Open Source Python Scientific/Engineering Software - Page 4
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Python Scientific/Engineering Software
View 201 business solutionsBrowse free open source Python Scientific/Engineering Software and projects below. Use the toggles on the left to filter open source Python Scientific/Engineering Software by OS, license, language, programming language, and project status.
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Marketing automation for any business | ActiveCampaignActive Intelligence revolutionizes how you work. You guide direction while AI handles execution, acts on insights, and shows you the path forward. It's how marketing should be.
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Intelligent testing agents | Checksum.aiCoding agents write the code. Checksum runs it—continuously testing against real APIs, real data, real edge cases—before it ever reaches production.
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Get Physics Done (GPD)
The first open-source agentic AI physicist
Get Physics Done (GPD) is an open-source project designed to accelerate scientific research in physics by leveraging modern computational tools and automation techniques. It aims to simplify the process of performing simulations, calculations, and experimental analysis by providing structured workflows that integrate computational physics methods with reproducible research practices. The project focuses on reducing the friction involved in setting up experiments, running simulations, and analyzing results, allowing researchers to focus more on scientific insight rather than infrastructure. It emphasizes automation and reproducibility, ensuring that experiments can be easily replicated and extended by other researchers. The framework is adaptable to different areas of physics, making it suitable for both theoretical and applied research scenarios. -
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RPy is a very simple, yet robust, Python interface to the R Programming Language. It can manage all kinds of R objects and can execute arbitrary R functions (including the graphic functions).
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gVirtualXRay
Virtual X-Ray Imaging Library on GPU
gVirtualXRay is a C++ library to simulate X-ray imaging. It is based on the Beer-Lambert law to compute the absorption of light (i.e. photons) by 3D objects (here polygon meshes). It is implemented on the graphics processing unit (GPU) using the OpenGL Shading Language (GLSL). SimpleGVXR is a smaller library build on the top of gVirtualXRay. It provides wrappers to Python, R, Ruby, Tcl, C#, Java, and GNU Octave. -
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OpenOPC for Python is an easy to use OPC (OLE for Process Control) library for use with the Python programming language. The project includes a Windows gateway service allowing non-Windows clients to also access OPC-DA calls.
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Bitdefender Ultimate Small Business SecurityGet exceptional protection against all digital threats for your business and employees.
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AlphaGenome
Programmatic access to the AlphaGenome model
The AlphaGenome API provides access to AlphaGenome, Google DeepMind’s unifying model for deciphering the regulatory code within DNA sequences. This repository contains client-side code, examples, and documentation to help you use the AlphaGenome API. AlphaGenome offers multimodal predictions, encompassing diverse functional outputs such as gene expression, splicing patterns, chromatin features, and contact maps. The model analyzes DNA sequences of up to 1 million base pairs in length and can deliver predictions at single-base-pair resolution for most outputs. AlphaGenome achieves state-of-the-art performance across a range of genomic prediction benchmarks, including numerous diverse variant effect prediction tasks. -
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Astropy
Repository for the Astropy core package
The Astropy Project is a community effort to develop a common core package for Astronomy in Python and foster an ecosystem of interoperable astronomy packages. Astropy is a Python library for use in astronomy. Learn Astropy provides a portal to all of the Astropy educational material through a single dynamically searchable web page. It allows you to filter tutorials by keywords, search for filters, and make search queries in tutorials and documentation simultaneously. The Anaconda Python Distribution includes Astropy and is the recommended way to install both Python and the Astropy package. The astropy package contains key functionality and common tools needed for performing astronomy and astrophysics with Python. It is at the core of the Astropy Project, which aims to enable the community to develop a robust ecosystem of affiliated packages covering a broad range of needs for astronomical research, data processing, and data analysis. -
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Brax
Massively parallel rigidbody physics simulation
Brax is a fast and fully differentiable physics engine for large-scale rigid body simulations, built on JAX. It is designed for research in reinforcement learning and robotics, enabling efficient simulations and gradient-based optimization. -
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Handcalcs
Python library for converting Python calculations into rendered latex
Handcalcs is a Python library that auto-renders calculation code in Jupyter notebooks or LaTeX documents with step-by-step symbolic substitution, giving output a “handwritten” feel. It supports cell magics and auto-LaTeX generation via configurable output options. -
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PyQuil
A Python library for quantum programming using Quil
PyQuil is a Python library for quantum programming using Quil, the quantum instruction language developed at Rigetti Computing. PyQuil serves three main functions. PyQuil has a ton of other features, which you can learn more about in the docs. However, you can also keep reading below to get started with running your first quantum program. Without installing anything, you can quickly get started with quantum programming by exploring our interactive Jupyter Notebook tutorials and examples. To run them in a preconfigured execution environment on Binder, click the "launch binder" badge at the top of the README or the link here! To learn more about the tutorials and how you can add your own, visit the rigetti/forest-tutorials repository. If you'd rather set everything up locally, or are interested in contributing to pyQuil, continue to the next section for instructions on installing pyQuil and the Forest SDK. -
Intelligent predictive dialer for outbound call centerOur autodialer software can massively increase productivity by dropping busy, unanswered and disconnected line, passing calls answered by real people back to your agents, and leaving messages on answering machines.
