7 and Python3.6.Starting Price: Free -
33
warcat
Python Software Foundation
Tool and library for handling Web ARChive (WARC) files. Naively join archives into one. Extract files from archive. List commands available. List contents of archive. Load archive and write it back out. Split archives into individual records. Verify digest and validate conformance. The library may not be entirely thread-safe yet. The goal of the Warcat project is to create a tool and library as easily and fast as manipulating any other archive such as tar and zip archives. Warcat is designed to handle large, gzip-ed files by partially extracting them as needed. Warcat is provided without warranty and cannot guarantee the safety of your files. Remember to make backups and test them! A WARC file contains one or more records concatenated together. Each record contains named fields, newline, a content block, newline, and newline. A Content Block may be two types, {binary data} or {Named Fields, newline, and binary data}.Starting Price: Free -
34
zope.interface
Python Software Foundation
This package is intended to be independently reusable in any Python project. It is maintained by the Zope Toolkit project. This package provides an implementation of “object interfaces” for Python. Interfaces are a mechanism for labeling objects as conforming to a given API or contract. So, this package can be considered as an implementation of the Design By Contract methodology support in Python. Interfaces are objects that specify (document) the external behavior of objects that “provide” them. An interface specifies behavior through informal documentation in a doc string, attribute definitions, and invariants, which are conditions that must hold for objects that provide the interface. Attribute definitions specify specific attributes. They define the attribute name and provide documentation and constraints of attribute values. Attribute definitions can take a number of forms.Starting Price: Free -
35
MakerSuite
Google
MakerSuite is a tool that simplifies this workflow. With MakerSuite, you’ll be able to iterate on prompts, augment your dataset with synthetic data, and easily tune custom models. When you’re ready to move to code, MakerSuite will let you export your prompt as code in your favorite languages and frameworks, like Python and Node.js. -
36
pexpect
pexpect
Pexpect makes Python a better tool for controlling other applications. Pexpect is a pure Python module for spawning child applications; controlling them, and responding to expected patterns in their output. Pexpect works like Don Libes’ Expect. Pexpect allows your script to spawn a child application and control it as if a human were typing commands. Pexpect can be used for automating interactive applications such as ssh, FTP, passwd, telnet, etc. It can be used to automate setup scripts for duplicating software package installations on different servers. It can be used for automated software testing. Pexpect is in the spirit of Don Libes’ Expect, but Pexpect is pure Python. Unlike other Expect-like modules for Python, Pexpect does not require TCL or Expect nor does it require C extensions to be compiled. It should work on any platform that supports the standard Python pty module. The Pexpect interface was designed to be easy to use.Starting Price: Free -
37
zdaemon
Python Software Foundation
zdaemon is a Unix (Unix, Linux, Mac OS X) Python program that wraps commands to make them behave as proper daemons. zdaemon provides a script, zdaemon, that can be used to run other programs as POSIX (Unix) daemons. (Of course, it is only usable on POSIX-complient systems.) Using zdaemon requires specifying a number of options, which can be given in a configuration file, or as command-line options. It also accepts commands teling it what to do. Start a process as a daemon. Stop a running daemon process. Stop and then restart a program. Find out if the program is running. Send a signal to the daemon process. Reopen the transcript log. Commands can be given on a command line, or can be given using an interactive interpreter. We can specify a program name and command-line options in the program command. Note, however, that the command-line parsing is pretty primitive.Starting Price: Free -
38
Kibo UI
Kibo UI
Kibo UI is a custom registry of composable, accessible, and open source components designed for use with shadcn/ui. Built with technologies like React, TypeScript, Tailwind CSS, Lucide, and Radix UI, Kibo UI offers a suite of functional and fully composable components that developers can build, customize, and extend to their specific needs. It includes a variety of components such as a color picker, an image zoom feature, a QR code generator, code blocks with syntax highlighting and copy-to-clipboard functionality, and a dropzone for drag-and-drop file uploads. Additionally, Kibo UI provides precomposed and animated blocks to help developers get their apps and websites up and running quickly. Examples include an AI chatbot interface and a collaborative canvas for real-time online collaboration. It also offers a pricing page template with a list of plans and features, emphasizing simplicity and transparency.Starting Price: Free -
39
DHTMLX
DHTMLX
