Showing 4932 open source projects for "python::module"

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  • 1
    Awesome Network Analysis

    Awesome Network Analysis

    A curated list of awesome network analysis resources

    awesome-network-analysis is a curated list of resources focused on network and graph analysis, including libraries, frameworks, visualization tools, datasets, and academic papers. It covers multiple programming languages and domains like sociology, biology, and computer science. This repository serves as a central reference for researchers, analysts, and developers working with network data.
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  • 2
    tslab

    tslab

    Interactive JavaScript and TypeScript programming with Jupyter

    tslab is an interactive programming environment and REPL with Jupyter for JavaScript and TypeScript users. You can write and execute JavaScript and TypeScript interactively on browsers and save results as Jupyter notebooks.
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  • 3
    Codespell

    Codespell

    Check code for common misspellings

    Codespell is a lightweight, open-source spell checker designed specifically for detecting and correcting common misspellings in source code, documentation, and text files. Unlike traditional spell checkers, Codespell is optimized for codebases, ensuring that it correctly identifies and suggests fixes for typographical errors without introducing false positives. It integrates easily into CI/CD pipelines, enabling developers to maintain clean and professional code and documentation. By...
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  • 4
    Transformers4Rec

    Transformers4Rec

    Transformers4Rec is a flexible and efficient library

    Transformers4Rec is an advanced recommendation system library that leverages Transformer models for sequential and session-based recommendations. The library works as a bridge between natural language processing (NLP) and recommender systems (RecSys) by integrating with one of the most popular NLP frameworks, Hugging Face Transformers (HF). Transformers4Rec makes state-of-the-art transformer architectures available for RecSys researchers and industry practitioners. Traditional recommendation...
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    Build Securely on Azure with Proven Frameworks

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  • 5
    Papis

    Papis

    Powerful and highly extensible command-line based document

    Papis is a powerful and highly extensible CLI document and bibliography manager. With Papis, you can search your library for books and papers, add documents and notes, import and export to and from other formats, and much much more. Papis uses a human-readable and easily hackable .yaml file to store each entry's bibliographical data. It strives to be easy to use while providing a wide range of features. And for those who still want more, Papis makes it easy to write scripts that extend its...
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  • 6
    Siddhi Core Libraries

    Siddhi Core Libraries

    Stream Processing and Complex Event Processing Engine

    ... to various endpoints in real time. Agile development experience with SQL-like query language and graphical drag-and-drop editor supporting event simulation. Lightweight runtime that can natively run on Kubernetes, Docker, VM, or bare metal, and embedded in any Java or Python application. Scalable, and highly available distributed event processing on Kubernetes, with NATS Streaming and Siddhi Kubernetes Operator.
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  • 7
    Graphtage

    Graphtage

    A semantic diff utility and library for tree-like files such as JSON

    Graphtage is a command-line utility and underlying library for semantically comparing and merging tree-like structures, such as JSON, XML, HTML, YAML, plist, and CSS files. Its name is a portmanteau of “graph” and “graftage”, the latter being the horticultural practice of joining two trees together such that they grow as one. Graphtage performs an analysis on an intermediate representation of the trees that is divorced from the filetypes of the input files. This means, for example, that you...
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  • 8
    EasyAuth

    EasyAuth

    Create a centralized Authentication and Authorization token server

    Create a centralized Authentication and Authorization token server. Easily secure FastAPI endpoints based on Users, Groups, Roles or Permissions with very little database usage. Centralized Auth - Single location for Users & Permissions to share across apps. Granular Endpoint Security - Verify user identity, and define explicitly who and what each user or group of users may access. Admin GUI - easy management of users, permissions, tokens, OAuth, and more! Advanced JWT - Token Based Client...
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  • 9
    OSRFramework

    OSRFramework

    OSRFramework, the Open Sources Research Framework is a AGPLv3+ project

    OSRFramework is a GNU AGPLv3+ set of libraries developed by i3visio to perform Open Source Intelligence collection tasks. They include references to a bunch of different applications related to username checking, DNS lookups, information leaks research, deep web search, regular expressions extraction and many others. At the same time, by means of ad-hoc Maltego transforms, OSRFramework provides a way of making these queries graphically as well as several interfaces to interact with like...
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  • 10
    CTGAN

    CTGAN

    Conditional GAN for generating synthetic tabular data

    CTGAN is a collection of Deep Learning based synthetic data generators for single table data, which are able to learn from real data and generate synthetic data with high fidelity. If you're just getting started with synthetic data, we recommend installing the SDV library which provides user-friendly APIs for accessing CTGAN. The SDV library provides wrappers for preprocessing your data as well as additional usability features like constraints. When using the CTGAN library directly, you may...
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  • 11
    Apprise

    Apprise

    Apprise - Push Notifications that work with just about every platform!

