Are you ready to start on an interesting journey into the world of programming? Whether you are a novice or an experienced developer seeking to expand your skill set, Python is a great choice. With its easy and fashionable syntax, Python has gained mammoth popularity in recent years, making it one of the most sought-after programming languages in the industry.
In this comprehensive manual, we are able to delve into the charming realm of Python programming. From the basics to extra-superior standards, this blog is your gateway to becoming gifted in Python. Let’s get started!
What is Python?
Python is a versatile, high-level, and interpreted programming language known for its clarity and simplicity. Created by Guido van Rossum in the late 1980s, Python was designed to be easy to apprehend and write, emphasizing code clarity and decreasing the cost of program renovation.
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Getting Started with Python
- Python requires that you specify the type of variable before it being assigned.
- Python supports both functional and object oriented programming.
- Python does not require a type for a variable declaration. It automatically assigns the data type at run time.
- Python requires you to explicitly set the correct data type and value before assigning a variable.
- A block is created using a colon following by a new line and indentation
- A block is created by a new line
- A block is created using a semi colon and a new line
- A block is created using a semi colon and indentation
- The remove keyword
- The def keyword
- The del keyword
- A variable cannot be deleted
- int()
- float()
- enumerate()
- str()
- True
- False
- It controls the flow of the loop and stops the current loop from executing any further.
- The break statement will suspend the code until continue is run.
- To terminate the code
- The break keywork is used to debug a for loop.
- True
- False
a = isinstance(str, "aa")
print(a)
- It will throw an error.
- “aa”
- False
- True
- input("")
- "" = input("My name is: " + name)
- input()
- name = input("What is your name? ")
Basic Programming with Python
- Which of the following is not a sequence data type in Python?
- Dictionary
- String
- Tuples
- List
- For a given list called new_list, which of the following options will work:
new_list = [1,2,3,4]
Select all that apply
- new_list[4] = 10
- new_list.extend(new_list)
- new_list.insert(0, 0)
- new_list.append(5)
- Which of the following is not a type of variable scope in Python?
- Local
- Global
- Enclosing
- Package
- Which of the following is a built-in data structure in Python?
- Queue
- Tree
- LinkedList
- Set
- For a given file called ‘names.txt’, which of the following is NOT a valid syntax for opening a file:
- with open(‘names.txt’, ‘r’) as file:
print(type(file))
- with open(‘names.txt’, ‘w’) as file:
print(type(file))
- with open(‘names.txt’, ‘rb’) as file:
print(type(file))
- with open(‘names.txt’, ‘rw’) as file:
print(type(file))
- Which among the following is not a valid Exception in Python?
- ZeroDivisionException
- FileNotFoundError
- IndexError
- LoopError
- For a file called name.txt containing the lines below:
| 1. And another! 2. Second line 3. First line |
What will be the output of the following code:
| 1. with open(‘names.txt’, ‘r’) as file: 2. lines = file.readlines() 3. print(lines) |
- ‘First line’
- [‘First line\n’,
‘Second line\n’,
‘And another !’]
- [‘First line’]
- ‘First line’
‘Second line’
‘And another !’
8. State TRUE or FALSE:
*args passed to the functions can accept the key-value pair.
- True
- False
Programming Paradigms
- (''' ''') - Triple quotation marks
- ({ }) - Curly Brackets
- · ( # ) - Hashtag *
- ( @ ) - At the rate sign
- value = 7
- class A:
- value = 5
- a = A()
- a.value = 3
- print (value)
- None of the above
- 5
- 7
- 3
- bravo = 3
- b = B()
- class B:
- bravo = 5
- print("Inside class B")
- c = B()
- print(b.bravo)
- 3
- None
- 5
- Error
- break
- pass
- continue
- skip
- Logarithmic Time
- Exponential Time
- Constant time
- Execution time
- Variables and methods
- Objects and Classes
- Procedures and functions
- All of the options.