DHTMLX is a JavaScript UI library that provides a set of highly customizable and flexible components for building modern and responsive web applications. The library includes more than 30 UI components, such as Gantt, Scheduler, Kanban, diagrams, charts, grids, spreadsheets, calendars, trees, forms, and more. DHTMLX helps to advance web development and build feature-rich data-intensive applications of any complexity. One of the key advantages of DHTMLX is its compatibility with different web frameworks, including React, Angular, and Vue.js, which makes it a great choice for developers who are already working with these frameworks. DHTMLX is also designed with performance in mind. Its components are optimized for fast rendering. A comprehensive and rich API provides a straightforward way to manipulate JavaScript/HTML5 UI widgets. The library has detailed API documentation, tutorials, and examples that help developers quickly get up to speed and start building their apps.Starting Price: $799 -
40
Tablecruncher
Tablecruncher
Tablecruncher is a lightweight yet powerful CSV editor for Mac, designed to handle large datasets efficiently. It can open files larger than 2GB, containing over 15 million rows, with a 100MB CSV file loading in under 5 seconds on a dual-core MacBook Pro. It supports various encodings, including UTF-8, UTF-16LE, UTF-16BE, Latin-1 (ISO-8859-1), and Windows 1252, automatically detecting most CSV formats and encodings. Users can utilize JavaScript as a macro language to manipulate CSV files, accessing all cells for content changes and calculations. Tablecruncher allows exporting table data to JSON, producing an array of objects if a header row is present, or an array of arrays otherwise. The find and replace dialog supports pattern searches within the table or selected areas, with Regular Expressions compliant with the ECMAScript 5 standard. It offers four color themes, including a dark mode compatible theme, enhancing user experience.Starting Price: $32.18 one-time payment -
41
dedupe
dedupe
Dedupe.io is a powerful tool that learns the best way to find similar rows in your data. Using cutting-edge research in machine learning we quickly and accurately identify matches in your Excel spreadsheet or database—saving you time and money. In today’s world of big data, there’s never been more information available to work with. Unfortunately, all this data is hard to use, especially if it’s been entered by hand or comes from different systems. The simple task of figuring out who is who in a spreadsheet or database can be a daunting, time-consuming task. That’s where Dedupe.io comes in. We developed the best dynamic and scalable solution for de-duplicating and linking datasets, and built a simple step-by-step wizard for anyone to use it.Starting Price: $9 per 1,000 rows -
42
openpyxl
openpyxl
openpyxl is a Python library to read/write Excel 2010 xlsx/xlsm/xltx/xltm files. It was born from a lack of an existing library to read/write natively from Python in the Office Open XML format. All kudos to the PHPExcel team as openpyxl was initially based on PHPExcel. By default, openpyxl does not guard against quadratic blowup or billion laughs XML attacks. To guard against these attacks install defusedxml. Install openpyxl using pip. It is advisable to do this in a Python virtualenv without system packages. Sometimes you might want to work with the checkout of a particular version. This may be the case if bugs have been fixed but a release has not yet been made. There is no need to create a file on the filesystem to get started with openpyxl. Just import the Workbook class and start work. Sheets are given a name automatically when they are created. Once you gave a worksheet a name, you can get it as a key of the workbook.Starting Price: Free -
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Datatrial Nucleus
Datatrial
One Platform to Research, Document, and Collate your Clinical Data. Simplify your research data with the Nucleus platform. A single platform to store your study documentation, clinical datasets, submission data and compliant media. Nucleus Documents enables document management and version control for your quality documentation and media. Control, manage, and share company content with ease. Collate and control your electronic trial master file documents with ease using our centralized regulatory document management solution. Nucleus Coding enables dictionary term coding against both MedDRA and WHODrug dictionaries, either in our standalone application, or integrated into your data capture system. -
44
pyglet
pyglet
The cross-platform windowing and multimedia library for Python. pyglet is a powerful, yet easy-to-use Python library for developing games and other visually-rich applications on Windows, Mac OS X, and Linux. It supports windowing, user interface event handling, Joysticks, OpenGL graphics, loading images, and videos, and playing sounds and music. All of this with a friendly Pythonic API, that's simple to learn and doesn't get in your way. pyglet is provided under the BSD open-source license, allowing you to use it for both commercial and other open-source projects with very little restriction. No external dependencies or installation requirements. For most application and game requirements, pyglet needs nothing else besides Python, simplifying distribution and installation. This makes it easy to package your project with freezers such as PyInstaller. pyglet provides real platform native windows, allowing you to take advantage of multiple windows and multi-monitor desktops.Starting Price: Free -
45
urllib3
urllib3
