1. Whetting Your Appetite

If you do much work on computers, eventually you find that there’s some task you’d like to automate. For example, you may wish to perform a search-and-replace over a large number of text files, or rename and rearrange a bunch of photo files in a complicated way. Perhaps you’d like to write a small custom database, or a specialized GUI application, or a simple game.

>>> fruits = ['orange', 'apple', 'pear', 'banana', 'kiwi', 'apple', 'banana']
>>> fruits.count('apple')
2
>>> fruits.count('tangerine')
0
>>> fruits.index('banana')
3
>>> fruits.index('banana', 4)  # Find next banana starting a position 4
6
>>> fruits.reverse()
>>> fruits
['banana', 'apple', 'kiwi', 'banana', 'pear', 'apple', 'orange']
>>> fruits.append('grape')
>>> fruits
['banana', 'apple', 'kiwi', 'banana', 'pear', 'apple', 'orange', 'grape']
>>> fruits.sort()
>>> fruits
['apple', 'apple', 'banana', 'banana', 'grape', 'kiwi', 'orange', 'pear']
>>> fruits.pop()
'pear'

If you’re a professional software developer, you may have to work with several C/C++/Java libraries but find the usual write/compile/test/re-compile cycle is too slow. Perhaps you’re writing a test suite for such a library and find writing the testing code a tedious task. Or maybe you’ve written a program that could use an extension language, and you don’t want to design and implement a whole new language for your application.

Python is just the language for you.

You could write a Unix shell script or Windows batch files for some of these tasks, but shell scripts are best at moving around files and changing text data, not well-suited for GUI applications or games. You could write a C/C++/Java program, but it can take a lot of development time to get even a first-draft program. Python is simpler to use, available on Windows, macOS, and Unix operating systems, and will help you get the job done more quickly.

Python is simple to use, but it is a real programming language, offering much more structure and support for large programs than shell scripts or batch files can offer. On the other hand, Python also offers much more error checking than C, and, being a very-high-level language, it has high-level data types built in, such as flexible arrays and dictionaries. Because of its more general data types Python is applicable to a much larger problem domain than Awk or even Perl, yet many things are at least as easy in Python as in those languages.

Python allows you to split your program into modules that can be reused in other Python programs. It comes with a large collection of standard modules that you can use as the basis of your programs — or as examples to start learning to program in Python. Some of these modules provide things like file I/O, system calls, sockets, and even interfaces to graphical user interface toolkits like Tk.

Python is an interpreted language, which can save you considerable time during program development because no compilation and linking is necessary. The interpreter can be used interactively, which makes it easy to experiment with features of the language, to write throw-away programs, or to test functions during bottom-up program development. It is also a handy desk calculator.

Python enables programs to be written compactly and readably. Programs written in Python are typically much shorter than equivalent C, C++, or Java programs, for several reasons:

• the high-level data types allow you to express complex operations in a single statement;

• statement grouping is done by indentation instead of beginning and ending brackets;

• no variable or argument declarations are necessary.

Python is extensible: if you know how to program in C it is easy to add a new built-in function or module to the interpreter, either to perform critical operations at maximum speed, or to link Python programs to libraries that may only be available in binary form (such as a vendor-specific graphics library). Once you are really hooked, you can link the Python interpreter into an application written in C and use it as an extension or command language for that application.

By the way, the language is named after the BBC show “Monty Python’s Flying Circus” and has nothing to do with reptiles. Making references to Monty Python skits in documentation is not only allowed, it is encouraged!

Now that you are all excited about Python, you’ll want to examine it in some more detail. Since the best way to learn a language is to use it, the tutorial invites you to play with the Python interpreter as you read.

In the next chapter, the mechanics of using the interpreter are explained. This is rather mundane information, but essential for trying out the examples shown later.

The rest of the tutorial introduces various features of the Python language and system through examples, beginning with simple expressions, statements and data types, through functions and modules, and finally touching upon advanced concepts like exceptions and user-defined classes.

Python Introduction

What is Python?

Python is a popular programming language. It was created by Guido van Rossum, and released in 1991.

It is used for:

• web development (server-side),
• software development,
• mathematics,
• system scripting.

What can Python do?

• Python can be used on a server to create web applications.
• Python can be used alongside software to create workflows.
• Python can connect to database systems. It can also read and modify files.
• Python can be used to handle big data and perform complex mathematics.
• Python can be used for rapid prototyping, or for production-ready software development.

Why Python?

