Python lessons for beginners from scratch – a complete course for learning to program in Python. Learn the python programming language for free, basics from scratch, complete python learning lecture course. The course video covers all the main topics with examples and practice necessary for a junior python developer. At the end of the course, you will know all the basic python syntax and be free to write your own code!
Python is a popular programming language.
Python can be used on a server to create web applications.
With our “Try it Yourself” editor, you can edit Python code and view the result.
Click on the “Try it Yourself” button to see how it works.
In our File Handling section you will learn how to open, read, write, and delete files.
In our database section you will learn how to access and work with MySQL and MongoDB databases:
Learn by examples! This tutorial supplements all explanations with clarifying examples.
Test your Python skills with a quiz.
You will also find complete function and method references:
Download Python from the official Python web site: https://python.org
Python is a popular programming language. It was created by Guido van Rossum, and released in 1991.
It is used for:
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):
C:\Users\Your Name>python --version
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:
python --version
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 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:
C:\Users\Your Name>python helloworld.py
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.
Simple as that. Save your file. Open your command line, navigate to the directory where you saved your file, and run:
C:\Users\Your Name>python helloworld.py
The output should read:
Hello, World!
Congratulations, you have written and executed your first Python program.
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:
C:\Users\Your Name>python
Or, if the “python” command did not work, you can try “py”:
C:\Users\Your Name>py
From there you can write any python, including our hello world example from earlier in the tutorial:
C:\Users\Your Name>python
Python 3.6.4 (v3.6.4:d48eceb, Dec 19 2017, 06:04:45) [MSC v.1900 32 bit (Intel)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> print("Hello, World!")
Which will write “Hello, World!” in the command line:
C:\Users\Your Name>python
Python 3.6.4 (v3.6.4:d48eceb, Dec 19 2017, 06:04:45) [MSC v.1900 32 bit (Intel)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> print("Hello, World!")
Hello, World!
Whenever you are done in the python command line, you can simply type the following to quit the python command line interface:
exit()
As we learned in the previous page, Python syntax can be executed by writing directly in the Command Line:
>>> print("Hello, World!")
Hello, World!
On this page
Or by creating a python file on the server, using the .py file extension, and running it in the Command Line:
C:\Users\Your Name>python myfile.py
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.
Python will give you an error if you skip the indentation:
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:
Syntax Error:
if 5 > 2:
print("Five is greater than two!")
print("Five is greater than two!")
In Python, variables are created when you assign a value to it:
Python has no command for declaring a variable.
You will learn more about variables in the Python Variables chapter.
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:
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.
Comments starts with a #
, and Python will ignore them:
Comments can be placed at the end of a line, and Python will ignore the rest of the line:
A comment does not have to be text that explains the code, it can also be used to prevent Python from executing code:
Python does not really have a syntax for multi line comments.
To add a multiline comment you could insert a #
for each line:
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!")
In programming, data type is an important concept.
Variables can store data of different types, and different types can do different things.
Python has the following data types built-in by default, in these categories:
Text Type: | str |
Numeric Types: | int , float , complex |
Sequence Types: | list , tuple , range |
Mapping Type: | dict |
Set Types: | set , frozenset |
Boolean Type: | bool |
Binary Types: | bytes , bytearray , memoryview |
You can get the data type of any object by using the type()
function:
In Python, the data type is set when you assign a value to a variable:
Example | Data Type | Try it |
---|---|---|
x = “Hello World” | str | Try it » |
x = 20 | int | Try it » |
x = 20.5 | float | Try it » |
x = 1j | complex | Try it » |
x = [“apple”, “banana”, “cherry”] | list | Try it » |
x = (“apple”, “banana”, “cherry”) | tuple | Try it » |
x = range(6) | range | Try it » |
x = {“name” : “John”, “age” : 36} | dict | Try it » |
x = {“apple”, “banana”, “cherry”} | set | Try it » |
x = frozenset({“apple”, “banana”, “cherry”}) | frozenset | Try it » |
x = True | bool | Try it » |
x = b”Hello” | bytes | Try it » |
x = bytearray(5) | bytearray | Try it » |
x = memoryview(bytes(5)) | memoryview | Try it » |
If you want to specify the data type, you can use the following constructor functions:
Example | Data Type | Try it |
---|---|---|
x = str(“Hello World”) | str | Try it » |
x = int(20) | int | Try it » |
x = float(20.5) | float | Try it » |
x = complex(1j) | complex | Try it » |
x = list((“apple”, “banana”, “cherry”)) | list | Try it » |
x = tuple((“apple”, “banana”, “cherry”)) | tuple | Try it » |
x = range(6) | range | Try it » |
x = dict(name=”John”, age=36) | dict | Try it » |
x = set((“apple”, “banana”, “cherry”)) | set | Try it » |
x = frozenset((“apple”, “banana”, “cherry”)) | frozenset | Try it » |
x = bool(5) | bool | Try it » |
x = bytes(5) | bytes | Try it » |
x = bytearray(5) | bytearray | Try it » |
x = memoryview(bytes(5)) | memoryview | Try it » |
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:
Int, or integer, is a whole number, positive or negative, without decimals, of unlimited length.
Integers:
x = 1
y = 35656222554887711
z = -3255522
print(type(x))
print(type(y))
print(type(z))
Float, or “floating point number” is a number, positive or negative, containing one or more decimals.
