Search Results for "google-visualization-python"
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Showing 6 open source projects for "google-visualization-python"
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1
flom
Free Lock Manager
...FLoM supports different types of abstract resources: simple, numeric, set, hierarchical and transactional sequence. libflom, the library shipped with FLoM, allows you to develop your own application using a simple C, C++, Java, Perl, PHP or Python client API. SSL/TLS security for network communication, X.509 certificates for peer to peer mutual authentication. -
2
Scripting Language Bindings
A port of WFOPT to the several scripting languages
This project contains bindings for various scripting languages to the Wheefun Options Parsing Library. It is meant to provide parity with the C implementation so .NET languages can take advantage of WFOPT. For more information, please see the main page. -
3
Hacker Scripts
Based on a true story
...The README explains the origin story and highlights several canonical scripts and provides usage notes such as required environment variables and cron examples for scheduling. Contributors have provided implementations and ports in many languages and folders (shell, Ruby, Python, Node, Perl, PowerShell, Go, Java, etc.), and the project explicitly welcomes pull requests that add additional language implementations. -
4
PulledPork
Pulled Pork for Snort and Suricata rule management (from Google code)
PulledPork is a Perl-based script that automates the management of Snort and Suricata IDS/IPS rulesets. It streamlines the process of downloading, parsing, and updating rules, ensuring that intrusion detection systems remain current and effective. -
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5
XcodeCoverage
Code coverage for Xcode projects (Objective-C only)
XcodeCoverage is a tool that automates the generation of code coverage reports for iOS and macOS projects. It helps developers measure how much of their code is tested, facilitating better testing practices and coverage improvement. -
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Fast Artificial Neural Network Library is a free open source neural network library, which implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks. Cross-platform execution in both fixed and floating point are supported. It includes a framework for easy handling of training data sets. It is easy to use, versatile, well documented, and fast. Bindings to more than 15 programming languages are available. An easy to read...
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