• Python works on different platforms (Windows, Mac, Linux, Raspberry Pi, etc).
• Python has a simple syntax similar to the English language.
• Python has syntax that allows developers to write programs with fewer lines than some other programming languages.
• Python runs on an interpreter system, meaning that code can be executed as soon as it is written. This means that prototyping can be very quick.
• Python can be treated in a procedural way, an object-oriented way or a functional way.

Good to know

• The most recent major version of Python is Python 3, which we shall be using in this tutorial. However, Python 2, although not being updated with anything other than security updates, is still quite popular.
• In this tutorial Python will be written in a text editor. It is possible to write Python in an Integrated Development Environment, such as Thonny, Pycharm, Netbeans or Eclipse which are particularly useful when managing larger collections of Python files.

Python Syntax compared to other programming languages

• Python was designed for readability, and has some similarities to the English language with influence from mathematics.
• Python uses new lines to complete a command, as opposed to other programming languages which often use semicolons or parentheses.
• Python relies on indentation, using whitespace, to define scope; such as the scope of loops, functions and classes. Other programming languages often use curly-brackets for this purpose.

print("Hello, World!")

Python Getting Started

Python Install

Many PCs and Macs will have python already installed.

To check if you have python installed on a Windows PC, search in the start bar for Python or run the following on the Command Line (cmd.exe):

To check if you have python installed on a Linux or Mac, then on linux open the command line or on Mac open the Terminal and type:

If you find that you do not have Python installed on your computer, then you can download it for free from the following website: https://www.python.org/

Python Quickstart

Python is an interpreted programming language, this means that as a developer you write Python (.py) files in a text editor and then put those files into the python interpreter to be executed.

The way to run a python file is like this on the command line:

Where “helloworld.py” is the name of your python file.

Let’s write our first Python file, called helloworld.py, which can be done in any text editor.

print("Hello, World!")

Simple as that. Save your file. Open your command line, navigate to the directory where you saved your file, and run:

The output should read:

Congratulations, you have written and executed your first Python program.

The Python Command Line

To test a short amount of code in python sometimes it is quickest and easiest not to write the code in a file. This is made possible because Python can be run as a command line itself.

Type the following on the Windows, Mac or Linux command line:

Or, if the “python” command did not work, you can try “py”:

From there you can write any python, including our hello world example from earlier in the tutorial:

Which will write “Hello, World!” in the command line:

Whenever you are done in the python command line, you can simply type the following to quit the python command line interface:

exit()

Python Syntax

Or by creating a python file on the server, using the .py file extension, and running it in the Command Line:

Python Indentation

Indentation refers to the spaces at the beginning of a code line.

Where in other programming languages the indentation in code is for readability only, the indentation in Python is very important.

Python uses indentation to indicate a block of code.

if 5 > 2:
  print("Five is greater than two!")

Python will give you an error if you skip the indentation:

if 5 > 2:
print("Five is greater than two!")

The number of spaces is up to you as a programmer, the most common use is four, but it has to be at least one.

if 5 > 2:
  print("Five is greater than two!")
if 5 > 2:
        print("Five is greater than two!")

You have to use the same number of spaces in the same block of code, otherwise Python will give you an error:

if 5 > 2:
  print("Five is greater than two!")
         print("Five is greater than two!")

Python Variables

In Python, variables are created when you assign a value to it:

x = 5
y = "Hello, World!"

Python has no command for declaring a variable.

You will learn more about variables in the Python Variables chapter.

Comments

Python has commenting capability for the purpose of in-code documentation.

Comments start with a #, and Python will render the rest of the line as a comment:

#This is a comment.
print("Hello, World!")

("Hello World")

Python Comments

Comments can be used to explain Python code.

Comments can be used to make the code more readable.

Comments can be used to prevent execution when testing code.

Creating a Comment

Comments starts with a #, and Python will ignore them:

#This is a comment
print("Hello, World!")

Comments can be placed at the end of a line, and Python will ignore the rest of the line:

print("Hello, World!") #This is a comment

A comment does not have to be text that explains the code, it can also be used to prevent Python from executing code:

#print("Hello, World!")
print("Cheers, Mate!")

Multi Line Comments

Python does not really have a syntax for multi line comments.

To add a multiline comment you could insert a # for each line:

#This is a comment
#written in
#more than just one line
print("Hello, World!")

Or, not quite as intended, you can use a multiline string.

Since Python will ignore string literals that are not assigned to a variable, you can add a multiline string (triple quotes) in your code, and place your comment inside it:

"""
This is a comment
written in
more than just one line
"""
print("Hello, World!")

