Examples

• 134

  Hello, World

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  134

  Python is a high-level, structured, open-source, dynamically typed programming language that can be used for a wide variety of programming tasks.

  Two major versions of Python are currently in active use:

  • Python 2.x is the legacy language
  • Python 3.x is the current language and is under active development

  You can download and install the latest version of Python 2 or Python 3 at the official website. See Python 2 vs. Python 3 for more info on differences between both versions. In addition, a number of providers offer re-packed versions of Python that add commonly used libraries and other features to ease setup for common uses—such as math, data-intensive or scientific use. See the list at the official website.

  Hello World Python file

  Create a new file hello.py containing the following line:

  print('Hello World')
  

  Python 2.x2.7

  If using Python 2, you may also type the line below. Note that this is not valid in Python 3 and thus not recommended as it reduces cross-version code compatibility.

  print 'Hello World'
  

  Execute with Python

  Verify that you have Python installed by running the following command in your favorite terminal (eg. cmd prompt, LXTerminal):

  $ python --version
  

  If you have Python 2 installed, and it is your default Python (see Troubleshooting for more details) you should see something like this:

  $ python --version
  Python 2.7.9
  

  If you have Python 3 installed, and it is your default Python (again, see Troubleshooting for more details) you should see something like this:

  $ python --version
  Python 3.5.2
  

  In the command prompt, navigate to the directory containing the file hello.py.

  For those who aren't familiar with the terminal, use cd <dir> to change directories. Windows users can also Shift-right-click and select Open command window here in a folder where hello.py is contained. MacOS users can drag any folder from a Finder window into the terminal to copy the path to that folder.

  Type python hello.py, then hit the Enter key.

  $ python hello.py
  Hello World
  

  You can also substitute hello.py with the path to your file. For example, if you have the file in your home directory and your user is "user" on Linux, you can type python /home/user/hello.py.

  You should see "Hello World" printed to the console.

  "Hello World" one liner

  You can also print "Hello World" in terminal by following way:

  $ python3 -c 'print('Hello World')'
  Hello World
  

  Launch Interactive Python Shell

  Just by executing python command in your terminal, you can swap into Interactive Python Shell:

  $ python
  Python 2.7.12 (default, Jul  1 2016, 15:12:24) 
  [GCC 5.4.0 20160609] on linux2
  Type "help", "copyright", "credits" or "license" for more information.
  >>> print('Hello World')
  Hello World
  >>>
  

  Interactive Python Shell is a very practical tool for learning and testing the features of the Python language while playing with the values and syntax interactively. Currently most of the system's default Python Interpreter is Python 2.x, so execute python3 command if you want to use Interactive Shell with Python 3.x Interpreter.

  Try Interactive Python Shell Online.

  Common guidelines for python coding standards are specified in PEP8 specs.

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• 53

  Creating variables and assigning values

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  53

  To create a variable in Python, all you need to do is specify the variable name, and then assign a value to it. Python uses = to assign values to variables. There's no need to declare a variable in advance (or to assign a data type to it), assigning a value to a variable itself declares and initiates the variable with that initial value. So you can not declare a variable without an initial value.

  a = 2
  print(a)
  # Out: 2
  
  b = 9223372036854775807
  print(b)
  # Out: 9223372036854775807
  
  pi = 3.14
  print(pi)
  # Out: 3.14
  
  c = 'A'
  print(c)
  # Out: A
  
  name = 'John Doe'
  print(name)
  # Out: John Doe
  
  q = True
  print(q)
  # Out: True
  
  x = None
  print(x)
  # Out: None
  

  Even though there's no need to specify a data type when declaring a variable in Python, while allocating the necessary area in memory for the variable, Python Interpreter automatically picks the most suitable built-in type for it:

  a = 2
  print(type(a))
  # Out: <type 'int'>
  
  b = 9223372036854775807
  print(type(b))
  # Out: <type 'int'>
  
  pi = 3.14
  print(type(pi))
  # Out: <type 'float'>
  
  c = 'A'
  print(type(c))
  # Out: <type 'str'>
  
  name = 'John Doe'
  print(type(name))
  # Out: <type 'str'>
  
  q = True
  print(type(q))
  # Out: <type 'bool'>
  
  x = None
  print(type(x))
  # Out: <type 'NoneType'>
  

  You can assign multiple values to multiple variables in one line. Note, that there must be the same number of arguments on the right and left sides of the = operator:

  a, b, c = 1, 2, 3
  print(a, b, c)
  # Out: 1 2 3
  
  a, b, c = 1, 2
  => Traceback (most recent call last):
  =>   File "name.py", line N, in <module>
  =>     a, b, c = 1, 2
  => ValueError: need more than 2 values to unpack
  
  a, b = 1, 2, 3
  => Traceback (most recent call last):
  =>   File "name.py", line N, in <module>
  =>     a, b = 1, 2, 3
  => ValueError: too many values to unpack
  