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Segments.ai
Segments.ai Python SDK
Multi-sensor labeling platform for robotics and autonomous vehicles. The platform for fast and accurate multi-sensor data annotation. Label in-house or with an external workforce. Intuitive labeling interfaces for images, videos, and 3D point clouds (lidar and RGBD). Obtain segmentation labels, vector labels, and more. Our labeling interfaces are set up to label fast and precise. Powerful ML assistance lets you label faster and reduce costs. Integrate data labeling into your existing ML pipelines and workflows using our simple yet powerful Python SDK. Onboard your own workforce or use one of our workforce partners. Our management tools make it easy to label and review large datasets together. Now, Segments.ai is providing a data labeling backbone to help robotics and AV companies build better datasets. -
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OdooPLM
A Full PLM system based on odoo
OdooPLM is an Open Source Odoo Application that allows you to manage PLM Data inside Odoo. You can upload data from the most common commercial CAD systems directly to Odoo with a unique and easy to use interface. Our approach, very quick, ready to use, is very useful for all companies that wants useful and powerful tools. You can install PLM module and its Client without any cost, touching the quality of our product in your real work environment. Official OdooPLM website https://odooplm.omniasolutions.website/ Try OdooPLM on Cloud at: https://www.v15.odooplm.cloud/ This project is maintained by OmniaSolutions. Find us at https://www.omniasolutions.website Odoo is a product of Odoo SA, world class leader in Open Source ERP system. Find it at https://www.odoo.com -
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Repeater-START
Showing The Amateur radio Repeaters Tool
Repeater-START (Showing The Amateur Repeaters Tool) is an app to view nearby ham radio repeaters. It runs on Windows, Android, Ubuntu Linux and Raspbian for Raspberry-pi, Librem Phone, Pinephone/Manjaro Linux etc. -
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asammdf
Fast Python reader and editor for ASAM MDF / MF4 (Measurement Format)
*asammdf* is a fast Python parser and editor for ASAM (Associtation for Standardisation of Automation and Measuring Systems) MDF / MF4 (Measurement Data Format) files. It supports MDF versions 2 (.dat), 3 (.mdf) and 4 (.mf4). *asammdf* works on Python 2.7, and Python >= 3.4 -
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MAGeCK
Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout
Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout (MAGeCK) is a computational tool to identify important genes from the recent genome-scale CRISPR-Cas9 knockout screens technology. For instructions and documentations, please refer to the wiki page. MAGeCK is developed by Wei Li and Han Xu from Dr. Xiaole Shirley Liu's lab at Dana-Farber Cancer Institute/Harvard School of Public Health, and is maintained by Wei Li lab at Children's National Medical Center. We thank the support from Claudia Adams Barr Program in Innovative Basic Cancer Research and NIH/NHGRI to develop MAGeCK. -
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BioXTAS RAW
Processing and analysis of Small Angle X-ray Scattering (SAXS) data.
BioXTAS RAW is a program for analysis of Small-Angle X-ray Scattering (SAXS) data. The software enables: creation of 1D scattering profiles from 2D detector images, standard data operations such as averaging and subtraction, analysis of radius of gyration (Rg) and molecular weight, and advanced analysis using GNOM and DAMMIF as well as electron density reconstructions using DENSS. It also allows easy processing of inline SEC-SAXS data and data deconvolution using the evolving factor analysis (EFA) or the regularized alternating least squares (REGALS) methods. Active source code is now maintained on github: https://github.com/jbhopkins/bioxtasraw To install: Check the instructions available at: http://bioxtas-raw.readthedocs.io/en/latest/install.html and in the Files tab. User guides: RAW guides are available at: http://bioxtas-raw.readthedocs.io/ and in the Files tab. To contact us, see: https://bioxtas-raw.readthedocs.io/en/latest/help.html -
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TANGO is a device oriented control system for Linux and Windows. It provides a framework in C++, Java and Python for implementing distributed control objects. TANGO has a full set of tools and hundreds of device servers.
