============= pyleaf README
pyleaf is the Python implementation of the Leaf system. The Leaf system is a pipeline (AKA data flow or data analysis protocol) management system that allows to design the pipeline as an ASCII-art diagram through a language called LGL (Leaf Graph Language, see https://github.com/franapoli/lglc - also see INSTALL paragraph below).
Please consider the reference below to cite Leaf if you are using it. The paper is also a good introductory guide.
Napolitano, F., Mariani-Costantini, R., Tagliaferri, R., 2013. Bioinformatic pipelines in Python with Leaf. BMC Bioinformatics 14, 201.
- Thin, lightweight, code-independent Abstraction Layer.
- Data flow graph embedded directly into Python source code.
- Automatic creation and management of variables associated with node outputs.
- Automatic persistent storage and retrieval of node outputs.
- Session persistence (i.e. run half project, reboot machine, automatically start again from the last processed node).
- Lazy builds (avoid running nodes that are not necessary for the build of a requested resource).
- Multiprocessing (independent nodes run in parallel).
- Enforcement of code version consistency between nodes (i.e. automatically reprocess all nodes deriving from node A if node A is found to be changed).
- Automatic time and space requirements statistics.
- Automatic publishing (producing hypertext with visual representation of the protocol, processing statistics, link to node outputs, node documentation and source code).
/ regression -> plots [F] getData < \ / @plots .< \ exportCSV [F]
pyleaf requires lglc. Precompiled Windows and Linux binaries are available at:
C++ sources from:
To install pyleaf:
python setup.py install
You may require administrator rights.
Please check the "doc" directory (if this is part of a source distribution you may need to build the documentation, see "site_and_doc" directory). You may also want to start with the tutorial "ex1_tut.txt" in the directory "samples".