Open Source Python Formats and Protocols - Page 3
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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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Academic File Converter
Import Bibtex publications and Jupyter Notebook posts into websites
Easily import publications and Jupyter notebooks to your Markdown-formatted website or book. -
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Connexion
Swagger/OpenAPI First framework for Python on top of Flask
Connexion is a framework on top of Flask that automagically handles HTTP requests defined using OpenAPI (formerly known as Swagger), supporting both v2.0 and v3.0 of the specification. Connexion allows you to write these specifications, then maps the endpoints to your Python functions. This is what makes it unique from other tools that generate the specification based on your Python code. You are free to describe your REST API with as much detail as you want and then Connexion guarantees that it will work as you specified. We built Connexion this way in order to simplify the development process. Reduce misinterpretation about what an API is going to look like. With Connexion, you write the spec first. Connexion then calls your Python code, handling the mapping from the specification to the code. This incentivizes you to write the specification so that all of your developers can understand what your API does, even before you write a single line of code. -
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CrowdAnki
Plugin for Anki SRS designed to facilitate cooperation
CrowdAnki is a plugin for http://ankisrs.net/ that allows users to import and export decks/notes and all relevant information in a JSON format. The main purpose is to facilitate crowd-sourcing for Anki decks and notes. Starting with version 0.6 it also features a close integration with Git. Providing you with the ability to automatically maintain a history of edits for your decks. My goal here is to provide a user-friendly description of collaboration workflow. In order to do that, I looked through multiple GUI git clients. For our purposes here, I think GitHub Desktop is the best choice (as the most user-friendly client that works). There is one problem with GitHub Desktop, though - it doesn't have a Linux version. Which makes me particularly sad, as I use Linux as my main OS. -
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DocArray
The data structure for multimodal data
DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API. Door to multimodal world: super-expressive data structure for representing complicated/mixed/nested text, image, video, audio, 3D mesh data. The foundation data structure of Jina, CLIP-as-service, DALL·E Flow, DiscoArt etc. Data science powerhouse: greatly accelerate data scientists’ work on embedding, k-NN matching, querying, visualizing, evaluating via Torch/TensorFlow/ONNX/PaddlePaddle on CPU/GPU. Data in transit: optimized for network communication, ready-to-wire at anytime with fast and compressed serialization in Protobuf, bytes, base64, JSON, CSV, DataFrame. Perfect for streaming and out-of-memory data. One-stop k-NN: Unified and consistent API for mainstream vector databases. -
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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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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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Mashumaro
Fast and well tested serialization library on top of dataclasses
When using data classes, you often need to dump and load objects based on the schema you have. Mashumaro not only lets you save and load things in different ways, but it also does it super quickly. -
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Remarshal
Convert between CBOR, JSON, MessagePack, TOML, and YAML
Convert between CBOR, JSON, MessagePack, TOML, and YAML. When installed, provides the command-line command remarshal as well as the short commands {cbor,json,msgpack,toml,yaml}2{cbor,json,msgpack,toml,yaml}. You can perform format conversion, reformatting, and error detection using these commands. CBOR, MessagePack, and YAML with binary fields cannot be converted to JSON or TOML. Binary fields are converted between CBOR, MessagePack, and YAML. -
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jsonschema
An implementation of the JSON Schema specification for Python
jsonschema is an implementation of the JSON Schema specification for Python. Full support for Draft 2020-12, Draft 2019-09, Draft 7, Draft 6, Draft 4 and Draft 3. Lazy validation that can iteratively report all validation errors. Programmatic querying of which properties or items failed validation. -
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latex2mathml
Pure Python library for LaTeX to MathML conversion
Pure Python library for LaTeX to MathML conversion. -
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m2cgen
Transform ML models into a native code
m2cgen (Model 2 Code Generator) - is a lightweight library that provides an easy way to transpile trained statistical models into a native code (Python, C, Java, Go, JavaScript, Visual Basic, C#, PowerShell, R, PHP, Dart, Haskell, Ruby, F#, Rust, Elixir). Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies. Some models force input data to be particular type during prediction phase in their native Python libraries. Currently, m2cgen works only with float64 (double) data type. You can try to cast your input data to another type manually and check results again. Also, some small differences can happen due to specific implementation of floating-point arithmetic in a target language. -
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msgspec
A fast serialization and validation library, with builtin
msgspec is a fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML. -
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openvpn-monitor
openvpn-monitor is a web based OpenVPN monitor
openvpn-monitor is a simple Python program to generate HTML that displays the status of an OpenVPN server, including all current connections. It uses the OpenVPN management console. It typically runs on the same host as the OpenVPN server, however, it does not necessarily need to. OpenVPN-monitor is a web-based OpenVPN monitor, that shows current connection information, such as users, location, and data transferred. -
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pandas-datareader
Extract data from a wide range of Internet sources
