Showing 8 open source projects for "python tools"

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  • The most advanced C and C++ source code analyzer Icon
    The most advanced C and C++ source code analyzer

    Combining the benefits of static and dynamic source code analysis to deliver the most advanced & exhaustive code verification tool.

    TrustInSoft Analyzer is a C and C++ source code analyzer powered by formal methods, mathematical & logical reasonings that allow for exhaustive analysis of source code. This analysis can be run without false positives or false negatives, so that every real bug in the code is found. Developers receive several benefits: a user-friendly graphical interface that directs developers to the root cause of bugs, and instant utility to expand the coverage of their existing tests. Unlike traditional source code analysis tools, TrustInSoft’s solution is not only the most comprehensive approach on the market but is also progressive, instantly deployable by developers, even if they lack experience with formal methods, from exhaustive analysis up to a functional proof that the software developed meets specifications.
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  • 1
    DataFrames.jl

    DataFrames.jl

    In-memory tabular data in Julia

    ...It provides a familiar, flexible, and efficient interface for handling datasets, making it easy to load, manipulate, join, and analyze structured data. With syntax inspired by data frames in R and pandas in Python, it offers intuitive tools while taking advantage of Julia’s speed and type system. The package is actively maintained by the JuliaData community, with contributions from over 200 developers worldwide. It is widely used for data science, research, and production applications, supported by extensive documentation, tutorials, and a free Julia Academy course. ...
    Downloads: 0 This Week
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  • 2
    InteractiveViz.jl

    InteractiveViz.jl

    Interactive visualization tools for Julia

    ...To allow generation of data points on demand through a graphics pipeline, requiring computation only at a level of detail appropriate for display at the viewing resolution. Additional data points can be generated on demand when zooming or panning. This package was partly inspired by the excellent Datashader package available in the Python ecosystem.
    Downloads: 0 This Week
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  • 3
    Vim Codefmt

    Vim Codefmt

    Vim plugin for syntax-aware code formatting

    ...The plugin ships with a registry of built-in formatters and a pluggable architecture, allowing other plugins to register additional formatters without friction. Configuration is handled through maktaba and Glaive flags, so you can choose per-filetype tools, pass custom options, or point to specific formatter executables. Autoformat can be enabled via standard Vim autocommands, making it easy to format on filetype or on write while still allowing opt-out on a per-buffer basis. With broad language coverage—from C, C++, Java, Python, and Go to Kotlin, Rust, Swift, Bazel, Markdown, and more—vim-codefmt helps teams maintain consistent style across heterogeneous codebases.
    Downloads: 4 This Week
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  • 4
    CounterfactualExplanations.jl

    CounterfactualExplanations.jl

    A package for Counterfactual Explanations and Algorithmic Recourse

    CounterfactualExplanations.jl is a package for generating Counterfactual Explanations (CE) and Algorithmic Recourse (AR) for black-box algorithms. Both CE and AR are related tools for explainable artificial intelligence (XAI). While the package is written purely in Julia, it can be used to explain machine learning algorithms developed and trained in other popular programming languages like Python and R. See below for a short introduction and other resources or dive straight into the docs.
    Downloads: 0 This Week
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    Unbeatably easy cloud-based digital signage platform

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    With Yodeck you can create, design and schedule content easily from the web, no matter how far away you are from your screens. Use attention-grabbing media like videos, images, PDF files, Office docs, data dashboards and social media to get your message across to the people that matter most to your business.
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  • 5
    The Julia Programming Language

    The Julia Programming Language

    High-level, high-performance dynamic language for technical computing

    ...Having a high level syntax, Julia is easy to use for programmers of every level and background. Julia has more than 2,800 community-registered packages including various mathematical libraries, data manipulation tools, and packages for general purpose computing. Libraries from Python, R, C/Fortran, C++, and Java can also be used.
    Downloads: 2 This Week
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  • 6
    ChatGPT Plugins Collection

    ChatGPT Plugins Collection

    An unofficial collection of Plugins for ChatGPT

    ChatGPT-Plugins-Collection is a community-driven repository that gathers examples and resources for building, testing, and experimenting with ChatGPT plugins. The collection provides a variety of plugin implementations that showcase different use cases, helping developers learn how to extend ChatGPT’s functionality. It is designed to serve both as a learning resource for beginners and a reference point for more experienced developers. By centralizing community contributions, the repository...
    Downloads: 7 This Week
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  • 7
    ScikitLearn.jl

    ScikitLearn.jl

    Julia implementation of the scikit-learn API

    The scikit-learn Python library has proven very popular with machine learning researchers and data scientists in the last five years. It provides a uniform interface for training and using models, as well as a set of tools for chaining (pipelines), evaluating, and tuning model hyperparameters. ScikitLearn.jl brings these capabilities to Julia. Its primary goal is to integrate both Julia- and Python-defined models together into the scikit-learn framework.
    Downloads: 0 This Week
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  • 8
    Pythonidae

    Pythonidae

    Curated decibans of scientific programming resources in Python

    Pythonidae is a curated collection of scientific programming resources in Python, designed to support research and development across a wide range of disciplines. The repository organizes tools and libraries into domain-specific categories, including mathematics, statistics, machine learning, artificial intelligence, biology, chemistry, physics, earth sciences, and supercomputing. It also covers practical areas such as build automation, databases, APIs, computer graphics, and utilities, offering a structured reference for both academic and applied work. ...
    Downloads: 3 This Week
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