Python Crash Course Functions, Modules 3 rd year Bachelors V1.0 dd Hour 5

Introduction to language - functions >>> def my_func(x, y=0.0, z=1.0):... a = x + y... b = a * z... return b... >>> my_func(1.0, 3.0, 2.0) 8.0 >>> my_func(1.0, 3.0) 4.0 >>> my_func(1.0, y=3.0) 4.0 >>> my_func(5.0) 5.0 >>> my_func(2.0, z=3.0) 6.0 >>> my_func(x=2.0, z=3.0) 6.0 Here are simple rules to define a function in Python: Function blocks begin with the keyword def followed by the function name and parentheses ( ). Any input parameters or arguments should be placed within these parentheses. You can also define parameters inside these parentheses. The code block within every function starts with a colon : and is indented. The statement return [expression] exits a function, optionally passing back an expression to the caller. A return statement with no arguments is the same as return None.

Introduction to language - functions >>> def fact(n):... if(n==0): return 1;... m = 1;... k = 1;... while(n >= k):... m = m * k;... k = k + 1;... return m; Recursion: >>> def fact(n):... if n > 0:... return n * fact(n-1) # Recursive call... return 1# exits function returning 1 >>> print fact(100) >>> print fact(1000)

Introduction to language - functions The Anonymous Functions: You can use the lambda keyword to create small anonymous functions. These functions are called anonymous because they are not declared by using the def keyword. Lambda forms can take any number of arguments but return just one value in the form of an expression. They cannot contain commands or multiple expressions. An anonymous function cannot be a direct call to print because lambda requires an expression. Lambda functions have their own local namespace and cannot access variables other than those in their parameter list and those in the global namespace. #!/usr/bin/python # Function definition is here sum = lambda arg1, arg2: arg1 + arg2; # Now you can call sum as a function print "Value of total : ", sum( 10, 20 ) print "Value of total : ", sum( 20, 20 ) Value of total : 30 Value of total : 40

Introduction to language - scope Variables defined within the function are local to the function. For variables referenced (by which we mean “used” i.e. on right hand side of assignment statement) in the function, interpreter looks first in the local symbol table, then outside (globally). >>> def fib(n):... # write Fibonacci series up to n... """Print a Fibonacci series up to n.""“... a, b = 0, 1... while a < n:... print a,... a, b = b, a+b... print x >>> x = “Hi there” >>> a = 11 >>> print a 11 >>> fib(2000) Hi there >>> print a 11

Introduction to language - arguments e.g. Arguments with default values: >>> def ask_ok(prompt, retries=4, complaint='Yes or no, please!'):... ”””Demonstrate default values”””... while True:... ok = raw_input(prompt)... if ok in ('y', 'ye', 'yes'):... return True... if ok in ('n', 'no', 'nop', 'nope'):... return False... retries = retries if retries < 0:... raise IOError('refusenik user')... print complaint

List comprehensions A neat way of creating lists (and arrays) without writing a loop a = [ x**2 for x in range(10)] my_fav_num = [3, 17, 22, 46, 71, 8] even_squared = [] for n in my_fav_num: if n%2 == 0: even_squared.append(n**2) # in one line: even_better = [n**2 for n in my_fav_num if n%2 == 0] # both produce [484, 2116, 64 freshfruit = [' banana', ' loganberry ', 'passion fruit '] stripped = [weapon.strip() for weapon in freshfruit] print(stripped) ['banana', 'loganberry', 'passion fruit']

Introduction to language - Modules def print_func( par ): print "Hello : ", par return #!/usr/bin/python # Import module hello import hello # Now you can call defined function that module as follows hello.print_func(“Earth") Hello : Earth from modname import name1[, name1[, … nameN]] from modname import * Importing into the current namespace should be done with care due to name clashes

Introduction to languge - Modules When you import a module, the Python interpreter searches for the module in the following sequences: The current directory. If the module isn't found, Python then searches each directory in the shell variable PYTHONPATH. If all else fails, Python checks the default path. On UNIX, this default path is normally /usr/local/lib/python/. The module search path is stored in the system module sys as the sys.path variable. The sys.path variable contains the current directory, PYTHONPATH, and the installation- dependent default. PYTHONPATH is an environment variable, consisting of a list of directories. The syntax of PYTHONPATH is the same as that of the shell variable PATH. /software/local/lib64/python2.7/site-packages

Introduction to language - modules Frequently used modules sys Information about Python itself (path, etc.) os Operating system functions os.path Portable pathname tools shutil Utilities for copying files and directory trees cmp Utilities for comparing files and directories glob Finds files matching wildcard pattern re Regular expression string matching time Time and date handling datetime Fast implementation of date and time handling doctest, unittest Modules that facilitate unit test

