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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.

In short: run your existing Python software much faster, with no change in your source. Think of Psyco as a kind of just-in-time (JIT) compiler, a little bit like what exists for other languages, that emit machine code on the fly instead of interpreting your Python program step by step. The difference with the traditional approach to JIT compilers is that Psyco writes several version of the same blocks (a block is a bit of a function), which are optimized by being specialized to some kinds of variables (a "kind" can mean a type, but it is more general). The result is that your unmodified Python programs run faster. Benefits 2x to 100x speed-ups, typically 4x, with an unmodified Python interpreter and unmodified source code, just a dynamically loadable C extension module. Drawbacks Psyco currently uses a lot of memory. It only runs on Intel 386-compatible processors (under any OS) right now. There are some subtle semantic differences (i.e. bugs) with the way Python works; they should not be apparent in most programs.

GUESS is an exploratory data analysis and visualization tool for graphs and networks. The system contains a domain-specific embedded language called Gython (an extension of Python, or more specifically Jython) which supports the operators and syntactic sugar necessary for working on graph structures in an intuitive manner. An interactive interpreter binds the text that you type in the interpreter to the objects being visualized for more useful integration. GUESS also offers a visualization front end that supports the export of static images and dynamic movies

PyACTS- http://www.pyacts.org -- PyACTS is a collection of Python Modules that are very useful to Parallel Computing in a High Performance Computing environment. This packages incorporates several modules like PyBLACS (allows communication data for Linear Algebra), PyPBLAS (distributed Matrix Operations) and PyScaLAPACK (solve linear systems and get the eigenvalue problems). These libraries are part of PyACTS project that provide interfaces to the ACTS Collection. Also is provided a parrallel interpreter for using this package that implements message-based parallel programming using MPI.

Pypar does not require the Python interpreter to be modified or recompiled: Parallel python programs use the standard Python and need merely import the pypar module. This means for example that you can upgrade Python independently of your parallel codes.

Pypar is an efficient but easy-to-use module that allows programs/scripts written in the Python programming language to run in parallel on multiple processors and communicate using message passing. Pypar provides bindings to an important subset of the message passing interface standard MPI. Other Python MPI bindings available from other developers include: PyMPI, Scientific Python and pythonMPI.

interpreter:>>>import matplotlib>>>matplotlib.interactive(True)>>>matplotlib.use("WXAgg")>>>from matplotlib.pylab import *>>>plot([1,2,3])>>>xlabel('time (s)') 

 > 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.

Install using binary installer Download installer from http://ipython.scipy.org/dist/pyreadline-1.3.win32.exe make sure no other readline is installed run installer The configuration file pyreadlineconfig.ini can be copied from Python24/lib/site-packages/pyreadline/configuration to your HOME directory (usually c:/documents and settings/YOURNAME). When using ipython pyreadline is automatically activated. If you want to use pyreadline from the interactive prompt of the python interpreter then you have to include the code in Python24/lib/site-packages/pyreadline/configuration/startup.py in your pythonstartup file or set the PYTHONSTARTUP environment variable to point to that file. Manual can be found in Python24/share/doc/pyreadline

pyobfuscate is a source code obfuscator: It makes Python source code hard to read for humans, while still being executable for the Python interpreter. For more information, see the README.