This is a comment

Python Data Types

x = 5
print(type(x))

x = 5
print(type(x))

Python Numbers

Python Numbers

There are three numeric types in Python:

• int
• float
• complex

Variables of numeric types are created when you assign a value to them:

x = 1    # int
y = 2.8  # float
z = 1j   # complex

To verify the type of any object in Python, use the type() function:

print(type(x))
print(type(y))
print(type(z))

Int

Int, or integer, is a whole number, positive or negative, without decimals, of unlimited length.

x = 1
y = 35656222554887711
z = -3255522

print(type(x))
print(type(y))
print(type(z))

Float

Float, or “floating point number” is a number, positive or negative, containing one or more decimals.

x = 1.10
y = 1.0
z = -35.59

print(type(x))
print(type(y))
print(type(z))

Float can also be scientific numbers with an “e” to indicate the power of 10.

x = 35e3
y = 12E4
z = -87.7e100

print(type(x))
print(type(y))
print(type(z))

Complex

Complex numbers are written with a “j” as the imaginary part:

x = 3+5j
y = 5j
z = -5j

print(type(x))
print(type(y))
print(type(z))

Type Conversion

You can convert from one type to another with the int(), float(), and complex() methods:

x = 1    # int
y = 2.8  # float
z = 1j   # complex

#convert from int to float:
a = float(x)

#convert from float to int:
b = int(y)

#convert from int to complex:
c = complex(x)

print(a)
print(b)
print(c)

print(type(x))
print(type(y))
print(type(z))

Random Number

Python does not have a random() function to make a random number, but Python has a built-in module called random that can be used to make random numbers:

import random

print(random.randrange(1, 10))

In our Random Module Reference you will learn more about the Random module.

x = 5
x = (x)

Python Casting

Specify a Variable Type

There may be times when you want to specify a type on to a variable. This can be done with casting. Python is an object-orientated language, and as such it uses classes to define data types, including its primitive types.

Casting in python is therefore done using constructor functions:

• int() – constructs an integer number from an integer literal, a float literal (by removing all decimals), or a string literal (providing the string represents a whole number)
• float() – constructs a float number from an integer literal, a float literal or a string literal (providing the string represents a float or an integer)
• str() – constructs a string from a wide variety of data types, including strings, integer literals and float literals

x = int(1)   # x will be 1
y = int(2.8) # y will be 2
z = int("3") # z will be 3

x = float(1)     # x will be 1.0
y = float(2.8)   # y will be 2.8
z = float("3")   # z will be 3.0
w = float("4.2") # w will be 4.2

x = str("s1") # x will be 's1'
y = str(2)    # y will be '2'
z = str(3.0)  # z will be '3.0'

Python Booleans

Booleans represent one of two values: True or False.

Boolean Values

In programming you often need to know if an expression is True or False.

You can evaluate any expression in Python, and get one of two answers, True or False.

When you compare two values, the expression is evaluated and Python returns the Boolean answer:

print(10 > 9)
print(10 == 9)
print(10 < 9)

When you run a condition in an if statement, Python returns True or False:

a = 200
b = 33

if b > a:
  print("b is greater than a")
else:
  print("b is not greater than a")

Evaluate Values and Variables

The bool() function allows you to evaluate any value, and give you True or False in return,

x = "Hello"
y = 15

print(bool(x))
print(bool(y))

Most Values are True

Almost any value is evaluated to True if it has some sort of content.

Any string is True, except empty strings.

Any number is True, except 0.

Any list, tuple, set, and dictionary are True, except empty ones.

bool("abc")
bool(123)
bool(["apple", "cherry", "banana"])

Some Values are False

In fact, there are not many values that evaluate to False, except empty values, such as (), [], {}, "", the number 0, and the value None. And of course the value False evaluates to False.

bool(False)
bool(None)
bool(0)
bool("")
bool(())
bool([])
bool({})

One more value, or object in this case, evaluates to False, and that is if you have an object that is made from a class with a __len__ function that returns 0 or False:

class myclass():
  def __len__(self):
    return 0

myobj = myclass()
print(bool(myobj))

Functions can Return a Boolean

You can create functions that returns a Boolean Value:

def myFunction() :
  return True

print(myFunction())

You can execute code based on the Boolean answer of a function:

def myFunction() :
  return True

if myFunction():
  print("YES!")
else:
  print("NO!")

Python also has many built-in functions that return a boolean value, like the isinstance() function, which can be used to determine if an object is of a certain data type:

x = 200
print(isinstance(x, int))

print(10 > 9)

Python Operators

Python Operators

Operators are used to perform operations on variables and values.

