Showing 675 open source projects for "python data analysis"

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  • 1
    WTForms

    WTForms

    A flexible forms validation and rendering library for Python

    WTForms is a flexible forms validation and rendering library for Python web development. It can work with whatever web framework and template engine you choose. It supports data validation, CSRF protection, internationalization (I18N), and more. There are various community libraries that provide closer integration with popular frameworks. WTForms is designed to work with any web framework and template engine. There are a number of community-provided libraries that make integrating...
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  • 2
    Mobly

    Mobly

    E2E test framework for tests with complex environment requirements

    Mobly is a Python-based test framework that specializes in supporting test cases that require multiple devices, complex environments, or custom hardware setups. P2P data transfer between two devices. Conference calls across three phones. Wearable device interacting with a phone. Internet-Of-Things devices interacting with each other. Testing RF characteristics of devices with special equipment. Testing LTE network by controlling phones, base stations, and eNBs. Mobly can support many different...
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  • 3
    Django OAuth Toolkit

    Django OAuth Toolkit

    OAuth2 goodies for the Djangonauts!

    Django OAuth Toolkit can help you by providing, out of the box, all the endpoints, data, and logic needed to add OAuth2 capabilities to your Django projects. Django OAuth Toolkit makes extensive use of the excellent OAuthLib, so that everything is rfc-compliant. OAuth is an open standard for access delegation, commonly used as a way for Internet users to grant websites or applications access to their information on other websites but without giving them the passwords. Django is a high-level...
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  • 4
    redshift_connector

    redshift_connector

    Amazon Redshift connector for Python

    redshift_connector is the Amazon Redshift connector for Python. Easy integration with pandas and numpy, as well as support for numerous Amazon Redshift-specific features help you get the most out of your data. redshift_connector integrates with various open-source projects to provide an interface to Amazon Redshift. Please open an issue with our project to request new integrations or get support for a redshift_connector issue seen in an existing integration. Following the DB-API specification...
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  • 5
    peewee

    peewee

    A small, expressive orm, which supports postgresql, mysql and sqlite

    .... Peewee handles converting between pythonic values and those used by the database, so you can use Python types in your code without having to worry. The real strength of our database is in how it allows us to retrieve data through queries. Relational databases are excellent for making ad-hoc queries. Peewee provides a magical helper fn(), which can be used to call any SQL function.
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  • 6
    Ray

    Ray

    A unified framework for scalable computing

    ... model and reduce training costs by using the latest optimization algorithms. Deploy your machine learning models at scale with Ray Serve, a Python-first and framework agnostic model serving framework. Scale reinforcement learning (RL) with RLlib, a framework-agnostic RL library that ships with 30+ cutting-edge RL algorithms including A3C, DQN, and PPO. Easily build out scalable, distributed systems in Python with simple and composable primitives in Ray Core.
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  • 7
    Boltons

    Boltons

    250+ constructs, recipes, and snippets which extend the Python library

    Boltons is a set of pure-Python utilities in the same spirit as, and yet conspicuously missing from, the standard library. Due to the nature of utilities, application developers might want to consider other integration options. Boltons is tested against Python 2.6-2.7, 3.4-3.7, and PyPy. The majority of boltons strive to be “good enough” for a wide range of basic uses, leaving advanced use cases to Python’s myriad specialized 3rd-party libraries. In many cases the respective boltons module...
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  • 8
    txtai

    txtai

    Build AI-powered semantic search applications

    txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications. Traditional search systems use keywords to find data. Semantic search applications have an understanding of natural language and identify results that have the same meaning, not necessarily the same keywords. Backed by state-of-the-art machine learning models, data is transformed into vector representations for search (also known as embeddings). Innovation is happening at a rapid pace...
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  • 9
    Django Rules

    Django Rules

    Awesome Django authorization, without the database

    ..., anything really. A good Django citizen. Seamless integration with Django views, templates and the Admin for testing for object-level permissions. Efficient and smart. No need to mess around with a database to figure out whether John really wrote that book. Simple. Dive in the code. You'll need 10 minutes to figure out how it works. Powerful. rules comes complete with advanced features, such as invocation context and storage for arbitrary data, skipping evaluation of predicates.
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  • 10
    RecBole

    RecBole

    A unified, comprehensive and efficient recommendation library

    A unified, comprehensive and efficient recommendation library. We design general and extensible data structures to unify the formatting and usage of various recommendation datasets. We implement more than 100 commonly used recommendation algorithms and provide formatted copies of 28 recommendation datasets. We support a series of widely adopted evaluation protocols or settings for testing and comparing recommendation algorithms. RecBole is developed based on Python and PyTorch for reproducing...
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  • 11
    Albumentations

    Albumentations

    Fast image augmentation library and an easy-to-use wrapper

    Albumentations is a computer vision tool that boosts the performance of deep convolutional neural networks. Albumentations is a Python library for fast and flexible image augmentations. Albumentations efficiently implements a rich variety of image transform operations that are optimized for performance, and does so while providing a concise, yet powerful image augmentation interface for different computer vision tasks, including object classification, segmentation, and detection. Albumentations...
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  • 12
    PyTorch Geometric

