To read from a file, you can use the open() function in Python, which opens a file and returns a file object. The read() method is used to read the contents of the file.
Syntax for Reading:
python
# Reading from a file file = open(‘file.txt’, ‘r’) # Opens the file in read mode (‘r’) content = file.read() # Reads the entire file content print(content) file.close() # Close the file after reading
Writing to Files (open() and write()):
To write to a file, open it with the appropriate mode (‘w’ for write, ‘a’ for append). The write() method is used to write content to the file.
Syntax for Writing:
python
# Writing to a file file = open(‘file.txt’, ‘w’) # Opens the file in write mode (‘w’) file.write(‘Hello, World!\n’) # Writes content to the file file.close() # Close the file after writing
B. File Modes and Operations:
File Modes:
Read Mode (‘r’): Opens a file for reading. Raises an error if the file does not exist.
Write Mode (‘w’): Opens a file for writing. Creates a new file if it doesn’t exist or truncates the file if it exists.
Append Mode (‘a’): Opens a file for appending new content. Creates a new file if it doesn’t exist.
Read and Write Mode (‘r+’): Opens a file for both reading and writing.
Binary Mode (‘b’): Used in conjunction with other modes (e.g., ‘rb’, ‘wb’) to handle binary files.
File Operations:
read(): Reads the entire content of the file or a specified number of bytes.
readline(): Reads a single line from the file.
readlines(): Reads all the lines of a file and returns a list.
write(): Writes content to the file.
close(): Closes the file when finished with file operations.
Using with Statement (Context Manager):
The with statement in Python is used to automatically close the file when the block of code is exited. It’s a good practice to use it to ensure proper file handling.
Syntax:
python
with open(‘file.txt’, ‘r’) as file: content = file.read() print(content) # File is automatically closed outside the ‘with’ block
VII. Object-Oriented Programming (OOP) Basics
A. Classes and Objects:
Classes:
Classes are blueprints for creating objects in Python. They encapsulate data (attributes) and behaviors (methods) into a single unit.
Syntax for Class Declaration:
python
# Class declaration class MyClass: # Class constructor (initializer) def __init__(self, attribute1, attribute2): self.attribute1 = attribute1 self.attribute2 = attribute2 # Class method def my_method(self): return “This is a method in MyClass”
Objects:
Objects are instances of classes. They represent real-world entities and have attributes and behaviors defined by the class.
Creating Objects from a Class:
python
# Creating an object of MyClass obj = MyClass(“value1”, “value2”)
B. Inheritance and Polymorphism:
Inheritance:
Inheritance allows a class (subclass/child class) to inherit attributes and methods from another class (superclass/parent class).
Syntax for Inheritance:
python
# Parent class class Animal: def sound(self): return “Some sound” # Child class inheriting from Animal class Dog(Animal): def sound(self): # Overriding the method return “Woof!”
Polymorphism:
Polymorphism allows objects of different classes to be treated as objects of a common superclass. It enables the same method name to behave differently for each class.
Example of Polymorphism:
python
# Polymorphism example def animal_sound(animal): return animal.sound() # Same method name, different behaviors # Creating instances of classes animal1 = Animal() dog = Dog() # Calling the function with different objects print(animal_sound(animal1)) # Output: “Some sound” print(animal_sound(dog)) # Output: “Woof!”
Exceptions are errors that occur during the execution of a program, disrupting the normal flow of the code.
Examples include dividing by zero, trying to access an undefined variable, or attempting to open a non-existent file.
Types of Exceptions:
Python has built-in exception types that represent different errors that can occur during program execution, like ZeroDivisionError, NameError, FileNotFoundError, etc.
B. Using Try-Except Blocks:
Handling Exceptions with Try-Except Blocks:
Try-except blocks in Python provide a way to handle exceptions gracefully, preventing the program from crashing when errors occur.
Syntax:
python
try: # Code that might raise an exception result = 10 / 0 # Example: Division by zero except ExceptionType as e: # Code to handle the exception print(“An exception occurred:”, e)
Handling Specific Exceptions:
You can catch specific exceptions by specifying the exception type after the except keyword.
Example:
python
try: file = open(‘nonexistent_file.txt’, ‘r’) except FileNotFoundError as e: print(“File not found:”, e)
Using Multiple Except Blocks:
You can use multiple except blocks to handle different types of exceptions separately.
Example:
python
try: result = 10 / 0 except ZeroDivisionError as e: print(“Division by zero error:”, e) except Exception as e: print(“An exception occurred:”, e)
Handling Exceptions with Else and Finally:
The else block runs if no exceptions are raised in the try block, while the finally block always runs, whether an exception is raised or not.
Example:
python
try: result = 10 / 2 except ZeroDivisionError as e: print(“Division by zero error:”, e) else: print(“No exceptions occurred!”) finally: print(“Finally block always executes”)
IX. Introduction to Python Libraries
A. Overview of Popular Libraries:
NumPy:
Description: NumPy is a fundamental package for scientific computing in Python. It provides support for arrays, matrices, and mathematical functions to operate on these data structures efficiently.