In the example below, we use the + operator to add together two values:

print(10 + 5)

Python divides the operators in the following groups:

• Arithmetic operators
• Assignment operators
• Comparison operators
• Logical operators
• Identity operators
• Membership operators
• Bitwise operators

Python Arithmetic Operators

Arithmetic operators are used with numeric values to perform common mathematical operations:

Python Assignment Operators

Assignment operators are used to assign values to variables:

Python Comparison Operators

Comparison operators are used to compare two values:

Python Logical Operators

Logical operators are used to combine conditional statements:

Python Identity Operators

Identity operators are used to compare the objects, not if they are equal, but if they are actually the same object, with the same memory location:

Python Membership Operators

Membership operators are used to test if a sequence is presented in an object:

Python Bitwise Operators

Bitwise operators are used to compare (binary) numbers:

print(10  5)

Python If … Else

Python Conditions and If statements

Python supports the usual logical conditions from mathematics:

• Equals: a == b
• Not Equals: a != b
• Less than: a < b
• Less than or equal to: a <= b
• Greater than: a > b
• Greater than or equal to: a >= b

These conditions can be used in several ways, most commonly in “if statements” and loops.

An “if statement” is written by using the if keyword.

a = 33
b = 200
if b > a:
  print("b is greater than a")

In this example we use two variables, a and b, which are used as part of the if statement to test whether b is greater than a. As a is 33, and b is 200, we know that 200 is greater than 33, and so we print to screen that “b is greater than a”.

Indentation

Python relies on indentation (whitespace at the beginning of a line) to define scope in the code. Other programming languages often use curly-brackets for this purpose.

a = 33
b = 200
if b > a:
print("b is greater than a") # you will get an error

Elif

The elif keyword is pythons way of saying “if the previous conditions were not true, then try this condition”.

a = 33
b = 33
if b > a:
  print("b is greater than a")
elif a == b:
  print("a and b are equal")

In this example a is equal to b, so the first condition is not true, but the elif condition is true, so we print to screen that “a and b are equal”.

Else

The else keyword catches anything which isn’t caught by the preceding conditions.

a = 200
b = 33
if b > a:
  print("b is greater than a")
elif a == b:
  print("a and b are equal")
else:
  print("a is greater than b")

In this example a is greater than b, so the first condition is not true, also the elif condition is not true, so we go to the else condition and print to screen that “a is greater than b”.

You can also have an else without the elif:

a = 200
b = 33
if b > a:
  print("b is greater than a")
else:
  print("b is not greater than a")

Short Hand If

If you have only one statement to execute, you can put it on the same line as the if statement.

if a > b: print("a is greater than b")

Short Hand If … Else

If you have only one statement to execute, one for if, and one for else, you can put it all on the same line:

a = 2
b = 330
print("A") if a > b else print("B")

You can also have multiple else statements on the same line:

a = 330
b = 330
print("A") if a > b else print("=") if a == b else print("B")

And

The and keyword is a logical operator, and is used to combine conditional statements:

a = 200
b = 33
c = 500
if a > b and c > a:
  print("Both conditions are True")

Or

The or keyword is a logical operator, and is used to combine conditional statements:

a = 200
b = 33
c = 500
if a > b or a > c:
  print("At least one of the conditions is True")

Nested If

You can have if statements inside if statements, this is called nested if statements.

x = 41

if x > 10:
  print("Above ten,")
  if x > 20:
    print("and also above 20!")
  else:
    print("but not above 20.")

The pass Statement

if statements cannot be empty, but if you for some reason have an if statement with no content, put in the pass statement to avoid getting an error.

a = 33
b = 200

if b > a:
  pass

a = 50
b = 10
 a  b
  print("Hello World")

Python While Loops

Python Loops

Python has two primitive loop commands:

• while loops
• for loops

The while Loop

With the while loop we can execute a set of statements as long as a condition is true.

i = 1
while i < 6:
  print(i)
  i += 1

The while loop requires relevant variables to be ready, in this example we need to define an indexing variable, i, which we set to 1.

The break Statement

With the break statement we can stop the loop even if the while condition is true:

i = 1
while i < 6:
  print(i)
  if i == 3:
    break
  i += 1

The continue Statement

With the continue statement we can stop the current iteration, and continue with the next:

i = 0
while i < 6:
  i += 1
  if i == 3:
    continue
  print(i)

The else Statement

With the else statement we can run a block of code once when the condition no longer is true:

i = 1
while i < 6:
  print(i)
  i += 1
else:
  print("i is no longer less than 6")

i = 1
 i < 6
  print(i)
  i += 1

Python For Loops

Python For Loops

A for loop is used for iterating over a sequence (that is either a list, a tuple, a dictionary, a set, or a string).

