Search Results for "static analysis tools for python" - Page 4
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Showing 141 open source projects for "static analysis tools for python"
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What is DracOS GNU/Linux Remastered ? DracOS GNU/Linux Remastered ( https://github.com/dracos-linux ) is the Linux operating system from Indonesia , open source is built based on Debian live project under the protection of the GNU General Public License v3.0. This operating system is one variant of Linux distributions, which is used to perform security testing (penetration testing). Dracos linux in Arm by hundreds hydraulic pentest, forensics and reverse engineering. Use a GUI-based...
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Interpret-Text
State-of-the-art explainers for text-based machine learning models
A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in dashboard. Interpret-Text builds on Interpret, an open source python package for training interpretable models and helping to explain blackbox machine learning systems. We have added extensions to support text models. Interpret-Text incorporates community-developed interpretability techniques for NLP models and a visualization dashboard to view the results. Users can run their experiments across multiple state-of-the-art explainers and easily perform comparative analysis on them. ... -
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Bareflank Hypervisor
lightweight hypervisor SDK written in C++
The Bareflank Hypervisor is an open source hypervisor Software Development Toolkit (SDK) for Rust and C++, led by Assured Information Security, Inc. (AIS), that provides the tools needed to rapidly prototype and create your own hypervisor on 64bit versions of Intel and AMD (ARMv8 CPUs, RISC-V and PowerPC also planned). The Bareflank SDK is intended for instructional/research purposes as it only provides enough virtualization support to start/stop a hypervisor. Bareflank can also be used as... -
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Apex Up
Deploy infinitely scalable serverless apps, APIs and sites
Up deploys infinitely scalable serverless apps, APIs, and static websites in seconds, so you can get back to working on what makes your product unique. Up focuses on deploying “vanilla” HTTP servers so there’s nothing new to learn, just develop with your favorite existing frameworks such as Express, Koa, Django, Golang net/HTTP or others. Up currently supports Node.js, Golang, Python, Java, Crystal, and static sites out of the box. Up is platform-agnostic, supporting AWS Lambda and API... -
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QtProjectTool
QtCreator plugin for some command line tools over a Qt (.pro) project.
qpt (Qt Project Tool) understands Qt C++ projects (.pro) and allows to pass this information to command line tools as "Code Counters" and "Static Analysis tools". It also can used inside QtCreator to act as a plugin for "Static Analysis tools" putting reported issues into QtCreator issues pane. -
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PyTorchVideo
A deep learning library for video understanding research
PyTorchVideo is a deep learning library for video understanding, providing modular components and pretrained models for tasks like action recognition, video classification, detection, and self-supervised learning. It is tightly integrated with PyTorch and PyTorch Lightning, offering flexible APIs for building and training spatiotemporal networks. The library includes efficient implementations of state-of-the-art architectures such as SlowFast, X3D, and MViT, optimized for both research... -
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earthengine-py-notebooks
A collection of 360+ Jupyter Python notebook examples
...Many of the notebooks integrate with tools like folium, ipyleaflet, and geemap to bridge Earth Engine data with Python’s rich ecosystem for plotting and analysis. Users can quickly adapt the examples for their own remote sensing, environmental monitoring, or spatial data science projects, and can run the code in environments like Google Colab. -
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Neural Networks Collection
Neural Networks Collection
This project implements in C++ a bunch of known Neural Networks. So far the project implements: LVQ in several variants, SOM in several variants, Hopfield network and Perceptron. Other neural network types are planned, but not implemented yet. The project can run in two modes: command line tool and Python 7.2 extension. Currently, Python version appears more functional, as it allows easy interaction with algorithms developed by other people. -
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fastNLP
fastNLP: A Modularized and Extensible NLP Framework
fastNLP is a lightweight framework for natural language processing (NLP), the goal is to quickly implement NLP tasks and build complex models. A unified Tabular data container simplifies the data preprocessing process. Built-in Loader and Pipe for multiple datasets, eliminating the need for preprocessing code. Various convenient NLP tools, such as Embedding loading (including ELMo and BERT), intermediate data cache, etc.. Provide a variety of neural network components and recurrence models... -
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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Makani
Makani was developed a commercial-scale airborne wind turbine
...This open-source repository contains the complete software stack that powered Makani’s research and flight systems, including the flight simulator, autopilot controller, avionics firmware, visualization tools, and ground control software. The software enables simulation, control, and analysis of the Makani M600 turbine system, designed to operate offshore and autonomously manage complex aerodynamic behaviors. Built primarily in C++ and Python, the codebase integrates real-time flight control, sensor fusion, aerodynamic modeling, and telemetry visualization. ... -
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Metrix++
Management of source code quality is possible.
