Open Source Python Library Management Software
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Python Library Management Software
View 83 business solutionsBrowse free open source Python Library Management Software and projects below. Use the toggles on the left to filter open source Python Library Management Software by OS, license, language, programming language, and project status.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Keep company data safe with Chrome EnterpriseMake AI work your way with Chrome Enterprise. Block unapproved sites and set custom data controls that align with your company's policies.
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Zero Install is a decentralised cross-distribution software installation system. Create one package that works everywhere! With dependency handling and automatic updates, full support for shared libraries, and integration with native package managers
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Archivematica
Free and open-source digital preservation system
Archivematica is a web- and standards-based, open-source application which allows your institution to preserve long-term access to trustworthy, authentic, and reliable digital content. Our target users are archivists, librarians, and anyone working to preserve digital objects. You are free to copy, modify, and distribute Archivematica with attribution under the terms of the AGPLv3 license. Archivematica is an open-source application based on recognized standards that makes it possible to preserve long-term access to your institution's digital content. Archivematica is a set of free software tools that allow the user to process digital objects from the moment they are entered into the system until their publication according to the ISO-OAIS functional model. The user can monitor and control the ingestion and preservation of micro-services through the control panel. Archivematica uses standards such as METS, PREMIS, Dublin Core, and the BagIt specification. -
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Stanza
Stanford NLP Python library for many human languages
Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza brings state-of-the-art NLP models to languages of your choosing. Stanza is a Python natural language analysis package. It contains tools, which can be used in a pipeline, to convert a string containing human language text into lists of sentences and words, to generate base forms of those words, their parts of speech and morphological features, to give a syntactic structure dependency parse, and to recognize named entities. The toolkit is designed to be parallel among more than 70 languages, using the Universal Dependencies formalism. Stanza is built with highly accurate neural network components that also enable efficient training and evaluation with your own annotated data. -
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PyTorch GAN Zoo
A mix of GAN implementations including progressive growing
PyTorch GAN Zoo is a comprehensive open research toolbox designed for experimenting with and developing Generative Adversarial Networks (GANs) using PyTorch. The project provides modular implementations of popular GAN architectures, including Progressive Growing of GANs (PGAN), DCGAN, and an experimental StyleGAN version. It is built to support both researchers and developers who want to train, evaluate, and extend GANs efficiently across diverse datasets such as CelebA-HQ, FashionGen, DTD, and CIFAR-10. In addition to core GAN training, the repository includes tools for model evaluation, such as Inception Score and SWD metrics, as well as advanced features like GDPP for diverse generation and AC-GAN conditioning for class-specific synthesis. The framework also supports “inspirational generation,” enabling style or content transfer from reference images through pre-trained models. -
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VulnX
Intelligent Bot, Shell can achieve automatic injection
vulnx, an intelligent Bot, Shell can achieve automatic injection, and help researchers detect security vulnerabilities in CMS systems. It can perform a quick CMS security detection, information collection (including sub-domain name, IP address, country information, organizational information and time zone, etc.), and vulnerability scanning. Vulnx is An Intelligent Bot Auto Shell Injector that detects vulnerabilities in multiple types of Cms, fast cms detection, information gathering, and vulnerability scanning of the target like subdomains, IP addresses, country, org, timezone, region, and more. Instead of injecting each and every shell manually as all the other tools do, VulnX analyses the target website checking the presence of a vulnerability if so the shell will be Injected by searching URLs with the dorks Tool. Detects CMS (wordpress, joomla, prestashop, drupal, opencart, magento, lokomedia). -
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moebinv
C++ libraries for manipulations in non-Euclidean geometry
These are two C++ libraries for symbolic, numeric and graphical manipulations in non-Euclidean geometry. There is GUI which allows to interact with these libraries by mouse clicks. On a dipper level the first library Cycle implements basic operations on cycles (quadrics) through FSCc construction. The second library Figure operates on ensembles of cycles connected by Moebius-invariant relations, e.g. orthogonality. Both libraries are based on the Clifford algebra capacities of the GiNaC computer algebra system (http://ginac.de). Besides C++ libraries there is a Python wrapper, which can be used in interactive mode (https://codeocean.com/capsule/7952650/). Both libraries work in arbitrary dimensions and signatures of metric. Additionally, there are some 2D/3D-specific routines including a visualisation to PostScript files through Asymptote (http://asymptote.sourcefourge.net) software. The source is written in literate programming NoWeb. -
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AllenNLP
An open-source NLP research library, built on PyTorch