This is less like the for keyword in other programming languages, and works more like an iterator method as found in other object-orientated programming languages.

With the for loop we can execute a set of statements, once for each item in a list, tuple, set etc.

fruits = ["apple", "banana", "cherry"]
for x in fruits:
  print(x)

The for loop does not require an indexing variable to set beforehand.

Looping Through a String

Even strings are iterable objects, they contain a sequence of characters:

for x in "banana":
  print(x)

The break Statement

With the break statement we can stop the loop before it has looped through all the items:

fruits = ["apple", "banana", "cherry"]
for x in fruits:
  print(x)
  if x == "banana":
    break

fruits = ["apple", "banana", "cherry"]
for x in fruits:
  if x == "banana":
    break
  print(x)

The continue Statement

With the continue statement we can stop the current iteration of the loop, and continue with the next:

fruits = ["apple", "banana", "cherry"]
for x in fruits:
  if x == "banana":
    continue
  print(x)

The range() Function

To loop through a set of code a specified number of times, we can use the range() function,

The range() function returns a sequence of numbers, starting from 0 by default, and increments by 1 (by default), and ends at a specified number.

for x in range(6):
  print(x)

The range() function defaults to 0 as a starting value, however it is possible to specify the starting value by adding a parameter: range(2, 6), which means values from 2 to 6 (but not including 6):

for x in range(2, 6):
  print(x)

The range() function defaults to increment the sequence by 1, however it is possible to specify the increment value by adding a third parameter: range(2, 30, 3):

for x in range(2, 30, 3):
  print(x)

Else in For Loop

The else keyword in a for loop specifies a block of code to be executed when the loop is finished:

for x in range(6):
  print(x)
else:
  print("Finally finished!")

for x in range(6):
  if x == 3: break
  print(x)
else:
  print("Finally finished!")

Nested Loops

A nested loop is a loop inside a loop.

The “inner loop” will be executed one time for each iteration of the “outer loop”:

adj = ["red", "big", "tasty"]
fruits = ["apple", "banana", "cherry"]

for x in adj:
  for y in fruits:
    print(x, y)

The pass Statement

for loops cannot be empty, but if you for some reason have a for loop with no content, put in the pass statement to avoid getting an error.

for x in [0, 1, 2]:
  pass

fruits = ["apple", "banana", "cherry"]
 x  fruits
  print(x)

Python Functions

A function is a block of code which only runs when it is called.

You can pass data, known as parameters, into a function.

A function can return data as a result.

Creating a Function

In Python a function is defined using the def keyword:

Calling a Function

To call a function, use the function name followed by parenthesis:

Arguments

Information can be passed into functions as arguments.

Arguments are specified after the function name, inside the parentheses. You can add as many arguments as you want, just separate them with a comma.

The following example has a function with one argument (fname). When the function is called, we pass along a first name, which is used inside the function to print the full name:

Parameters or Arguments?

The terms parameter and argument can be used for the same thing: information that are passed into a function.

Number of Arguments

By default, a function must be called with the correct number of arguments. Meaning that if your function expects 2 arguments, you have to call the function with 2 arguments, not more, and not less.

If you try to call the function with 1 or 3 arguments, you will get an error:

Arbitrary Arguments, *args

If you do not know how many arguments that will be passed into your function, add a * before the parameter name in the function definition.

This way the function will receive a tuple of arguments, and can access the items accordingly:

Keyword Arguments

You can also send arguments with the key = value syntax.

This way the order of the arguments does not matter.

Arbitrary Keyword Arguments, **kwargs

If you do not know how many keyword arguments that will be passed into your function, add two asterisk: ** before the parameter name in the function definition.

This way the function will receive a dictionary of arguments, and can access the items accordingly:

Default Parameter Value

The following example shows how to use a default parameter value.

If we call the function without argument, it uses the default value:

Passing a List as an Argument

You can send any data types of argument to a function (string, number, list, dictionary etc.), and it will be treated as the same data type inside the function.

E.g. if you send a List as an argument, it will still be a List when it reaches the function:

Return Values

To let a function return a value, use the return statement:

The pass Statement

function definitions cannot be empty, but if you for some reason have a function definition with no content, put in the pass statement to avoid getting an error.

Recursion

Python also accepts function recursion, which means a defined function can call itself.

Recursion is a common mathematical and programming concept. It means that a function calls itself. This has the benefit of meaning that you can loop through data to reach a result.

The developer should be very careful with recursion as it can be quite easy to slip into writing a function which never terminates, or one that uses excess amounts of memory or processor power. However, when written correctly recursion can be a very efficient and mathematically-elegant approach to programming.