Float can also be scientific numbers with an “e” to indicate the power of 10.
Floats:
x = 35e3
y = 12E4
z = -87.7e100
print(type(x))
print(type(y))
print(type(z))
Complex numbers are written with a “j” as the imaginary part:
You can convert from one type to another with the int()
, float()
, and complex()
methods:
Convert from one type to another:
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(a))
print(type(b))
print(type(c))
Note: You cannot convert complex numbers into another number type.
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 the random module, and display a random number between 1 and 9:
import random
print(random.randrange(1, 10))
In our Random Module Reference you will learn more about the Random module.
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:
Integers:
x = int(1) # x will be 1
y = int(2.8) # y will be 2
z = int("3") # z will be 3
Floats:
x = int(1) # x will be 1.0
y = int(2.8) # y will be 2.8
z = int("3") # z will be 3.0
w = float("4.2") # w will be 4.2
Strings:
x = str("s1") # x will be 's1'
y = str(2) # y will be '2'
z = str(3.0) # z will be '3.0'
Booleans represent one of two values: True
or False
.
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:
When you run a condition in an if statement, Python returns True
or False
:
Print a message based on whether the condition is True
or False
:
a = 200
b = 33
if b > a:
print(“b is greater than a”)
else:
print(“b is not greater than a”)
The bool()
function allows you to evaluate any value, and give you True
or False
in return,
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.
The following will return True:
bool("abc")
bool(123)
bool(["apple", "cherry", "banana"])
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
.
The following will return 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))
You can create functions that returns a Boolean Value:
Print the answer of a function:
def myFunction() :
return True
print(myFunction())
You can execute code based on the Boolean answer of a function:
Print “YES!” if the function returns True, otherwise print “NO!”:
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:
Operators are used to perform operations on variables and values.
In the example below, we use the +
operator to add together two values:
Python divides the operators in the following groups:
Arithmetic operators are used with numeric values to perform common mathematical operations:
Operator | Name | Example | Try it |
---|---|---|---|
+ | Addition | x + y | Try it » |
– | Subtraction | x – y | Try it » |
* | Multiplication | x * y | Try it » |
/ | Division | x / y | Try it » |
% | Modulus | x % y | Try it » |
** | Exponentiation | x ** y | Try it » |
// | Floor division | x // y | Try it » |
Assignment operators are used to assign values to variables:
Operator | Example | Same As | Try it |
---|---|---|---|
= | x = 5 | x = 5 | Try it » |
+= | x += 3 | x = x + 3 | Try it » |
-= | x -= 3 | x = x – 3 | Try it » |
*= | x *= 3 | x = x * 3 | Try it » |
/= | x /= 3 | x = x / 3 | Try it » |
%= | x %= 3 | x = x % 3 | Try it » |
//= | x //= 3 | x = x // 3 | Try it » |
**= | x **= 3 | x = x ** 3 | Try it » |
&= | x &= 3 | x = x & 3 | Try it » |
|= | x |= 3 | x = x | 3 | Try it » |
^= | x ^= 3 | x = x ^ 3 | Try it » |
>>= | x >>= 3 | x = x >> 3 | Try it » |
<<= | x <<= 3 | x = x << 3 | Try it » |
Comparison operators are used to compare two values:
Operator | Name | Example | Try it |
---|---|---|---|
== | Equal | x == y | Try it » |
!= | Not equal | x != y | Try it » |
> | Greater than | x > y | Try it » |
< | Less than | x < y | Try it » |
>= | Greater than or equal to | x >= y | Try it » |
<= | Less than or equal to | x <= y | Try it » |
Logical operators are used to combine conditional statements:
Operator | Description | Example | Try it |
---|---|---|---|
and | Returns True if both statements are true | x < 5 and x < 10 | Try it » |
or | Returns True if one of the statements is true | x < 5 or x < 4 | Try it » |
not | Reverse the result, returns False if the result is true | not(x < 5 and x < 10) | Try it » |
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:
Operator | Description | Example | Try it |
---|---|---|---|
is | Returns True if both variables are the same object | x is y | Try it » |
is not | Returns True if both variables are not the same object | x is not y | Try it » |
Membership operators are used to test if a sequence is presented in an object:
Operator | Description | Example | Try it |
---|---|---|---|
in | Returns True if a sequence with the specified value is present in the object | x in y | Try it » |
not in | Returns True if a sequence with the specified value is not present in the object | x not in y | Try it » |
Bitwise operators are used to compare (binary) numbers:
Operator | Name | Description |
---|---|---|
& | AND | Sets each bit to 1 if both bits are 1 |
| | OR | Sets each bit to 1 if one of two bits is 1 |
^ | XOR | Sets each bit to 1 if only one of two bits is 1 |
~ | NOT | Inverts all the bits |
<< | Zero fill left shift | Shift left by pushing zeros in from the right and let the leftmost bits fall off |
>> | Signed right shift | Shift right by pushing copies of the leftmost bit in from the left, and let the rightmost bits fall off |
Python supports the usual logical conditions from mathematics:
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.
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”.
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.
If statement, without indentation (will raise an error):
a = 33
b = 200
if b > a:
print("b is greater than a") # you will get an error
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”.
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")
If you have only one statement to execute, you can put it on the same line as the if statement.
If you have only one statement to execute, one for if, and one for else, you can put it all on the same line:
This technique is known as Ternary Operators, or Conditional Expressions.