Key Features:
Multi-dimensional arrays and matrices.
Mathematical functions for array manipulation.
Linear algebra, Fourier transforms, and random number capabilities.
Example:
python
import numpy as np # Creating a NumPy array arr = np.array([1, 2, 3, 4, 5])
Pandas:
Description: Pandas is a powerful library for data manipulation and analysis. It provides data structures like Series and DataFrame, making it easy to handle structured data.
Key Features:
Data manipulation tools for reading, writing, and analyzing data.
Data alignment, indexing, and handling missing data.
Time-series functionality.
Example:
python
import pandas as pd # Creating a DataFrame data = {‘Name’: [‘Alice’, ‘Bob’, ‘Charlie’], ‘Age’: [25, 30, 35]} df = pd.DataFrame(data)
Matplotlib:
Description: Matplotlib is a comprehensive library for creating static, interactive, and animated visualizations in Python. It provides functionalities to visualize data in various formats.
Key Features:
Plotting 2D and 3D graphs, histograms, scatter plots, etc.
Customizable visualizations.
Integration with Jupyter Notebook for interactive plotting.
Example:
python
import matplotlib.pyplot as plt # Plotting a simple line graph x = [1, 2, 3, 4, 5] y = [2, 4, 6, 8, 10] plt.plot(x, y) plt.xlabel(‘X-axis’) plt.ylabel(‘Y-axis’) plt.title(‘Simple Line Graph’) plt.show()
B. Installing and Importing Libraries:
Installing Libraries using pip:
Open a terminal or command prompt and use the following command to install libraries:
pip install numpy pandas matplotlib
Importing Libraries in Python:
Once installed, import the libraries in your Python script using import statements:
Python import numpy as np import pandas as pd import matplotlib.pyplot as plt
After importing, you can use the functionalities provided by these libraries in your Python code.
X. Real-life Examples and Projects
A. Simple Projects for Practice:
To-Do List Application:
Create a command-line to-do list application that allows users to add tasks, mark them as completed, delete tasks, and display the list.
Temperature Converter:
Build a program that converts temperatures between Celsius and Fahrenheit or other temperature scales.
Web Scraper:
Develop a web scraper that extracts information from a website and stores it in a structured format like a CSV file.
Simple Calculator:
Create a basic calculator that performs arithmetic operations such as addition, subtraction, multiplication, and division.
Hangman Game:
Implement a command-line version of the Hangman game where players guess letters to reveal a hidden word.
Address Book:
Develop an address book application that stores contacts with details like name, phone number, and email address.
File Organizer:
Write a script that organizes files in a directory based on their file extensions or other criteria.
B. Exploring Python’s Applications in Different Fields:
Web Development (Django, Flask):
Python is widely used for web development. Explore frameworks like Django or Flask to build web applications, REST APIs, or dynamic websites.
Data Science and Machine Learning:
Use libraries like NumPy, Pandas, Scikit-learn, or TensorFlow to perform data analysis, create machine learning models, or work on predictive analytics projects.
Scientific Computing:
Python is used extensively in scientific computing for simulations, modeling, and solving complex mathematical problems. Use libraries like SciPy or SymPy for scientific computations.
Natural Language Processing (NLP):
Explore NLP with Python using libraries like NLTK or spaCy for text processing, sentiment analysis, or language translation tasks.
Game Development:
Develop simple games using Python libraries like Pygame, allowing you to create 2D games and learn game development concepts.
Automation and Scripting:
Create scripts to automate repetitive tasks like file manipulation, data processing, or system administration using Python’s scripting capabilities.
IoT (Internet of Things) and Raspberry Pi Projects:
Experiment with Python for IoT projects by controlling sensors, actuators, or devices using Raspberry Pi and Python libraries like GPIO Zero.
XI. Conclusion
A. Recap of Key Points:
Python Basics: Python is a high-level, versatile programming language known for its simplicity, readability, and vast ecosystem of libraries and frameworks.
Core Concepts: Understanding Python’s syntax, data types, control structures, functions, and handling exceptions is crucial for effective programming.
Popular Libraries: Libraries like NumPy, Pandas, Matplotlib, etc., offer specialized functionalities for data manipulation, scientific computing, visualization, and more.
Project Ideas: Simple projects, such as to-do lists, calculators, web scrapers, etc., provide practical experience and reinforce learning.
Real-world Applications: Python’s applications span diverse fields like web development, data science, machine learning, scientific computing, automation, IoT, and more.
B. Encouragement for Further Exploration:
Continuous Learning: Python’s versatility and vast ecosystem offer endless opportunities for learning and growth.
Practice and Projects: Build upon your knowledge by working on more complex projects, contributing to open-source, and experimenting with different libraries and domains.
Community Engagement: Engage with the Python community through forums, meetups, conferences, and online platforms to learn, share experiences, and collaborate.
