Open Source Python Software Development Software - Page 32
Sort By:
Python Software Development Software
View 5766 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.
-
Resolve Support Tickets 2x Faster with ServoDeskWhat if You Could Automate 90% of Your Repetitive Tasks in Under 30 Days? At ServoDesk, we help businesses like yours automate operations with AI, allowing you to cut service times in half and increase productivity by 25% - without hiring more staff.
-
Repair-CRMAll-In-One Solution with an Online Booking portal for automating scheduling & dispatching to ditch paperwork and improve the productivity of your technicians!
-
1
A Menu Kit to provide a common pythonic interface to the menu systems of common gui's. Menus built with this kit will work unchanged with Tkinter, Qt4, Gtk an wxPython. An aid for developers and a tool to assist cross gui support.
-
2
This is an editor for the pylab package. This editor work with ipython shell and pylab, and it enables us to run a script file or selection lines easily. It is suitable for writing a small script for daily scientific/engineering/academic report.
-
3
-
4
AALib/PyAALib - Asynchronous Action Library Project - The project is a Framework based on Pure Object Oriented Concepts to develop asynchronous communication between threads (thread safety) and external process. Platforms: Windows, MacOSX, Linux,Sola
-
Rezku Point of SaleRezku is an all-inclusive ordering platform and management solution for all types of restaurant and bar concepts. You can now get a fully custom branded downloadable smartphone ordering app for your restaurant exclusively from Rezku.
-
5
ADOMA stands for: Alternative Display Of Multiple Alignment. ADOMA can create four different displays of a multiple sequence alignment: a ClustalW alignment in HTML format, a simplified ClustalW alignment in HTML and/or txt format and a colored ClustalW alignment in HTML format. For examples of these outputfiles check the screenshots. ADOMA uses ClustalW to create the multiple alignment from DNA or protein sequences and displays them slightly different than the normal output of ClustalW. ADOMA is a commandline program that can easily be used in pipelines. For more information check the README.md in the Files section. How to cite ADOMA: Zaal, D. and Nota, B. (2016), ADOMA: A Command Line Tool to Modify ClustalW Multiple Alignment Output. Mol. Inf., 35: 42–44. doi: 10.1002/minf.201500083 http://onlinelibrary.wiley.com/doi/10.1002/minf.201500083/abstract
-
6
ADP
ADP is a bare-bones Python Debugger
Another Debugger for Python was written in Python3 using PySimpleGui and has a window showing your script and some buttons and another window showing variables and their values. The buttons entirely control ADP, they are accompanied by help buttons. ADP stores details of the path taken by your script and variables and their values in a SQLITE3 database. The current release supports LIVE running. A future release will support DEAD running. In DEAD runs you’ll be able to replay a LIVE run from the database recording, which means that you can start at any point and travel in either direction and the value of the variables will be those that were current at that point of time in the LIVE run. Imagine your script crashed and you can replay from there backwards, and see how you got there and the values the variables had. Extra functionality will allow running queries forwards and backwards. -
7
AI-Agent-Host
The AI Agent Host is a module-based development environment.
The AI Agent Host integrates several advanced technologies and offers a unique combination of features for the development of language model-driven applications. The AI Agent Host is a module-based environment designed to facilitate rapid experimentation and testing. It includes a docker-compose configuration with QuestDB, Grafana, Code-Server and Nginx. The AI Agent Host provides a seamless interface for managing and querying data, visualizing results, and coding in real-time. The AI Agent Host is built specifically for LangChain, a framework dedicated to developing applications powered by language models. LangChain recognizes that the most powerful and distinctive applications go beyond simply utilizing a language model and strive to be data-aware and agentic. Being data-aware involves connecting a language model to other sources of data, enabling a comprehensive understanding and analysis of information. -
8
AICodeBot
AI-powered tool for developers, simplifying coding tasks
AICodeBot is a terminal-based coding assistant designed to make your coding life easier. Think of it as your AI version of a pair programmer. Perform code reviews, create helpful commit messages, debug problems, and help you think through building new features. A team member that accelerates the pace of development and helps you write better code. We've planned to build out multiple different interfaces for interacting with AICodeBot. To start, it's a command-line tool that you can install and run in your terminal and a GitHub Action for Code Reviews. This project was built before AI Coding Assistants were cool. As such, much of the functionality has been replicated in various IDEs. Where AICodeBot shines is a) it's in the terminal, not GUI, and b) it can be used in processes like GitHub actions. We're using AICodeBot to build AICodeBot, and it's upward spiraling all the time.️ We're looking for contributors to help us build it out. -
9
AIMET
AIMET is a library that provides advanced quantization and compression