You can also have multiple else statements on the same line:
One line if else statement, with 3 conditions:
a = 330
b = 330
print("A") if a > b else print("=") if a == b else print("B")
The and keyword is a logical operator, and is used to combine conditional statements:
Test if a
is greater than b
, AND if c
is greater than a
:
a = 200
b = 33
c = 500
if a > b and c > a:
print("Both conditions are True")
The or
keyword is a logical operator, and is used to combine conditional statements:
Test if a
is greater than b
, OR if a
is greater than c
:
a = 200
b = 33
c = 500
if a > b or a > c:
print("At least one of the conditions is True")
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.”)
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.
Python has two primitive loop commands:
With the while loop we can execute a set of statements as long as a condition is true.
Print i as long as i is less than 6:
i = 1
while i < 6:
print(i)
i += 1
Note: remember to increment i, or else the loop will continue forever.
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.
With the break statement we can stop the loop even if the while condition is true:
Exit the loop when i is 3:
i = 1
while i < 6:
print(i)
if i == 3:
break
i += 1
With the continue statement we can stop the current iteration, and continue with the next:
Continue to the next iteration if i is 3:
i = 0
while i < 6:
i += 1
if i == 3:
continue
print(i)
With the else statement we can run a block of code once when the condition no longer is true:
Print a message once the condition is false:
i = 1
while i < 6:
print(i)
i += 1
else:
print("i is no longer less than 6")
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.
Print each fruit in a fruit list:
fruits = ["apple", "banana", "cherry"]
for x in fruits:
print(x)
The for loop does not require an indexing variable to set beforehand.
Even strings are iterable objects, they contain a sequence of characters:
With the break statement we can stop the loop before it has looped through all the items:
Exit the loop when x
is “banana”:
fruits = ["apple", "banana", "cherry"]
for x in fruits:
print(x)
if x == "banana":
break
Exit the loop when x
is “banana”, but this time the break comes before the print:
fruits = ["apple", "banana", "cherry"]
for x in fruits:
if x == "banana":
break
print(x)
With the continue statement we can stop the current iteration of the loop, and continue with the next:
Do not print banana:
fruits = ["apple", "banana", "cherry"]
for x in fruits:
if x == "banana":
continue
print(x)
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.
Using the range() function:
for x in range(6):
print(x)
Note that range(6) is not the values of 0 to 6, but the values 0 to 5.
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):
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):
Increment the sequence with 3 (default is 1):
for x in range(2, 30, 3):
print(x)
The else
keyword in a for
loop specifies a block of code to be executed when the loop is finished:
Print all numbers from 0 to 5, and print a message when the loop has ended:
for x in range(6):
print(x)
else:
print("Finally finished!")
Note: The else
block will NOT be executed if the loop is stopped by a break
statement.
Break the loop when x
is 3, and see what happens with the else
block:
for x in range(6):
if x == 3: break
print(x)
else:
print("Finally finished!")
A nested loop is a loop inside a loop.
The “inner loop” will be executed one time for each iteration of the “outer loop”:
Print each adjective for every fruit:
adj = ["red", "big", "tasty"]
fruits = ["apple", "banana", "cherry"]
for x in adj:
for y in fruits:
print(x, y)
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.
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.
In Python a function is defined using the def keyword:
def my_function():
print("Hello from a function")
To call a function, use the function name followed by parenthesis:
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:
def my_function(fname):
print(fname + " Refsnes")
my_function(“Emil”)
my_function(“Tobias”)
my_function(“Linus”)
Arguments are often shortened to args in Python documentations.
The terms parameter and argument can be used for the same thing: information that are passed into a function.
From a function’s perspective:
A parameter is the variable listed inside the parentheses in the function definition.
An argument is the value that is sent to the function when it is called.
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.
This function expects 2 arguments, and gets 2 arguments:
def my_function(fname, lname):
print(fname + " " + lname)
my_function(“Emil”, “Refsnes”)
If you try to call the function with 1 or 3 arguments, you will get an error:
This function expects 2 arguments, but gets only 1:
def my_function(fname, lname):
print(fname + " " + lname)
my_function(“Emil”)
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:
If the number of arguments is unknown, add a *
before the parameter name:
def my_function(*kids):
print("The youngest child is " + kids[2])
my_function(“Emil”, “Tobias”, “Linus”)
Arbitrary Arguments are often shortened to *args in Python documentations.
You can also send arguments with the key = value syntax.
This way the order of the arguments does not matter.
def my_function(child3, child2, child1):
print("The youngest child is " + child3)
my_function(child1 = “Emil”, child2 = “Tobias”, child3 = “Linus”)
The phrase Keyword Arguments are often shortened to kwargs in Python documentations.
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:
If the number of keyword arguments is unknown, add a double **
before the parameter name:
def my_function(**kid):
print("His last name is " + kid["lname"])
my_function(fname = “Tobias”, lname = “Refsnes”)
Arbitrary Kword Arguments are often shortened to **kwargs in Python documentations.
The following example shows how to use a default parameter value.
If we call the function without argument, it uses the default value:
def my_function(country = "Norway"):
print("I am from " + country)
my_function(“Sweden”)
my_function(“India”)
my_function()
my_function(“Brazil”)
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:
def my_function(food):
for x in food:
print(x)
fruits = [“apple”, “banana”, “cherry”]
my_function(fruits)
To let a function return a value, use the return
statement:
def my_function(x):
return 5 * x
print(my_function(3))
print(my_function(5))
print(my_function(9))
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.