AllenNLP makes it easy to design and evaluate new deep learning models for nearly any NLP problem, along with the infrastructure to easily run them in the cloud or on your laptop. AllenNLP includes reference implementations of high quality models for both core NLP problems (e.g. semantic role labeling) and NLP applications (e.g. textual entailment). AllenNLP supports loading "plugins" dynamically. A plugin is just a Python package that provides custom registered classes or additional allennlp subcommands. There is ecosystem of open source plugins, some of which are maintained by the AllenNLP team here at AI2, and some of which are maintained by the broader community. AllenNLP will automatically find any official AI2-maintained plugins that you have installed, but for AllenNLP to find personal or third-party plugins you've installed, you also have to create either a local plugins file named .allennlp_plugins in the directory where you run the allennlp command. -
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Brain Tokyo Workshop
Experiments and code from Google Brain’s Tokyo research workshop
The Brain Tokyo Workshop repository hosts a collection of research materials and experimental code developed by the Google Brain team based in Tokyo. It showcases a variety of cutting-edge projects in artificial intelligence, particularly in the areas of neuroevolution, reinforcement learning, and model interpretability. Each project explores innovative approaches to learning, prediction, and creativity in neural networks, often through unconventional or biologically inspired methods. The repository includes implementations, experimental data, and supporting research papers that accompany published studies. Notable works such as Weight Agnostic Neural Networks and Neuroevolution of Self-Interpretable Agents highlight the team’s exploration of how AI can learn more efficiently and transparently. Overall, this repository serves as an open research hub for sharing ideas and advancing the understanding of intelligent systems. -
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DIG
A library for graph deep learning research
The key difference with current graph deep learning libraries, such as PyTorch Geometric (PyG) and Deep Graph Library (DGL), is that, while PyG and DGL support basic graph deep learning operations, DIG provides a unified testbed for higher level, research-oriented graph deep learning tasks, such as graph generation, self-supervised learning, explainability, 3D graphs, and graph out-of-distribution. If you are working or plan to work on research in graph deep learning, DIG enables you to develop your own methods within our extensible framework, and compare with current baseline methods using common datasets and evaluation metrics without extra efforts. It includes unified implementations of data interfaces, common algorithms, and evaluation metrics for several advanced tasks. Our goal is to enable researchers to easily implement and benchmark algorithms. -
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Newspaper3k
News, full-text, and article metadata extraction in Python 3
Inspired by requests for its simplicity and powered by lxml for its speed. Newspaper is an amazing python library for extracting & curating articles. Newspaper delivers Instapaper style article extraction. Newspaper is a Python3 library! If you are certain that an entire news source is in one language, go ahead and use the same api. Works in 10+ languages, English, Chinese, German, Arabic, and more! On python3 you must install newspaper3k, not newspaper. newspaper is our python2 library. Although installing newspaper is simple with pip, you will run into fixable issues if you are trying to install on ubuntu. Source objects are an abstraction of online news media websites like CNN or ESPN. You can initialize them in two different ways. Building a Source will extract its categories, feeds, articles, brand, and description for you. You may also provide configuration parameters like language, browser_user_agent, and etc seamlessly. -
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nanoGPT
The simplest, fastest repository for training/finetuning models
NanoGPT is a minimalistic yet powerful reimplementation of GPT-style transformers created by Andrej Karpathy for educational and research use. It distills the GPT architecture into a few hundred lines of Python code, making it far easier to understand than large, production-scale implementations. The repo is organized with a training pipeline (dataset preprocessing, model definition, optimizer, training loop) and inference script so you can train a small GPT on text datasets like Shakespeare or custom corpora. It emphasizes readability and clarity: the training loop is cleanly written, and the code avoids heavy abstractions, letting students follow the architecture step by step. While simple, it can still train non-trivial models on modern GPUs and generate coherent text. The project has become widely used in tutorials, courses, and experiments for people learning how transformers work under the hood. -
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This project is intended to provide code to be used with MySQL and Python to create a database of major league baseball game events which are freely provided by the mlb.com Gameday application. Older version also support creating a retrosheet.org database but that is no longer supported. All major and minor league pitch location and game statistic data can be downloaded using BBOS. Installation Videos! Part 1: http://youtu.be/rnv2VLcG-eI Part 2: http://youtu.be/eFudbMWHNlQ Special thanks to Wells Oliver for the code for downloading Retrosheet files. And the Chadwick project for its Retrosheet tools. https://sourceforge.net/projects/chadwick/?source=recommended
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xrayutilities
a package with useful scripts for X-ray diffraction physicists
xrayutilities is a python package used to analyze x-ray diffraction data. It can support with performing diffraction experiments and used for common steps in the data analysis. It can read experimental data from several data formats (spec, edf, xrdml, ...); convert them to reciprocal space for arbitrary goniometer geometries and different detector systems (point, linear as well as area detectors); for further processing the data can be gridded (transformed to a regular grid). More detailed description as well as documentation can be found at webpage http://xrayutilities.sourceforge.io/. Downloads for windows can be found on http://pypi.python.org/pypi/xrayutilities Development is performed on github: https://github.com/dkriegner/xrayutilities -
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BibteXML is a bibliography schema for XML that expresses the content model of BibTeX – the bibliographic system for use with LaTeX. Stylesheets and conversion tools are provided.