- Recursion is memory-efficient
- Recursive code can make your code look neater
- Easier to follow
- Easy to debug
Modules, packages, libraries, and tools
- It ensures that the entire code is covered for testing.
- Test-driven development can only have one cycle of testing and error correction.
- In TDD, the requirements and standards are highlighted from the beginning.
- The process can also be called Red-Green refactor cycle.
- PyTest
- Robot Framework
- Selenium
- Pyunit or Unittest
- assert
- lambda
- async
- yield
- Velocity
- Variability
- Volume
- Variety
- from math import pi
- print(math.pi)
- ImportError: No module named math
- NameError: name ‘math’ is not defined
- 3.141592653589793
- There will be no output
- Seaborn
- Matplotlib
- Scrapy
- OpenCV
- Python Standard Library
- Built-in Module
- pip
- Python Package Index (pypi)
- Functions Variables Packages Modules
End-of-Course Graded Assessment: Using Python
- The source code is converted into bytecode that is then executed by the Python virtual machine.
- Python needs to be built prior to it being run.
- The source code is pre-built and compiled before running.
- Python will save all code first prior to running.
- The code will compile faster with indentation.
- Python used indentation to determine which code block starts and ends.
- It makes the code more readable.
- The code will be read in a sequential manner
- names = ["Anna", "Natasha", "Mike"]
- names.insert(2, "Xi")
- print(names)
- [“Anna”, “Natasha”, 2, “Xi”, “Mike”]
- [“Anna”, “Natasha”, Xi]
- [“Anna”, “Xi”, ”Mike” ]
- [“Anna”, “Natasha”, “Xi”, “Mike”]
- print(int((str((float(x))))))
- “one”, “two”
- 1.0, 2.0
- Will give an error
- 1 , 2
- sample_dict = {1: 'Coffee', 2: 'Tea', 3: 'Juice'}
- for x in sample_dict:
- print(x)
- (1, 'Coffee')
- 1 2 3
- {1 2 3}
- ‘Coffee’, ‘Tea’, ‘Juice’
- def recursion(num):
- print(num)
- next = num - 3
- if next > 1:
- recursion(next)
- recursion(11)
- 2 5 8 11
- 2 5 8
- 11 8 5 2
- 8 5 2
- def bigo(numbers):
- for i in numbers:
- print (numbers)
- bigo([1, 7, 13, 19])
- Logarithmic Time
- Quadratic Time
- Constant Time
- Linear Time
- str = 'Pomodoro'
- for l in str:
- if l == 'o':
- str = str.split()
- print(str, end=", ")
- [‘Pomodoro’, ‘modoro’, ‘doro‘, ‘ro’]
- ['Pomodoro']
- Will throw an error
- [‘P’, ‘m’, ‘d’, ‘o’]
- def d():
- color = "green"
- def e():
- Non-local color
- color = "yellow"
- e()
- print("Color: " + color)
- color = "red"
- color = "blue"
- d()
- num = 9
- class Car:
- num = 5
- bathrooms = 2
- def cost_evaluation(num):
- num = 10
- return num
- class Bike():
- num = 11
- cost_evaluation(num)
- car = Car()
- bike = Bike()
- car.num = 7
- Car.num = 2
- print(num)
- 10
- 9
- 2
- 5
- print(issubclass(p,C))
- print(issubclass(P,C))
- print(issubclass(C,c))
- print(issubclass(C,P))
- Micro-framework
- Asynchronous framework
- Full-stack framework
- It is where the application is tested as a whole.
- Tests the flow of data from one component to another.
- It combines unit tests.
- Primarily dealt by the tester.
- class A:
- def a(self):
- return "Function inside A"
- class B:
- def a(self):
- return "Function inside B"
- class C:
- pass
- class D(C, A, B):
- pass
- d = D()
- print(d.a())
- Function inside B
- No output
- Function inside A
- None of the above
Why Python?