Up-to-date remote data access for pandas. Works for multiple versions of pandas. Install using pip and then import and use one of the data readers. This example reads 5-years of 10-year constant maturity yields on U.S. government bonds. Stable documentation is available on github.io. A second copy of the stable documentation is hosted on read the docs for more details. -
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pyment
Format and convert Python docstrings and generates patches
Create, update or convert docstrings in existing Python files, managing several styles. This Python3 program intends to help Python programmers to enhance inside code documentation using docstrings. It is useful for code not well documented, or code without docstrings, or some not yet or partially documented code, or a mix of all of this. It can be helpful also to harmonize or change a project docstring style format. It will parse one or several python scripts and retrieve existing docstrings. Then, for all found functions/methods/classes, it will generate formatted docstrings with parameters, default values. At the end, patches can be generated for each file. Then, man can apply the patches to the initial scripts. It is also possible to update the files directly without generating patches, or to output on stdout. It is also possible to generate the python file with the new docstrings, or to retrieve only the docstrings. -
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pyspider
A powerful Spider(Web Crawler) system in Python
pyspider is a powerful Spider(Web Crawler) system in Python. Components are connected by message queue. Every component, including message queue, is running in their own process/thread, and replaceable. That means, when process is slow, you can have many instances of processor and make full use of multiple CPUs, or deploy to multiple machines. This architecture makes pyspider really fast. benchmarking. Since pyspider has various components, you can just run pyspider to start a standalone and third service free instance. Or using MySQL or MongoDB and RabbitMQ to deploy a distributed crawl cluster. To deploy pyspider in product environment, running component in each process and store data in database service is more reliable and flexible. To deploy pyspider components in each single processes, you need at least one database service. pyspider now supports MySQL, MongoDB and PostgreSQL. You can choose one of them. -
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python-benedict
dict subclass with keylist/keypath support
python-benedict is a dict subclass with keylist/keypath/keyattr support, I/O shortcuts (base64, cli, csv, ini, json, pickle, plist, query-string, toml, xls, xml, yaml) and many utilities... for humans, obviously. -
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zjuthesis
Zhejiang University Graduation Thesis LaTeX Template
LaTeX template suite designed for Zhejiang University graduation theses. It includes templates tailored for undergraduate, master’s, and doctoral students—including graduate‑level English templates—and aligns with Zhejiang University formatting guidelines. -
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csv2odf
csv2odf can convert csv data to formatted spreadsheets and documents.
csv2odf can create business intelligence reports from csv data sources with output to ods, odt, html, xlsx, or docx documents. It uses a template file that you design to control the layout, fonts, and colors. Just query your database with output to csv (or tsv), then use csv2odf to insert the data into your template to produce a nice looking formatted output. It is a command line tool and you can automate the generation of reports by using scripts and cron. It can be used to create spreadsheets and documents for LibreOffice, OpenOffice, Microsoft Office Excel and Word. It is open source GPL v3 and crossplatform, it can run on most operating systems that can run Python (Python is required). More details, example files, and online manual at http://csv2odf.sf.net. -
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Bots-ediint open source edi translator
open source edi translator
Bots-ediint is a file translator for EDI (Electronic Data Interchange). Translate files and databases data format to another one: edifact, x12, tradacoms, xml, json, raw, database (postgres, sqlite, mysql, oracle, ...) and more. Bots-ediint is based on Bots https://bots.sourceforge.net Support Python 2 and Python 3 AS2 communications are carried out with my external software that could work in standalone and/or in a Bots channel to send and receive AS2 messages (SYNC and ASYNC) Help the future to be an open world. -
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MyDBF2MySQL
Extract, transform, and load DBF into MySQL
This is an ETL software which loads data from DBF/XBase files into MySQL. This utility has command line interface, designed to work without user interaction.">
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TextureAtlas Extractor and GIF Generator
A powerful, free and open-source tool for extracting frames and animat
TextureAtlas to GIF and Frames converts texture atlases into organized frame collections and GIF/WebP/APNG animations. Perfect for creating showcases and galleries of game sprites. Supported Spritesheet Types * Starling / Sparrow (XML) * TextPacker (TXT) + Can now also attempt to extract unsupported spritesheet formats through pixel, color and bounding box detection Official Download Sites: * https://sourceforge.net/projects/textureatlas-to-gif-and-frames/ * https://github.com/MeguminBOT/TextureAtlas-to-GIF-and-Frames/releases * https://gamebanana.com/tools/16621 * https://autisticlulu.itch.io/textureatlas-to-gif-and-frames Website: https://meguminbot.github.io/TATGF/ -
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EpiDoc: Epigraphic Documents in TEI XML
XML text markup for ancient documents
The EpiDoc Collaborative is developing specifications and tools for standards-based, digital publication and interchange of scholarly and educational editions of documentary and literary texts like inscriptions and papyri. The link below will take you to the EpiDoc home page on this site. -
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Redland is a set of object-based, modular and portable C RDF libraries providing RDF APIs for the graph, triple storage (librdf), RDF/XML parsing and serializing (Raptor), SPARQL RDF querying (Rasqal). Language APIs in Perl, PHP, Python, Ruby and others.
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OpenDAFF
Directional Audio File Format
OpenDAFF is a free, open-source software package for directional audio data - like the directivity of microphones, speakers, as well as head-related transfer functions (HRTFs)