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ACORBA
Automated approach to measure root tip angles of Arabidopsis thaliana
Gravitropic response is studied in most of the laboratories working with Arabidopsis thaliana, for example, to detect new phenotypes in mutants. However, manual analysis of images and microscopy data are known to be subjected to human bias. This is particularly the case for manual measurements of root bending as the angle is set subjectively. In this context, it is essential to develop and use automated or semi-automated image analysis to produce faster, reproducible, and unbiased data. In this context, we developped ACORBA (Automatic Calculation Of Root Bending Angles), a fully automated software to measure root bending angle over time. -
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fb2combiner
This program allows embedding books in fb2 format in one, super-book.
Fb2Combiner builds a collection of fb2-formatted books in one container (also in fb2 format). Each book is embedded as a chapter. -
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Libro
An interactive program for statistical analysis of texts
A cross-platform text analysis program written in Python and Free Pascal/Lazarus which scans a whole text file (in plain text, HTML, EPUB, or ODT formats) and ranks all used words according to frequency, performing a quantitative analysis of the text using Shannon-Weaver information statistic and Zipf power law function. It counts words, sentences, chars, spaces, and syllables. Also computes readability indexes (Gunning-Fog, Coleman-Liau, Automated Readability Index (ARI), SMOG grade, Flesch–Kincaid grade level and Flesch Reading Ease). -
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C++, Matlab and Python library for Hidden-state Conditional Random Fields. Implements 3 algorithms: LDCRF, HCRF and CRF. For Windows and Linux, 32- and 64-bits. Optimized for multi-threading. Works with sparse or dense input features.
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PS-Drone
Programming a Parrot AR.Drone 2.0 with Python - The Easy Way
The PS-Drone-API is a full featured SDK, written in and for Python, for Parrot's AR.Drone 2.0. It was designed to be easy to learn, but it offers the full set of the possibilities of the AR.Drone 2.0, including Sensor-Data (aka NavData), Configuration and full Video-support. The video function is not restricted to mere viewing, it is also possible to analyze video images data using OpenCV2. Obviously, the PS-Drone is perfect for teaching purposes; however, even the requirements for professional purposes can be satisfied. PS-Drone comes with a tutorial, explaining its most important commands and the drone's most important sensor values. The examples are easy to understand for people with little programming experience. A full list of commands and a description of all sensor data is available in a detailed documentation. It took several months to create PS-Drone, so it would be nice to get some donations for further development (e.g. Parrot's Bebop) and as a appreciation. -
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Acoustic Research Tool (ART)
Acoustic Simulation Library for Frequency and Time Domain Simulations.
ART is a flexible simulation framework for wind instruments. It includes a growing library of modelling elements. So far bore discontinuities, branches, tone holes, cylindrical and conical tubes, Bessel horns and bent tubes are available for frequency domain modelling. In the time domain generic bidirectional propagation elements, scattering elements, fractional delays, convolution with reflection functions and general z-domain networks are available and can be described using MuParserX expressions. Cylindrical and conical ducts can also be defined based on their geometry. Available models and their parameters can be enumerated and combined to form simulators for complex acoustical structures. Parameters can be specified symbolically by expressions containing other parameter values or global variables. Dependencies between parameters are resolved at run time. However, MuParserX expressions are compiled at design time. Zero-delay loops are detected and reported. -
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Python/FEniCS Examples
phase-field simulation and other examples with Python/FEniCS
The main goal of this project was developing phase-field simulations of lithium dendrite growth with FEniCS programmed in Python. The problem was based in the grand potential-based model of Zijian Hong and Venkatasubramanian Viswanathan (https://doi.org/10.1021/acsenergylett.8b01009) . Some simpler examples were developed before for a first approach with FEniCS: heat equation and combustion model. -
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AngelReader
An E-book, Audio-book, & Library Loader in One Application
AngelReader: A minimalist but powerful GUI application that has the capacity to load [1] E-books in plain text format with the least use of both software and hardware resources. It can also load [2] Audio-books with the basic functions of play, stop, pause, and resume with the same minimalist economy that doesn't hog computer resources. When used in integration with the AngelReader Library Selector, it can function as a mini library management system for books in electronic formats. It's in fact three apps integrated into one intuitively portable, cross platform, robust software. The app can be useful for either classroom or office environment; for personal or commercial use; for general learning or access to practical information. -
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Python module for reading and writing MARC records in both transport (z39.2) and plain-text mnemonic formats. Also includes simple command-line tools for translation between these formats.
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Python Console Library Project
Console functions
Compendium of console functions for Python (similar to BC conio.h) Actually: atof(s): btoi(ch): btos(ch): charfilter(ch): clrscr(n=150): cmp(a, b): finput(b=""): getarrow(): getch(): gotoxy(x=0,y=0): imput(b=""): ink(x=7): isint(x=0): islin (): iswin (): nceil(x, d=0): nfloor(x, d=0): ninput(b=""): noalpha(s="c4as."): nround(x, d=0): paper(x=0): pause(n=0): putchar(ch): putch(ch): val(s): -
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SimpleElastix
Medical Image Registration Library
SimpleElastix is an extension of SimpleITK that comes with the elastix C++ image registration library. This makes state-of-the-art medical image registration really easy to do in languages like Python, Java, C# and R.