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.
Recursion Example
def tri_recursion(k):
if(k > 0):
result = k + tri_recursion(k - 1)
print(result)
else:
result = 0
return result
print(“\n\nRecursion Example Results”)
tri_recursion(6)
A lambda function is a small anonymous function.
A lambda function can take any number of arguments, but can only have one expression.
lambda arguments : expression
The expression is executed and the result is returned:
Add 10 to argument a
, and return the result:
x = lambda a : a + 10
print(x(5))
Lambda functions can take any number of arguments:
Multiply argument a
with argument b
and return the result:
x = lambda a, b : a * b
print(x(5, 6))
Summarize argument a
, b
, and c
and return the result:
x = lambda a, b, c : a + b + c
print(x(5, 6, 2))
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:
def myfunc(n):
return lambda a : a * n
Use that function definition to make a function that always doubles the number you send in:
def myfunc(n):
return lambda a : a * n
mydoubler = myfunc(2)
print(mydoubler(11))
Or, use the same function definition to make a function that always triples the number you send in:
def myfunc(n):
return lambda a : a * n
mytripler = myfunc(3)
print(mytripler(11))
Or, use the same function definition to make both functions, in the same program:
def myfunc(n):
return lambda a : a * n
mydoubler = myfunc(2)
mytripler = myfunc(3)
print(mydoubler(11))
print(mytripler(11))
Use lambda functions when an anonymous function is required for a short period of time.
Note: Python does not have built-in support for Arrays, but Python Lists can be used instead.
Note: This page shows you how to use LISTS as ARRAYS, however, to work with arrays in Python you will have to import a library, like the NumPy library.
Arrays are used to store multiple values in one single variable:
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:
car1 = “Ford”
car2 = “Volvo”
car3 = “BMW”
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.
You refer to an array element by referring to the index number.
Use the len()
method to return the length of an array (the number of elements in an array).
Return the number of elements in the cars
array:
x = len(cars)
Note: The length of an array is always one more than the highest array index.
You can use the for in
loop to loop through all the elements of an array.
You can use the append()
method to add an element to an array.
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.
Note: The list’s remove()
method only removes the first occurrence of the specified value.
Python has a set of built-in methods that you can use on lists/arrays.
Method | Description |
---|---|
append() | Adds an element at the end of the list |
clear() | Removes all the elements from the list |
copy() | Returns a copy of the list |
count() | Returns the number of elements with the specified value |
extend() | Add the elements of a list (or any iterable), to the end of the current list |
index() | Returns the index of the first element with the specified value |
insert() | Adds an element at the specified position |
pop() | Removes the element at the specified position |
remove() | Removes the first item with the specified value |
reverse() | Reverses the order of the list |
sort() | Sorts the list |
Note: Python does not have built-in support for Arrays, but Python Lists can be used instead.
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.
To create a class, use the keyword class
:
Now we can use the class named MyClass to create objects:
Create an object named p1, and print the value of x:
p1 = MyClass()
print(p1.x)
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:
Create a class named Person, use the __init__() function to assign values for name and age:
class Person:
def __init__(self, name, age):
self.name = name
self.age = age
p1 = Person("John", 36)
print(p1.name)
print(p1.age)
Note: The __init__()
function is called automatically every time the class is being used to create a new object.
Objects can also contain methods. Methods in objects are functions that belong to the object.
Let us create a method in the Person class:
Insert a function that prints a greeting, and execute it on the p1 object:
class Person:
def __init__(self, name, age):
self.name = name
self.age = age
def myfunc(self):
print(“Hello my name is “ + self.name)
p1 = Person("John", 36)
p1.myfunc()
Try it Yourself »
Note: The self
parameter is a reference to the current instance of the class, and is used to access variables that belong to the class.
The self Parameter
Theself
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 namedself
, you can call it whatever you like, but it has to be the first parameter of any function in the class:
Example
Use the words mysillyobject and abc instead of self:
class Person:
def __init__(mysillyobject, name, age):
mysillyobject.name = name
mysillyobject.age = age
def myfunc(abc):
print("Hello my name is " + abc.name)
p1 = Person("John", 36)
p1.myfunc()
You can modify properties on objects like this:
You can delete properties on objects by using the del
keyword:
You can delete objects by using the del
keyword:
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.
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.
Any class can be a parent class, so the syntax is the same as creating any other class:
Create a class named Person
, with firstname
and lastname
properties, and a printname
method:
class Person:
def __init__(self, fname, lname):
self.firstname = fname
self.lastname = lname
def printname(self):
print(self.firstname, self.lastname)
#Use the Person class to create an object, and then execute the printname method:
x = Person(“John”, “Doe”)
x.printname()
To create a class that inherits the functionality from another class, send the parent class as a parameter when creating the child class:
Create a class named Student
, which will inherit the properties and methods from the Person
class:
class Student(Person):
pass
Note: Use the pass
keyword when you do not want to add any other properties or methods to the class.
Now the Student class has the same properties and methods as the Person class.
Use the Student
class to create an object, and then execute the printname
method:
x = Student("Mike", "Olsen")
x.printname()
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).
Note: The __init__()
function is called automatically every time the class is being used to create a new object.
Add the __init__()
function to the Student
class:
class Student(Person):
def __init__(self, fname, lname):
#add properties etc.