  You can also assign a single value to several variables simultaneously.

  a = b = c = 1
  print(a, b, c)
  # Out: 1 1 1
  

  In this case, a, b, and c, are all independent -- changing one will not change the others:

  a = b = c = 1
  print(a, b, c)
  # Out: 1 1 1
  b = 2
  print(a, b, c)
  # Out: 1 2 1
  

  However, note that changing the contents of the object that is referred to by the variable will be reflected through all the others. That is, if x and y are mutable objects(lists, dictionaries, sets and byte arrays), changing the contents of one will be seen through the others:

  x = y = [7, 8, 9]   # x and y refer to the same list i.e. refer to same memory location
  x = [13, 8, 9]      # now we are assigning a brand new list to x (memory location for x changed!)
  print(y)            # y is unchanged, so it's OK
  # Out: [7, 8, 9]
  

  But:

  x = y = [7, 8, 9]   # x and y refer to the same list i.e. refer to same memory location
  x[0] = 13           # now we are replacing first element of x with 13 (memory location for x unchanged)
  print(y)            # this time y changed!
  # Out: [13, 8, 9]
  

  In plain English:

  x = y = [7, 8, 9]   # creates hardware level bonds between x and y because [7, 8, 9] is a mutable object
  x = y = 7           # does not create any bonds, just assigns because 7 is an immutable object
  

  Lastly, Python uses duck typing, so variables do not have to stay the same type as which they were first defined -- you can simply use = to assign a new value to a variable, even if that value is of a different type.

  a = 2 
  print(a)
  # Out: 2
  
  a = "New value"
  print(a)
  # Out: New value
  

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• 34

  Block Indentation

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  34

  First of all, unlike the other popular programming languages (except CoffeScript, Haskell etc.), indentation in Python is mandatory. Because indentation's itself seamlessly defines the code blocks and with this Python aims to be more human-readable. Despite that, this rule can cause you some troubles if your code editor is miscalibrated.

  Python uses the colon symbol (:) and indentation for showing where blocks of code begin and end (If you come from another language, do not confuse this with somehow being related to the ternary operator). That is, blocks in Python, such as functions, loops, if clauses and other constructs, have no ending identifiers. All blocks start with a colon and then contain the indented lines below it.

  For example:

  def my_function():    # This is a function definition. Note the colon (:)
      a = 2             # This line belongs to the function because it's indented
      return a          # This line also belongs to the same function
  print(my_function())  # This line is OUTSIDE the function block
  

  or

  if a > b:             # If block starts here
      print(a)          # This is part of the if block
  else:                 # else must be at the same level as if
      print(b)          # This line is part of the else block
  

  Blocks that contain exactly one single-line statement may be put on the same line, though this form is generally not considered good style:

  if a > b: print(a)
  else: print(b)  
  

  Attempting to do this with more than a single statement will not work:

  if x > y: y = x
      print(y) # IndentationError: unexpected indent
  
  if x > y: while y != z: y -= 1  # SyntaxError: invalid syntax
  

  An empty block causes an IndentationError. Use pass (a command that does nothing) when you have a block with no content:

  def will_be_implemented_later():
      pass
  

  Spaces vs. Tabs

  In short: always use 4 spaces for indentation.

  Using tabs exclusively is possible but PEP 8, the style guide for Python code, states that spaces are preferred.

  Python 3.x3.0

  Python 3 disallows mixing the use of tabs and spaces for indentation. In such case a compile-time error is generated: Inconsistent use of tabs and spaces in indentation and the program will not run.

  Python 2.x2.7

  Python 2 allows mixing tabs and spaces in indentation; this is strongly discouraged. The tab character completes the previous indentation to be a multiple of 8 spaces. Since it is common that editors are configured to show tabs as multiple of 4 spaces, this can cause subtle bugs.

  Citing PEP 8:

  When invoking the Python 2 command line interpreter with the -t option, it issues warnings about code that illegally mixes tabs and spaces. When using -tt these warnings become errors. These options are highly recommended!

  Many editors have "tabs to spaces" configuration. When configuring the editor, one should differentiate between the tab character ('\t') and the Tab key.

  • The tab character should be configured to show 8 spaces, to match the language semantics - at least in cases when (accidental) mixed indentation is possible. Editors can also automatically convert the tab character to spaces.
  • However, it might be helpful to configure the editor so that pressing the Tab key will insert 4 spaces, instead of inserting a tab character.

  Python source code written with a mix of tabs and spaces, or with non-standard number of indentation spaces can be made pep8-conformant using autopep8. (A less powerful alternative comes with most Python installations: reindent.py)

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• 15

  IDLE - Python GUI

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  15

  IDLE is Python’s Integrated Development and Learning Environment and is an alternative to the command line. As the name may imply, IDLE is very useful for developing new code or learning python. On Windows this comes with the Python interpreter, but in other operating systems you may need to install it through your package manager.