In this example, tri_recursion() is a function that we have defined to call itself (“recurse”). We use the k variable as the data, which decrements (-1) every time we recurse. The recursion ends when the condition is not greater than 0 (i.e. when it is 0).

To a new developer it can take some time to work out how exactly this works, best way to find out is by testing and modifying it.

:
  print("Hello from a function")

Python Lambda

A lambda function is a small anonymous function.

A lambda function can take any number of arguments, but can only have one expression.

Syntax

The expression is executed and the result is returned:

Lambda functions can take any number of arguments:

Why Use Lambda Functions?

The power of lambda is better shown when you use them as an anonymous function inside another function.

Say you have a function definition that takes one argument, and that argument will be multiplied with an unknown number:

Use that function definition to make a function that always doubles the number you send in:

Or, use the same function definition to make a function that always triples the number you send in:

Or, use the same function definition to make both functions, in the same program:

x =    

Python Arrays

Arrays

Arrays are used to store multiple values in one single variable:

What is an Array?

An array is a special variable, which can hold more than one value at a time.

If you have a list of items (a list of car names, for example), storing the cars in single variables could look like this:

However, what if you want to loop through the cars and find a specific one? And what if you had not 3 cars, but 300?

The solution is an array!

An array can hold many values under a single name, and you can access the values by referring to an index number.

Access the Elements of an Array

You refer to an array element by referring to the index number.

The Length of an Array

Use the len() method to return the length of an array (the number of elements in an array).

Looping Array Elements

You can use the for in loop to loop through all the elements of an array.

Adding Array Elements

You can use the append() method to add an element to an array.

Removing Array Elements

You can use the pop() method to remove an element from the array.

You can also use the remove() method to remove an element from the array.

Array Methods

Python has a set of built-in methods that you can use on lists/arrays.

Python Classes and Objects

Python Classes/Objects

Python is an object oriented programming language.

Almost everything in Python is an object, with its properties and methods.

A Class is like an object constructor, or a “blueprint” for creating objects.

Create a Class

To create a class, use the keyword class:

Create Object

Now we can use the class named MyClass to create objects:

The __init__() Function

The examples above are classes and objects in their simplest form, and are not really useful in real life applications.

To understand the meaning of classes we have to understand the built-in __init__() function.

All classes have a function called __init__(), which is always executed when the class is being initiated.

Use the __init__() function to assign values to object properties, or other operations that are necessary to do when the object is being created:

Object Methods

Objects can also contain methods. Methods in objects are functions that belong to the object.

Let us create a method in the Person class:

The self Parameter

The self parameter is a reference to the current instance of the class, and is used to access variables that belongs to the class.

It does not have to be named self , you can call it whatever you like, but it has to be the first parameter of any function in the class:

Modify Object Properties

You can modify properties on objects like this:

Delete Object Properties

You can delete properties on objects by using the del keyword:

Delete Objects

You can delete objects by using the del keyword:

The pass Statement

class definitions cannot be empty, but if you for some reason have a class definition with no content, put in the pass statement to avoid getting an error.

 MyClass:
  x = 5

Python Inheritance

Python Inheritance

Inheritance allows us to define a class that inherits all the methods and properties from another class.

Parent class is the class being inherited from, also called base class.

Child class is the class that inherits from another class, also called derived class.

Create a Parent Class

Any class can be a parent class, so the syntax is the same as creating any other class:

Create a Child Class

To create a class that inherits the functionality from another class, send the parent class as a parameter when creating the child class:

Now the Student class has the same properties and methods as the Person class.

Add the __init__() Function

So far we have created a child class that inherits the properties and methods from its parent.

We want to add the __init__() function to the child class (instead of the pass keyword).

When you add the __init__() function, the child class will no longer inherit the parent’s __init__() function.

To keep the inheritance of the parent’s __init__() function, add a call to the parent’s __init__() function:

Now we have successfully added the __init__() function, and kept the inheritance of the parent class, and we are ready to add functionality in the __init__() function.

Use the super() Function

Python also has a super() function that will make the child class inherit all the methods and properties from its parent:

By using the super() function, you do not have to use the name of the parent element, it will automatically inherit the methods and properties from its parent.

Add Properties

In the example below, the year 2019 should be a variable, and passed into the Student class when creating student objects. To do so, add another parameter in the __init__() function:

Add Methods

If you add a method in the child class with the same name as a function in the parent class, the inheritance of the parent method will be overridden.

class :

Python Iterators

Python Iterators

An iterator is an object that contains a countable number of values.