Introduction to language - modules More frequently used modules pdb Debugger hotshot Code profiling pickle, cpickle, marshal, shelve Used to save objects and code to files getopt, optparse Utilities to handle shell-level argument parsing math, cmath Math functions (real and complex) faster for scalars random Random generators (likewise) gzip read and write gzipped files struct Functions to pack and unpack binary data structures StringIO, cStringIO String-like objects that can be read and written as files (e.g., in-memory files) types Names for all the standard Python type

Introduction to language - modules Modules are searched for in the following places: the current working directory (for interactive sessions) the directory of the top-level script file (for script files) the directories defined in PYTHONPATH Standard library directories >>> # Get the complete module search path: >>> import sys >>> print sys.path

Introduction to language - modules Modules can contain any code Classes, functions, definitions, immediately executed code Can be imported in own namespace, or into the global namespace >>> import math >>> math.cos(math.pi) >>> math.cos(pi) Traceback (most recent call last): File " ", line 1, in NameError: name 'pi' is not defined >>> from math import cos, pi >>> cos(pi) >>> from math import *

Introduction to language - modules Use from...import and import...as with care. Both make your code harder to understand. Do not sacrifice code clearness for some keystrokes! In some cases, the use is acceptable: –In interactive work ( import math as m ) –If things are absolutely clear (e.g. all functions of an imported module obey a clear naming convention; cfits_xyz) import.. as : As last resort in case of name clashes between module names >>> from math import sin >>> print sin(1.0) >>> print cos(1.0) # won’t work >>> from math import * >>> # All attributes copied to global namespace Extremely dangerous >>> print tan(1.0)

Introduction to language - modules >>> import numpy >>> dir(numpy) ['ALLOW_THREADS', 'BUFSIZE', 'CLIP', 'ComplexWarning', 'DataSource', 'ERR_CALL', 'ERR_DEFAULT', 'ERR_DEFAULT2', 'ERR_IGNORE', 'ERR_LOG', 'ERR_PRINT', 'ERR_RAISE', 'ERR_WARN', 'FLOATING_POINT_SUPPORT', 'FPE_DIVIDEBYZERO', 'FPE_INVALID', 'FPE_OVERFLOW', 'FPE_UNDERFLOW', 'False_', 'Inf', 'Infinity', 'MAXDIMS', 'MachAr', 'NAN', 'NINF', 'NZERO', 'NaN', 'PINF', 'PZERO', 'PackageLoader', 'RAISE', 'RankWarning', 'SHIFT_DIVIDEBYZERO', 'SHIFT_INVALID', 'SHIFT_OVERFLOW', 'SHIFT_UNDERFLOW', 'ScalarType', 'Tester', 'True_', 'UFUNC_BUFSIZE_DEFAULT', 'UFUNC_PYVALS_NAME', 'WRAP', '__NUMPY_SETUP__', '__all__', '__builtins__', '__config__', '__doc__', '__file__', '__git_revision__', '__name__', '__package__', '__path__', '__version__', '_import_tools', '_mat', 'abs', 'absolute', 'add', 'add_docstring', 'add_newdoc', 'add_newdocs', 'alen', 'all', 'allclose', 'alltrue', 'alterdot', 'amax', 'amin', 'angle', 'any', 'append', 'apply_along_axis',... 'typeNA', 'typecodes', 'typename', 'ubyte', 'ufunc', 'uint', 'uint0', 'uint16', 'uint32', 'uint64', 'uint8', 'uintc', 'uintp', 'ulonglong', 'unicode', 'unicode0', 'unicode_', 'union1d', 'unique', 'unpackbits', 'unravel_index', 'unsignedinteger', 'unwrap', 'ushort', 'vander', 'var', 'vdot', 'vectorize', 'version', 'void', 'void0', 'vsplit', 'vstack', 'where', 'who', 'zeros', 'zeros_like'] Inspecting module methods

Introduction to language - modules >>> import numpy >>> numpy.random # Submodule >>> numpy.random.randn() # Function in submodule (Restart Python) >>> import numpy.random # Import submodule only >>> numpy.random.randn() (Restart Python) >>> from numpy import random # Alternative form >>> random.randn() (Restart Python) >>> from numpy.random import * # Previous warnings >>> randn() # apply here as well! Importing submodules

Your own package myMath/ __init__.py adv/ __init__.py sqrt.py add.py subtract.py multiply.py divide.py # outer __init__.py from add import add from divide import division from multiply import multiply from subtract import subtract from adv.sqrt import squareroot import mymath print mymath.add(4,5) print mymath.division(4, 2) print mymath.multiply(10, 5) print mymath.squareroot(48)) # add.py def add(x, y): """""" return x + y The main difference between a module and a package is that a package is a collection of modules AND it has an __init__.py file. # sqrt.py import math def squareroot(n): """""" return math.sqrt(n)

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