  In IDLE, hit F5 or run Python Shell to launch an interpreter. Using IDLE can be a better learning experience for new users because code is interpreted as the user writes.

  Troubleshooting

  • Windows

    If you're on Windows, the default command is python. If you receive a "'python' is not recognized" error, the most likely cause is that Python's location is not in your system's PATH environment variable. This can be accessed by right-clicking on 'My Computer' and selecting 'Properties' or by navigating to 'System' through 'Control Panel'. Click on 'Advanced system settings' and then 'Environment Variables...'. Edit the PATH variable to include the directory of your Python installation, as well as the Script folder (usually C:\Python27;C:\Python27\Scripts). This requires administrative privileges and may require a restart.

    When using multiple versions of Python on the same machine, a possible solution is to rename one of the python.exe files. For example, naming one version python27.exe would cause python27 to become the Python command for that version.

    You can also use the Python Launcher for Windows, which is available through the installer and comes by default. It allows you to select the version of Python to run by using py -[x.y] instead of python[x.y]. You can use the latest version of Python 2 by running scripts with py -2 and the latest version of Python 3 by running scripts with py -3.

  • Debian/Ubuntu/MacOS

    This section assumes that the location of the python executable has been added to the PATH environment variable.

    If you're on Debian/Ubuntu/MacOS, open the terminal and type python for Python 2.x or python3 for Python 3.x.

    Type which python to see which Python interpreter will be used.

  • Arch Linux

    The default Python on Arch Linux (and descendants) is Python 3, so use python or python3 for Python 3.x and python2 for Python 2.x.

  • Other systems

    Python 3 is sometimes bound to python instead of python3. To use Python 2 on these systems where it is installed, you can use python2.

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  +5
• 14

  Datatypes

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  14

  Built-in Types

  Booleans

  • bool: A boolean value us either True or False.

  Numbers

  • int: Integer number

    a = 2
    b = 100
    c = 123456789
    

    Note: in older versions of Python, a long type was available and this was distinct from int. The two have been unified.

  • float: Floating point number; precision depends on the implementation and system architecture, for Cpython the Float datatype corresponds to a C double.

    a = 2.0
    b = 100.e0
    c = 123456789.e1
    

  • complex: Complex numbers

    a = 2 + 1j
    b = 100 + 10j
    

  Sequences and collections

  Python differentiates between ordered sequences and unordered collections (such as set and dict).

  • str: Character string; in Python 3 it is a unicode string, while in Python 2 it is a byte string.

  • unicode: In Python 3 this type does not exist, str replaces; in Python 2 it represents an unicode encoded string.

  • bytes: In Python 3 this represents a string of bytes, without encoding defined; in Python 2 this is a synonym of str.

  • tuple: An ordered collection of n values of any type (n >= 0); supports indexing; immutable; hashable if all its members are hashable.

    a = (1, 2, 3)
    b = ('a', 1, 'python', (1, 2))
    b[2] = 'something else' # returns an error
    

  • list: An ordered collection of n values (n >= 0); not hashable; mutable.

    a = [1, 2, 3]
    b = ['a', 1, 'python', (1, 2), [1, 2]]
    b[2] = 'something else' # allowed
    

  • set: An unordered collection of unique values.

    a = {1, 2, 'a'}
    

  • dict: An unordered collection of unique key-value pairs; keys must be hashable.

    An object is hashable if it has a hash value which never changes during its lifetime (it needs a __hash__() method), and can be compared to other objects (it needs an __eq__() method). Hashable objects which compare equal must have the same hash value.

    a = {1: 'one',
         2: 'two'}
    
    b = {'a': [1, 2, 3],
         'b': 'a string'}
    

  Built-in constants

  In conjunction with the built-in datatypes there are a small number of built-in constants in the built-in namespace:

  • True: The true value of the built-in type bool
  • False: The false value of the built-in type bool
  • None: A singleton object used to signal that a value is absent.
  • Ellipsis or ...: not used in core Python itself but numpy and related packages use this as a 'include everything' reference in arrays.
  • NotImplemented: a singleton used to indicate to Python that a special method doesn't support the specific arguments, and Python will try alternatives if available.

  a = None # No value will be assigned. Any valid datatype can be assigned later
  

  Python 3.x3.0

  None doesn't have any natural ordering. Using ordering comparison operators (<, <=, >=, >) isn't supported anymore and will raise a TypeError.

  Python 2.x2.7

  None is always less than any number (None < -32 evaluates toTrue`).

  Testing the type of variables

  In python, we can check the datatype of an object using the built-in function type.

  a = '123'
  print(type(a))
  #Out: <class 'str'>
  b = 123
  print(type(b))
  #Out: <class 'int'>
  

  In conditional statements it is possible to test the datatype with isinstance. However, it is usually not encouraged to rely on the type of the variable.

  i = 7
  if isinstance(i, int):
      i += 1
  elif isinstance(i, str):
      i = int(i)
      i += 1
  

  For information on the differences between type() and isinstance() read: Differences between isinstance and type in Python

  To test if something is of NoneType:

  x = None
  if x is None:
      print('Not a surprise, I just defined x as None.')
  

