Celery - Distributed Task Queue — Celery v2.0.0 (stable) documentation. Navigation Documentation has moved Celery is now using Read the Docs to host the documentation for the development version, where the pages are automatically updated as new changes are made (YAY!)
The new location for this page is: If you wanted documentation for the latest stable version instead, please go to: PDF, Epub, and HTMLZip documents for every Celery version, including development -- is located here: This Page Show Source Quick search. Working with virtualenv — Arthur Koziel. SingleFileExecutable - py2exe.org.
The "extending" example that comes with Py2Exe shows a nicely integrated approach for using Inno Setup to create single file executables.
This example isn't so nicely integrated, but it uses NSIS instead of Inno Setup in case you prefer that. Drop a copy of this script in your source directory alongside setup.py and modify the first two lines. The first points to py2exe's output directory and the second is the name of the executable in that directory as well as the name of the executable that NSIS will create. You can also select compression behavior - NSIS' LZMA compression (based on 7-Zip) is pretty impressive - wxPython applications start at about 3.5 - 4 MB instead of 10 - 12 MB.
Compression may slow startup time for your executable somewhat. Once you've built your executable with py2exe, then compile the installer script with NSIS and an executable will be created in the same folder as the script. Pycron. Pycron Instructions A good introductory article about pycron can be found at "This article will discuss using a Cron type system, as used on Unix and Linux systems, to bring the flexibility, scalability and a need for more out of a task automation tool, to the Win32 environment.
" Juno: A Lightweight and Simple Web Framework. EasyExtend. Abstract EasyExtend is a constructive approach to extend the Python language using pure Python.
EasyExtend is developed as a Python framework depending only on tools provided by the CPython interpreter suite ( compiler ) and standard library as well as some pieces of code borrowed from the PyPy project. Opposite to toolkits for writing extension modules in C ( or RPython in future ) the EasyExtend framework is dedicated to extend the language itself by adding new grammar rules and transformation of parse trees. Acting directly on the nodes of syntax trees makes EasyExtend safe and extensible. Moreover the parser and the transformations are considerably fast.
Overview 0. How to find the source tree and what it contains. 1. Explains the very basics of EE - the world of CST surgery. 2. We need to label our extensions. 3. Ruby/Python Documentation. Python packaging: a few observations, cabal for a solution ? « Nothing to say. The python packaging situation has been causing quite some controversy for some time.
The venerable distutils has been augmented with setuptools, zc.buildout, pip, yolk and what not. Some people praise those tools, some other despise them; in particular, discussion about setuptools keeps coming up in the python community, and almost every time, the discussion goes nowhere, because what some people consider broken is a feature for the other. It seems to me that the conclusion of those discussions is obvious: no tool can make everybody happy, so there has to be a system such as different tools can be used for different usage, without intefering with each other. The solution is to agree on common format and data/metadata, so that people can build on it and communicate each other.
You can find a lot of information on people who like setuptools/eggs, and their rationale for it. Distutils limitation Most of those tools are built on top of distutils, which is a first problem. College: Computer Science: PIL (Python Imaging Library) PIL (aka the Python Imaging Library) is used in many of the Carleton College Intro CS courses.
NOTE: PIL is NOT available for Python 3. This page contains installation instructions for Python 2.x: Python Memory Management. Tracing Python memory leaks. While I was writing a python daemon, I noticed that my application process memory usage is growing over time. The data wasn’t increasing so there must have been some memory leak. It’s not so easy for a Python application to leak memory. Usually there are three scenarios: some low level C library is leaking your Python code have global lists or dicts that grow over time, and you forgot to remove the objects after use there are some reference cycles in your app I remembered the post from Marius Gedminas , in which he traced his memory leaks, but I haven’t noticed before that he published his tools .
Python's getattr : orestis.gr. An interesting question So, yesterday I was asked an interesting question: Int: Are you familiar with Python's getattr?
Me: Um, yes? Interviewer clarifies what it's all about Int: So I now want you to implement __getattr__ in such a way that when a method is called with the prefix print it'll print it's name before calling it. Step by step: Compiling extensions with MS Visual C++ Toolkit 2003 - msvccompiler-patch.txt (0/1)