Search Results for "software development" - Page 12
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Showing 3600 open source projects for "software development"
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Cython
The most widely used Python to C compiler
Cython is an optimizing static compiler for both the Python programming language and the extended Cython programming language (based on Pyrex). It makes writing C extensions for Python as easy as Python itself. Write Python code that calls back and forth from and to C or C++ code natively at any point. Easily tune readable Python code into plain C performance by adding static type declarations, also in Python syntax. Use combined source code level debugging to find bugs in your Python,... -
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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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PyObjC
The Python <-> Objective-C Bridge with bindings for macOS frameworks
PyObjC is a Python-Objective-C bridge that allows Python scripts to interact with macOS Cocoa libraries. It enables developers to write native macOS apps entirely in Python by accessing Objective-C APIs. -
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Toot
toot - Mastodon CLI & TUI
Toot is a CLI and TUI tool for interacting with Mastodon instances from the command line. -
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pywinauto
Windows GUI Automation with Python (based on text properties)
pywinauto is a set of Python modules to automate the Microsoft Windows GUI. At its simplest it allows you to send mouse and keyboard actions to Windows dialogs and controls, but it has support for more complex actions like getting text data. -
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PyExcelerate
Accelerated Excel XLSX Writing Library for Python 2/3
Accelerated Excel XLSX writing library for Python. PyExcelerate is a Python for writing Excel-compatible XLSX spreadsheet files, with an emphasis on speed. -
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ipytest
Pytest in IPython notebooks
ipytest allows you to run Pytest in Jupyter notebooks. ipytest aims to give access to the full pytest experience and to make it easy to transfer tests out of notebooks into separate test files. -
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Haiku
JAX-based neural network library
Haiku is a library built on top of JAX designed to provide simple, composable abstractions for machine learning research. Haiku is a simple neural network library for JAX that enables users to use familiar object-oriented programming models while allowing full access to JAX’s pure function transformations. Haiku is designed to make the common things we do such as managing model parameters and other model state simpler and similar in spirit to the Sonnet library that has been widely used... -
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tvm
Open deep learning compiler stack for cpu, gpu, etc.
Apache TVM is an open source machine learning compiler framework for CPUs, GPUs, and machine learning accelerators. It aims to enable machine learning engineers to optimize and run computations efficiently on any hardware backend. The vision of the Apache TVM Project is to host a diverse community of experts and practitioners in machine learning, compilers, and systems architecture to build an accessible, extensible, and automated open-source framework that optimizes current and emerging... -
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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Eric Integrated Development Environment
Python Development Environment with all batteries included
Eric is a Python IDE written using PyQt and QScintilla. It provides various features such as any number of open editors, an integrated (remote) debugger, project management facilities, unit test, refactoring and much more. -
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PydanticAI
Agent Framework / shim to use Pydantic with LLMs
When I first found FastAPI, I got it immediately. I was excited to find something so innovative and ergonomic built on Pydantic. Virtually every Agent Framework and LLM library in Python uses Pydantic, but when we began to use LLMs in Pydantic Logfire, I couldn't find anything that gave me the same feeling. PydanticAI is a Python Agent Framework designed to make it less painful to build production-grade applications with Generative AI. Built by the team behind Pydantic (the validation layer... -
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TorchQuantum
A PyTorch-based framework for Quantum Classical Simulation
A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers. Researchers on quantum algorithm design, parameterized quantum circuit training, quantum optimal control, quantum machine learning, and quantum neural networks. Dynamic computation graph, automatic gradient computation, fast GPU support, batch model terrorized processing. -
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Slack Machine
A simple, yet powerful and extendable Slack bot
Slack Machine is a simple, yet powerful and extendable Slack bot framework. More than just a bot, Slack Machine is a framework that helps you develop your Slack workspace into a ChatOps powerhouse. Slack Machine is built with an intuitive plugin system that lets you build bots quickly but also allows for easy code organization. A plugin can look as simple as this: -
