Python Programming

RRDTool is a really good back-end for storing time-series data. If you are developing tools that need a data repository and graphing capabilities, this provides you both. You create an RRD and then you begin inserting data values at regular intervals. You then call the graphing API to have a graph displayed. The neat thing about this data storage is its “round robin” nature. You define various time spans, and the granularity at which you want them stored. A fixed binary file is created, which never grows in size over time. As you insert more data, it is inserted into each span. As results are collected, they are averaged and rolled into successive time spans. It makes a much more efficient system than using your own complex data structures, relational database, or file system storage.

For example edge labels can be added using matplotlib "text" objects like this: import networkx as nx import pylab as plot K=nx.XGraph(name="Konigsberg", multiedges=True, selfloops=False) K.add_edges_from([("A","B","Honey Bridge"),     ("A","B","Blacksmith's Bridge"),     ("A","C","Green Bridge"),     ("A","C","Connecting Bridge"),     ("A","D","Merchant's Bridge"),     ("C","D","High Bridge"),     ("B","D","Wooden Bridge")]) pos=nx.spring_layout(K) nx.draw_nx(K,pos) xa,ya=pos['A'] xb,yb=pos['B'] plot.text((xa+xb)/2,(ya+yb)/2,"Blacksmith's Bridge") plot.show() With a little work you can get the label rotated and exactly how you want it positioned.  You can also set the node positions directly in the "pos" dictionary above.

Pexpect does not currently work on the standard Windows Python

For drawing you can use pygraphviz (also available at networkx.lanl.gov) or the built-in drawing tools.

PyNGL (pronounced "pingle") is a Python language module used to visualize scientific data, with an emphasis on high quality 2D visualizations. A working knowledge of Python is assumed.

I wrote dbtxt because I needed a small, flat database in a python environment that didn't depend upon any external libraries. Most libraries are contaminated with the GPL, and this needed to be OK for commercial distribution without any complications. So that's what we have here - a complete (though small) database system that depends on nothing at all other than the Python language and its internal libraries. The entire database comes in at about 20k bytes (that's right, "k", not hundreds of k or megabytes) and I was able to implement all the functions I needed. So I was happy. Will you be happy? Well, download it and read the docs and see what you think. The download, zipped, is about 13k. Yep. 13k. :-) By all means, if you have a need for the same kind of thing, feel free to make any use of dbtxt you please. I have released it as PD, so you can use it in projects that are commercial, GPL, BSD, PD, private, government... whatever you like. Below you'll find a basic description taken from beginning of the docs; in the archive you'll download there is complete documentation, two sample databases, a test program and the database engine itself.

lternative: if your file has indent 4 and you want an indent of 3 and gg=G is not working as expected, try :set inde=indent(v:lnum)/4*3 then go ahead with the well known gg=G use tabs or spaces, doesn't matter

Replace globals with context-safe variables and services

When running "python test.py" the interpreter will first precompile the test.py source file, and then execute it. When running "python test.pyc", the interpreter will go straight to the execution of the script.

PQRC-2.4-A4-latest.pdf 30-Apr-2007 14:02 599K

""" a class for generating permutations from an array # choose 2 letters from 'abcd' c = Chooser(['a', 'b', 'c', 'd'], 2) while c.hasMoreElements(): print c.next() """ import time, copy class NoMoreChoices(StandardError): pass class Chooser:

>     Generate all ways to place n indistiguishable items into k >     distinguishable boxes

Mpmath is a pure-Python library for multiprecision floating-point arithmetic. It provides an extensive set of transcendental functions, unlimited exponent sizes, complex numbers, interval arithmetic, numerical integration and differentiation, root-finding, linear algebra, and much more. Almost any calculation can be performed just as well at 10-digit or 1000-digit precision, and in many cases mpmath implements asymptotically fast algorithms that scale well for extremely high precision work. If available, mpmath will (optionally) use gmpy to speed up high precision operations.

Neat script I wrote for a friend to annotate a Python script with the types observed during a run of the program

pylize is a Python script that makes the creation of on-screen presentations a matter of a few minutes. It generates a template master document, which you can edit with your favourite text or HTML editor. The master document is then processed by pylize to generate HTML files for every slide plus a file for the table of contents. You can view the presentation with any CSS-capable webbrowser.

PyScripter and most Python IDEs redirect sys.stdout.  Also GUI apps like PyScripter have no standard output.  What you need to do is PyObject *f = PySys_GetObject("stdout") and then use PyFile_WriteString for writing to the sys.stdout. This is what Python itself is doing and I think this is the best way

googlecalendarsync is a tool written in python to bidirectional synchronize a local iCal (.ics) file with Google Calendar