Showing 4 open source projects for "python-dpkt"

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  • 1
    NetworkX

    NetworkX

    Network analysis in Python

    NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. Data structures for graphs, digraphs, and multigraphs. Many standard graph algorithms. Network structure and analysis measures. Generators for classic graphs, random graphs, and synthetic networks. Nodes can be "anything" (e.g., text, images, XML records).
    Downloads: 3 This Week
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  • 2
    django-webpack-loader

    django-webpack-loader

    Transparently use webpack with django

    Use webpack to generate your static bundles without django's static files or opaque wrappers. Django webpack loader consumes the output generated by webpack-bundle-tracker and lets you use the generated bundles in Django. Test cases cover Django>=2.0 on Python>=3.5. 100% code coverage is the target so we can be sure everything works anytime. It should probably work on older versions of Django as well but the package does not ship any test cases for them. Before configuring django-webpack-loader, let's first configure what's necessary on the webpack-bundle-tracker side. Update your Webpack configuration file (it's usually on webpack.config.js in the project root). ...
    Downloads: 0 This Week
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  • 3
    Nebula-Python-SDK

    Nebula-Python-SDK

    A python SDK for managing Nebula container orchestrator

    A python SDK for managing Nebula container orchestrator. First, get NebulaPythonSDK onto your machine, now use it in your code. Nebula container orchestrator aims to help devs and ops treat IoT devices just like distributed Dockerized apps. It aim is to act as Docker orchestrator for IoT devices as well as for distributed services such as CDN or edge computing that can span thousands (possibly even millions) of devices worldwide and it does it all while being open-source and completely free. ...
    Downloads: 0 This Week
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  • 4
    Javelina is an advanced code coverage tool that uses dynamic instrumentation to minimize the overhead for collecting coverage data. Additionally, Javelina allows the application of logical operations to code coverage data.
    Downloads: 0 This Week
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