///Learn Python in 10 Minutes

Learn Python in 10 Minutes

Learn Python

Preliminary fluff

So, you want to learn the Python programming language
but can’t find a concise and yet full-featured tutorial. This tutorial
will attempt to teach you Python in 10 minutes. It’s probably not so
much a tutorial as it is a cross between a tutorial and a cheatsheet,
so it will just show you some basic concepts to start you off.
Obviously, if you want to really learn a language you need to program
in it for a while. I will assume that you are already familiar with
programming and will, therefore, skip most of the non-language-specific
stuff. The important keywords will be highlighted so you can easily spot them. Also, pay attention because, due to the terseness of this tutorial, some things will be introduced directly in code and only briefly commented on.

Properties

Python is strongly typed (i.e. types are enforced), dynamically, implicitly typed (i.e. you don’t have to declare variables), case sensitive (i.e. var and VAR are two different variables) and object-oriented (i.e. everything is an object).

Syntax

Python has no mandatory statement termination characters and blocks are specified by indentation. Indent in to begin a block, indent out to end one. Statements that expect an indentation level end in a colon (:). Comments start with the pound (#) sign and are single-line, multi-line strings are used for multi-line comments. Values are assigned with the equals sign ("="), and equality testing is done using two equals
signs ("=="). You can increment/decrement values using the += and -=
operators respectively. This works on many datatypes, strings included.
You can also use multiple variables on one line. For example:

>>> myvar = 3
>>> myvar += 2
>>> myvar -= 1
"""This is a multiline comment.
The following lines concatenate the two strings."
""
>>> mystring = "Hello"
>>> mystring += " world."
>>> print mystring
Hello world.
# This swaps the variables in one line(!).
>>> myvar, mystring = mystring, myvar

Data types

The data structures available in python are lists, tuples and dictionaries. Sets are available in the sets
library. Lists are like one-dimensional arrays (but you can also have
lists of other lists), dictionaries are associative arrays (a.k.a. hash
tables) and tuples are immutable one-dimensional arrays (Python
"arrays" can be of any type, so you can mix e.g. integers, strings, etc
in lists/dictionaries/tuples). The first item in all array types is 0.
Negative numbers count from the end towards the beginning, -1 is the
last item. Variables can point to functions. The usage is as follows:

>>> sample = [1, ["another", "list"], ("a", "tuple")]
>>> mylist = ["List item 1", 2, 3.14]
>>> mylist[0] = "List item 1 again"
>>> mylist[-1] = 3.14
>>> mydict = {"Key 1": "Value 1", 2: 3, "pi": 3.14}
>>> mydict["pi"] = 3.15
>>> mytuple = (1, 2, 3)
>>> myfunction = len
>>> print myfunction(mylist)
3

You can access array ranges
using a colon (:). Leaving the start index empty assumes the first
item, leaving the end index assumes the last item. Negative indexes
count from the last item backwards (thus -1 is the last item) like so:

>>> mylist = ["List item 1", 2, 3.14]
>>> print mylist[:]
['List item 1', 2, 3.1400000000000001]
>>> print mylist[0:2]
['List item 1', 2]
>>> print mylist[-3:-1]
['List item 1', 2]
>>> print mylist[1:]
[2, 3.14]

Strings

Its strings can use either single or double quotation marks,
and you can have quotation marks of one kind inside a string that uses
the other kind (i.e. "He said 'hello'." is valid). Multiline strings
are enclosed in triple double (or single) quotes ("""). Python supports Unicode out of the box, using the syntax u"This is a unicode string". To fill a string with values,
you use the % (modulo) operator and a tuple. Each %s gets replaced with
an item from the tuple, left to right, and you can also use dictionary
substitutions, like so:

>>>print "Name: %s\nNumber: %s\nString: %s" % (myclass.name, 3, 3 * "-")
Name: Poromenos
Number: 3
String: ---
 
strString = """This is
a multiline
string."
""
 
# WARNING: Watch out for the trailing s in "%(key)s".
>>> print "This %(verb)s a %(noun)s." % {"noun": "test", "verb": "is"}
This is a test.

Flow control statements

Flow control statements are while, if, and for. There is no select; instead, use if. Use for to enumerate through members of a list. To obtain a list of numbers, use range(<number>). These statements' syntax is thus:

rangelist = range(10)
>>> print rangelist
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
for number in rangelist:
# Check if number is one of
# the numbers in the tuple.
if number in (3, 4, 7, 9):
# "Break" terminates a for without
# executing the "else" clause.
break
else:
# "Continue" starts the next iteration
# of the loop. It's rather useless here,
# as it's the last statement of the loop.
continue
else:
# The "else" clause is optional and is
# executed only if the loop didn't "break".
pass # Do nothing
 
if rangelist[1] == 2:
print "The second item (lists are 0-based) is 2"
elif rangelist[1] == 3:
print "The second item (lists are 0-based) is 3"
else:
print "Dunno"
 
while rangelist[1] == 1:
pass

Functions

Functions are declared with the "def" keyword. Optional arguments are set in the function declaration after the mandatory arguments by being assigned a default value. For named arguments,
the name of the argument is assigned a value. Functions can return a
tuple (and using tuple unpacking you can effectively return multiple values). Lambda functions are ad hoc functions that are comprised of a single statement. Parameters are passed by reference, but mutable types (tuples, lists, ints, strings, etc) cannot be changed. For example:

# arg2 and arg3 are optional, they have default values
# if one is not passed (100 and "test", respectively).
def myfunction(arg1, arg2 = 100, arg3 = "test"):
return arg3, arg2, arg1
 