  Converting between datatypes

  You can perform explicit datatype conversion.

  For example, '123' is of str type and it can be converted to integer using int function.

  a = '123'
  b = int(a)
  

  Converting from a float string such as '123.456' can be done using float function.

  a = '123.456'
  b = float(a)
  

  You can also convert sequence or collection types

  a = 'hello'
  list(a) # returns ['h', 'e', 'l', 'l', 'o']
  set(a)  # returns {'o', 'e', 'l', 'h'}
  

  Explicit string type at definition of literals

  With one letter labels just in front of the quotes you can tell what type of string you want to define.

  • b'foo bar': results bytes in Python 3, str in Python 2
  • u'foo bar': results str in Python 3, unicode in Python 2
  • 'foo bar': results str
  • r'foo bar': results so called raw string, where escaping special characters is not necessary, everything is taken verbatim as you typed

  To see how raw string makes a difference, try this:

  normal = 'foo\nbar'
  escaped = 'foo\\nbar'
  raw = r'foo\nbar'
  print(normal)
  # Out: foo
  #      bar
  print(escaped)
  # Out: foo\nbar
  print(raw)
  # Out: foo\nbar
  

  Datatype related exceptions (errors)

  If the original value is not valid value for target type, then a ValueError exception will be raised.

  int('a')
  '''
  Out: Traceback (most recent call last):
       File "<stdin>", line 1, in <module>
       ValueError: invalid literal for int() with base 10: 'a'
  '''
  

  This method is a simple solution for example if you want to the user input (which, in Python 3, is always str) to a number:

  value = int(input()) # Read user input and convert to integer
  

  (However, in a real application, not a bad idea to add some checking and error handling.)

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  +11
• 11

  User Input

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  11

  Interactive input

  To get input from the user, use the input function (note: in Python 2.x, the function is called raw_input instead, although Python 2.x has its own version of input that is completely different):

  Python 2.x2.3

  name = raw_input("What is your name? ")
  # Out: What is your name? _
  

  Security Remark Do not use input() in Python2 - the entered text is will be evaluated as if it were a Python expression (equivalent to eval(input()) in Python3), which might easily become a vulnerability. See this article for further information on the risks of using this function.

  Python 3.x3.0

  name = input("What is your name? ")
  # Out: What is your name? _
  

  The remainder of this example will be using Python 3 syntax.

  The function takes a string argument, which it displays as a prompt, and returns a string. The above provides a prompt, waiting for me to type my name in:

  name = input("What is your name? ")
  # Out: What is your name?
  

  If I type "Bob" and hit enter, now the variable name contains the string "Bob":

  name = input("What is your name? ")
  # Out: What is your name? Bob
  print(name)
  # Out: Bob
  

  Note that the input is always of type str, which is important if you want the user to enter numbers. Therefore, you need to convert the str before trying to use it as a number:

  x = input("Write a number:")
  # Out: Write a number: 10
  x / 2
  # Out: TypeError: unsupported operand type(s) for /: 'str' and 'int'
  float(x) / 2
  # Out: 5.0
  

  ---

  NB: It's recommended to use try/except blocks to catch exceptions when dealing with user inputs. For instance, if your code wants to cast a raw_input into an int, and what the user writes is uncastable, it raises a ValueError.

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  +11
• 7

  Collection Types

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  7

  Lists

  There are a number of collection types in Python. While types such as int and str hold a single value, collection types hold multiple values.

  The list type is probably the most commonly used collection type in Python. Despite its name, a list is more like an array in other languages, mostly JavaScript. In Python, a list is merely a ordered collection of valid Python values. The values are not restricted to a single data type, which makes sense given Python is a dynamic language. Lists are also variable length, so you can add and remove values. They are also mutable, so you can change the values in a list. A list can be created by enclosing values, separated by commas, in square brackets:

  my_list = [1, 2, 3, 'a', 'b', 'c', True, False, None, ['another', 'list'], []]
  

  As you can see, lists can be nested and can also be empty. The elements of a list can be accessed via an index, or numeric representation of their position. Lists in Python are zero-indexed meaning that the first element in the list is at index 0, the second element is at index 1 and so on. Indices can also be negative which which start at the end of the list. So:

  last_element = my_list[-1]
  

  Would return the last element in the above list which is the empty list: [].

  You can iterate over the list elements like below

  for element in my_list:
      print (element)
  

  Tuples

  A tuple is similar to a list except that is it fixed-length and immutable. So the values in the tuple cannot be changed nor the values be added to or removed from the tuple. Tuples are commonly used for small collections of values that will not need to change, such as an IP address and port. Tuples are represented with parentheses instead of square brackets:

  ip_address = ('10.20.30.40', 8080)
  

  The same indexing rules for lists also apply to tuples. Tuples can also be nested and the values can be any valid Python valid.

