Abstract workflows for distributed data-intensive applications
dispel4py is a free and open-source Python library for describing abstract stream-based workflows for distributed data-intensive applications. It enables users to focus on their scientific methods, avoiding distracting details and retaining flexibility over the computing infrastructure they use. It delivers mappings to diverse computing infrastructures, including cloud technologies, HPC architectures and specialised data-intensive machines, to move seamlessly into production with large-scale data loads. The dispel4py system maps workflows dynamically onto multiple enactment systems, such as MPI, STORM and Multiprocessing, without users having to modify their workflows.
Among all the features of dispel4py we would like highlight the following ones:
What makes dispel4py different from other workflow systems is that it is built on the strength and familiarity of Python, it gains from many available scientific libraries, and it uses the tools that users normally use to program. It operates on data units in data streams rather than tasks on files and processes run continuously and concurrently coupled by streams. It can therefore deal with continuous data streams from observations, as well as handle finite streams from archives.
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|File Name & Checksum SHA256 Checksum Help||Version||File Type||Upload Date|
|dispel4py-1.2.1-py2.py3-none-any.whl (80.5 kB) Copy SHA256 Checksum SHA256||any||Wheel||Dec 6, 2016|
|dispel4py-1.2.1.tar.gz (42.3 kB) Copy SHA256 Checksum SHA256||–||Source||Dec 6, 2016|