An iterator is an object that can be iterated upon, meaning that you can traverse through all the values.

Technically, in Python, an iterator is an object which implements the iterator protocol, which consist of the methods __iter__() and __next__().

Iterator vs Iterable

Lists, tuples, dictionaries, and sets are all iterable objects. They are iterable containers which you can get an iterator from.

All these objects have a iter() method which is used to get an iterator:

Even strings are iterable objects, and can return an iterator:

Looping Through an Iterator

We can also use a for loop to iterate through an iterable object:

The for loop actually creates an iterator object and executes the next() method for each loop.

Create an Iterator

To create an object/class as an iterator you have to implement the methods __iter__() and __next__() to your object.

As you have learned in the Python Classes/Objects chapter, all classes have a function called __init__(), which allows you to do some initializing when the object is being created.

The __iter__() method acts similar, you can do operations (initializing etc.), but must always return the iterator object itself.

The __next__() method also allows you to do operations, and must return the next item in the sequence.

StopIteration

The example above would continue forever if you had enough next() statements, or if it was used in a for loop.

To prevent the iteration to go on forever, we can use the StopIteration statement.

In the __next__() method, we can add a terminating condition to raise an error if the iteration is done a specified number of times:

Python Scope

A variable is only available from inside the region it is created. This is called scope.

Local Scope

A variable created inside a function belongs to the local scope of that function, and can only be used inside that function.

Function Inside Function

As explained in the example above, the variable x is not available outside the function, but it is available for any function inside the function:

Global Scope

A variable created in the main body of the Python code is a global variable and belongs to the global scope.

Global variables are available from within any scope, global and local.

Naming Variables

If you operate with the same variable name inside and outside of a function, Python will treat them as two separate variables, one available in the global scope (outside the function) and one available in the local scope (inside the function):

Global Keyword

If you need to create a global variable, but are stuck in the local scope, you can use the global keyword.

The global keyword makes the variable global.

Also, use the global keyword if you want to make a change to a global variable inside a function.

Python Modules

What is a Module?

Consider a module to be the same as a code library.

A file containing a set of functions you want to include in your application.

Create a Module

To create a module just save the code you want in a file with the file extension .py:

Use a Module

Now we can use the module we just created, by using the import statement:

Variables in Module

The module can contain functions, as already described, but also variables of all types (arrays, dictionaries, objects etc):

Naming a Module

You can name the module file whatever you like, but it must have the file extension .py

Re-naming a Module

You can create an alias when you import a module, by using the as keyword:

Built-in Modules

There are several built-in modules in Python, which you can import whenever you like.

Using the dir() Function

There is a built-in function to list all the function names (or variable names) in a module. The dir() function:

Import From Module

You can choose to import only parts from a module, by using the from keyword.

 mymodule

Python Datetime

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Python Math

Python has a set of built-in math functions, including an extensive math module, that allows you to perform mathematical tasks on numbers.

Built-in Math Functions

The min() and max() functions can be used to find the lowest or highest value in an iterable:

The abs() function returns the absolute (positive) value of the specified number:

The pow(x, y) function returns the value of x to the power of y (x^y).

The Math Module

Python has also a built-in module called math, which extends the list of mathematical functions.

To use it, you must import the math module:

When you have imported the math module, you can start using methods and constants of the module.

The math.sqrt() method for example, returns the square root of a number:

The math.ceil() method rounds a number upwards to its nearest integer, and the math.floor() method rounds a number downwards to its nearest integer, and returns the result:

The math.pi constant, returns the value of PI (3.14…):

Complete Math Module Reference

In our Math Module Reference you will find a complete reference of all methods and constants that belongs to the Math module.

Python JSON

JSON is a syntax for storing and exchanging data.

JSON is text, written with JavaScript object notation.

JSON in Python

Python has a built-in package called json, which can be used to work with JSON data.

Parse JSON – Convert from JSON to Python

If you have a JSON string, you can parse it by using the json.loads() method.

Convert from Python to JSON

If you have a Python object, you can convert it into a JSON string by using the json.dumps() method.

You can convert Python objects of the following types, into JSON strings:

• dict
• list
• tuple
• string
• int
• float
• True
• False
• None

When you convert from Python to JSON, Python objects are converted into the JSON (JavaScript) equivalent:

Format the Result

The example above prints a JSON string, but it is not very easy to read, with no indentations and line breaks.

The json.dumps() method has parameters to make it easier to read the result:

You can also define the separators, default value is (“, “, “: “), which means using a comma and a space to separate each object, and a colon and a space to separate keys from values:

Order the Result

The json.dumps() method has parameters to order the keys in the result:

Python RegEx

A RegEx, or Regular Expression, is a sequence of characters that forms a search pattern.

