Open Source Python Formats and Protocols
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Python Formats and Protocols
View related business solutionsBrowse free open source Python Formats and Protocols and projects below. Use the toggles on the left to filter open source Python Formats and Protocols by OS, license, language, programming language, and project status.
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OCRmyPDF
OCRmyPDF adds an OCR text layer to scanned PDF files
OCRmyPDF adds an optical character recognition (OCR) text layer to scanned PDF files, allowing them to be searched. PDF is the best format for storing and exchanging scanned documents. Unfortunately, PDFs can be difficult to modify. OCRmyPDF makes it easy to apply image processing and OCR (recognized, searchable text) to existing PDFs. -
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PdfBooklet is a Python Gtk application which allows to make books or booklets from existing pdf files. It can also adjust margins, rotate, scale, merge files or extract pages.
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lxml
The lxml XML toolkit for Python
A Python library for efficient XML and HTML processing, known for speed and compatibility. The lxml XML toolkit is a Pythonic binding for the C libraries libxml2 and libxslt. It is unique in that it combines the speed and XML feature completeness of these libraries with the simplicity of a native Python API, mostly compatible but superior to the well-known ElementTree API. The latest release works with all CPython versions from 3.6 to 3.12. See the introduction for more information about the background and goals of the lxml project. -
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Grassroots DICOM
Cross-platform DICOM implementation
Grassroots DiCoM is a C++ library for DICOM medical files. It is accessible from Python, C#, Java and PHP. It supports RAW, JPEG, JPEG 2000, JPEG-LS, RLE and deflated transfer syntax. It comes with a super fast scanner implementation to quickly scan hundreds of DICOM files. It supports SCU network operations (C-ECHO, C-FIND, C-STORE, C-MOVE). PS 3.3 & 3.6 are distributed as XML files. It also provides PS 3.15 certificates and password based mecanism to anonymize and de-identify DICOM datasets. -
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BioSig is a software library for processing of biomedical signals (EEG, ECG, etc.) with Matlab, Octave, C/C++ and Python. About 50 different data formats are supported.
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Asymptote
2D & 3D TeX-Aware Vector Graphics Language
Asymptote is a powerful descriptive vector graphics language for technical drawing, inspired by MetaPost but with an improved C++-like syntax. Asymptote provides for figures the same high-quality typesetting that LaTeX does for scientific text. -
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Docker Compose
Define and run multi-container applications with Docker
Docker Compose is an open source tool for defining and running multi-container applications with Docker. Compose lets you use a YAML file to configure your application’s services, and then create and start all the services from your configuration with just a single command. Compose works great in all environments: production, staging, testing, development, and on CI workflows. Compose has commands for every stage of your application lifecycle, from starting, stopping and rebuilding services, through to status viewing, streaming of log output and running a one-off command on a service. -
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PDF-Shuffler is a small python-gtk application, which helps the user to merge or split pdf documents and rotate, crop and rearrange their pages using an interactive and intuitive graphical interface. It is a frontend for python-pyPdf.
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ZK is an open-source Java framework for building modern web and mobile applications. It enables developers to create rich, interactive UIs using only Java — no JavaScript required. With 200+ Ajax-powered components, event-driven architecture, and support for popular technologies like Spring, Java EE, and JSP/JSF, ZK makes it simple to deliver powerful and user-friendly web applications.