>>>ret1, ret2, ret3 = myfunction("Argument 1", arg3 = "Named argument")
# Using "print" with multiple values prints them all, separated by a space.
>>> print ret1, ret2, ret3
Named argument 100 Argument 1
 
# Same as def f(x): return x + 1
functionvar = lambda x: x + 1
>>> print functionvar(1)
2

Classes

Python supports a limited form of multiple inheritance in classes. Private variables and methods
can be declared (by convention, this is not enforced by the language)
by adding at least two leading underscores and at most one trailing one
(e.g. "__spam"). We can also assign arbitrary variables to class instances. An example follows:

class MyClass:
common = 10
def __init__(self):
self.myvariable = 3
def myfunction(self, arg1, arg2):
return self.myvariable
 
# This is the class instantiation
>>> classinstance = MyClass()
>>> classinstance.myfunction(1, 2)
3
# This variable is shared by all classes.
>>> classinstance2 = MyClass()
>>> classinstance.common
10
>>> classinstance2.common
10
# Note how we use the class name
# instead of the instance.
>>> MyClass.common = 30
>>> classinstance.common
30
>>> classinstance2.common
30
# This will not update the variable on the class,
# instead it will create a new one on the class
# instance and assign the value to that.
>>> classinstance.common = 10
>>> classinstance.common
10
>>> classinstance2.common
30
>>> MyClass.common = 50
# This has not changed, because "common" is
# now an instance variable.
>>> classinstance.common
10
>>> classinstance2.common
50
 
# This class inherits from MyClass. Multiple
# inheritance is declared as:
# class OtherClass(MyClass1, MyClass2, MyClassN)
class OtherClass(MyClass):
def __init__(self, arg1):
self.myvariable = 3
print arg1
 
>>> classinstance = OtherClass("hello")
hello
>>> classinstance.myfunction(1, 2)
3
# This class doesn't have a .test member, but
# we can add one to the instance anyway. Note
# that this will only be a member of classinstance.
>>> classinstance.test = 10
>>> classinstance.test
10

Exceptions

Exceptions in Python are handled with try-except [exceptionname] blocks:

def somefunction():
try:
# Division by zero raises an exception
10 / 0
except ZeroDivisionError:
print "Oops, invalid."
else:
# Exception didn't occur, we're good.
pass
 
>>> fnExcept()
Oops, invalid.

Importing

External libraries are used with the import [libname] keyword. You can also use from [libname] import [funcname] for individual functions. Here is an example:

import random
from time import clock
 
randomint = random.randint(1, 100)
>>> print randomint
64

File I/O

Python has a wide array of libraries built in. As an example, here is how serializing (converting data structures to strings using the pickle library) with file I/O is used:

import pickle
mylist = ["This", "is", 4, 13327]
# Open the file C:\binary.dat for writing. The letter r before the
# filename string is used to prevent backslash escaping.
myfile = file(r"C:\binary.dat", "w")
pickle.dump(mylist, myfile)
myfile.close()
 
myfile = file(r"C:\text.txt", "w")
myfile.write("This is a sample string")
myfile.close()
 
myfile = file(r"C:\text.txt")
>>> print myfile.read()
'This is a sample string'
myfile.close()
 
# Open the file for reading.
myfile = file(r"C:\binary.dat")
loadedlist = pickle.load(myfile)
myfile.close()
>>> print loadedlist
['This', 'is', 4, 13327]

Miscellaneous

  • Conditions can be chained. 1 < a < 3 checks that a is both less than 3 and more than 1.
  • You can use del to delete variables or items in arrays.
  • List comprehensions provide a powerful way to create and manipulate lists. They consist of an expression followed by a for clause followed by zero or more if@ or @for clauses, like so:

>>> lst1 = [1, 2, 3]
>>> lst2 = [3, 4, 5]
>>> print [x * y for x in lst1 for y in lst2]
[3, 4, 5, 6, 8, 10, 9, 12, 15]
>>> print [x for x in lst1 if 4 > x > 1]
[2, 3]
# Check if an item has a specific property.
# "any" returns true if any item in the list is true.
>>> any(i % 3 for i in [3, 3, 4, 4, 3])
True
# Check how many items have this property.
>>> sum(1 for i in [3, 3, 4, 4, 3] if i == 3)
3
>>> del lst1[0]
>>> print lst1
[2, 3]
>>> del lst1
  • Global variables
    are declared outside of functions and can be read without any special
    declarations, but if you want to write to them you must declare them at
    the beginning of the function with the "global" keyword, otherwise
    Python will create a local variable and assign to that (be careful of
    that, it's a small catch that can get you if you don't know it). For
    example:

number = 5
 
def myfunc():
# This will print 5.
print number
 
def anotherfunc():
# This raises an exception because the variable has not
# been assigned to before printing. Python knows that it a
# value will be assigned to it later and creates a new, local
# number instead of accessing the global one.
print number
number = 3
 
def yetanotherfunc():
global number
# This will correctly change the global.
number = 3

Epilogue

This tutorial is not meant to be an exhaustive list of all (or even
a subset) of Python. Python has a vast array of libraries and much much
more functionality which you will have to discover through other means,
such as the excellent online book Dive into Python.
I hope I have made your transition in Python easier. Please leave
comments if you believe there is something that could be improved or
added or if there is anything else you would like to see (classes,
error handling, anything).

2010-05-25T22:48:59+00:00 December 12th, 2007|Python|0 Comments

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