    PyTorch Geometric

    Geometric deep learning extension library for PyTorch

    ... of functionality of PyTorch Geometric to other packages, which needs to be additionally installed. These packages come with their own CPU and GPU kernel implementations based on C++/CUDA extensions. We do not recommend installation as root user on your system python. Please setup an Anaconda/Miniconda environment or create a Docker image. We provide pip wheels for all major OS/PyTorch/CUDA combinations.
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  • 13
    Otter-Grader

    Otter-Grader

    A Python and R autograding solution

    Otter Grader is a light-weight, modular open-source autograder developed by the Data Science Education Program at UC Berkeley. It is designed to work with classes at any scale by abstracting away the autograding internals in a way that is compatible with any instructor's assignment distribution and collection pipeline. Otter supports local grading through parallel Docker containers, grading using the autograder platforms of 3rd party learning management systems (LMSs), the deployment...
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  • 14
    OpenWPM

    OpenWPM

    A web privacy measurement framework

    OpenWPM is a web privacy measurement framework that makes it easy to collect data for privacy studies on a scale of thousands to millions of websites. OpenWPM is built on top of Firefox, with automation provided by Selenium. It includes several hooks for data collection. Check out the instrumentation section below for more details. OpenWPM is tested on Ubuntu 18.04 via TravisCI and is commonly used via the docker container that this repo builds, which is also based on Ubuntu. Although we don't...
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  • 15
    Avalanche

    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...
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  • 16
    Full Stack FastAPI and PostgreSQL

    Full Stack FastAPI and PostgreSQL

    Full stack, modern web application generator

    Generate a backend and frontend stack using Python, including interactive API documentation. Production ready Python web server using Uvicorn and Gunicorn. Very high performance, on par with NodeJS and Go (thanks to Starlette and Pydantic). Great editor support. Completion everywhere. Less time debugging. Designed to be easy to use and learn. Less time reading docs. Minimize code duplication. Multiple features from each parameter declaration. Get production-ready code. With automatic...
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  • 17
    FastUI

    FastUI

    Build better UIs faster

    FastUI is a library that lets developers build interactive user interfaces for FastAPI applications using Pydantic models. It automatically generates frontend components based on data schemas and endpoint logic, reducing the need for manual UI development. Designed to be type-safe, reactive, and fast, FastUI streamlines the creation of web dashboards, admin panels, and internal tools within a FastAPI backend.
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  • 18
    Django Bootstrap Modal Forms

    Django Bootstrap Modal Forms

    A Django plugin for creating AJAX driven forms in Bootstrap modal

    A Django plugin for creating AJAX-driven forms in Bootstrap modal. This repository includes Dockerfile and docker-compose.yml files so you can easily setup and start to experiment with django-bootstrap-modal-forms running inside of a container on your local machine. Any changes you make in bootstrap_modal_forms, examples and test folders are reflected in the container (see docker-compose.yml) and the data stored in the sqlite3 database are persistent even if you remove the stopped container...
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  • 19
    Flama

    Flama

    Fire up your models with the flame

    Flama is a python library which establishes a standard framework for development and deployment of APIs with special focus on machine learning (ML). The main aim of the framework is to make ridiculously simple the deployment of ML APIs, simplifying (when possible) the entire process to a single line of code. The library builds on Starlette, and provides an easy-to-learn philosophy to speed up the building of highly performant GraphQL, REST and ML APIs. Besides, it comprises an ideal solution...
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  • 20
    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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  • 21
    TurboGears

    TurboGears

    Python web framework with full-stack layer

    TurboGears is a hybrid web framework able to act both as a Full Stack framework or as a Microframework. TurboGears helps you get going fast and gets out of your way when you want it! TurboGears can be used both as a full stack framework or as a microframework in single-file mode. TurboGears 2 is built on top of the experience of several next-generation web frameworks including TurboGears 1 (of course), Django, and Rails. All of these frameworks had limitations that frustrated us, and TG2 was...
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  • 22
    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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  • 23
    DGL

    DGL

    Python package built to ease deep learning on graph

    ... want to make it easy to implement graph neural networks model family. We also want to make the combination of graph based modules and tensor based modules (PyTorch or MXNet) as smooth as possible. DGL provides a powerful graph object that can reside on either CPU or GPU. It bundles structural data as well as features for a better control. We provide a variety of functions for computing with graph objects including efficient and customizable message passing primitives for Graph Neural Networks.
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  • 24
    Prompt Declaration Language

    Prompt Declaration Language

    Prompt Declaration Language is a declarative prompt programming lang

    LLMs will continue to change the way we build software systems. They are not only useful as coding assistants, providing snipets of code, explanations, and code transformations, but they can also help replace components that could only previously be achieved with rule-based systems. Whether LLMs are used as coding assistants or software components, reliability remains an important concern. LLMs have a textual interface and the structure of useful prompts is not captured formally. Programming...
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  • 25
    Django Notebook

    Django Notebook

    Django + shell_plus + Jupyter notebooks made easy

    Django + shell_plus + Jupyter notebooks made easy. A Jupyter notebook with access to objects from the Django ORM is a powerful tool to introspect data and run ad-hoc queries. Built-in integration with the imported objects from django-extensions shell_plus. Saves the state between sessions so you don't need to remember what you did. Inheritance diagrams on any object, including ORM models.
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