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IPython on resizeable Win32 Console If you are on win32, you might want to use Console, an open source replacement for that inflexible old win32 terminal. Here's how. Install IPython using the .exe installer. Download stable version of Console (1.5 at this time). Create a shortcut to console.exe, right-click -> properties. Set target to e.g. C:\opt\Console\console.exe -c "/k python c:\python25\scripts\ipython.py -p sh" you can also create a tab dedicated to Ipython (and have other dedicated to other shells or command-line app). go to edit->settings->tabs : click on the add button and fill the following fields : * title : ipython ico : C:\Python24\py.ico shell : cmd.exe /k "ipython" start-up dir : whatever is good for you. note that python.exe need to be in the path Using IPython with Version 2 of Console use the -r option for creating the shortcut, e.g. C:\opt\Console2\console.exe -r "/k python c:\python25\scripts\ipython.py -p sh" Some advantages of Console2 over normal console (for IPython use) Distinctive taskbar icon Can reside in system tray There are many other benefits, so it's well worth setting up Example config for Console-2.00b120-Beta (you need to edit the xml file): http://vvtools.googlecode.com/svn/trunk/config/console.xml If you have problems with ctrl+C killing Console2 immediately, launch ipython from a normal Console2 session manually.

This tutorial teaches the fundamental concepts of symbolic debuggers. We will be using Winpdb to debug Python scripts. The concepts that you learn here, however, are fundamental to working with debuggers in general. At the end of the exercise, you should feel comfortable with using symbolic debuggers and have an inherent understanding of why these tools prove to reduce time and effort needed in debugging without altering the code itself to do so.

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

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

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.

This is a project to develop a cross-platform pythonic GUI API.  The goals of this project are:

ProfitPy is a set of libraries and tools for the development, testing, and execution of automated stock trading systems Specifically, ProfitPy is a collection of Python packages, modules, and scripts that work together to help you implement an automated stock trading program (or programs). The package features: A library with classes for accounts, orders, tickers, and more A GUI program for executing and plotting trades in real-time A GUI tool to collect ticker data for off-line use A CLI tool to back-test trading strategies Dozens of technical indicators and plotting widgets to display them An X11 keystroke tool for automating the TWS application

Stackless Python is an alternative implementation of Python created by independent developer Christian Tismer. He started with the conventional Python language processor managed by the language's inventor, Guido van Rossum, and patched his own Stackless invention in place of a small but central part of Python's internals. Stackless Python is the result. This article introduces Tismer's technology and its significance. In future articles, you'll be able to read about how to make your own start at programming Stackless Python, as well as the prospects for a merger between Stackless and the main Python distribution.

In our last article on compression we showed you how to demonstrate run time encoding in Python. In this article we'll show you how to implement another kind of compression, Huffman encoding, which is useful when dealing with small sets of items, such as character strings.