Python Programming

my Python threads programming tutorial

Eric is a full featured Python and Ruby editor and IDE, written in python. It is based on the cross platform Qt gui toolkit, integrating the highly flexible Scintilla editor control. It is designed to be usable as everdays' quick and dirty editor as well as being usable as a professional project management tool integrating many advanced features Python offers the professional coder. Current stable version is eric4 based on Qt4. For Qt3 based systems eric3 is still available.

StatPy: Statistical Computing with Python Welcome to StatPy, a collection of resources to help you do statistical computing with Python, with a special emphasis on astrostatistics (statistics in astronomy). This web site is brand-spanking-new, and still very much under construction; please be patient with our "dust" and check back again frequently as building continues.

Pycha is a very simple Python package for drawing charts using the great Cairo library. Its goals are: Lightweight Simple to use Nice looking with default values Customization It won't try to draw any possible chart on earth but draw the most common ones nicely. There are some other options you may want to look at like pyCairoChart Pycha is based on Plotr which is based on PlotKit. Both libraries are written in JavaScript and are great for client web programming. I needed the same for the server side so that's the reason I ported Plotr to Python. Now we can deliver charts to people with JavaScript disabled or embed them in PDF reports.

Testoob is an advanced unit testing framework for Python. It integrates effortlessly with existing PyUnit (module ‘unittest’) test suites.

There are two applications that require using the NumPy array type in C extension modules: Access to numerical libraries: Extension modules can be used to make numerical libraries written in C (or languages linkable to C, such as Fortran) accessible to Python programs. The NumPy array type has the advantage of using the same data layout as arrays in C and Fortran. Mixed-language numerical code: In most numerical applications, only a small part of the total code is CPU time intensive. Only this part should thus be written in C, the rest can be written in Python. NumPy arrays are important for the interface between these two parts, because they provide equally simple access to their contents from Python and from C. This document is a tutorial for using NumPy arrays in C extensions.

This is something I always forget how to do, and it's kind of hard to Google or search the Python docs because you can't search for **.The point is, when using **kwargs, you have to use the ** prefix not only in the function definition, but also in the call, prefixed to the variable you want to use as a keyword dictionary.

Charming Python: Using state machinesAlgorithms and programming approaches in Python

> Is there a way to find the number of processors on a machine (on linux/ > windows/macos/cygwin) using python code (using the same code/cross > platform code)? From processing <http://cheeseshop.python.org/pypi/processing/0.34> : def cpuCount():     '''     Returns the number of CPUs in the system     '''     if sys.platform == 'win32':         try:             num = int(os.environ['NUMBER_OF_PROCESSORS'])         except (ValueError, KeyError):             pass     elif sys.platform == 'darwin':         try:             num = int(os.popen('sysctl -n hw.ncpu').read())         except ValueError:             pass     else:         try:             num = os.sysconf('SC_NPROCESSORS_ONLN')         except (ValueError, OSError, AttributeError):             pass     if num >= 1:         return num     else:         raise NotImplementedError --

 > According to the fact that all Thread run on the same CPU (if i didn't  > understand wrong), i'm asking if python will suffer from the future  > multicore CPU. Will not python use only one core, then a half or a  > quarter of CPU ? It could be a serious problem for the future of python... I agree that it could potentially be a serious hindrance for cpython if "multiple core" CPUs become commonplace. This is in contrast to jython and ironpython, both of which support multiple-cpu parallelism. Although I completely accept the usual arguments offered in defense of the GIL, i.e. that it isn't a problem in the great majority of use cases, I think that position will become more difficult to defend as desktop CPUs sprout more and more execution pipelines. I think that this also fits in with AM Kuchling's recent musing/thesis/prediction that the existing cpython VM may no longer be in use in 5 years, and that it may be superceded by python "interpreters" running on top of other VMs, namely the JVM, the CLR, Smalltalk VM, Parrot, etc, etc, etc. http://www.amk.ca/diary/archives/cat_python.html#003382 I too agree with Andrew's basic position: the Python language needs a period of library consolidation. There is so much duplication of functionality out there, with the situation only getting worse as people re-invent the wheel yet again using newer features such generators, gen-exps and decorators.

Few programming languages provide direct support for graphs as a data type, and Python is no exception. However, graphs are easily built out of lists and dictionaries. For instance, here's a simple graph (I can't use drawings in these columns, so I write down the graph's arcs):

Charming Python: SimPy simplifies complex models

SendKeys SendKeys(keys, pause = 0.05, with_spaces = False, with_tabs = False, with_newlines = False, turn_off_numlock = True) Parameters keys : str A string of keys. pause : float The number of seconds to wait between sending each key or key combination. with_spaces : bool Whether to treat spaces as {SPACE}. If False, spaces are ignored. with_tabs : bool Whether to treat tabs as {TAB}. If False, tabs are ignored. with_newlines : bool Whether to treat newlines as {ENTER}. If False, newlines are ignored. turn_off_numlock : bool Whether to turn off NUMLOCK before sending keys.

Key Code BACKSPACE {BACKSPACE}, {BS}, or {BKSP} BREAK {BREAK} CAPS LOCK {CAPSLOCK} or {CAP} DEL or DELETE {DELETE} or {DEL} DOWN ARROW {DOWN} END {END} ENTER {ENTER} or ~ ESC {ESC} HELP {HELP} HOME {HOME} INS or INSERT {INSERT} or {INS} LEFT ARROW {LEFT} NUM LOCK {NUMLOCK} PAGE DOWN {PGDN} PAGE UP {PGUP} PRINT SCREEN {PRTSC} RIGHT ARROW {RIGHT} SCROLL LOCK {SCROLLLOCK} SPACE BAR {PACE} TAB {TAB} UP ARROW {UP} F1 {F1} F2 {F2} F3 {F3} F4 {F4} F5 {F5} F6 {F6} F7 {F7} F8 {F8} F9 {F9} F10 {F10} F11 {F11} F12 {F12} F13 {F13} F14 {F14} F15 {F15} F16 {F16} F17 {F17} F18 {F18} F19 {F19} F20 {F20} F21 {F21} F22 {F22} F23 {F23} F24 {F24} Keypad add {ADD} Keypad subtract {SUBTRACT} Keypad multiply {MULTIPLY} Keypad divide {DIVIDE} Left Windows(R) {LWIN} Right Windows(R) {RWIN}