Open Source Python Software Development Software - Page 42
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Python Software Development Software
View 6112 business solutionsBrowse free open source Python Software Development Software and projects below. Use the toggles on the left to filter open source Python Software Development Software by OS, license, language, programming language, and project status.
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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BRAHMS is a Modular Execution Framework for dynamical systems. It knits together independently-authored software modules implementing dynamical processes into an integrated system, and supervises the deployment and execution of that system.
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Build System for Java offers an enhanced build environment that ties together deployment instructions, environment configuration and source code as a releaseable entity. A new paradigm for configuration management!
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Baby Buddy
Helps caregivers track sleep, feedings, diaper changes, and tummy time
A buddy for babies! Helps caregivers track sleep, feedings, diaper changes, tummy time and more to learn about and predict baby's needs without (as much) guesswork. A buddy to help caregivers track sleep, feedings, diaper changes, and tummy time to learn about and predict baby's needs without (as much) guess work. A demo of Baby Buddy is available on Heroku. The demo instance resets every hour. Baby Buddy is available in a variety of languages thanks to the efforts of numerous translators. Language can be set on a per-user basis from the user settings page (/user/settings/). -
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BabyAGI
Experimental framework for a self-building autonomous agent
BabyAGI is an experimental prototype framework for building self-building autonomous agents. The project became known for exploring how AI agents can manage functions, dependencies, executions, and configurations as part of a more autonomous workflow. Its newer dashboard-oriented structure provides tools for registering, updating, and managing functions through a user-friendly interface. It also supports dependency visualization so users can understand how functions relate to each other. Secret management and execution monitoring make it more practical for agent experimentation than a simple script alone. It is best understood as a research and prototyping framework for people exploring autonomous agents, tool use, and self-improving AI systems. -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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BackAnt CLI
Let your AI agent create clean, easy to maintain flask backends
BackAnt CLI is an AI-native backend scaffolding tool designed to generate production-ready Flask APIs from a JSON specification or a small set of CLI commands. Its main goal is to reduce the repetitive work involved in setting up layered backend projects by generating key application components automatically rather than forcing developers to assemble them by hand. The tool creates a structured backend architecture that includes routes, services, repositories, models, startup files, Docker Compose configurations, and CI/CD workflows, which makes it especially useful for teams that want consistency across projects. It can scaffold an entire API or extend an existing project by generating a single route or sub-route, so it supports both greenfield development and iterative expansion. BackAnt CLI is also designed to work with coding agents through an MCP server, which allows compatible AI development tools to generate and modify backend code directly from chat-driven workflows. -
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Backtrack Sampler
An easy-to-understand framework for LLM samplers
Backtrack Sampler is a framework designed for experimenting with custom sampling strategies for language models (LLMs), enabling the ability to rewind and revise generated tokens. It allows developers to create and test their own token generation strategies by providing a base structure for manipulating logits and probabilities, making it a flexible tool for those interested in fine-tuning the behavior of LLMs. -
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Bandicoot is a collections of organizing tools. These tools are CLI oriented to do batch organizing tasks.
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Barfi
A Python visual Flow Based Programming library
A Python visual Flow-Based Programming library that integrates into your existing workflow. Barfi is a Flow-Based Programming environment that provides a graphical programming interface. It is integratable into your existing Python workflows. A schema is built using barfi.Blocks. Then the schema is executed with barfi.ComputeEngine. Each barfi.Block has some properties that enable the FBP and schema building. Firstly, each Block has Input and Output interfaces that link to other Blocks. Each Block can carry an executable function, that is specified by the user. This function can access/get data from the Input interface, perform computations or calculations, and set the Output interface. In general, Barfi is an abstraction of Graphical Programming, Flow-Based Programming, or Node programming. Where the Block is synonymous to a Node, and a Link (connection) is synonymous with an Edge. There are many ways to call this, each serving a specific need or a philosophy. -
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Baselines
High-quality implementations of reinforcement learning algorithms
Unlike the other two, openai/baselines is not currently a maintained or prominent repo in the OpenAI organization (and I found no strong reference in OpenAI’s main GitHub). Historically, “baselines” repositories are often used for baseline implementations of reinforcement learning algorithms or reference models (e.g. in the RL domain). If there was an OpenAI “baselines” repo, it might have contained reference implementations for reinforcement learning or model policy baselines to compare new work against. However, I couldn’t locate an active “openai/baselines” in the latest OpenAI repos, so it may have been archived, removed, or merged into other projects. If you meant a different “baselines” (e.g. OpenAI Baselines for reinforcement learning), I can look up that specific one. -
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A component framework to develop n-tier applications in python on top of Twisted (http://twistedmatrix.com).