    Take advantage of Apprise through your network with a user-friendly API. Apprise API was designed to easily fit into existing (and new) eco-systems that are looking for a simple notification solution. There is a small built-in Configuration Manager that can be optionally accessed through your web browser allowing you to create and save as many configurations as you'd like. Each configuration is differentiated by a unique {KEY} that you decide on. Once you've saved your configuration, you'll...
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  • 12
    Flask-Limiter

    Flask-Limiter

    Rate Limiting extension for Flask

    Flask-Limiter provides rate-limiting features to flask applications. It allows configuring various backends to persist the rate limits, which is provided by the limits library. Sponsored by Zuplo - fully-managed API Gateway with rate limiting, authentication, and more. Add rate limiting to your API in minutes, try it at zuplo.com Test it out. The fast endpoint respects the default rate limit while the slow endpoint uses the decorated one. ping has no rate limit associated with it. By adding...
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  • 13
    Flask App Builder

    Flask App Builder

    Simple and rapid application development framework

    Simple and rapid application development framework, built on top of Flask. includes detailed security, auto CRUD generation for your models, google charts and much more. Automatic permissions lookup, based on exposed methods. Inserts on the Database all the detailed permissions possible on your application. Public (no authentication needed) and Private permissions. Role-based permissions. Authentication support for OpenID, Database and LDAP. Support for self-user registration. Automatic,...
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  • 14
    Mythril

    Mythril

    Security analysis tool for EVM bytecode. Supports smart contracts

    Mythril is a security analysis tool for EVM bytecode. It detects security vulnerabilities in smart contracts built for Ethereum, Hedera, Quorum, Vechain, Roostock, Tron and other EVM-compatible blockchains. It uses symbolic execution, SMT solving and taint analysis to detect a variety of security vulnerabilities. It's also used (in combination with other tools and techniques) in the MythX security analysis platform. If you are a smart contract developer, we recommend using MythX tools which...
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  • 15
    django-split-settings

    django-split-settings

    Organize Django settings into multiple files and directories

    Organize Django settings into multiple files and directories. Easily override and modify settings. Use wildcards in settings file paths and mark settings files as optional. Managing Django’s settings might be tricky. There are severals issues which are encountered by any Django developer along the way. First one is caused by the default project structure. Django clearly offers us a single settings.py file. It seams reasonable at the first glance. And it is actually easy to use just after the...
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  • 16
    django-organizations

    django-organizations

    Multi-user accounts for Django projects

    Separate individual user identity from accounts and subscriptions. Django Organizations adds user-managed, multi-user groups to your Django project. Use Django Organizations whether your site needs organizations that function like social groups or multi-user account objects to provide account and subscription functionality beyond the individual user. Works with your existing user model, whether django.contrib.auth or a custom model. No additional user or authentication functionality is...
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  • 17
    Django Wiki

    Django Wiki

    A wiki system with complex functionality for simple integration

    A wiki system with complex functionality for simple integration and a superb interface. Store your knowledge with style: Use django models. Readability, however, is emphasized above all else. A Markdown-formatted document should be publishable as-is, as plain text, without looking like it's been marked up with tags or formatting instructions. While Markdown's syntax has been influenced by several existing text-to-HTML filters -- including Setext, atx, Textile, reStructuredText, Grutatext,...
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  • 18
    django-viewflow

    django-viewflow

    Reusable workflow library for Django

    Viewflow is a lightweight reusable workflow library that helps to organize people collaboration business logic in Django applications. In conjunction with Django-material, they could be used as the framework to build ready-to-use business applications in minutes. Django web framework solves only technical problems related to the client-server interaction on top of the stateless HTTP protocol. Model-View-Template separation pattern helps to maintain simple CRUD-based logic. Viewflow is the...
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  • 19
    Opacus

    Opacus

    Training PyTorch models with differential privacy

    Opacus is a library that enables training PyTorch models with differential privacy. It supports training with minimal code changes required on the client, has little impact on training performance, and allows the client to online track the privacy budget expended at any given moment. Vectorized per-sample gradient computation that is 10x faster than micro batching. Supports most types of PyTorch models and can be used with minimal modification to the original neural network. Open source,...
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  • 20
    Lightweight' GAN

    Lightweight' GAN

    Implementation of 'lightweight' GAN, proposed in ICLR 2021

    Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contribution of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before...
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  • 21
    Tiny CUDA Neural Networks

    Tiny CUDA Neural Networks

    Lightning fast C++/CUDA neural network framework

    ... memory in its default configuration. It will likely only work on an RTX 3090, an RTX 2080 Ti, or high-end enterprise GPUs. Lower-end cards must reduce the n_neurons parameter or use the CutlassMLP (better compatibility but slower) instead. tiny-cuda-nn comes with a PyTorch extension that allows using the fast MLPs and input encodings from within a Python context. These bindings can be significantly faster than full Python implementations; in particular for the multiresolution hash encoding.
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  • 22
    Imagen - Pytorch

    Imagen - Pytorch

    Implementation of Imagen, Google's Text-to-Image Neural Network

    Implementation of Imagen, Google's Text-to-Image Neural Network that beats DALL-E2, in Pytorch. It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior...
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  • 23
    PyG

    PyG

    Graph Neural Network Library for PyTorch

    PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data. It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support,...
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  • 24
    AWS Neuron

    AWS Neuron

    Powering Amazon custom machine learning chips

    AWS Neuron is a software development kit (SDK) for running machine learning inference using AWS Inferentia chips. It consists of a compiler, run-time, and profiling tools that enable developers to run high-performance and low latency inference using AWS Inferentia-based Amazon EC2 Inf1 instances. Using Neuron developers can easily train their machine learning models on any popular framework such as TensorFlow, PyTorch, and MXNet, and run it optimally on Amazon EC2 Inf1 instances. You can...
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  • 25
    AWS Deep Learning Containers

    AWS Deep Learning Containers

    A set of Docker images for training and serving models in TensorFlow

    AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference,...
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