When you add the __init__()
function, the child class will no longer inherit the parent’s __init__()
function.
Note: The child’s __init__()
function overrides the inheritance of the parent’s __init__()
function.
To keep the inheritance of the parent’s __init__()
function, add a call to the parent’s __init__()
function:
class Student(Person):
def __init__(self, fname, lname):
Person.__init__(self, fname, lname)
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.
Python also has a super()
function that will make the child class inherit all the methods and properties from its parent:
class Student(Person):
def __init__(self, fname, lname):
super().__init__(fname, lname)
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 a property called graduationyear
to the Student
class:
class Student(Person):
def __init__(self, fname, lname):
super().__init__(fname, lname)
self.graduationyear = 2019
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 a year
parameter, and pass the correct year when creating objects:
class Student(Person):
def __init__(self, fname, lname, year):
super().__init__(fname, lname)
self.graduationyear = year
x = Student(“Mike”, “Olsen”, 2019)
Add a method called welcome
to the Student
class:
class Student(Person):
def __init__(self, fname, lname, year):
super().__init__(fname, lname)
self.graduationyear = year
def welcome(self):
print(“Welcome”, self.firstname, self.lastname, “to the class of”, self.graduationyear)
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.
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__()
.
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:
Return an iterator from a tuple, and print each value:
mytuple = ("apple", "banana", "cherry")
myit = iter(mytuple)
print(next(myit))
print(next(myit))
print(next(myit))
Even strings are iterable objects, and can return an iterator:
Strings are also iterable objects, containing a sequence of characters:
mystr = "banana"
myit = iter(mystr)
print(next(myit))
print(next(myit))
print(next(myit))
print(next(myit))
print(next(myit))
print(next(myit))
We can also use a for
loop to iterate through an iterable object:
Iterate the values of a tuple:
mytuple = ("apple", "banana", "cherry")
for x in mytuple:
print(x)
The for
loop actually creates an iterator object and executes the next() method for each loop.
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.
Create an iterator that returns numbers, starting with 1, and each sequence will increase by one (returning 1,2,3,4,5 etc.):
class MyNumbers:
def __iter__(self):
self.a = 1
return self
def __next__(self):
x = self.a
self.a += 1
return x
myclass = MyNumbers()
myiter = iter(myclass)
print(next(myiter))
print(next(myiter))
print(next(myiter))
print(next(myiter))
print(next(myiter))
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:
Stop after 20 iterations:
class MyNumbers:
def __iter__(self):
self.a = 1
return self
def __next__(self):
if self.a <= 20:
x = self.a
self.a += 1
return x
else:
raise StopIteration
myclass = MyNumbers()
myiter = iter(myclass)
for x in myiter:
print(x)
A variable is only available from inside the region it is created. This is called scope.
A variable created inside a function belongs to the local scope of that function, and can only be used inside that function.
A variable created inside a function is available inside that function:
def myfunc():
x = 300
print(x)
myfunc()
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:
The local variable can be accessed from a function within the function:
def myfunc():
x = 300
def myinnerfunc():
print(x)
myinnerfunc()
myfunc()
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.
A variable created outside of a function is global and can be used by anyone:
x = 300
def myfunc():
print(x)
myfunc()
print(x)
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):
The function will print the local x
, and then the code will print the global x
:
x = 300
def myfunc():
x = 200
print(x)
myfunc()
print(x)
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.
If you use the global
keyword, the variable belongs to the global scope:
def myfunc():
global x
x = 300
myfunc()
print(x)
Also, use the global
keyword if you want to make a change to a global variable inside a function.
To change the value of a global variable inside a function, refer to the variable by using the global
keyword:
x = 300
def myfunc():
global x
x = 200
myfunc()
print(x)
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.
To create a module just save the code you want in a file with the file extension .py
:
Save this code in a file named mymodule.py
def greeting(name):
print("Hello, " + name)
Now we can use the module we just created, by using the import
statement:
Import the module named mymodule, and call the greeting function:
import mymodule
mymodule.greeting("Jonathan")
Note: When using a function from a module, use the syntax: module_name.function_name.
The module can contain functions, as already described, but also variables of all types (arrays, dictionaries, objects etc):
Save this code in the file mymodule.py
person1 = {
"name": "John",
"age": 36,
"country": "Norway"
}
Import the module named mymodule, and access the person1 dictionary:
import mymodule
a = mymodule.person1["age"]
print(a)
You can name the module file whatever you like, but it must have the file extension .py
You can create an alias when you import a module, by using the as
keyword:
Create an alias for mymodule
called mx
:
import mymodule as mx
a = mx.person1["age"]
print(a)
There are several built-in modules in Python, which you can import whenever you like.
Import and use the platform
module:
import platform
x = platform.system()
print(x)
There is a built-in function to list all the function names (or variable names) in a module. The dir()
function:
List all the defined names belonging to the platform module:
import platform
x = dir(platform)
print(x)
Note: The dir() function can be used on all modules, also the ones you create yourself.
You can choose to import only parts from a module, by using the from
keyword.
The module named mymodule
has one function and one dictionary:
def greeting(name):
print("Hello, " + name)
person1 = {
"name": "John",
"age": 36,
"country": "Norway"
}
Import only the person1 dictionary from the module:
from mymodule import person1
print (person1["age"])
Note: When importing using the from
keyword, do not use the module name when referring to elements in the module. Example: person1["age"]
, not mymodule.person1["age"]
A date in Python is not a data type of its own, but we can import a module named datetime
to work with dates as date objects.
