Search Results for "mac os linux" - Page 2
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Showing 383 open source projects for "mac os linux"
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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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pdfly
CLI tool to extract (meta)data from PDF and manipulate PDF files
A Python library designed for manipulating PDF files with functionalities for extraction, transformation, and document generation. -
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arxiv_latex_cleaner
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper
This tool allows you to easily clean the LaTeX code of your paper to submit to arXiv. From a folder containing all your code, e.g. /path/to/latex/, it creates a new folder /path/to/latex_arXiv/, that is ready to ZIP and upload to arXiv. -
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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... -
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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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simplejson
simplejson is a simple, fast, extensible JSON encoder/decoder
simplejson is a simple, fast, complete, correct and extensible JSON <http://json.org> encoder and decoder for Python 3.3+ with legacy support for Python 2.5+. It is pure Python code with no dependencies but includes an optional C extension for a serious speed boost. simplejson is the externally maintained development version of the json library included with Python (since 2.6). This version is tested with the latest Python 3.8 and maintains backward compatibility with Python 3.3+ and the... -
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WriteTeX
An Inkscape extension: Latex/Tex editor for Inkscape
Due to an incompatible change of the Inkscape extension API, this extension has to split into two versions. For Inkscape versions lower than 1.0, users should use the files in the 0.9.x folder, the other users should use files in the 1.0.x folder. -
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TexSoup
Fault-tolerant Python3 package for searching LaTeX documents
Navigate, Search, and Modify LaTeX Documents in Python. Easy and reliable: No C extensions, no installation dependencies, and 100% test coverage. TexSoup is a fault-tolerant, Python3 package for searching, navigating, and modifying LaTeX documents. You can skip installation and try TexSoup directly, using the pytwiddle demo. -
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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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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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AWS Lambda Python Runtime Interf Client
Seamlessly extend your preferred base images to be Lambda compatible
We have open-sourced a set of software packages, Runtime Interface Clients (RIC), that implement the Lambda Runtime API, allowing you to seamlessly extend your preferred base images to be Lambda compatible. The Lambda Runtime Interface Client is a lightweight interface that allows your runtime to receive requests from and send requests to the Lambda service. The Lambda Python Runtime Interface Client is vended through pip. You can include this package in your preferred base image to make... -
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TrendRadar
AI-driven public opinion trend monitor with multi-platform aggregation
TrendRadar is an AI-powered trend and hotspot tracking system that aggregates information from dozens of news, social, and content platforms to help users cut through information overload and focus on what matters. It automatically crawls and monitors trends across 30+ sources with smart filtering, keyword triggers, sentiment analysis, and natural language summarization to give actionable insights. The tool supports multiple alert modes—such as daily summaries, incremental change monitoring,... -
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Jupyter Enterprise Gateway
Enables Jupyter Notebooks to share resources across clusters
Jupyter Enterprise Gateway is a headless web server with a pluggable framework for anyone supporting multiple notebook users in a managed-cluster environment. Some of the core functionality it provides is better optimization of compute resources, improved multi-user support, and more granular security for your Jupyter notebook environment - making it suitable for enterprise, scientific, and academic implementations. From a technical perspective, Jupyter Enterprise Gateway is a web 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... -
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RSS to Telegram Bot
A Telegram RSS bot that cares about your reading experience
A Telegram RSS bot that cares about your reading experience. -
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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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Memvid
Video-based AI memory library. Store millions of text chunks in MP4
Memvid encodes text chunks as QR codes within MP4 frames to build a portable “video memory” for AI systems. This innovative approach uses standard video containers and offers millisecond-level semantic search across large corpora with dramatically less storage than vector DBs. It's self-contained—no DB needed—and supports features like PDF indexing, chat integration, and cloud dashboards. -
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SQLModel
SQL databases in Python, designed for simplicity, compatibility
SQLModel, SQL databases in Python, designed for simplicity, compatibility, and robustness. SQLModel is a library for interacting with SQL databases from Python code, with Python objects. It is designed to be intuitive, easy to use, highly compatible, and robust. SQLModel is based on Python-type annotations, and powered by Pydantic and SQLAlchemy. -
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Cortex Analyzers
Cortex Analyzers Repository
Analyzers can be written in any programming language supported by Linux such as Python, Ruby, Perl, etc. Refer to the How to Write and Submit an Analyzer page for details on how to write and submit one. -
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Markdown package LaTeX
Package for converting and rendering markdown documents in TeX
The Markdown package converts CommonMark markup to TeX commands. The functionality is provided both as a Lua module, and as plain TeX, LaTeX, and ConTeXt macro packages that can be used to directly typeset TeX documents containing markdown markup. Unlike other convertors, the Markdown package does not require any external programs and makes it easy to redefine how each and every markdown element is rendered. Creative abuse of the markdown syntax is encouraged. -
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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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jsondiff
Diff JSON and JSON-like structures in Python
Diff JSON and JSON-like structures in Python. -
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pylatexenc
Simple LaTeX parser providing latex-to-unicode and unicode-to-latex
Simple LaTeX parser providing latex-to-unicode and unicode-to-latex conversion. Python 3.4 or 2.7. The library is designed to be as backward-compatible as reasonably possible and is able to run on old Python versions should it be necessary. (Use the setup.py script directly if you have Python 3.7, poetry doesn't seem to work with old Python versions.) The pylatexenc.latexencode module provides a function unicode_to_latex() which converts a Unicode string into LaTeX text and escape sequences.... -
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pyserde
Yet another serialization library on top of dataclasses
Yet another serialization library on top of data classes, inspired by serde-rs. Declare a class with pyserde's @serde decorator. -
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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.