1. Beginner-Friendly
Python’s straightforward and clean syntax is best for novices. It reads almost like English, making it easy to comprehend for those new to programming.
2. Versatile
Python is a multi-reason language, appropriate for net development, facts analysis, medical computing, synthetic intelligence, and greater.
3. Rich Library Ecosystem
Python boasts a sizable series of libraries and frameworks, consisting of NumPy, Django, and TensorFlow, that simplify complicated obligations.
4. Cross-Platform Compatibility
Python runs on diverse platforms, such as Windows, macOS, and Linux, making it a general preference.
5. Thriving Community
A strong network of Python builders and enthusiasts ensures consistent aid and a wealth of assets.
Getting Started
Setting Up Python
Before diving into Python, you need to install your development environment. Follow the steps:
Install Python: Visit the official Python website (python.org) and download the modern-day version of Python.
Install an Integrated Development Environment (IDE): Choose an IDE that fits your choices. Popular selections include PyCharm, Visual Studio Code, and Jupyter Notebook.
Write Your First Python Program: Launch your IDE, open a new mission, and write a simple “Hello, World!” program to ensure the entire program is installed effectively.
Variables and Data Types
In Python, you can paint with various information kinds, inclusive of integers, floats, strings, and extras. Here’s a quick overview:
Integers: Whole numbers (e.g., 5, -3, a thousand)
Floats: Numbers with decimal factors (e.g., three.14, -0.5, 2.0)
Strings: Textual data (e.g., “Hello, Python!”, ‘123’, “three.14“)
Lists: Ordered collections of objects
Dictionaries: Key-fee pairs for green data retrieval
Boolean: Represents True or False values
Control Structures
Python affords important control systems for decision-making and repetition.
If Statements: Conditional execution primarily based on a real or fake circumstance.
Loops: The for and while loops can help you carry out repetitive duties.
Functions: Reusable blocks of code to streamline your program.
Libraries and Modules
Python’s energy lies in its giant libraries and modules. Here are a few interesting ones:
NumPy is ideal for numerical computations.
Pandas: Perfect for records manipulation and analysis.
Matplotlib: An effective library for facts visualization.
Django: A high-stage internet framework for building web programs.
TensorFlow and PyTorch: Leading libraries for gadget learning and deep mastering.
Intermediate Python
Object-Oriented Programming (OOP)
Python supports item-oriented programming, where you can create training and items to version actual-world entities. OOP allows for organizing and structuring code efficiently.
File Handling
Learn how to read and write files in Python. This ability is essential for information manipulation, configuration control, and more.
Error Handling
Discover how to cope with exceptions gracefully. Python besides blocks lets you address surprising mistakes without crashing your application.
Advanced Python
Decorators
Decorators are a powerful function in Python that allows you to alter features or methods. They are generally used in web frameworks like Flask and Django.
Concurrency
Python supports concurrent programming with threads and processes. Learn a way to write efficient, multi-threaded applications.
Python for Web Development
Explore internet development with Python through the use of frameworks like Flask and Django. Create dynamic net programs and study REST APIs.
Data Science and Machine Learning
Delve into facts technology and machine learning using Python. Utilize libraries like scikit-analyze and TensorFlow to build predictive models and perform records analysis.
Conclusion
In this text, we’ve launched into a thrilling journey through the world of Python programming. We’ve explored its simplicity, versatility, and the giant environment of libraries and frameworks that make it a top choice for developers.
HOW TO START PROGRAMMING IN PYTHON
Whether you’re a beginner trying to begin your coding adventure or a skilled developer searching to add Python to your skill set, this guide has furnished you with the essential understanding to get started. Python’s clarity and fashionable syntax make it a remarkable choice for everyone interested in programming.
So, what are you waiting for? Dive into the Python sector and begin writing your code today. The opportunities are limitless, and you’re now equipped with the understanding to make the most of them. Happy coding!