Qualcomm Innovation Center (QuIC) is at the forefront of enabling low-power inference at the edge through its pioneering model-efficiency research. QuIC has a mission to help migrate the ecosystem toward fixed-point inference. With this goal, QuIC presents the AI Model Efficiency Toolkit (AIMET) - a library that provides advanced quantization and compression techniques for trained neural network models. AIMET enables neural networks to run more efficiently on fixed-point AI hardware accelerators. Quantized inference is significantly faster than floating point inference. For example, models that we’ve run on the Qualcomm® Hexagon™ DSP rather than on the Qualcomm® Kryo™ CPU have resulted in a 5x to 15x speedup. Plus, an 8-bit model also has a 4x smaller memory footprint relative to a 32-bit model. However, often when quantizing a machine learning model (e.g., from 32-bit floating point to an 8-bit fixed point value), the model accuracy is sacrificed. -
Dun and Bradstreet Risk Analytics - Supplier IntelligenceRisk, procurement, and compliance teams across the globe are under pressure to deal with geopolitical and business risks. Third-party risk exposure is impacted by rapidly scaling complexity in domestic and cross-border businesses, along with complicated and diverse regulations. It is extremely important for companies to proactively manage their third-party relationships. An AI-powered solution to mitigate and monitor counterparty risks on a continuous basis, this cutting-edge platform is powered by D&B’s Data Cloud with 520M+ Global Business Records and 2B+ yearly updates for third-party risk insights. With high-risk procurement alerts and multibillion match points, D&B Risk Analytics leverages best-in-class risk data to help drive informed decisions. Perform quick and comprehensive screening, using intelligent workflows. Receive ongoing alerts of key business indicators and disruptions.
-
10
Data server for user intelligent agents. Written in Python, using XML-RPC as client/server communication and RDBMS as storage.
-
11
The Automatic Model Optimization Reference Implementation, AMORI, is a framework that integrates the modelling and the optimization processes by providing a plug-in interface for both. A genetic algorithm and Markov simulations are currently implemented.
-
12
Python script to get the last 5 minutes of accepted traffic logs via the trendmicro email security API and send them to a syslog server Script Python para obtener los ultimos 5 minutos de logs de trafico aceptado por medio de la API de trendmicro email security y enviarlos a un servidor de syslog Crontab */5 * * * * /usr/local/bin/python3.9 /home/user/tmes-syslog_0.02.py 2>&1 > /home/user/errores.txt ------------ # API documentation # Getting Started with Trend Micro Email Security APIs # https://docs.trendmicro.com/en-us/enterprise/trend-micro-email-security-rest-api-online-help/getting-started-with.aspx # Obtaining the API Key # https://docs.trendmicro.com/en-us/enterprise/trend-micro-email-security-rest-api-online-help/getting-started-with/obtaining-the-api-ke.aspx # List Mail Tracking Logs # https://docs.trendmicro.com/en-us/enterprise/trend-micro-email-security-rest-api-online-help/supported-apis/logs/list-mail-tracking-l.aspx
-
13
API Correios
API correios.com.br in Python
pycorreios is a Python library aimed at interacting with Brazil’s postal service (Correios) APIs, making it easier for developers to track shipments, calculate postage, query service availability, and integrate with Brazilian e-commerce flows. The library abstracts the raw SOAP or REST endpoints exposed by Correios, providing Pythonic methods to perform common tasks like tracking a package by its code or computing shipping cost/lead time between postal codes. It handles serialization and mapping of API responses into Python objects so developers don’t manually parse raw XML or JSON. With this tool, developers building Brazilian market e-commerce or logistics solutions can integrate postal services smoothly. Because it is open source, improvements can be contributed to support new endpoints, changes in the postal service API, or additional features like caching or async requests. -
14
Simplified interface to the Augmented Reality library ARToolKit for Python and other programming languages.
-
15
ARREA
Collaborative editor, requirements management tool and much more
ARREA (A Reasonable Requirements Engineering Application) is a simple yet powerful requirements management tool that uses arbitrary files to store information and Subversion to allow team collaboration. Its simple conventions make it suitable for much other purposes. In fact, for any document-oriented tasks focused on collaborative work and exhaustive change and traceability management. At its heart, ARREA provides a thin layer on top of SVN that allows it to be used as a powerful time-aware NoSQL database, accessible through an easy REST API. -
16
ART ASCII Library
ASCII art library for Python
ASCII art is also known as "computer text art". It involves the smart placement of typed special characters or letters to make a visual shape that is spread over multiple lines of text. ART is a Python lib for text converting to ASCII art fancy. -
17
ASDRAD is a source code generator which reads a configuration file and generates *.c, *.h, makefiles etc. It's written in Python and uses templates. Output files are for AmigaOS and derivates like AROS and MorphOS.
-
18
ASN.1 types and codecs (BER, CER, DER) implementation in Python programming language. A collection of various ASN.1-based protocols data structures is supplied in a dedicated Python package. Project moved to GitHub: https://github.com/etingof/pyasn1
-
19
AT Managed File is a project originally developed by Enfold Systems company for Plone 2.5. This is product version patched to work in Plone version 3.x. AT Managed File product stores files in local path insted of ZOBD while maintains a Plone instance.
