Search Results for "python::module" - Page 48
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Showing 16961 open source projects for "python::module"
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Recommenders
Best practices on recommendation systems
The Recommenders repository provides examples and best practices for building recommendation systems, provided as Jupyter notebooks. The module reco_utils contains functions to simplify common tasks used when developing and evaluating recommender systems. Several utilities are provided in reco_utils to support common tasks such as loading datasets in the format expected by different algorithms, evaluating model outputs, and splitting training/test data. Implementations of several state... -
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Crawlab
Distributed web crawler admin platform for spiders management
Golang-based distributed web crawler management platform, supporting various languages including Python, NodeJS, Go, Java, PHP and various web crawler frameworks including Scrapy, Puppeteer, Selenium. Please use docker-compose to one-click to start up. By doing so, you don't even have to configure MongoDB database. The frontend app interacts with the master node, which communicates with other components such as MongoDB, SeaweedFS and worker nodes. Master node and worker nodes communicate... -
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xonsh
Python-powered, cross-platform, Unix-gazing shell
Xonsh is a Python-powered, cross-platform, Unix-gazing shell language and commands prompt. The language is a superset of Python 3.6+ with additional shell primitives that you are used to from Bash and IPython. It works on all major systems including Linux, OSX, and Windows. Xonsh is meant for the daily use of experts and novices. The xonsh shell lets you easily mix Python and shell commands in a powerful and simplified approach to the command line. The xonsh language has shell primitives... -
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Pyparsing
Python library for creating PEG parsers
pyparsing is a Python library that facilitates the creation of parsers using a parsing expression grammar (PEG) approach. It allows developers to construct grammars directly in Python code, offering an alternative to traditional parsing methods. -
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Mastodon.py
Python wrapper for the Mastodon
Python wrapper for the Mastodon API. Feature complete for public API as of Mastodon version 3.5.5 and easy to get started with. -
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liquidpy
A port of liquid template engine for python
A port of liquid template engine for Python, on the shoulder of jinja2. -
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AI Upscaler for Blender
AI Upscaler for Blender using Real-ESRGAN
Blender add-on to dramatically reduce render times using the Real-ESRGAN upscaler. Rendering an HD image in Blender takes 37 minutes. Upscaling can render a similar quality image in 5 mins total. Any PC or laptop can now do 3D rendering. 4k images can be rendered in the time it would take to render HD 1080p images. HD 1080p images can be rendered in record time on low-end hardware. Installation is easy. Just install the addon. No special hardware or GPU is required. Upscaling is done... -
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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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Nodeenv
Virtual environment for Node.js & integrator with virtualenv
A Python tool that creates isolated Node.js virtual environments, similar to Python's virtualenv. -
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PyTextRank
Python implementation of TextRank algorithms
PyTextRank is a Python implementation of TextRank as a spaCy pipeline extension, for graph-based natural language work -- and related knowledge graph practices. -
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go1pylib
go1pylib is a Python library designed to control the Go1 robot
go1pylib is a Python library designed to control the Go1 robot by Unitree Robotics. It provides an easy-to-use interface for robot movement, state management, collision avoidance, battery monitoring, and MQTT communication. Ideal for research and robotics development. -
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TensorLy
Tensor Learning in Python
TensorLy is a Python library that aims at making tensor learning simple and accessible. It allows to easily perform tensor decomposition, tensor learning and tensor algebra. Its backend system allows to seamlessly perform computation with NumPy, PyTorch, JAX, TensorFlow, CuPy or Paddle, and run methods at scale on CPU or GPU. -
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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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troposphere
Python library to create AWS CloudFormation descriptions
The troposphere library allows for easier creation of the AWS CloudFormation JSON by writing Python code to describe the AWS resources. troposphere also includes some basic support for OpenStack resources via Heat. To facilitate catching CloudFormation or JSON errors early the library has property and type checking built into the classes. -
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Pony ORM
