Python: Lambda Functions Python supports the creation of anonymous functions (i.e. functions that are not bound to a name) at runtime, using a construct called "lambda". This is not exactly the same as lambda in functional programming languages, but it is a very powerful concept that's well integrated into Python and is often used in conjunction with typical functional concepts like filter(), map() and reduce(). This piece of code shows the difference between a normal function definition ("f") and a lambda function ("g"): As you can see, f() and g() do exactly the same and can be used in the same ways. Note that the lambda definition does not include a "return" statement -- it always contains an expression which is returned. The following code fragments demonstrate the use of lambda functions. The above code defines a function "make_inrementor" that creates an anonymous function on the fly and returns it. The following takes this a step further. In the second example, map() is used to convert our list.
How not to write Python code – Ikke's blog Lately I’ve been reading some rather unclean Python code. Maybe this is mainly because the author(s) of the code had no in-depth knowledge of the Python language itself, the ‘platform’ delivered with cPython,… Here’s a list of some of the mistakes you should really try to avoid when writing Python code: Some days ago RealNitro pointed me at this list of essential Python readings. That’s about it for now, maybe I’ll add some more items to this list later on. Posted in Development, Technology. Tagged with Development, python. By Nicolas – February 8, 2008
HowTo/Sorting Original version by Andrew Dalke with a major update by Raymond Hettinger Python lists have a built-in sort() method that modifies the list in-place and a sorted() built-in function that builds a new sorted list from an iterable. There are many ways to use them to sort data and there doesn't appear to be a single, central place in the various manuals describing them, so I'll do so here. Sorting Basics A simple ascending sort is very easy -- just call the sorted() function. >>> sorted([5, 2, 3, 1, 4]) [1, 2, 3, 4, 5] You can also use the list.sort() method of a list. >>> a = [5, 2, 3, 1, 4] >>> a.sort() >>> a [1, 2, 3, 4, 5] Another difference is that the list.sort() method is only defined for lists. Key Functions Starting with Python 2.4, both list.sort() and sorted() added a key parameter to specify a function to be called on each list element prior to making comparisons. For example, here's a case-insensitive string comparison: The same technique works for objects with named attributes.
PyPy Status Blog PEP 257 -- Docstring Conventions What is a Docstring? A docstring is a string literal that occurs as the first statement in a module, function, class, or method definition. Such a docstring becomes the __doc__ special attribute of that object. All modules should normally have docstrings, and all functions and classes exported by a module should also have docstrings. String literals occurring elsewhere in Python code may also act as documentation. String literals occurring immediately after a simple assignment at the top level of a module, class, or __init__ method are called "attribute docstrings".String literals occurring immediately after another docstring are called "additional docstrings". Please see PEP 258, "Docutils Design Specification" , for a detailed description of attribute and additional docstrings. XXX Mention docstrings of 2.2 properties. For consistency, always use """triple double quotes""" around docstrings. There are two forms of docstrings: one-liners and multi-line docstrings. Multi-line Docstrings
Planet Python guaranteed-stable sort with the decorate-sort-undecorate idiom ( "decorate-sort-undecorate" is a general and common idiom that allows very flexible and speedy sorting of Python sequences. An auxiliary list is first built (the 'decorate' step) where each item is made up of all sort-keys (in descending order of significance) of the corresponding item of the input sequence (must include all of the information in the whole corresponding item, and/or an index to it so we can fetch it back [or reconstruct it] in the third step). This is then sorted by its builtin sort method without arguments. Finally, the desired sorted-list is extracted/reconstructed by "undecorating" the now-sorted auxiliary-list. Steps 1 and 3 can be performed in several ways, with map, zip, list comprehensions, and explicit loops, all possible. This 'naturally' supplies a sorted _copy_, but if the input-sequence is a list we can just assign to its "include everything" slice to get in-place effect.
The Mouse Vs. The Python The Python Tutorial — Python v2.6.4 documentation Python is an easy to learn, powerful programming language. It has efficient high-level data structures and a simple but effective approach to object-oriented programming. Python’s elegant syntax and dynamic typing, together with its interpreted nature, make it an ideal language for scripting and rapid application development in many areas on most platforms. The Python interpreter and the extensive standard library are freely available in source or binary form for all major platforms from the Python web site, and may be freely distributed. The Python interpreter is easily extended with new functions and data types implemented in C or C++ (or other languages callable from C). This tutorial introduces the reader informally to the basic concepts and features of the Python language and system. For a description of standard objects and modules, see The Python Standard Library. The Glossary is also worth going through.