Functions in Python

by Admin | Feb 10, 2023 | Python

Functions in Python

A function in Python is a block of code that performs a specific task and returns a result. Functions help break down a program into smaller, more manageable pieces and make the code easier to read, test, and maintain. Functions define using the def keyword, followed by the name of the function, a set of parentheses, and a colon. The code within the function indent under the definition and execute when the function can call.

def func_name (optional_arguments)

statement

…

return optional_value

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Data Structure in Python

by netvital | Jan 18, 2023 | Python

Data Structure in Python

Data structure in python makes it possible to store and organize data in a very efficient way. Using it, we can link the data together and perform the desired operations on them.
In programming, this process is especially important because it enables us to access and recall data more easily.

There is four general Data Structures in Python:

• List: ordered, changeable, duplicate members.
• Dictionary: ordered, changeable, No duplicate members.
• Set: unordered, unchangeable, unindexed, No duplicate members.
• Tuples: ordered, unchangeable, duplicate members.

LIST: 

>>>a = []

for example:

>>>a = [2, 5, 10]             >>>b = [1.2, 5.9, “Hi”, 8]

To recall form List: >>>a [0]      result:  2              >>>a [1]      result:  5

To change in List : >>>a [0]=3           >>>a          result  a[3, 5, 10]

Methods :

• append(): Add element end of list
• remove(): Remove first element
• clear(): Remove all list
• copy(): Copy of list
• count(): Number of elements with value
• extend(): Add to end of list
• index(): Index of first element with value
• insert(): Add element to the list
• pop(): Remove element from list
• reverse(): Reverse list
• sort(): Sort list

for i in a:

print(i)

Result: 3   5   10

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DICTIONARY: 

Different between Dictionary with other Data Structure is, we can make Data with TAG, now you ask what is mean? let’s to see some examples:

>>>a = {}             >>>a = {“Quantiy”: 5, “Price”: 20}

>>>b = {}             >>>b = {0: 5, 1:20}

In the second example, we use Tag 0 for “Quantity” and Tag 1 for “Price”, that’s same as first one.

>>>c = {}          >>>c = {“name”: “XXX”, “family”: “YYY”}

for z,x in c.items():

print(z, ” : “, x)

Result

name : XXX
family : YYY

Methods:

• clear(): Removes all
• copy(): get copy
• fromkeys(): get the specified keys and value
• get(): get value of the specified key
• items(): get a list for each key value pair
• keys(): get a list with keys
• pop(): Removes by specified key
• popitem(): Removes the last element
• setdefault(): get the value of the specified key
• update(): Updates with the specified key-value pairs
• values(): get a list of all the values

in this structure, we can make for each element, one Tag, so that’s too easy to save and recall data of this method.

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SET: 

SET structure is same as DICTIONARY but in SET we dont have TAG. let’s to see some examples:

>>> a = {}         a = {1, 2, 3}

in this structure if we have same number, it will remove by compiler, that’s mean, we dont have repeat in this structure.

>>> a = {1, 4, 2, 5, 1, 6, 2} ==> compiler remove 1, 2 because we have same.

for i in a:

print(i)

>>1, 2, 3, 5, 6

Methods :

• add(): Adds element
• clear(): Removes all
• copy(): get a copy
• difference(): get difference between two or more sets
• difference_update(): Removes the items included in another
• discard(): Remove the item
• intersection(): get the intersection of two more sets
• intersection_update(): Removes the items that do not present in other
• isdisjoint(): get a intersection or not
• issubset(): get contains or not
• issuperset(); get contains another set or not
• pop(): Removes element
• remove(): Removes the specified element
• symmetric_difference(): Get symmetric differences of two sets
• symmetric_difference_update(): inserts the symmetric differences
• union(): get containing the union of sets
• update(): Update

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TUPLE: 

TUPLE is unchangeable, and when we assign value, we cannot change it after.

in TUPLE, we have access to the element by command for example a = [0], in this command it return value of first element of these data

>>>a = ()                 >>>a = (1, 2, 3, 4)     or           >>> a = 1, 2, 3, 4

as you see TUPLE is same as int, if we want to make TUPLE with one element, we must use comma after it, let’s see

>>> a = (1,)     or     >>>a = 1,

Methods :

• count(): Get the number of times with specified value
• index(): Get the position of where it was found

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Python Standard Library

by netvital | Jan 1, 2023 | Python

Python Standard Library

With Python Standard Library, we call module code that is ready to use. We cannot use these modules without recall and if we need, we must call them.

The Python standard library is very extensive and offers many features. In this library, we see internal modules that are often written in C language. For example, we can access the file input/output system through these modules, without these modules, Python programming will be inaccessible.

These modules provide increased programming capabilities. In the installed version of Python in Windows or Mac, usually the entire standard library also install and accessible and there is no need to add them, but in Unix, they are a set of packages that we can install separately.

Modules are the main unit of code in Python and there are two types of modules in Python:

• Pure module: This module is written in Python and is in a .py file
• Extension module: This module is written in these languages: C/C++ for Python, Java for Python.

we have many Modules in Python, for example Modules:

• OS: operating system dependent functionality
• Random: random number generators
• Datetime: manipulating dates and times
• Sys: information about system
• Collection: data structure and datatypes providing

How we can recall a library in Python:

for recalling, we have two options:

1. Recall all module: In this way, we recall all module and when we want to use commande we write module. Submodule (X)
2. Recall a specific sub module: In this way, in command we write just submodule (X), and it doesn’t need to write module name before submodule

here a command for recalling:

1. import module
2. from module import submodule

let’s to see some examples by module random:

1. import random
   random.randrange(10)
2. from random import randrange
   randrange(10)

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