Import the datetime module and display the current date:
import datetime
x = datetime.datetime.now()
print(x)
When we execute the code from the example above the result will be:
2022-04-28 23:32:48.609004
The date contains year, month, day, hour, minute, second, and microsecond.
The datetime
module has many methods to return information about the date object.
Here are a few examples, you will learn more about them later in this chapter:
Return the year and name of weekday:
import datetime
x = datetime.datetime.now()
print(x.year)
print(x.strftime("%A"))
To create a date, we can use the datetime()
class (constructor) of the datetime
module.
The datetime()
class requires three parameters to create a date: year, month, day.
Create a date object:
import datetime
x = datetime.datetime(2020, 5, 17)
print(x)
The datetime()
class also takes parameters for time and timezone (hour, minute, second, microsecond, tzone), but they are optional, and has a default value of 0
, (None
for timezone).
The datetime
object has a method for formatting date objects into readable strings.
The method is called strftime()
, and takes one parameter, format
, to specify the format of the returned string:
Display the name of the month:
import datetime
x = datetime.datetime(2018, 6, 1)
print(x.strftime("%B"))
A reference of all the legal format codes:
Directive | Description | Example | Try it |
---|---|---|---|
%a | Weekday, short version | Wed | Try it » |
%A | Weekday, full version | Wednesday | Try it » |
%w | Weekday as a number 0-6, 0 is Sunday | 3 | Try it » |
%d | Day of month 01-31 | 31 | Try it » |
%b | Month name, short version | Dec | Try it » |
%B | Month name, full version | December | Try it » |
%m | Month as a number 01-12 | 12 | Try it » |
%y | Year, short version, without century | 18 | Try it » |
%Y | Year, full version | 2018 | Try it » |
%H | Hour 00-23 | 17 | Try it » |
%I | Hour 00-12 | 05 | Try it » |
%p | AM/PM | PM | Try it » |
%M | Minute 00-59 | 41 | Try it » |
%S | Second 00-59 | 08 | Try it » |
%f | Microsecond 000000-999999 | 548513 | Try it » |
%z | UTC offset | +0100 | |
%Z | Timezone | CST | |
%j | Day number of year 001-366 | 365 | Try it » |
%U | Week number of year, Sunday as the first day of week, 00-53 | 52 | Try it » |
%W | Week number of year, Monday as the first day of week, 00-53 | 52 | Try it » |
%c | Local version of date and time | Mon Dec 31 17:41:00 2018 | Try it » |
%C | Century | 20 | Try it » |
%x | Local version of date | 12/31/18 | Try it » |
%X | Local version of time | 17:41:00 | Try it » |
%% | A % character | % | Try it » |
%G | ISO 8601 year | 2018 | Try it » |
%u | ISO 8601 weekday (1-7) | 1 | Try it » |
%V | ISO 8601 weeknumber (01-53) | 01 | Try it » |
Python has a set of built-in math functions, including an extensive math module, that allows you to perform mathematical tasks on numbers.
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 function returns the value of x to the power of y (xy).pow(x, y)
Return the value of 4 to the power of 3 (same as 4 * 4 * 4):
x = pow(4, 3)
print(x)
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:
import math
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:
import math
x = math.ceil(1.4)
y = math.floor(1.4)
print(x) # returns 2
print(y) # returns 1
The math.pi
constant, returns the value of PI (3.14…):
In our Math Module Reference you will find a complete reference of all methods and constants that belongs to the Math module.
JSON is a syntax for storing and exchanging data.
JSON is text, written with JavaScript object notation.
Python has a built-in package called json
, which can be used to work with JSON data.
Import the json module:
import json
If you have a JSON string, you can parse it by using the json.loads()
method.
The result will be a Python dictionary.
Convert from JSON to Python:
import json
# some JSON:
x = '{ "name":"John", "age":30, "city":"New York"}'
# parse x:
y = json.loads(x)
# the result is a Python dictionary:
print(y["age"])
If you have a Python object, you can convert it into a JSON string by using the json.dumps()
method.
Convert from Python to JSON:
import json
# a Python object (dict):
x = {
"name": "John",
"age": 30,
"city": "New York"
}
# convert into JSON:
y = json.dumps(x)
# the result is a JSON string:
print(y)
Convert Python objects into JSON strings, and print the values:
import json
print(json.dumps({"name": "John", "age": 30}))
print(json.dumps(["apple", "bananas"]))
print(json.dumps(("apple", "bananas")))
print(json.dumps("hello"))
print(json.dumps(42))
print(json.dumps(31.76))
print(json.dumps(True))
print(json.dumps(False))
print(json.dumps(None))
When you convert from Python to JSON, Python objects are converted into the JSON (JavaScript) equivalent:
Python | JSON |
---|---|
dict | Object |
list | Array |
tuple | Array |
str | String |
int | Number |
float | Number |
True | true |
False | false |
None | null |
Convert a Python object containing all the legal data types:
import json
x = {
"name": "John",
"age": 30,
"married": True,
"divorced": False,
"children": ("Ann","Billy"),
"pets": None,
"cars": [
{"model": "BMW 230", "mpg": 27.5},
{"model": "Ford Edge", "mpg": 24.1}
]
}
print(json.dumps(x))
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:
Use the indent
parameter to define the numbers of indents:
json.dumps(x, indent=4)
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:
Use the separators
parameter to change the default separator:
json.dumps(x, indent=4, separators=(". ", " = "))
The json.dumps()
method has parameters to order the keys in the result:
Use the sort_keys
parameter to specify if the result should be sorted or not:
json.dumps(x, indent=4, sort_keys=True)
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.