-
20
Automated Test Framework for Embedded Software: A system to perform test scripts 'in system' on embedded software. It uses Python as a high level description language and interfaces with GDB to communicate with the embedded platform.
-
21
AWS Chalice
Python Serverless Microframework for AWS
Chalice is a Python microframework for writing and deploying serverless applications on AWS with minimal ceremony. You define routes, event handlers, and background tasks in plain Python, and Chalice turns them into AWS Lambda functions wired to API Gateway, Amazon EventBridge schedulers, S3/SNS/SQS triggers, and more. A single command builds your app, bundles dependencies, generates infrastructure templates, and deploys to your account with sensible defaults. The framework includes local development tools so you can iterate on HTTP routes and inspect logs before shipping to the cloud. It also manages per-stage configuration, environment variables, IAM permissions scaffolding, and packaging optimizations to keep cold starts small. While it’s intentionally lightweight, it supports common production needs like CORS, custom authorizers, binary responses, and fine-grained IAM so you can grow from prototype to production without rewriting your stack. -
22
AWS IoT Device SDK v2 for Python
Next generation AWS IoT Client SDK for Python
Next-generation AWS IoT Client SDK for Python using the AWS Common Runtime. This document provides information about the AWS IoT Device SDK v2 for Python. This SDK is built on the AWS Common Runtime, a collection of libraries (aws-c-common, aws-c-io, aws-c-mqtt, aws-c-compression, aws-c-http, aws-c-cal, aws-c-auth, s2n ...) written in C to be cross-platform, high-performance, secure, and reliable. The libraries are bound to Python by the awscrt package (PyPI). AWS IoT provides the cloud services that connect your IoT devices to other devices and AWS cloud services. AWS IoT provides device software that can help you integrate your IoT devices into AWS IoT-based solutions. If your devices can connect to AWS IoT, AWS IoT can connect them to the cloud services that AWS provides. AWS IoT lets you select the most appropriate and up-to-date technologies for your solution. -
23
AWS IoT Greengrass Core SDK
SDK to use with functions running on Greengrass Core using Python
The AWS IoT Greengrass Core SDK is meant to be used by AWS Lambda functions running on an AWS IoT Greengrass Core. It will enable Lambda functions to invoke other Lambda functions deployed to the Greengrass Core, publish messages to the Greengrass Core and work with the local Shadow service. To use the AWS IoT Greengrass Core SDK, you must first import the AWS IoT Greengrass Core SDK in your Lambda function as you would with any other external libraries. You then need to create a client for ‘iot-data’ or ‘lambda’. Use ‘iot-data’ if you wish to publish messages to the local Greengrass Core and interact with the local Shadow service. Use ‘lambda’ if you wish to invoke other Lambda functions deployed to the same Greengrass Core. As new features are added to AWS IoT Greengrass, newer versions of the AWS IoT Greengrass SDK may be incompatible with older versions of the AWS IoT Greengrass core. -
24
AWS Jupyter Proxy
Jupyter server extension to proxy requests with AWS SigV4 authentican
A Jupyter server extension to proxy requests with AWS SigV4 authentication. This server extension enables the usage of the AWS JavaScript/TypeScript SDK to write Jupyter frontend extensions without having to export AWS credentials to the browser. A single /awsproxy endpoint is added on the Jupyter server which receives incoming requests from the browser, uses the credentials on the server to add SigV4 authentication to the request, and then proxies the request to the actual AWS service endpoint. All requests are proxied back-and-forth as-is, e.g., a 4xx status code from the AWS service will be relayed back as-is to the browser. Using this requries no additional dependencies in the client-side code. Just use the regular AWS JavaScript/TypeScript SDK methods and add any dummy credentials and change the endpoint to the /awsproxy endpoint. -
25
AWS Lambda Python Runtime Interf Client
Seamlessly extend your preferred base images to be Lambda compatible
We have open-sourced a set of software packages, Runtime Interface Clients (RIC), that implement the Lambda Runtime API, allowing you to seamlessly extend your preferred base images to be Lambda compatible. The Lambda Runtime Interface Client is a lightweight interface that allows your runtime to receive requests from and send requests to the Lambda service. The Lambda Python Runtime Interface Client is vended through pip. You can include this package in your preferred base image to make that base image Lambda compatible. To make it easy to locally test Lambda functions packaged as container images we open-sourced a lightweight web-server, Lambda Runtime Interface Emulator (RIE), which allows your function packaged as a container image to accept HTTP requests. You can install the AWS Lambda Runtime Interface Emulator on your local machine to test your function. Then when you run the image function, you set the entry point to be the emulator.
