Search Results for "api" - Page 2
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Showing 109 open source projects for "api"
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Flask-SocketIO
Socket.IO integration for Flask applications
Flask-SocketIO is an extension for the Flask web framework that enables real-time bi-directional communication between clients and servers using WebSockets or long-polling fallbacks, making it possible to build interactive applications like chat systems, live dashboards, and collaborative tools. It abstracts the complexities of asynchronous sockets by providing a familiar Flask-style API where developers can define event handlers that trigger on client messages, broadcast to connected users, and manage namespaces and rooms. The extension supports multiple asynchronous workers through integrations with popular async servers like eventlet or gevent, allowing scalable handling of concurrent connections. It also includes features such as session and user tracking across socket connections, JSON message support, and simple decorators to bind events to handler functions. -
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Docker SDK for Python
A Python library for the Docker Engine API
A Python library for the Docker Engine API. It lets you do anything the docker command does, but from within Python apps, run containers, manage containers, manage Swarms, etc. The latest stable version is available on PyPI. Either add docker to your requirements.txt file or install with pip. To communicate with the Docker daemon, you first need to instantiate a client. The easiest way to do that is by calling the function from_env(). -
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spaCy
Industrial-strength Natural Language Processing (NLP)
...It comes with pretrained statistical models and word vectors, convolutional neural network models, easy deep learning integration and so much more. spaCy is the fastest syntactic parser in the world according to independent benchmarks, with an accuracy within 1% of the best available. It's blazing fast, easy to install and comes with a simple and productive API. -
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FairChem
FAIR Chemistry's library of machine learning methods for chemistry
FAIRChem is a unified library for machine learning in chemistry and materials, consolidating data, pretrained models, demos, and application code into a single, versioned toolkit. Version 2 modernizes the stack with a cleaner core package and breaking changes relative to V1, focusing on simpler installs and a stable API surface for production and research. The centerpiece models (e.g., UMA variants) plug directly into the ASE ecosystem via a FAIRChem calculator, so users can run relaxations, molecular dynamics, spin-state energetics, and surface catalysis workflows with the same pretrained network by switching a task flag. Tasks span heterogeneous domains—catalysis (OC20-style), inorganic materials (OMat), molecules (OMol), MOFs (ODAC), and molecular crystals (OMC)—allowing one model family to serve many simulations. ... -
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Avalanche
End-to-End Library for Continual Learning based on PyTorch
Avalanche is an end-to-end Continual Learning library based on Pytorch, born within ContinualAI with the unique goal of providing a shared and collaborative open-source (MIT licensed) codebase for fast prototyping, training and reproducible evaluation of continual learning algorithms. Avalanche can help Continual Learning researchers in several ways. This module maintains a uniform API for data handling: mostly generating a stream of data from one or more datasets. It contains all the major CL benchmarks (similar to what has been done for torchvision). Provides all the necessary utilities concerning model training. This includes simple and efficient ways of implementing new continual learning strategies as well as a set of pre-implemented CL baselines and state-of-the-art algorithms you will be able to use for comparison! ... -
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Amazon Braket Python Schemas
A library that contains schemas for Amazon Braket
Amazon Braket Python Schemas is an open source library that contains the schemas for Braket, including intermediate representations (IR) for Amazon Braket quantum tasks and offers serialization and deserialization of those IR payloads. Think of the IR as the contract between the Amazon Braket SDK and Amazon Braket API for quantum programs. Schemas for the S3 results of each quantum task. Schemas for the device capabilities of each device. The preferred way to get Amazon Braket Python Schemas is by installing the Amazon Braket Python SDK, which will pull in the schemas. You can install from source by cloning this repository and running a pip install command in the root directory of the repository. ... -
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Anomalib
An anomaly detection library comprising state-of-the-art algorithms
Anomalib is an open-source deep learning library focused on anomaly detection and localization tasks, collecting state-of-the-art algorithms and tools under one modular framework. It provides implementations of leading anomaly detection methods drawn from current research, as well as a full set of utilities for training, evaluating, benchmarking, and deploying these models on both public and private datasets. Anomalib emphasizes flexibility and reproducibility: you can use its simple APIs to... -
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UCO3D
Uncommon Objects in 3D dataset
...The repository includes automated downloaders with checksum verification, fine-grained controls to fetch only selected modalities or super-categories, and a lightweight Python API for loading frames, geometry, and splats on demand. Metadata is indexed in SQLite for quick queries at scale, and helper builders handle alignment, undistortion, frame extraction from videos, and cropping around the object. -
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pyTermTk
Python Terminal Toolkit - a Spiced Up TUI Library
pyTermTk is a Text-based user interface library (TUI). Evolved from the discontinued project pyCuT and inspired by a mix of Qt5, GTK, and tkinter API definition with a touch of personal interpretation. -
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PyOpenCL
OpenCL integration for Python, plus shiny features
PyOpenCL is a Python wrapper for the OpenCL framework, providing seamless access to parallel computing on CPUs, GPUs, and other accelerators. It enables developers to harness the full power of heterogeneous computing directly from Python, combining Python’s ease of use with the performance benefits of OpenCL. PyOpenCL also includes convenient features for managing memory, compiling kernels, and interfacing with NumPy, making it a preferred choice in scientific computing, data analysis, and... -
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Public APIs
A collective list of free APIs