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Python ADB
Python ADB + Fastboot implementation
python-adb provides a pure-Python implementation of the Android Debug Bridge protocol so you can script Android devices without depending on the platform adb binary. It exposes high-level helpers for device discovery, shell commands, file push/pull, port forwarding, and log collection, making it easy to build automation around phones and emulators. Under the hood it speaks the ADB protocol directly and can connect via USB or over TCP, which is useful for lab setups and headless servers. Because it’s Python, you can compose device actions with your favorite testing, scraping, or data-collection libraries in one process. The project also includes utilities for robust connection handling and timeouts so flaky USB links don’t derail long runs. It’s well-suited to CI test farms, large-scale telemetry, and custom device control workflows. -
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TikZ
TikZ figures for concepts in physics/chemistry/ML
Collection of 111 standalone TikZ figures for illustrating concepts in physics, chemistry, and machine learning. Check out janosh.github.io to search, sort, open in Overleaf, and download figures (PDF/SVG/PNG) from this collection. -
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autopep8
A tool that automatically formats Python code to conform to the PEP 8
autopep8 automatically formats Python code to conform to the PEP 8 style guide. It uses the pycodestyle utility to determine what parts of the code need to be formatted. autopep8 is capable of fixing most of the formatting issues that can be reported by pycodestyle. Correct deprecated or non-idiomatic Python code (via lib2to3). Use this for making Python 2.7 code more compatible with Python 3. Put a blank line between a class docstring and its first method declaration. Remove blank lines between a function declaration and its docstring. -
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FreeTAKServer
Situational Awareness Server compatible with TAK clients
FTS is a Python3 implementation of a TAK Server for devices like ATAK, WinTAK, and ITAK, it is cross-platform and runs from a multi-node installation on AWS down to the Android edition. It's free and open source (released under the Eclipse Public License. FTS allows you to connect ATAK clients to share geo-information, to chat with all the connected clients, exchange files and more. It intends to support all the major use cases of the original TAK server. -
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Great Expectations
Always know what to expect from your data
Great Expectations helps data teams eliminate pipeline debt, through data testing, documentation, and profiling. Software developers have long known that testing and documentation are essential for managing complex codebases. Great Expectations brings the same confidence, integrity, and acceleration to data science and data engineering teams. Expectations are assertions for data. They are the workhorse abstraction in Great Expectations, covering all kinds of common data issues. Expectations are a great start, but it takes more to get to production-ready data validation. Where are Expectations stored? How do they get updated? How do you securely connect to production data systems? How do you notify team members and triage when data validation fails? Great Expectations supports all of these use cases out of the box. Instead of building these components for yourself over weeks or months, you will be able to add production-ready validation to your pipeline in a day. -
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Pix2Text
Open-Source Python3 tool for recognizing layouts, tables, and math
An Open-Source Python3 tool for recognizing layouts, tables, math formulas, and text in images, converting them into Markdown format. A free alternative to Mathpix, empowering seamless conversion of visual content into text-based representations. 80+ languages are supported. Pix2Text (P2T) aims to be a free and open-source Python alternative to Mathpix, and it can already accomplish Mathpix's core functionality. Pix2Text (P2T) can recognize layouts, tables, images, text, and mathematical formulas, and integrate all of these contents into Markdown format. P2T can also convert an entire PDF file (which can contain scanned images or any other format) into Markdown format. -
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TOML
Tom Preston-Werner's obvious, minimal language
Tom's Obvious, Minimal Language. By Tom Preston-Werner, Pradyun Gedam, et al. TOML aims to be a minimal configuration file format that's easy to read due to obvious semantics. TOML is designed to map unambiguously to a hash table. TOML should be easy to parse into data structures in a wide variety of languages. TOML shares traits with other file formats used for application configuration and data serialization, such as YAML and JSON. TOML and JSON both are simple and use ubiquitous data types, making them easy to code for or parse with machines. TOML and YAML both emphasize human readability features, like comments that make it easier to understand the purpose of a given line. TOML differs in combining these, allowing comments (unlike JSON) but preserving simplicity (unlike YAML). Because TOML is explicitly intended as a configuration file format, parsing it is easy, but it is not intended for serializing arbitrary data structures. -
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orjson
Fast, correct Python JSON library supporting dataclasses, datetimes
orjson is a fast, correct JSON library for Python. It benchmarks as the fastest Python library for JSON and is more correct than the standard json library or other third-party libraries. It serializes dataclass, datetime, numpy, and UUID instances natively. orjson supports CPython 3.8, 3.9, 3.10, 3.11, and 3.12. It distributes amd64/x86_64, aarch64/armv8, arm7, POWER/ppc64le, and s390x wheels for Linux, amd64 and aarch64 wheels for macOS, and amd64 and i686/x86 wheels for Windows. orjson does not support PyPy. Releases follow semantic versioning and serializing a new object type without an opt-in flag is considered a breaking change. -