  A tuple with only one member must be defined (note the comma) this way:

  one_member_tuple = ('Only member',)
  

  or

  one_member_tuple = 'Only member',   # No brackets
  

  or just using tuple syntax

  one_member_tuple = tuple(['Only member'])
  

  Dictionaries

  A dictionary in Python is a collection of key-value pairs. The dictionary is surrounded by curly braces. Each pair is separated by a comma and the key and value are separated by a colon. Here is an example:

  state_capitols = {
      'Arkanasas': 'Little Rock',
      'Colorado': 'Denver',
      'California': 'Sacremento', 
      'Georgia': 'Atlanta'
  }
  

  To get a value, refer to it by its key:

  ca_capitol = state_capitols['California']
  

  You can also get all of the keys in a dictionary and then iterate over them:

  for k in state_capitols.keys():
      print('{} is the capitol of {}'.format(state_capitol[k], k))
  

  If dictionaries remind you of JSON, you're not dreaming! The native json module in the Python standard library converts between JSON and dictionaries. In fact, JSON is one of the most common uses of dictionaries.

  defaultdict

  A defaultdict is a dictionary with a default value for keys, so that keys for which no value has been explicitly defined can be accessed without errors. defaultdict is especially useful when the values in the dictionary are collections(lists, dicts etc) in the sense that it doesnt need to be initialized everytime when a new key is used.

  A defaultdict will never raise a KeyError. Any key that does not exist gets the default value returned.

  For example, consider the following dictionary

  >>> state_capitols = {
      'Arkanasas': 'Little Rock',
      'Colorado': 'Denver',
      'California': 'Sacremento', 
      'Georgia': 'Atlanta'
  }
  

  If we try to access a non-existent key, python returns us an error as follows

  >>> state_capitols['Alabama']
  Traceback (most recent call last):
  
    File "<ipython-input-61-236329695e6f>", line 1, in <module>
      state_capitols['Alabama']
  
  KeyError: 'Alabama'
  

  Let us try with a defaultdict. It can be found in the collections module.

  >>> from collections import defaultdict
  >>> state_capitols = defaultdict(lambda: 'Boston')
  

  What we did here is to set a default value (Boston) incase the give key doesnt exist. let us try to populate the dict as before

  >>> state_capitols['Arkanasas'] = 'Little Rock'
  >>> state_capitols['California'] = 'Sacremento'
  >>> state_capitols['Colorado'] = 'Denver'
  >>> state_capitols['Georgia'] = 'Atlanta'
  

  If we try to access the dict with a non-existent key, python will return us the default value i.e. Boston

  >>> state_capitols['Alabama']
  'Boston'
  

  and returns the created values for existing key just like a normal dictionary

  >>> state_capitols['Arkanasas']
  'Little Rock'
  

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• 4

  Built in Modules and Functions

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  4

  A module is a file containing Python definitions and statements. Function is a piece of code which execute some logic.

  >>> pow(2,3)
      8
  

  To check the built in function in python

  >>> dir(__builtins__)
  [
      'ArithmeticError', 
      'AssertionError', 
      'AttributeError', 
      'BaseException', 
      'BufferError', 
      'BytesWarning', 
      'DeprecationWarning', 
      'EOFError', 
      'Ellipsis', 
      'EnvironmentError', 
      'Exception', 
      'False', 
      'FloatingPointError', 
      'FutureWarning', 
      'GeneratorExit', 
      'IOError', 
      'ImportError', 
      'ImportWarning', 
      'IndentationError', 
      'IndexError', 
      'KeyError', 
      'KeyboardInterrupt', 
      'LookupError', 
      'MemoryError', 
      'NameError', 
      'None', 
      'NotImplemented', 
      'NotImplementedError', 
      'OSError', 
      'OverflowError', 
      'PendingDeprecationWarning', 
      'ReferenceError', 
      'RuntimeError', 
      'RuntimeWarning', 
      'StandardError', 
      'StopIteration', 
      'SyntaxError', 
      'SyntaxWarning', 
      'SystemError', 
      'SystemExit', 
      'TabError', 
      'True', 
      'TypeError', 
      'UnboundLocalError', 
      'UnicodeDecodeError', 
      'UnicodeEncodeError', 
      'UnicodeError', 
      'UnicodeTranslateError', 
      'UnicodeWarning', 
      'UserWarning', 
      'ValueError', 
      'Warning', 
      'ZeroDivisionError', 
      '__debug__', 
      '__doc__', 
      '__import__', 
      '__name__', 
      '__package__', 
      'abs', 
      'all', 
      'any', 
      'apply', 
      'basestring', 
      'bin', 
      'bool', 
      'buffer', 
      'bytearray', 
      'bytes', 
      'callable', 
      'chr', 
      'classmethod', 
      'cmp', 
      'coerce', 
      'compile', 
      'complex', 
      'copyright', 
      'credits', 
      'delattr', 
      'dict', 
      'dir', 
      'divmod', 
      'enumerate', 
      'eval', 
      'execfile', 
      'exit', 
      'file', 
      'filter', 
      'float', 
      'format', 
      'frozenset', 
      'getattr', 
      'globals', 
      'hasattr', 
      'hash', 
      'help', 
      'hex', 
      'id', 
      'input', 
      'int', 
      'intern', 
      'isinstance', 
      'issubclass', 
      'iter', 
      'len', 
      'license', 
      'list', 
      'locals', 
      'long', 
      'map', 
      'max', 
      'memoryview', 
      'min', 
      'next', 
      'object', 
      'oct', 
      'open', 
      'ord', 
      'pow', 
      'print', 
      'property', 
      'quit', 
      'range', 
      'raw_input', 
      'reduce', 
      'reload', 
      'repr', 
      'reversed', 
      'round', 
      'set', 
      'setattr', 
      'slice', 
      'sorted', 
      'staticmethod', 
      'str', 
      'sum', 
      'super', 
      'tuple', 
      'type', 
      'unichr', 
      'unicode', 
      'vars', 
      'xrange', 
      'zip'
  ]
  