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Python module for creating functions computing the Cyclic Redundancy Check (CRC). Any generating polynomial producing 8, 16, 24, 32, or 64 bit CRCs is allowed. Generated functions can be used in Python or C/C++ source code can be generated.
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The auditory modeling toolbox (AMT) is a Matlab/Octave toolbox for the development and application of auditory computational models. Over 50 auditory models implemented in Matlab, Octave, C, C++, and Python can be run from Matlab and Octave, on Windows and Linux. The AMT provides a well-structured in-code documentation, includes auditory data required to run the models. It integrates functionality to reproduce the model predictions. Model implementations can be evaluated in two stages, by running so-called demonstrations which are quick presentations of a model and by starting so-called experiments aimed at reproducing results from the corresponding publications. Easy installation and user-friendly access help students and researchers to work with and to advance existing models.
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Automatically geocode pictures from your camera and a GPS track log. Following Google code closure the only official webpage is (doc, support, code) : https://github.com/notfrancois/GPicSync
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PowerTalk automatically speaks Microsoft PowerPoint presentations. For presenters who find speaking difficult, audiences containing people with visual impairments and fun educational uses. Uses synthesised computer speech provided with Windows
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ASCEND is a modelling environment and solver for large or small systems of non-linear equations, for use in engineering, thermodynamics, chemistry, physics, mathematics and biology. Solvers for both steady and dynamic (NLA & DAE) problems, are provid
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BQSKit
Berkeley Quantum Synthesis Toolkit
The Berkeley Quantum Synthesis Toolkit (BQSKit) [bis • kit] is a powerful and portable quantum compiler framework. It can be used with ease to compile quantum programs to efficient physical circuits for any QPU. A standard workflow utilizing BQSKit consists of loading a program into the framework, modeling the target QPU, compiling the program, and exporting the resulting circuit. -
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Dummy-Robot
My super mini robotic arm robot project
Dummy-Robot is an open source robotics project by Peng Zhihui that showcases the design and implementation of a compact robotic arm . The repository contains full hardware design files, firmware, control software, and 3D models. It includes components such as a gripper, LED light ring PCB, wireless spatial positioning controller, and a portable case. The project demonstrates advanced engineering with stepper motor drivers, custom controllers, and debugging tools. While the original version is CNC-machined, a simplified 3D-printable "youth edition" is planned to lower costs. This project serves as both an educational resource and a demonstration of innovative DIY robotics. -
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Earth Enterprise
Google Earth Enterprise - Open Source
Earth Enterprise is the open source version of Google Earth Enterprise (GEE), a powerful geospatial application suite that enables organizations to build and host custom 3D globes and 2D maps using their own imagery and data. Unlike Google Maps or Google Earth, Earth Enterprise does not include Google’s proprietary imagery but instead provides the tools needed to manage and visualize private geospatial datasets. The system is composed of three main components: Fusion, which processes and integrates imagery, vector, and terrain data into unified map layers; Server, which hosts the resulting globes or maps via Apache or Tornado-based web servers; and Client, which includes the Google Earth Enterprise Client (EC) for 3D visualization and the Google Maps JavaScript API V3 for 2D viewing. Designed for enterprise, research, and government use, it allows for secure, scalable deployment of geospatial visualization systems within private infrastructure. -
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Mathematics Dataset
This dataset code generates mathematical question and answer pairs
The Mathematics Dataset, developed by Google DeepMind, is a synthetic dataset designed to evaluate and train machine learning models on mathematical reasoning and symbolic manipulation. It generates question-and-answer pairs across a wide range of mathematical topics typically found in school-level curricula, testing a model’s ability to reason about algebra, arithmetic, calculus, probability, and more. Each question is programmatically generated with structured templates to ensure clear logic and reproducibility. The dataset enables models to learn mathematical problem-solving through examples that involve both numeric and symbolic reasoning. Version 1.0 includes over 2 million examples per category, with training splits labeled as “easy,” “medium,” and “hard,” supporting curriculum-based learning strategies. The data can be accessed via PyPI or generated locally using provided Python scripts, with outputs formatted for direct use in training or evaluation pipelines.