RegEx can be used to check if a string contains the specified search pattern.

RegEx Module

Python has a built-in package called re, which can be used to work with Regular Expressions.

Import the re module:

RegEx in Python

When you have imported the re module, you can start using regular expressions:

RegEx Functions

The re module offers a set of functions that allows us to search a string for a match:

Metacharacters

Metacharacters are characters with a special meaning:

Special Sequences

A special sequence is a \ followed by one of the characters in the list below, and has a special meaning:

Sets

A set is a set of characters inside a pair of square brackets [] with a special meaning:

The findall() Function

The findall() function returns a list containing all matches.

The list contains the matches in the order they are found.

If no matches are found, an empty list is returned:

The search() Function

The search() function searches the string for a match, and returns a Match object if there is a match.

If there is more than one match, only the first occurrence of the match will be returned:

If no matches are found, the value None is returned:

The split() Function

The split() function returns a list where the string has been split at each match:

You can control the number of occurrences by specifying the maxsplit parameter:

The sub() Function

The sub() function replaces the matches with the text of your choice:

You can control the number of replacements by specifying the count parameter:

Match Object

A Match Object is an object containing information about the search and the result.

The Match object has properties and methods used to retrieve information about the search, and the result:

.span() returns a tuple containing the start-, and end positions of the match.
.string returns the string passed into the function
.group() returns the part of the string where there was a match

Python PIP

What is PIP?

PIP is a package manager for Python packages, or modules if you like.

What is a Package?

A package contains all the files you need for a module.

Modules are Python code libraries you can include in your project.

Check if PIP is Installed

Navigate your command line to the location of Python’s script directory, and type the following:

Install PIP

If you do not have PIP installed, you can download and install it from this page: https://pypi.org/project/pip/

Download a Package

Downloading a package is very easy.

Open the command line interface and tell PIP to download the package you want.

Navigate your command line to the location of Python’s script directory, and type the following:

Now you have downloaded and installed your first package!

Using a Package

Once the package is installed, it is ready to use.

Import the “camelcase” package into your project.

Find Packages

Find more packages at https://pypi.org/.

Remove a Package

Use the uninstall command to remove a package:

The PIP Package Manager will ask you to confirm that you want to remove the camelcase package:

Press y and the package will be removed.

List Packages

Use the list command to list all the packages installed on your system:

Python Try Except

The try block lets you test a block of code for errors.

The except block lets you handle the error.

The else block lets you execute code when there is no error.

The finally block lets you execute code, regardless of the result of the try- and except blocks.

Exception Handling

When an error occurs, or exception as we call it, Python will normally stop and generate an error message.

These exceptions can be handled using the try statement:

Since the try block raises an error, the except block will be executed.

Without the try block, the program will crash and raise an error:

Many Exceptions

You can define as many exception blocks as you want, e.g. if you want to execute a special block of code for a special kind of error:

Else

You can use the else keyword to define a block of code to be executed if no errors were raised:

Finally

The finally block, if specified, will be executed regardless if the try block raises an error or not.

This can be useful to close objects and clean up resources:

The program can continue, without leaving the file object open.

Raise an exception

As a Python developer you can choose to throw an exception if a condition occurs.

To throw (or raise) an exception, use the raise keyword.

The raise keyword is used to raise an exception.

You can define what kind of error to raise, and the text to print to the user.

Python User Input

User Input

Python allows for user input.

That means we are able to ask the user for input.

The method is a bit different in Python 3.6 than Python 2.7.

Python 3.6 uses the input() method.

Python 2.7 uses the raw_input() method.

The following example asks for the username, and when you entered the username, it gets printed on the screen:

Python String Formatting

To make sure a string will display as expected, we can format the result with the format() method.

String format()

The format() method allows you to format selected parts of a string.

Sometimes there are parts of a text that you do not control, maybe they come from a database, or user input?

To control such values, add placeholders (curly brackets {}) in the text, and run the values through the format() method:

You can add parameters inside the curly brackets to specify how to convert the value:

Check out all formatting types in our String format() Reference.

Multiple Values

If you want to use more values, just add more values to the format() method:

And add more placeholders:

Index Numbers

You can use index numbers (a number inside the curly brackets {0}) to be sure the values are placed in the correct placeholders:

Also, if you want to refer to the same value more than once, use the index number:

Named Indexes

You can also use named indexes by entering a name inside the curly brackets {carname}, but then you must use names when you pass the parameter values txt.format(carname = "Ford"):