====== Python ====== * [[notes:py:inst|Installation]] * [[notes:urls:py:net|Python and networks and graphs]] * [[notes:urls:py:vis|Python and Visualization]] * [[notes:urls:py:dan|Python and Data analysis]] * [[notes:urls:py:ipy|iPython]] * [[notes:urls:py:int|Python and Internet]] ===== Mix ===== What order of magnitude are you going to be working on? Thousands of elements? Millions? Boost is linked to your code like any other library, you might want to have a look at: http://www.boost.org/doc/libs/1_39_0/more/getting_started/unix-variants.html Other than this, you might want to have a look at Networkx, or iGraph (for Python) for rapid prototyping purposes, if you want to quickly test an algorithm (https://networkx.github.io/ and http://igraph.org/redirect.html). I have used Networkx with datasets of a few hundred thousand nodes without any problems. Other than this, graphviz can be used to visualise graphs with millions of nodes but you are going to need a machine with a lot of memory (>6GB). Typical rendering times for such tasks might go well over 2hrs (http://www.graphviz.org/ and http://yifanhu.net/GALLERY/GRAPHS/index.html). ===== Text analysis ===== * http://blog.aylien.com/post/102959410858/text-analysis-and-python-getting-started-with * http://nlp.stanford.edu/software/corenlp.shtml , https://github.com/brendano/stanford_corenlp_pywrapper ===== Software ===== * http://snap.stanford.edu/snappy/ * https://networkit.iti.kit.edu/ ; http://parco.iti.kit.edu ===== Examples ===== * https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=31628 ===== Mixed ===== ===== Compare ===== * http://www.r-bloggers.com/fastest-growing-software-for-scholarly-analytics-python-r-knime/ * http://blog.udacity.com/2015/01/python-vs-r-learn-first.html * http://ucanalytics.com/blogs/r-vs-python-comparison-and-awsome-books-free-pdfs-to-learn-them/ * http://blog.datacamp.com/r-or-python-for-data-analysis/ * http://ucanalytics.com/blogs/r-vs-python-comparison-and-awsome-books-free-pdfs-to-learn-them/ * http://blog.datacamp.com/r-or-python-for-data-analysis/ * http://siliconangle.com/blog/2015/06/15/databricks-updates-spark-with-support-for-r-and-python-3/ ===== Mixed ===== * Scott Weingart: [[http://www.scottbot.net/HIAL/?p=6279|Nets intro]], [[http://www.scottbot.net/HIAL/?page_id=39166|Knowledge]] * http://stackoverflow.com/questions/9402255/drawing-a-huge-graph-with-networkx-and-matplotlib * http://lachlanblackhall.com/wp-content/uploads/2014/08/Graphs-Networks-and-Python.pdf * http://sociograph.blogspot.com/2012/11/visualizing-adjacency-matrices-in-python.html * https://github.com/jsexauer/networkx_viewer * https://www.wakari.io/sharing/bundle/twneale/Citation%20Network%20Analysis * Bogotobogo: [[http://www.bogotobogo.com/python/python_graph_data_structures.php|Graph DS]], [[http://www.bogotobogo.com/python/python_Dijkstras_Shortest_Path_Algorithm.php|Dijkstra]], [[http://www.bogotobogo.com/python/python_Prims_Spanning_Tree_Data_Structure.php|Prim]] * http://www.pyret.org/ * http://en.wikipedia.org/wiki/Python_%28programming_language%29 * https://www.bluecoat.com/security-blog/2014-06-10/snake-grass-python-based-malware-used-targeted-attacks * [[http://nealcaren.github.io/|New site]], [[http://nealcaren.github.io/python-tutorials/|Tutorials]] * https://pypi.python.org/pypi/pip , https://pypi.python.org/pypi?:action=browse&c=533&show=all * http://pydoc.net/Python/palabra/0.1.7/ * http://pythontutor.com/ * http://interactivepython.org/runestone/static/pythonds/index.html * http://www.sympy.org/en/index.html * http://stackoverflow.com/questions/6234252/how-to-embed-lua-inside-python * https://pypi.python.org/pypi/lupa * https://github.com/bastibe/lunatic-python * https://conferences.matheo.si/conferenceDisplay.py?confId=6 * http://bokeh.pydata.org/en/latest/ * https://pypi.python.org/pypi/GraphLab-Create * https://docs.python.org/3/library/time.html * http://docs.h5py.org/en/latest/ * http://zvonka.fmf.uni-lj.si/netbook/doku.php?id=book:pynet:text:idx * http://www.mdpi.com/journal/algorithms * * [[http://stackoverflow.com/questions/8677376/draw-a-weighted-complex-network-with-networkx|Draw a weighted complex network with Networkx]] * [[http://qt-apps.org/content/show.php/Social+Networks+Visualizer?content=97698|Social+Networks+Visualizer]] * [[http://flowingdata.com/2012/08/02/how-to-make-an-interactive-network-visualization/|How to make an interactive network visualization]] * [[http://nodebox.net/code/index.php/Graph|Graph]] * [[http://snipplr.com/view/1950/graph-javascript-framework-version-001/|graph javascript framework]] * http://graph-tool.skewed.de/ * [[http://www.python-course.eu/networkx.php|Networkx python course]] * [[http://networkx.lanl.gov/index.html|Networkx]] * [[http://www.cl.cam.ac.uk/~cm542/teaching.html|STNA]]; [[http://www.cl.cam.ac.uk/~cm542/teaching/2011/stna-pdfs/|2011]]; [[http://www.cl.cam.ac.uk/teaching/1314/L109/materials.html|2013/14]] * [[http://sourceforge.net/projects/dia-installer/|Dia]] * [[http://www.slideshare.net/arnicas/a-quick-and-dirty-intro-to-networkx-and-d3|A quick and dirty intro to Networkx and d3]] * http://mlg.ucd.ie/ * http://snap.stanford.edu/class/cs224w-2012/nx_tutorial.pdf * http://felix-kling.de/JSNetworkX/ * http://www.elifulkerson.com/projects/python-subnet-allocator.php * http://www.tutorialspoint.com/python/tk_canvas.htm * http://sbml.org/Software/libSBML/docs/python-api/group__layout.html * https://devcharm.com/articles/tag/python/ * https://devcharm.com/articles/202/python-for-data-analysis/ * http://search.cpan.org/~pasky/Graph-Layderer-0.03/ * http://guides.library.duke.edu/content.php?pid=383688&sid=3143980 * http://www.damiantrilling.net/downloads/py_for_cs.pdf * http://docs.python-guide.org/en/latest/scenarios/scrape/ * http://badhessian.org/category/python/ * http://www2.imm.dtu.dk/pubdb/views/edoc_download.php/5781/pdf * http://people.compute.dtu.dk/faan/fnielsenlife.html#Python%20programming * http://neuro.imm.dtu.dk/wiki/Finn_%C3%85rup_Nielsen * http://people.compute.dtu.dk/faan/ * https://www.kevinsheppard.com/images/0/09/Python_introduction.pdf * ===== Unicode ===== * http://unicode.org/ * https://en.wikipedia.org/wiki/Unicode * https://en.wikipedia.org/wiki/UTF-8 * BabelPad: http://www.babelstone.co.uk/Software/BabelPad.html * SC UniPad: http://www.unipad.org/main/