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attrs
Python Classes Without Boilerplate
attrs is a Python package that lets you write classes without all the usual drudgery. Its ultimate goal is to help you write concise and correct software without slowing down your code. attrs provides a class decorator and a means to declaratively define the attributes on that class. This results in a concise and explicit overview of the class's attributes, a human-readable __repr__, a complete set of comparison methods and more, all without having to repetitively write dull boilerplate code... -
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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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asyncpg
A fast PostgreSQL Database Client Library for Python/asyncio
asyncpg is a high-performance PostgreSQL client library designed for Python's asyncio framework. It offers a clean and efficient implementation of the PostgreSQL server binary protocol, enabling developers to execute database operations asynchronously. This approach allows for scalable and responsive applications that can handle numerous concurrent database connections. -
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ChatDBG
ChatDBG - AI-assisted debugging. Uses AI to answer 'why'
ChatDBG is an AI-assisted debugging tool that integrates large language models into standard debuggers like pdb, lldb, and gdb. It allows developers to engage in a dialog with the debugger, asking open-ended questions about their program's behavior, and provides error diagnoses and suggested fixes. -
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Pydantic-Core
Core validation logic for pydantic written in rust
pydantic-core is the Rust-based core validation logic for Pydantic, a widely used data validation library in Python. It offers significant performance improvements over its predecessor, enabling faster and more efficient data parsing and validation. -
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CRUFT
Allows you to maintain all the necessary cruft for building projects
cruft allows you to maintain all the necessary boilerplate for packaging and building projects separate from the code you intentionally write. Fully compatible with existing Cookiecutter templates. Cruft is a tool built on top of CookieCutter that helps maintain the boilerplate code for packaging and building projects separately from the intentional code. It ensures that projects remain up-to-date with their templates. -
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Semantix
Non-Pydantic, Non-JSON Schema, efficient AutoPrompting
Semantix empowers developers to infuse meaning into their code through enhanced variable typing (semantic typing). By leveraging the power of large language models (LLMs) behind the scenes, Semantix transforms ordinary functions into intelligent, context-aware operations without explicit LLM calls. -
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libtmux
Python API / wrapper for tmux
libtmux is a typed Python library that provides a wrapper for interacting programmatically with tmux, a terminal multiplexer. You can use it to manage tmux servers, sessions, windows, and panes. Additionally, libtmux powers tmuxp, a tmux workspace manager. libtmux builds upon tmux’s target and formats to create an object mapping to traverse, inspect and interact with live tmux sessions. -
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Jupyter Notebook Tools for Sphinx
Sphinx source parser for Jupyter notebooks
nbsphinx is a Sphinx extension that provides a source parser for *.ipynb files. Custom Sphinx directives are used to show Jupyter Notebook code cells (and of course their results) in both HTML and LaTeX output. Un-evaluated notebooks – i.e. notebooks without stored output cells – will be automatically executed during the Sphinx build process. -
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SENAITE LIMS
SENAITE Meta Package
SENAITE is a beautiful trigonal, oil-green to greenish-black crystal, with almost the hardness of a diamond. Although the crystal is described with a complex formula, it still has clear and straight shapes. Therefore, it reflects nicely the complexity of the LIMS, while providing a modern, intuitive, and friendly UI/ UX. Amongst other functionalities, SENAITE comes with highly-customizable workflows to drive users through the analytical process, easy-to-use UI for data registration,... -
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Awesome Fraud Detection Research Papers
A curated list of data mining papers about fraud detection
A curated list of data mining papers about fraud detection from several conferences. -
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Deepchecks
Test Suites for validating ML models & data
Deepchecks is the leading tool for testing and for validating your machine learning models and data, and it enables doing so with minimal effort. Deepchecks accompany you through various validation and testing needs such as verifying your data’s integrity, inspecting its distributions, validating data splits, evaluating your model and comparing between different models. While you’re in the research phase, and want to validate your data, find potential methodological problems, and/or validate...