Python has a built-in package called re
, which can be used to work with Regular Expressions.
Import the re
module:
import re
When you have imported the re
module, you can start using regular expressions:
Search the string to see if it starts with “The” and ends with “Spain”:
import re
txt = "The rain in Spain"x = re.search("^The.*Spain$", txt)
The re
module offers a set of functions that allows us to search a string for a match:
Function | Description |
---|---|
findall | Returns a list containing all matches |
search | Returns a Match object if there is a match anywhere in the string |
split | Returns a list where the string has been split at each match |
sub | Replaces one or many matches with a string |
Metacharacters are characters with a special meaning:
Character | Description | Example | Try it |
---|---|---|---|
[] | A set of characters | “[a-m]” | Try it » |
\ | Signals a special sequence (can also be used to escape special characters) | “\d” | Try it » |
. | Any character (except newline character) | “he..o” | Try it » |
^ | Starts with | “^hello” | Try it » |
$ | Ends with | “planet$” | Try it » |
* | Zero or more occurrences | “he.*o” | Try it » |
+ | One or more occurrences | “he.+o” | Try it » |
? | Zero or one occurrences | “he.?o” | Try it » |
{} | Exactly the specified number of occurrences | “he.{2}o” | Try it » |
| | Either or | “falls|stays” | Try it » |
() | Capture and group |
A special sequence is a \
followed by one of the characters in the list below, and has a special meaning:
Character | Description | Example | Try it |
---|---|---|---|
\A | Returns a match if the specified characters are at the beginning of the string | “\AThe” | Try it » |
\b | Returns a match where the specified characters are at the beginning or at the end of a word (the “r” in the beginning is making sure that the string is being treated as a “raw string”) | r”\bain” r”ain\b” | Try it » Try it » |
\B | Returns a match where the specified characters are present, but NOT at the beginning (or at the end) of a word (the “r” in the beginning is making sure that the string is being treated as a “raw string”) | r”\Bain” r”ain\B” | Try it » Try it » |
\d | Returns a match where the string contains digits (numbers from 0-9) | “\d” | Try it » |
\D | Returns a match where the string DOES NOT contain digits | “\D” | Try it » |
\s | Returns a match where the string contains a white space character | “\s” | Try it » |
\S | Returns a match where the string DOES NOT contain a white space character | “\S” | Try it » |
\w | Returns a match where the string contains any word characters (characters from a to Z, digits from 0-9, and the underscore _ character) | “\w” | Try it » |
\W | Returns a match where the string DOES NOT contain any word characters | “\W” | Try it » |
\Z | Returns a match if the specified characters are at the end of the string | “Spain\Z” | Try it » |
A set is a set of characters inside a pair of square brackets []
with a special meaning:
Set | Description | Try it |
---|---|---|
[arn] | Returns a match where one of the specified characters (a , r , or n ) are present | Try it » |
[a-n] | Returns a match for any lower case character, alphabetically between a and n | Try it » |
[^arn] | Returns a match for any character EXCEPT a , r , and n | Try it » |
[0123] | Returns a match where any of the specified digits (0 , 1 , 2 , or 3 ) are present | Try it » |
[0-9] | Returns a match for any digit between 0 and 9 | Try it » |
[0-5][0-9] | Returns a match for any two-digit numbers from 00 and 59 | Try it » |
[a-zA-Z] | Returns a match for any character alphabetically between a and z , lower case OR upper case | Try it » |
[+] | In sets, + , * , . , | , () , $ ,{} has no special meaning, so [+] means: return a match for any + character in the string | Try it » |
The findall()
function returns a list containing all matches.
Print a list of all matches:
import re
txt = “The rain in Spain”
x = re.findall(“ai”, txt)
print(x)
The list contains the matches in the order they are found.
If no matches are found, an empty list is returned:
Return an empty list if no match was found:
import re
txt = “The rain in Spain”
x = re.findall(“Portugal”, txt)
print(x)
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:
Search for the first white-space character in the string:
import re
txt = “The rain in Spain”
x = re.search(“\s”, txt)
print(“The first white-space character is located in position:”, x.start())
If no matches are found, the value None
is returned:
Make a search that returns no match:
import re
txt = “The rain in Spain”
x = re.search(“Portugal”, txt)
print(x)
The split()
function returns a list where the string has been split at each match:
Split at each white-space character:
import re
txt = "The rain in Spain"
x = re.split("\s", txt)
print(x)
You can control the number of occurrences by specifying the maxsplit
parameter:
Split the string only at the first occurrence:
import re
txt = "The rain in Spain"
x = re.split("\s", txt, 1)
print(x)
The sub()
function replaces the matches with the text of your choice:
Replace every white-space character with the number 9:
import re
txt = "The rain in Spain"
x = re.sub("\s", "9", txt)
print(x)
You can control the number of replacements by specifying the count
parameter:
Replace the first 2 occurrences:
import re
txt = "The rain in Spain"
x = re.sub("\s", "9", txt, 2)
print(x)
A Match Object is an object containing information about the search and the result.