  To know the functionality of any function, we can use built in function help .

  >>> help(max)
  Help on built-in function max in module __builtin__:
  max(...)
      max(iterable[, key=func]) -> value
      max(a, b, c, ...[, key=func]) -> value
      With a single iterable argument, return its largest item.
      With two or more arguments, return the largest argument.
  

  Built in modules contains extra functionalities.For example to get square of a number we need to include math module.

  >>> import math
  >>> math.sqrt(16) #to get the square root of number we use 'sqrt'
      4.0
  

  edited Sep 29 at 2:30

  

  

  

  

  

  +1
• 4

  Creating a module

  edit move example delete share

  4

  A module is an importable file containing definitions and statements.

  A module can be created by creating a .py file.

  # hello.py
  def say_hello():
      print("Hello!")
  

  Functions in a module can be used by importing the module.

  $ python
  >>> import hello
  >>> hello.say_hello()
  => "Hello!"
  

  Modules can be imported by other modules.

  # greet.py
  import hello
  hello.say_hello()
  

  Specific functions of a module can be imported.

  # greet.py
  from hello import say_hello
  say_hello()
  

  Modules can be aliased.

  # greet.py
  import hello as ai
  ai.say_hello()
  

  A module can be stand-alone runnable script.

  # run_hello.py
  if __name__ == '__main__':
      import hello
  

  Run it!

  $ python run_hello.py
  => "Hello!"
  

  edited Sep 29 at 2:30

  

  

  

  

  
• 4

  List the identifiers that an object defines

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  4

  The identifiers of the built-in function dir() are the functions, classes and variables defined in that object. The dir() function returns a list of strings.

  If called without an argument, return the names in the current scope.

  >>> dir()
  ['__builtins__', '__doc__', '__name__', '__package__']
  
  
  >>> import os
  >>> dir()
  ['__builtins__', '__doc__', '__name__', '__package__', 'os']
  

  Else, return an alphabetized list of names comprising (some of) the attributes of the given object, and of attributes reachable from it.