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The Basil project's mission is to build a parsing and modeling environment where one is able to work with, code in, integrate, and design a wide variety of computer languages.
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Baum is a Qt based GUI application framework with a built in python interpreter. Baum allows rapid creation of GUI's with simple python scripts. Programmers can re-use available python and widget library.
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BayesianOptimization
A Python implementation of global optimization with gaussian processes
BayesianOptimization is a Python library that helps find the maximum (or minimum) of expensive or unknown objective functions using Bayesian optimization. This technique is especially useful for hyperparameter tuning in machine learning, where evaluating the objective function is costly. The library provides an easy-to-use API for defining bounds and optimizing over parameter spaces using probabilistic models like Gaussian Processes. -
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The Python scripting language provides the ability to fairly easily and quickly develop applications and to control existing applications. The Be Python Components is a collection of Python modules which provide access to the underlying BeOS API.
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BeaEngine 5
BeaEngine disasm project
BeaEngine is a C library designed to decode instructions from 16-bit, 32-bit and 64-bit intel architectures. It includes standard instructions set and instructions set from FPU, MMX, SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2, VMX, CLMUL, AES, MPX, AVX, AVX2, AVX512 (VEX & EVEX prefixes), CET, BMI1, BMI2, SGX, UINTR, KL, TDX and AMX extensions. If you want to analyze malicious codes and more generally obfuscated codes, BeaEngine sends back a complex structure that describes precisely the analyzed instructions. You can use it in C/C++ (usable and compilable with Visual Studio, GCC, MinGW, DigitalMars, BorlandC, WatcomC, SunForte, Pelles C, LCC), in assembler (usable with masm32 and masm64, nasm, fasm, GoAsm) in C#, in Python3, in Delphi, in PureBasic and in WinDev. You can use it in user mode and kernel mode. -
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Beamology
Beamology: Semicom Project Management
Beamology is the leading field of project management for SuperWikia Alpha semicom codesmiths. Its residency programs offer vital resources for SuperWikia vertical environment development and utilities needed for SA-VEC certification. Beamology residents are automatically licensed to access the Transcom system. -
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Behaviour Suite Reinforcement Learning
bsuite is a collection of carefully-designed experiments
bsuite is a research framework developed by Google DeepMind that provides a comprehensive collection of experiments for evaluating the core capabilities of reinforcement learning (RL) agents. Its main goal is to identify, measure, and analyze fundamental aspects of learning efficiency and generalization in RL algorithms. The library enables researchers to benchmark their agents on standardized tasks, facilitating reproducible and transparent comparisons across different approaches. Each experiment in bsuite is meticulously designed to capture key challenges in RL, such as exploration, credit assignment, and stability. The framework supports automated logging and analysis, generating standardized output compatible with Jupyter notebooks for streamlined evaluation. It also integrates easily with existing RL libraries and can be used locally or via cloud computing platforms, including Google Cloud. -
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Belay Device
Automated Provisioning and Testing Framework
Belay Device has moved! https://github.com/BelayTechnologies/Belay-Device -
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Belkerda
a customizable number-guessing system
Belkerda is a simple Python AI program that takes a user's input, builds a log of random numbers, picks a random entry, and displays it. If it is correct, then it reenters that number back into the log several times, overwriting the original, random numbers. If it is not, however, it overwrites a lower amount of entries. -
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Benetech Human Rights Program Utility Library: Collection of utilities used by the Benetech Human Rights programming for processing human rights data in preparation for statistical analysis. Library handles DSV files, name canonicalization, binarray, et
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BentoML
Unified Model Serving Framework
BentoML simplifies ML model deployment and serves your models at a production scale. Support multiple ML frameworks natively: Tensorflow, PyTorch, XGBoost, Scikit-Learn and many more! Define custom serving pipeline with pre-processing, post-processing and ensemble models. Standard .bento format for packaging code, models and dependencies for easy versioning and deployment. Integrate with any training pipeline or ML experimentation platform. Parallelize compute-intense model inference workloads to scale separately from the serving logic. Adaptive batching dynamically groups inference requests for optimal performance. Orchestrate distributed inference graph with multiple models via Yatai on Kubernetes. Easily configure CUDA dependencies for running inference with GPU. Automatically generate docker images for production deployment. -
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An Open Source IEC 61131-3 Integrated Development Environment, providing PLCOpen SoftPLC programming, CanOpen IO's, and SVG based HMI.
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Berkeley Yacc is an LALR(1) parser generator. Berkeley Yacc has been made as compatible as possible with AT&T Yacc. Berkeley Yacc has been extended to generate Python, Perl and Java code.
