Showing 8 open source projects for "robot framework test data"

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  • 1
    Robot Framework

    Robot Framework

    Generic automation framework for acceptance testing and RPA

    Robot Framework is a generic open source automation framework. It can be used for test automation and robotic process automation (RPA). Robot Framework is supported by Robot Framework Foundation. Many industry-leading companies use the tool in their software development. Robot Framework is open and extensible. Robot Framework can be integrated with virtually any other tool to create powerful and flexible automation solutions. ...
    Downloads: 3 This Week
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  • 2
    Union Pandera

    Union Pandera

    Light-weight, flexible, expressive statistical data testing library

    The open-source framework for precision data testing for data scientists and ML engineers. Pandera provides a simple, flexible, and extensible data-testing framework for validating not only your data but also the functions that produce them. A simple, zero-configuration data testing framework for data scientists and ML engineers seeking correctness. Access a comprehensive suite of built-in tests, or easily create your own validation rules for your specific use cases. ...
    Downloads: 1 This Week
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  • 3
    Mobly

    Mobly

    E2E test framework for tests with complex environment requirements

    Mobly is a Python-based test framework that specializes in supporting test cases that require multiple devices, complex environments, or custom hardware setups. P2P data transfer between two devices. Conference calls across three phones. Wearable device interacting with a phone. Internet-Of-Things devices interacting with each other. Testing RF characteristics of devices with special equipment.
    Downloads: 0 This Week
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  • 4
    PaddleX

    PaddleX

    PaddlePaddle End-to-End Development Toolkit

    ...When the model is trained, we need to divide the training set, the validation set and the test set. Therefore, we need to divide the above data. Using the paddlex command, the data set can be randomly divided into 70% training set, 20% validation set and 10% test set. If you use the PaddleX visualization client for model training, the data set division function is integrated in the client, and you do not need to use command division by yourself.
    Downloads: 0 This Week
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  • 5
    Blankly

    Blankly

    Easily build, backtest and deploy your algo in just a few lines

    ​Blankly is a live trading engine, backtest runner and development framework wrapped into one powerful open-source package. Models can be instantly backtested, paper traded, sandbox tested and run live by simply changing a single line. We built blankly for every type of quant including training & running ML models in the same environment, cross-exchange/cross-symbol arbitrage, and even long/short positions on stocks (all with built-in WebSockets). Blankly is the first framework to enable...
    Downloads: 0 This Week
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  • 6

    PortablePythonWithRobot

    Portable Python with Robot Framework (for Magik testing)

    This fork of Portable Python has provided a portable Robot Framework (test automation) installation on window systems, named PortablePythonWithRobot (PPR). It is not maintained anymore, cause it is nowadays much easier to install a collection of robot modul using a virtualenv and pip or pipenv.
    Downloads: 0 This Week
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  • 7
    Robot Framework FTP Library

    Robot Framework FTP Library

    FTP client for Robot Framework

    SOURCE CODE MOVED TO https://github.com/kowalpy/Robot-Framework-FTP-Library . NEW RELEASES WILL APPEAR ONLY AT GITHUB AND PYPI. This Python library makes it possible to test or use FTP server using Robot Framework keywords. Together with the library, there are also available project example and keywords documentation created by libdoc. This sourceforge webpage is linked from http://robotframework.org/#test-libraries as external library so it can be considered as the official Robot Framework library.
    Downloads: 0 This Week
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  • 8
    aim is to provide support for monitoring system behaviour through dynamic analysis, and for analysing and modeling this data for a better understanding of system behaviour and for test automation
    Downloads: 0 This Week
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