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title: Parsl A Parallel Scripting Library for Python
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             <h1>Productive parallel programming in Python</h1>
             <p>Use Parsl to create parallel programs composed of Python functions and external components. Execute Parsl programs on any compute resource from laptops to supercomputers.</p>
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            <h2><a href='parslfest/parslfest2024.html' style="color: white;">ParslFest 2024 Talk Recordings Now Available for Viewing</a></h2>
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            <h2>Try Parsl</h2>
            <p>Try Parsl tutorials in our hosted Jupyter notebooks. No installation required!</p>
            <p><a class="btn btn-secondary" href="https://mybinder.org/v2/gh/Parsl/parsl-tutorial/master" role="button">Try now »</a></p>
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            <h2>Install Parsl</h2>
            <p>Pip install Parsl or checkout Parsl from source.</p>
            <p><a class="btn btn-secondary" href="https://parsl.readthedocs.io/en/stable/quickstart.html" role="button">Quickstart »</a></p>
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            <h2>Contribute</h2>
            <p>View, fork, and contribute to the open source Parsl on GitHub.</p>
            <p><a class="btn btn-secondary" href="https://github.com/Parsl/parsl" role="button">View source »</a></p>
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            <h2 class="featurette-heading">Pure Python. <span class="text-muted">Easily parallelize Python code.</span></h2> 
            <p class="lead">Parsl provides an intuitive, pythonic way of parallelizing codes by annotating "apps": Python functions or external applications that run concurrently. Natural parallel programming!</p>
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            <h2 class="featurette-heading">Implicit dataflow. <span class="text-muted">Apps execute concurrently while respecting data dependencies.</span></h2> 
            <p class="lead">Parsl creates a dynamic graph of tasks and their data dependencies. Tasks are only executed when their dependencies are met.</p>
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            <h2 class="featurette-heading">Scalable Jupyter notebooks. <span class="text-muted">Easily manage execution across distributed resources.</span></h2>
            <p class="lead">Parsl works seamlessly with Jupyter notebooks allowing apps within a notebook to be executed in parallel and on remote resources.</p>
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            <h2 class="featurette-heading">Write once, run anywhere. <span class="text-muted">From laptops to supercomputers.</span></h2>
            <p class="lead">Parsl scripts are independent of the execution environment. A single script can be executed on one or more execution resources without modifying the script.</p>
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