5e0b6567cd
New bag implementation improves a lot how bonobo works, even if this is highly backward incompatible (sorry, that's needed, and better sooner than later). * New implementation uses the same approach as python's namedtuple, by dynamically creating the python type's code. This has drawbacks, as it feels like not the right way, but also a lot of benefits that cannot be achieved using a regular approach, especially the constructor parameter order, hardcoded. * Memory usage is now much more efficient. The "keys" memory space will be used only once per "io type", being spent in the underlying type definition instead of in the actual instances. * Transformations now needs to use tuples as output, which will be bound to its "output type". The output type can be infered from the tuple length, or explicitely set by the user using either `context.set_output_type(...)` or `context.set_output_fields(...)` (to build a bag type from a list of field names). Jupyter/Graphviz integration is more tight, allowing to easily display graphs in a notebook, or displaying the live transformation status in an html table instead of a simple <div>. For now, context processors were hacked to stay working as before but the current API is not satisfactory, and should be replaced. This new big change being unreasonable without some time to work on it properly, it is postponed for next versions (0.7, 0.8, ...). Maybe the best idea is to have some kind of "local services", that would use the same dependency injection mechanism as the execution-wide services. Services are now passed by keywoerd arguments only, to avoid confusion with data-arguments.
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🐵 bonobo
==========
Data-processing for humans.
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Bonobo is an extract-transform-load framework for python 3.5+ (see comparisons with other data tools).
Bonobo uses plain old python objects (functions, generators and iterators), allows them to be linked together in a directed graph, and then executed using a parallelized strategy, without having to worry about the underlying complexity.
Developers can focus on writing simple and atomic operations, that are easy to unit-test by-design, while the focus of the
framework is to apply them concurrently to rows of data.
One thing to note: write pure transformations and you'll be safe.
Bonobo is a young rewrite of an old python2.7 tool that ran millions of transformations per day for years on production.
Although it may not yet be complete or fully stable (please, allow us to reach 1.0), the basics are there.
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*Bonobo is under heavy development, we're doing our best to keep the core as stable as possible while still moving forward. Please allow us to reach 1.0 stability and our sincere apologies for anything we break in the process (feel free to complain on issues, allowing us to correct breakages we did not expect)*
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Homepage: https://www.bonobo-project.org/ (`Roadmap <https://www.bonobo-project.org/roadmap>`_)
Documentation: http://docs.bonobo-project.org/
Contributing guide: http://docs.bonobo-project.org/en/latest/contribute/index.html
Issues: https://github.com/python-bonobo/bonobo/issues
Slack: https://bonobo-slack.herokuapp.com/
Release announcements: http://eepurl.com/csHFKL
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Made with ♥ by `Romain Dorgueil <https://twitter.com/rdorgueil>`_ and `contributors <https://github.com/python-bonobo/bonobo/graphs/contributors>`_.
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