  >>> dir(os)
  ['EX_CANTCREAT', 'EX_CONFIG', 'EX_DATAERR', 'EX_IOERR', 'EX_NOHOST', 'EX_NOINPUT','EX_NOPERM', 'EX_NOUSER', 'EX_OK', 'EX_OSERR', 'EX_OSFILE', 'EX_PROTOCOL', 'EX_SOFTWARE', 'EX_TEMPFAIL', 'EX_UNAVAILABLE', 'EX_USAGE', 'F_OK', 'NGROUPS_MAX', 'O_APPEND', 'O_ASYNC', 'O_CREAT', 'O_DIRECT', 'O_DIRECTORY', 'O_DSYNC', 'O_EXCL', 'O_LARGEFILE', 'O_NDELAY', 'O_NOATIME', 'O_NOCTTY', 'O_NOFOLLOW', 'O_NONBLOCK', 'O_RDONLY', 'O_RDWR', 'O_RSYNC', 'O_SYNC', 'O_TRUNC', 'O_WRONLY', 'P_NOWAIT', 'P_NOWAITO', 'P_WAIT', 'R_OK', 'SEEK_CUR', 'SEEK_END', 'SEEK_SET', 'ST_APPEND', 'ST_MANDLOCK', 'ST_NOATIME', 'ST_NODEV', 'ST_NODIRATIME', 'ST_NOEXEC', 'ST_NOSUID', 'ST_RDONLY', 'ST_RELATIME', 'ST_SYNCHRONOUS', 'ST_WRITE', 'TMP_MAX', 'UserDict', 'WCONTINUED', 'WCOREDUMP', 'WEXITSTATUS', 'WIFCONTINUED', 'WIFEXITED', 'WIFSIGNALED', 'WIFSTOPPED', 'WNOHANG', 'WSTOPSIG', 'WTERMSIG', 'WUNTRACED', 'W_OK', 'X_OK', '_Environ', '__all__', '__builtins__', '__doc__', '__file__', '__name__', '__package__', '_copy_reg', '_execvpe', '_exists', '_exit', '_get_exports_list', '_make_stat_result', '_make_statvfs_result', '_pickle_stat_result', '_pickle_statvfs_result', '_spawnvef', 'abort', 'access', 'altsep', 'chdir', 'chmod', 'chown', 'chroot', 'close', 'closerange', 'confstr', 'confstr_names', 'ctermid', 'curdir', 'defpath', 'devnull', 'dup', 'dup2', 'environ', 'errno', 'error', 'execl', 'execle', 'execlp', 'execlpe', 'execv', 'execve', 'execvp', 'execvpe', 'extsep', 'fchdir', 'fchmod', 'fchown', 'fdatasync', 'fdopen', 'fork', 'forkpty', 'fpathconf', 'fstat', 'fstatvfs', 'fsync', 'ftruncate', 'getcwd', 'getcwdu', 'getegid', 'getenv', 'geteuid', 'getgid', 'getgroups', 'getloadavg', 'getlogin', 'getpgid', 'getpgrp', 'getpid', 'getppid', 'getresgid', 'getresuid', 'getsid', 'getuid', 'initgroups', 'isatty', 'kill', 'killpg', 'lchown', 'linesep', 'link', 'listdir', 'lseek', 'lstat', 'major', 'makedev', 'makedirs', 'minor', 'mkdir', 'mkfifo', 'mknod', 'name', 'nice', 'open', 'openpty', 'pardir', 'path', 'pathconf', 'pathconf_names', 'pathsep', 'pipe', 'popen', 'popen2', 'popen3', 'popen4', 'putenv', 'read', 'readlink', 'remove', 'removedirs', 'rename', 'renames', 'rmdir', 'sep', 'setegid', 'seteuid', 'setgid', 'setgroups', 'setpgid', 'setpgrp', 'setregid', 'setresgid', 'setresuid', 'setreuid', 'setsid', 'setuid', 'spawnl', 'spawnle', 'spawnlp', 'spawnlpe', 'spawnv', 'spawnve', 'spawnvp', 'spawnvpe', 'stat', 'stat_float_times', 'stat_result', 'statvfs', 'statvfs_result', 'strerror', 'symlink', 'sys', 'sysconf', 'sysconf_names', 'system', 'tcgetpgrp', 'tcsetpgrp', 'tempnam', 'times', 'tmpfile', 'tmpnam', 'ttyname', 'umask', 'uname', 'unlink', 'unsetenv', 'urandom', 'utime', 'wait', 'wait3', 'wait4', 'waitpid', 'walk', 'write']
  

  If the object supplies a method named __dir__, it will be used;

  >>> os.__dir__
  Traceback (most recent call last):
    File "<stdin>", line 1, in <module>
  

  Otherwise the default dir() logic is used and returns:

  • For a module object: the module's attributes.

  >>> dir(os)
  

  • For a class object: its attributes, and recursively the attributes of its bases.

  >>> dir(dict)
  ['__class__', '__cmp__', '__contains__', '__delattr__', '__delitem__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__getitem__', '__gt__', '__hash__', '__init__', '__iter__', '__le__', '__len__', '__lt__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__setitem__', '__sizeof__', '__str__', '__subclasshook__', 'clear', 'copy', 'fromkeys', 'get', 'has_key', 'items', 'iteritems', 'iterkeys', 'itervalues', 'keys', 'pop', 'popitem', 'setdefault', 'update', 'values', 'viewitems', 'viewkeys', 'viewvalues']
  

  • For any other object: its attributes, its class's attributes, and recursively the attributes of its class's base classes.

  >>> class MyClassObject(object):
  ...     pass
  ... 
  >>> dir(MyClassObject)
  ['__class__', '__delattr__', '__dict__', '__doc__', '__format__', '__getattribute__', '__hash__', '__init__', '__module__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', '__weakref__']
  

  Requesting a subidentifier:

  >>> dir(os.close)
  ['__call__', '__class__', '__cmp__', '__delattr__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__gt__', '__hash__', '__init__', '__le__', '__lt__', '__module__', '__name__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__self__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__']
  

  edited Jul 28 at 10:35

  

  
• 3

  Installation of Python 2.7.x and 3.x

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  3

  Note: Following instructions are written for Python 2.7 (unless specified): instructions for Python 3.x are similar.

  WINDOWS

  First, download the latest version of Python 2.7 from the official Website (https://www.python.org/downloads/). Version is provided as an MSI package. To install it manually, just double-click the file.

  By default, Python installs to a directory:

   C:\Python27\
  

  Warning: installation does not automatically modify the PATH environment variable.