...Curated by community contributors and the team at APILayer, it serves as a centralized resource for discovering APIs across a wide range of domains, including data, machine learning, weather, entertainment, and finance. The project aims to make API exploration and integration more accessible by offering a single, organized index of open and free-to-use APIs. Developers can leverage this list to enhance their products, prototypes, or research projects without the need to build data sources from scratch. The repository’s open nature encourages contributions, allowing anyone to submit new APIs or updates through pull requests. ... -
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Kubernetes Python Client
Official Python client library for kubernetes
Official Python client library for Kubernetes. Kubernetes supports three minor releases at a time. "Support" means we expect users to be running that version in production, though we may not port fixes back before the latest minor version. For example, when v1.3 comes out, v1.0 will no longer be supported. In consistent with the Kubernetes support policy, we expect to support three GA major releases (corresponding to three Kubernetes minor releases) at a time. -
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Opacus
Training PyTorch models with differential privacy
...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, modular API for differential privacy research. Everyone is welcome to contribute. ML practitioners will find this to be a gentle introduction to training a model with differential privacy as it requires minimal code changes. Differential Privacy researchers will find this easy to experiment and tinker with, allowing them to focus on what matters. -
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Graphene
GraphQL in Python Made Easy
...GraphQL is a data query language developed internally by Facebook as an alternative to REST and ad-hoc webservice architectures. With Graphene you have all the tools you need to implement a GraphQL API in Python, with multiple integrations with different frameworks including Django, SQLAlchemy and Google App Engine. -
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Nevergrad
A Python toolbox for performing gradient-free optimization
Nevergrad is a Python library for derivative-free optimization, offering robust implementations of many algorithms suited for black-box functions (i.e. functions where gradients are unavailable or unreliable). It targets hyperparameter search, architecture search, control problems, and experimental tuning—domains in which gradient-based methods may fail or be inapplicable. The library provides an easy interface to define an optimization problem (parameter space, loss function, budget) and... -
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claude-code-transcripts
Tools for publishing transcripts for Claude Code sessions
...It is designed to make the often dense and verbose outputs from AI coding sessions easier to read, share, and archive by breaking conversations into paginated, annotated pages with navigable timelines of prompts and responses. Users can run this tool locally or fetch sessions from the Claude API, giving flexibility for individual workflows or team documentation practices. The generated HTML includes interactive navigation and can optionally be published to GitHub Gists for sharing with collaborators or embedding in other documentation. It also supports including the raw session JSON alongside the transcript for forensic or archival purposes. -
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Penzai
A JAX research toolkit to build, edit, & visualize neural networks
...The library integrates tightly with Treescope, an advanced pretty-printer for visualizing deeply nested JAX pytrees and NDArray structures. Penzai’s penzai.nn module provides a compositional, combinator-based API for building neural networks. -
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Theseus
A library for differentiable nonlinear optimization
Theseus is a library for differentiable nonlinear optimization that lets you embed solvers like Gauss-Newton or Levenberg–Marquardt inside PyTorch models. Problems are expressed as factor graphs with variables on manifolds (e.g., SE(3), SO(3)), so classical robotics and vision tasks—bundle adjustment, pose graph optimization, hand–eye calibration—can be written succinctly and solved efficiently. Because solves are differentiable, you can backpropagate through optimization to learn cost... -
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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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Selenium-python Helium
Selenium-python but lighter: Helium is the best Python library
Under the hood, Helium forwards each call to Selenium. The difference is that Helium's API is much more high-level. In Selenium, you need to use HTML IDs, XPaths and CSS selectors to identify web page elements. Helium on the other hand lets you refer to elements by user-visible labels. As a result, Helium scripts are typically 30-50% shorter than similar Selenium scripts. What's more, they are easier to read and more stable with respect to changes in the underlying web page. -
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Homemade Machine Learning
Python examples of popular machine learning algorithms
...The purpose is pedagogical: you’ll see linear regression, logistic regression, k-means clustering, neural nets, decision trees, etc., built in Python using fundamentals like NumPy and Matplotlib, not hidden behind API calls. It is well suited for learners who want to move beyond library usage to understand how algorithms operate internally—how cost functions, gradients, updates and predictions work. -
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Petastorm
Petastorm library enables single machine or distributed training
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code. Petastorm is an open-source data access library developed at Uber ATG. This library enables single machine or distributed training and evaluation of deep learning models directly from datasets in Apache Parquet format. Petastorm supports popular... -
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DeepPavlov
A library for deep learning end-to-end dialog systems and chatbots
...Use BERT and other state-of-the-art deep learning models to solve classification, NER, Q&A and other NLP tasks. DeepPavlov Agent allows building industrial solutions with multi-skill integration via API services. -
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This library helps you easily create a Python application with WhatsApp API. https://green-api.com/en/
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Yandex Music API
Non-official Python library for works with API service Index
This library provides Python interface for anyone undocumented and self-made API Yandex Music. It is compatible with Python 3.7 + and supports working with both synchronous and asyncio code. In addition to implementing a clean API, this library has a number of — high-level wrapping classes in order to make the development of customers and scripts simple and understandable. All documentation was written from scratch based on logical analysis during reverse development (reverse engineering) API.