Pony Object Relational Mapper
Pony ORM is a Python ORM that enables developers to write database queries using generator expressions and Pythonic syntax, making code more readable and intuitive. It automatically translates Python expressions into SQL and supports multiple databases including SQLite, MySQL, PostgreSQL, and Oracle. With an emphasis on simplicity and maintainability, Pony ORM is suitable for both small projects and complex applications. -
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Rio
WebApps in pure Python. No JavaScript, HTML and CSS needed
Rio is a Python framework designed to build web applications without the need for HTML, CSS, or JavaScript. Inspired by frameworks like Flutter and React, Rio offers a declarative interface and reusable components, enabling developers to create dynamic web apps entirely in Python. It streamlines the development process by managing both frontend and backend seamlessly. -
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MechanicalSoup
A Python library for automating interaction with websites
A Python library for automating interaction with websites. MechanicalSoup automatically stores and sends cookies, follows redirects, and can follow links and submit forms. It doesn't do JavaScript. MechanicalSoup was created by M Hickford, who was a fond user of the Mechanize library. Unfortunately, Mechanize was incompatible with Python 3 until 2019 and its development stalled for several years. MechanicalSoup provides a similar API, built on Python giants Requests (for HTTP sessions... -
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PEP 8 Speaks
A GitHub app to automatically review Python code style
A GitHub app to automatically review Python code style over Pull Requests. PEP 8 Speaks is a GitHub integration which detects Python code style issues on new Pull Requests. You can install it on your Python projects and configure with your own code style. Check out the project on GitHub. Maintainers of Python projects have a difficult time reviewing Pull Requests by new contributors who may not be aware of the code style. This project makes reviewing Pull Requests a little bit easier. Style... -
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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... -
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uwsgi-nginx-flask
Docker image with uWSGI and Nginx for Flask applications in Python
Image with uWSGI and Nginx for Flask apps in Python running in a single container. Docker image with uWSGI and Nginx for Flask web applications in Python running in a single container. Optionally using Alpine Linux. This Docker image allows you to create Flask web applications in Python that run with uWSGI and Nginx in a single container. The combination of uWSGI with Nginx is a common way to deploy Python Flask web applications. It is widely used in the industry and would give you decent... -
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Transcrypt
Python 3.7 to JavaScript compiler
Python in the browser, precompiled for speed. Transcrypt started out as a personal repo, owned by Jacques de Hooge. As the project caught on and the number of people contributing issues, ideas and code grew, the repo was transferred to the QQuick organization, to be able to form a developer team on GitHub. There's a simple parallel between the Python and the JavaScript code. In combination with the use of source maps, this enables efficient debugging. Also, code can be tested from the command... -
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A simple WebSocket server
A simple WebSocket server
A simple WebSocket server. -
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Krixik
Documentation for the Krixik Python client
Small/specialized AI models are an oft-necessary complement—or alternative—to "big AI" offerings. However, infrastructure for small AI tends to be underwhelming, so building with specialized AI can be difficult, time-consuming, and even expensive. Iterating with different models, and particularly with different combinations of these models, can thus be rendered unfeasible. -
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PyKEEN
A Python library for learning and evaluating knowledge graph embedding
PyKEEN (Python KnowlEdge EmbeddiNgs) is a Python package designed to train and evaluate knowledge graph embedding models (incorporating multi-modal information). PyKEEN is a Python package for reproducible, facile knowledge graph embeddings. PyKEEN has a function pykeen.env() that magically prints relevant version information about PyTorch, CUDA, and your operating system that can be used for debugging. If you’re in a Jupyter Notebook, it will be pretty-printed as an HTML table. -
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Hamilton DAGWorks
Helps scientists define testable, modular, self-documenting dataflow
Hamilton is a lightweight Python library for directed acyclic graphs (DAGs) of data transformations. Your DAG is portable; it runs anywhere Python runs, whether it's a script, notebook, Airflow pipeline, FastAPI server, etc. Your DAG is expressive; Hamilton has extensive features to define and modify the execution of a DAG (e.g., data validation, experiment tracking, remote execution). To create a DAG, write regular Python functions that specify their dependencies with their parameters...