  Assuming that your Python installation is in C:\Python27, add this to your PATH:

  C:\Python27\;C:\Python27\Scripts\
  

  Now to check if Python installation is valid write in cmd:

  python --version
  

  LINUX

  The latest versions of CentOS, Fedora, Redhat Enterprise (RHEL) and Ubuntu come with Python 2.7.

  To install Python 2.7 on linux manually, just do the following in terminal:

  wget --no-check-certificate https://www.python.org/ftp/python/2.7.X/Python-2.7.X.tgz
  tar -xzf Python-2.7.X.tgz  
  cd Python-2.7.X
  ./configure  
  make  
  sudo make install
  

  Also add the path of new python in PATH environment variable. If new python is in /root/python-2.7.X then run "export PATH = $PATH:/root/python-2.7.X"

  Now to check if Python installation is valid write in terminal:

  python --version
  

  macOS

  As we speak, macOS comes installed with Python 2.7.10, but this version is outdated and slightly modified from the regular Python.

  The version of Python that ships with OS X is great for learning but it’s not good for development. The version shipped with OS X may be out of date from the official current Python release, which is considered the stable production version. (source)

  Install Homebrew:

  /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
  

  Install Python 2.7:

  brew install python
  

  For Python 3.x, use the command brew install python3 instead.

  edited Aug 10 at 13:40

  

  
• 3

  String function - str() and repr()

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  3

  These two functions can be used to obtain a readable representation of an object.

  In-short:

  repr(x) returns x.__repr__(): representation of x. Usually eval will convert it back to that object.

  str(x) returns x.__str__(): whatever you think is that object in a human-readable text form.

  ---

  str()

  For strings, this returns the string itself. The difference with repr(object) is that str(object) does not always attempt to return a string that is acceptable to eval(); its goal is to return a printable string. If no argument is given, returns the empty string, ''.

  repr()

  For many types, this function makes an attempt to return a string that would yield an object with the same value when passed to eval(), otherwise the representation is a string enclosed in angle brackets that contains the name of the type of the object together with additional information often including the name and address of the object.

  Example 1:

  s = """w'o"w"""
  repr(s) # Output: '\'w\\\'o"w\''  
  str(s)  # Output: 'w\'o"w'
  eval(str(s)) == s  # Gives a SyntaxError 
  eval(repr(s)) == s # Output: True
  

  Example 2:

  import datetime
  today = datetime.datetime.now()
  str(today)  # Output: '2016-09-15 06:58:46.915000'
  repr(today) # Output: 'datetime.datetime(2016, 9, 15, 6, 58, 46, 915000)'
  

  edited Sep 15 at 8:13

  

  

  
• 2

  Help Utility

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  2

  Python has several functions built into the interpreter. If you want to get information of keywords, built-in functions, modules or topics open a Python console and enter:

  >>> help()
  

  You will receive information by entering keywords directly:

  >>> help(help)
  

  or within the utility:

  help> help
  

  which will show an explanation:

  Help on _Helper in module _sitebuiltins object:
  
  class _Helper(builtins.object)
   |  Define the builtin 'help'.
   |  
   |  This is a wrapper around pydoc.help that provides a helpful message
   |  when 'help' is typed at the Python interactive prompt.
   |  
   |  Calling help() at the Python prompt starts an interactive help session.
   |  Calling help(thing) prints help for the python object 'thing'.
   |  
   |  Methods defined here:
   |  
   |  __call__(self, *args, **kwds)
   |  
   |  __repr__(self)
   |  
   |  ----------------------------------------------------------------------
   |  Data descriptors defined here:
   |  
   |  __dict__
   |      dictionary for instance variables (if defined)
   |  
   |  __weakref__
   |      list of weak references to the object (if defined)
  

  You can also request subclasses of modules:

  help(pymysql.connections)
  

  Close the helper with 'quit'

  created Jul 22 at 17:42

  
• 1

  Installing external modules using pip

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  1

  pip is your friend when you need to install any package from the plethora of choices available at the python package index (PyPI). pip is already installed if you're using Python 2 >= 2.7.9 or Python 3 >= 3.4 downloaded from python.org. For computers running Linux or another *Nix with a native package manager, pip must often be manually installed.

  On instances with both Python 2 and Python 3 installed, pip often refers to Python 2 and pip3 to Python 3. Using pip will only install packages for Python 2 and pip3 will only install packages for Python 3.

  Installing a package is a simple as typing

  $ pip install [package_name] # latest version of the package

  $ pip install [package_name]==x.x.x # specific version of the package

  $ pip install '[package_name]>=x.x.x' # minimum version of the package

  where x.x.x is the version number of the package you want to install.

  You can upgrade your existing pip installation by using the following commands

  On Linux or OS X: pip install -U pip

  You may need to use sudo with pip on some Linux Systems

  On Windows: py -m pip install -U pip or python -m pip install -U pip

  For more information regarding pip do read here.

  edited Aug 27 at 12:39