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tqdm
A Fast, Extensible Progress Bar for Python and CLI
tqdm is a fast, extensible progress bar for Python and CLI that enables you to see the progress of your loops in a clear and smart way. Simply wrap any iterable with tqdm(iterable), and sit back and watch that progress meter go! tqdm can be wrapped around any iterable, or executed as a module with pipes. Just by inserting tqdm (or python -m tqdm) between pipes will pass through all stdin to stdout while printing progress to stderr. tqdm does not require any dependencies, has a very low overhead and uses smart algorithms to predict the remaining time and skip unnecessary iteration displays. It works on just about any platform, console or in a GUI, as well as IPython/Jupyter notebooks. -
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srsly
Modern high-performance serialization utilities for Python
This package bundles some of the best Python serialization libraries into one standalone package, with a high-level API that makes it easy to write code that's correct across platforms and Pythons. This allows us to provide all the serialization utilities we need in a single binary wheel. Currently supports JSON, JSONL, MessagePack, Pickle, and YAML. Serialization is hard, especially across Python versions and multiple platforms. After dealing with many subtle bugs over the years (encodings, locales, large files) our libraries like spaCy and Prodigy have steadily grown a number of utility functions to wrap the multiple serialization formats we need to support (especially json, msgpack and pickle). These wrapping functions ended up duplicated across our codebases, so we wanted to put them in one place. -
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FontForge Windows builds
Unofficial Windows builds of FontForge
The aim of this project is to compile up-to-date Windows builds of FontForge. For 'stable' builds, see https://github.com/fontforge/fontforge/releases The build system used was based off that offered by Matthew Petroff (http://www.mpetroff.net/software/fontforge-windows/), but has since been practically rewritten. New in 11/07/2020: * Synced with the 20201107 release. New in 06/04/2020: * Updated to latest master, picks up a clipboard copying fix New in 14/03/2020: * Synced with the 20200314 release. New in 01/03/2020: * Updated to latest master, now built with CMake. (prerelease) New in 02/06/2019: * The 32-bit build now uses Python 3 (3.7) instead of Python 2. No further Python 2 builds will be provided. * The GDK3 backend is now used. VcXsrv is no longer bundled. New in 31/07/2017: KNOWN ISSUES: * CTRL-C from console no longer interrupts/stops FontForge -
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JupyterLab LaTeX
JupyterLab extension for live editing of LaTeX documents
An extension for JupyterLab which allows for live-editing of LaTeX documents. To use, right-click on an open .tex document within JupyterLab, and select Show LaTeX Preview. This extension includes both a notebook server extension (which interfaces with the LaTeX compiler) and a lab extension (which provides the UI for the LaTeX preview). The Python package named jupyterlab_latex provides both of them as a prebuilt extension. -
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PackageDev
Tools to ease the creation of snippets, syntax definitions, etc.
PackageDev provides syntax highlighting and other helpful utility for Sublime Text resource files. Resource files are ways of configuring the Sublime Text text editor to various extends, including but not limited to: custom syntax definitions, context menus (and the main menu), and key bindings. Thus, this package is ideal for package developers, but even normal users of Sublime Text who want to configure it to their liking should find it very useful. -
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Rdbtools
Parse Redis dump.rdb files, Analyze Memory, and Export Data to JSON
Rdbtools is a parser for Redis' dump.rdb files. The parser generates events similar to an XML sax parser and is very efficient memory-wise. Rdbtools is written in Python, though there are similar projects in other languages. Every run of RDB Tool requires to specify a command to indicate what should be done with the parsed RDB data. Valid commands are JSON, diff, justkeys, justkeyvals and protocol. The JSON command output is UTF-8 encoded JSON. By default, the callback try to parse RDB data using UTF-8 and escape non 'ASCII printable' characters with the \U notation, or non-UTF-8 parsable bytes with \x. Attempting to decode RDB data can lead to binary data corruption, this can be avoided by using the --escape raw option. Another option is to use -e base64 for Base64 encoding of binary data. -
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yq JSON
Command-line YAML, XML, TOML processor
Before using yq, you also have to install its dependency, jq. See the jq installation instructions for details and directions specific to your platform. On macOS, yq is also available on Homebrew use brew install python-yq. -
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Budou
Budou is an auto organizer tool for beautiful line breaking in CJK
Budou is a Python library developed by Google to improve web typography for CJK (Chinese, Japanese, Korean) languages by producing semantically meaningful line breaks. Unlike English, CJK scripts lack spaces or hyphenation cues, often resulting in awkward or unreadable text wrapping on web pages. Budou addresses this issue by segmenting sentences into logical lexical chunks and wrapping each chunk in non-breaking HTML <span> tags. These spans can be styled with CSS to ensure smooth, visually coherent line breaks without splitting words or phrases. The tool supports multiple segmentation backends, including Google Cloud Natural Language API, MeCab, and TinySegmenter, enabling flexibility for both cloud-based and offline processing. Budou can be used via command line, in Python scripts, or integrated into web applications, and it provides advanced options such as caching and entity recognition for improved segmentation accuracy.