Note: If there is no match, the value None
will be returned, instead of the Match Object.
Do a search that will return a Match Object:
import re
txt = "The rain in Spain"
x = re.search("ai", txt)
print(x) #this will print an object
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
Print the position (start- and end-position) of the first match occurrence.
The regular expression looks for any words that starts with an upper case “S”:
import re
txt = "The rain in Spain"
x = re.search(r"\bS\w+", txt)
print(x.span())
Print the string passed into the function:
import re
txt = "The rain in Spain"
x = re.search(r"\bS\w+", txt)
print(x.string)
Print the part of the string where there was a match.
The regular expression looks for any words that starts with an upper case “S”:
import re
txt = "The rain in Spain"
x = re.search(r"\bS\w+", txt)
print(x.group())
Note: If there is no match, the value None
will be returned, instead of the Match Object.
PIP is a package manager for Python packages, or modules if you like.
Note: If you have Python version 3.4 or later, PIP is included by default.
A package contains all the files you need for a module.
Modules are Python code libraries you can include in your project.
Navigate your command line to the location of Python’s script directory, and type the following:
Check PIP version:
C:\Users\Your Name\AppData\Local\Programs\Python\Python36-32\Scripts>pip --version
If you do not have PIP installed, you can download and install it from this page: https://pypi.org/project/pip/
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:
Download a package named “camelcase”:
C:\Users\Your Name\AppData\Local\Programs\Python\Python36-32\Scripts>pip install camelcase
Now you have downloaded and installed your first package!
Once the package is installed, it is ready to use.
Import the “camelcase” package into your project.
Import and use "camelcase":
import camelcase
c = camelcase.CamelCase()
txt = "hello world"
print(c.hump(txt))
Find more packages at https://pypi.org/.
Use the uninstall
command to remove a package:
Uninstall the package named “camelcase”:
C:\Users\Your Name\AppData\Local\Programs\Python\Python36-32\Scripts>pip uninstall camelcase
The PIP Package Manager will ask you to confirm that you want to remove the camelcase package:
Uninstalling camelcase-02.1:
Would remove:
c:\users\Your Name\appdata\local\programs\python\python36-32\lib\site-packages\camecase-0.2-py3.6.egg-info
c:\users\Your Name\appdata\local\programs\python\python36-32\lib\site-packages\camecase\*
Proceed (y/n)?
Press y
and the package will be removed.
Use the list
command to list all the packages installed on your system:
List installed packages:
C:\Users\Your Name\AppData\Local\Programs\Python\Python36-32\Scripts>pip list
Result:
Package Version
-----------------------
camelcase 0.2
mysql-connector 2.1.6
pip 18.1
pymongo 3.6.1
setuptools 39.0.1
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.
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:
The try
block will generate an exception, because x
is not defined:
try:
print(x)
except:
print("An exception occurred")
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:
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:
Print one message if the try block raises a NameError
and another for other errors:
try:
print(x)
except NameError:
print("Variable x is not defined")
except:
print("Something else went wrong")
You can use the else
keyword to define a block of code to be executed if no errors were raised:
In this example, the try
block does not generate any error:
try:
print("Hello")
except:
print("Something went wrong")
else:
print("Nothing went wrong")
The finally
block, if specified, will be executed regardless if the try block raises an error or not.
try:
print(x)
except:
print("Something went wrong")
finally:
print("The 'try except' is finished")
This can be useful to close objects and clean up resources:
Try to open and write to a file that is not writable:
try:
f = open("demofile.txt")
try:
f.write("Lorum Ipsum")
except:
print("Something went wrong when writing to the file")
finally:
f.close()
except:
print("Something went wrong when opening the file")
The program can continue, without leaving the file object open.
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.
Raise an error and stop the program if x is lower than 0:
x = -1
if x < 0:
raise Exception("Sorry, no numbers below zero")
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.
Raise a TypeError if x is not an integer:
x = "hello"
if not type(x) is int:
raise TypeError("Only integers are allowed")
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 stops executing when it comes to the input()
function, and continues when the user has given some input.
To make sure a string will display as expected, we can format the result with the format()
method.
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:
Add a placeholder where you want to display the price:
price = 49
txt = "The price is {} dollars"
print(txt.format(price))
You can add parameters inside the curly brackets to specify how to convert the value:
Format the price to be displayed as a number with two decimals:
txt = "The price is {:.2f} dollars"
Check out all formatting types in our String format() Reference.
If you want to use more values, just add more values to the format() method:
print(txt.format(price, itemno, count))
And add more placeholders:
quantity = 3
itemno = 567
price = 49
myorder = "I want {} pieces of item number {} for {:.2f} dollars."
print(myorder.format(quantity, itemno, price))
You can use index numbers (a number inside the curly brackets {0}
) to be sure the values are placed in the correct placeholders:
quantity = 3
itemno = 567
price = 49
myorder = "I want {0} pieces of item number {1} for {2:.2f} dollars."
print(myorder.format(quantity, itemno, price))
Also, if you want to refer to the same value more than once, use the index number:
age = 36
name = "John"
txt = "His name is {1}. {1} is {0} years old."
print(txt.format(age, name))
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")
:
myorder = "I have a {carname}, it is a {model}."
print(myorder.format(carname = "Ford", model = "Mustang"))
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