The project has been moved to https://github.com/metrixplusplus/metrixplusplus ______________________ Metrix++ is an extendable tool to collect and analyse code metrics. - Multiple languages supported - Multiple metrics available - Configurable. Every metric has got 'turn-on' and other configuration options. There are no predefined thresholds for metrics or rules. You can choose and configure any limit you want. - High-performance. Processes thousands of files per minutes. -... -
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HDL Checker
Repurposing existing HDL tools to help writing better code
HDL Checker is a language server that wraps VHDL/Verilg/SystemVerilog tools that aims to reduce the boilerplate code needed to set things up. It supports Language Server Protocol or a custom HTTP interface; can infer the library VHDL files likely to belong to, besides working out mixed language dependencies, compilation order, interpreting some compiler messages and providing some (limited) static checks. Notice that currently, the unused reports has caveats, namely declarations with the... -
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Hercules
Gaining advanced insights from Git repository history
...The second is a Python script that shows some predefined plots over the collected data. These two tools are normally used together through a pipe. It is possible to write custom analyses using the plugin system. It is also possible to merge several analysis results together - relevant for organizations. The analyzed commit history includes branches, merges, etc. -
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Microsoft Python Language Server
Microsoft Language Server for Python
Microsoft Python Language Server implements the Language Server Protocol. Its primary clients are the Python extension for VS Code and Python Tools for Visual Studio. Feel free to file issues or ask questions on our issue tracker, and we welcome code contributions. Linting can be controlled via the user configuration. In VS Code, this is settings.json. -
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Olex2 is visualisation software for small-molecule crystallography developed at Durham University/EPSRC. It provides comprehensive tools for crystallographic model manipulation for the end user and an extensible development framework for programmers. The project has been supported by Olexsys Ltd since 2010.
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Active Learning
Framework and examples for active learning with machine learning model
Active Learning is a Python-based research framework developed by Google for experimenting with and benchmarking various active learning algorithms. It provides modular tools for running reproducible experiments across different datasets, sampling strategies, and machine learning models. The system allows researchers to study how models can improve labeling efficiency by selectively querying the most informative data points rather than relying on uniformly sampled training sets. The main... -
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Python Taint
Static Analysis Tool for Detecting Security Vulnerabilities in Python
Static analysis of Python web applications based on theoretical foundations (Control flow graphs, fixed point, dataflow analysis) Detect command injection, SSRF, SQL injection, XSS, directory traveral etc. A lot of customization is possible. For functions from builtins or libraries, e.g. url_for or os.path.join, use the -m option to specify whether or not they return tainted values given tainted inputs, by default this file is used. -
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pangu.py
Paranoid text spacing in Python
pangu.py is a Python port of the Pangu spacing tool that automatically inserts proper whitespace between CJK characters and Latin letters, numbers, or symbols. Mixed-script text often becomes cramped or ambiguous, and this library applies simple but effective typography rules to make it instantly more readable. It works both as a Python library and a command-line utility, so you can process strings in code, tidy files in bulk, or wire it into documentation and build pipelines. The... -
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awesome-ci
Awesome Continuous Integration
awesome-ci is a suite of command-line tools aimed at enhancing Continuous Integration (CI) workflows. It focuses on static code analysis, syntax checking, and file validation to maintain code quality across projects. -
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Functional, Data Science Intro To Python
[tutorial]A functional, Data Science focused introduction to Python
The first section is an intentionally brief, functional, data science-centric introduction to Python. The assumption is a someone with zero experience in programming can follow this tutorial and learn Python with the smallest amount of information possible. The sections after that, involve varying levels of difficulty and cover topics as diverse as Machine Learning, Linear Optimization, build systems, command line tools, recommendation engines, Sentiment Analysis and Cloud Computing. -
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CSBB-v3.0
CSBB - Computational Suite for Bioinformaticians and Biologists
CSBB is a command line-based bioinformatics suite to analyze biological data acquired through varied avenues of biological experiments. CSBB is implemented in Perl, while it also leverages the use of R, java, python and ruby in background for specific modules. Major focus of CSBB is to allow users from biology and bioinformatics community, to get benefited by performing down-stream analysis tasks while eliminating the need to write programming code. CSBB is currently available on Linux,... -
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Grumpy
Grumpy is a Python to Go source code transcompiler and runtime
Grumpy is a Python-to-Go transcompiler and runtime designed as a near drop-in replacement for CPython 2.7 that compiles Python source to Go, then to native code. Instead of executing Python bytecode in a VM, Grumpy translates modules into Go code that calls a Go runtime library emulating Python semantics, which can yield performance and deployment benefits in Go ecosystems. The approach integrates with Go’s toolchain, enabling static binaries and potentially easier distribution in... -
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cnn-benchmarks
Benchmarks for popular CNN models
The cnn-benchmarks project is a collection of benchmarking scripts designed to evaluate the performance of convolutional neural networks across different hardware and configurations. It provides standardized implementations of popular CNN architectures, enabling developers to measure training speed, memory usage, and computational efficiency. The project focuses on reproducibility, allowing consistent comparisons between models and environments. It is particularly useful for testing GPUs and... -
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Needle
The iOS Security Testing Framework
Needle is an open-source, modular framework to streamline the process of conducting security assessments of iOS apps. Needle was originally made to work with iOS 9 and iOS 10. Since then, Frida was released and become the defacto tool to use with mobile security assessments. Some common Frida mobile security scripts were later implemented within Needle, as some of these scripts worked better or addressed some issues that were present in Needle's custom tooling. Assessing the security of an... -
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C++ Core Guidelines
The C++ Core Guidelines are a set of tried-and-true guidelines
...The guidelines encourage use of modern language features—RAII, smart pointers, move semantics, ranges, and constexpr—while steering developers away from brittle idioms and unsafe constructs. Enforcement is a central theme: many rules are designed to be checkable by static analysis tools and linters so teams can automate compliance. As a community artifact, it evolves with the language standard, offering a practical compass for teams upgrading legacy code or establishing standards for greenfield projects.