urllib3 is a powerful, user-friendly HTTP client for Python. Much of the Python ecosystem already uses urllib3 and you should too. urllib3 brings many critical features that are missing from the Python standard libraries. Thread safety, connection pooling, client-side TLS/SSL verification. File uploads with multipart encoding. Helpers for retrying requests and dealing with HTTP redirects. Support for gzip, deflate, and brotli encoding. Proxy support for HTTP and SOCKS. 100% test coverage. urllib3 is one of the most downloaded packages on PyPI and is a dependency of many popular Python packages like Requests, Pip, and more! urllib3 is made available under the MIT License. The API Reference documentation provides API-level documentation. The User Guide is the place to go to learn how to use the library and accomplish common tasks. The more in-depth Advanced Usage guide is the place to go for lower-level tweaking.Starting Price: Free -
46
python-docx
python-docx
python-docx is a Python library for creating and updating Microsoft Word (.docx) files. Paragraphs are fundamental in Word. They’re used for body text, but also for headings and list items like bullets. You’re free to specify both width and height, but usually, you wouldn’t want to. If you specify only one, python-docx uses it to calculate the properly scaled value of the other. This way the aspect ratio is preserved and your picture doesn’t look stretched. If you don’t know what a Word paragraph style is you should definitely check it out. Basically, it allows you to apply a whole set of formatting options to a paragraph at once. python-docx allows you to create new documents as well as make changes to existing ones. Actually, it only lets you make changes to existing documents; it’s just that if you start with a document that doesn’t have any content, it might feel at first like you’re creating one from scratch.Starting Price: Free -
47
TypeGPU
Software Mansion
TypeGPU is a TypeScript library that enhances the WebGPU API, allowing resource management in a type-safe, declarative way. It is designed to change the way developers work with GPU rendering and computing by bringing stronger structure, validation, and developer experience to WebGPU workflows. TypeGPU helps developers easily encode and decode GPU data, using typed binary so they do not have to think about raw bytes when writing GPU programs. Complex data types such as structs and arrays can be described directly, while TypeScript automatically validates outgoing and incoming data. It works on React Native through react-native-wgpu, expanding WebGPU development beyond the browser. TypeGPU’s roadmap is focused on end-to-end type safety on the GPU through interoperating primitives such as data structures, buffers, bind groups, a linker, functions, pipelines, and imperative code. -
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Mozilla Data Collective
Mozilla
Mozilla Data Collective is a platform built to rebuild the AI-data ecosystem by putting communities at its center. It gives data-creators and stewards the power to share datasets on their own terms, retaining ownership and controlling who accesses their data and under what conditions. Users can upload datasets, choose licenses (such as Creative Commons or bespoke terms), set access rules, require compensation or recognition, and govern datasets as individuals, cooperatives, or trusts. The platform emphasises ethical stewardship, transparency, and community agency, challenging extractive models of data harvesting and enabling more equitable participation. It hosts more than 300 high-quality global datasets created by and for communities, covers a wide range of use-cases (for example, multilingual speech-data collections), and makes developer-friendly tools available (such as a public API) so datasets can be integrated into applications. -
49
Modeller
Paragon Business Solutions
Over thirty years of credit risk modelling expertise wrapped into model building software for today’s age of machine learning. Modeller is a feature-rich, flexible, interactive and transparent tool that helps organizations get the best from their analytical teams. It supports a choice of techniques, the rapid development of powerful models, full explainability and the advancement of less experienced team members. Choose from numerous modeling techniques, including machine learning, for optimal predictive accuracy – especially on datasets with multicollinearity and complex interrelationships. Create industry-standard continuous and binary target models at the click of a button. Use decision tree modeling with CART and CHAID trees. Choose from logistic regression, elastic net models, survival analysis (Cox PH), random forests, XGBoost, stochastic gradient descent and more. Export options for implementation in other scoring and decisioning software include SAS, SQL, PMML and Python. -
50
Scapy
Scapy
Scapy is a powerful interactive packet manipulation program. It is able to forge or decode packets of a wide number of protocols, send them on the wire, capture them, match requests and replies, and much more. It can easily handle most classical tasks like scanning, tracerouting, probing, unit tests, attacks, or network discovery (it can replace hping, 85% of nmap, arpspoof, arp-sk, arping, tcpdump, tshark, p0f, etc.). It also performs very well at a lot of other specific tasks that most other tools can’t handle, like sending invalid frames, injecting your own 802.11 frames, combining technics (VLAN hopping+ARP cache poisoning, VOIP decoding on WEP encrypted channel), etc. Scapy runs natively on Linux, Windows, OSX, and on most Unixes with libpcap. The same code base now runs natively on both Python 2 and Python 3. Scapy development uses the Git version control system. Scapy reference repository is hosted on GitHub.Starting Price: Free