Stay Curious: Python evolves continuously, and exploring new libraries, updates, or trends keeps your skills up-to-date and opens doors to new possibilities.
Persistence: Embrace challenges as learning opportunities. Persistence and dedication in learning Python will yield rewarding results in the long run.
C. Final Thoughts:
Python is an exceptional programming language renowned for its simplicity, readability, and versatility. Its applications span across numerous fields, from web development to scientific computing, data analysis, machine learning, and beyond. Whether you’re a beginner starting your programming journey or an experienced developer seeking new avenues, Python offers a rich ecosystem and a supportive community to aid your exploration and growth.
Python is an interpreted language
”’ print(5*4,end=” and “); # will evaluate print(‘5*4’) #will print as it is print(“5*6”); print(“5*6=”,‘\n‘+str(5*6)) # functions have arguments- they are separated by
, print(“20”+“30”,20+30,20,30) print(“5*6=”+str(5*6))
# This isn’t right! print(“This isn’t right!”) # He asked,”What’s your name”? print(”’He asked,”What’s your name”?”’) print(“””He asked,”What’s your
name”?”””) print(‘This isn\’t right!’) print(“He asked,\”What\’s your name\”?”)
# \ – is called as ESCAPE SEQUENCE
# \ will add or remove power from you print(“\\n is used for newline in Python”) print(“\\\\n will result in \\n”) print( r”\\n will result in \n”
) # regular expression print(“HELLO”);print(“HI”)
## datatypes
#numeric: integer (int), float (float), complex (complex)
#text: string (str) – ‘ ” ”’
“””
#boolean: boolean(bool) – True and False x = 1275 # let x = 5 y = 6 print(x+y) print(type(x))
# basic data types: var1 = 5 print(type(var1)) #<class ‘int’> var1 = 5.0 print(type(var1)) #<class ‘float’> var1 = “5.0” print(type(var1)) #<class ‘str’> var1 = “””5.0″”” print(type(var1)) #<class ‘str’> var1 = True print(type(var1)) #<class ‘bool’> var1 = 5j print(type(var1)) #<class ‘complex’> length = 100 breadth = 15 area = length * breadth peri = 2*(length + breadth) print(“Area of a rectangle with length”,length,“and breadth”,breadth,“is”,area,“and perimeter is”,peri) # f-string print(f”Area of a rectangle with length {length} and breadth {breadth} is {area} and perimeter is {peri}“) print(f”Area of a rectangle with length {length} and breadth {breadth} is {area} and perimeter is {peri}“)
# float value tot_items= 77 tot_price = 367 price_item =tot_price/tot_items print(f”Cost of each item when total price paid is {tot_price} for {tot_items} items is {price_item:.1f} currency”)
”’ Assignment submission process: 1. Create Google drive folder: share with the instructor 2. within this folder – add your .py files ”’ ”’ Assignment 1: 1. Write a program to calculate area and circumference of a circle and display info in a formatted manner 2. WAP to calculate area and perimeter of a square 3. WAP to calculate simple interest to be paid when principle amount, rate of interest and time is given 4. WAP to take degree celcius as input and give Fahrenheit output ”’ name, country,position=“Virat”,“India”,“Opening” print(f”Player {name:<10} plays for {country:>12} as a/an {position:^15} in the cricket.”) name, country,position=“Mangwaba”,“Zimbabwe”,“Wicket-keeper” print(f”Player {name:<10} plays for {country:>12} as a/an {position:^15} in the cricket.”)
# Comparison operators – compare the values # asking, is … # your output is always a bool value – True or False val1,val2,val3 = 20,20,10 print(val1 > val2) #val1 greater than val2 ? print(val1 >= val2) print(val1 > val3) #val1 greater than val3 ? print(val1 >= val3) # True print(“Second set:”) print(val1 < val2) #F print(val1 <= val2) #T print(val1 < val3) #F print(val1 <= val3) #F print(“third set:”) print(val1 == val2) # T print(val2==val3) # F print(val1 != val2) # F print(val2!=val3) # T ”’ a = 5 # assign value 5 to the variable a a ==5 # is the value of a 5? a!=5 # is value of a not equal to 5 ? ”’ ## Logical operators: and or not ”’ Committment: I am going to cover Python and SQL in this course Actual 1: I covered Python and SQL Actual 2: I covered SQL Actual 3: I covered Python Committment 2: I am going to cover Python or SQL in this course Actual 1: I covered Python and SQL Actual 2: I covered SQL Actual 3: I covered Python ”’ #logical operators takes bool values as input and also output is another bool print(True and True ) # T print(False and True ) #F print(True and False ) #F print(False and False ) #F print(“OR:”) print(True or True ) # T print(False or True ) #T print(True or False ) #T print(False or False ) #F print(“NOT”) print(not True) print(not False) val1,val2,val3 = 20,20,10 print(val1 > val2 and val1 >= val2 or val1 > val3 and val1 >= val3 or val1 < val2 and val2!=val3) # F and T or T and T or F and T # F or T or F # T # Self Practice: output is True – solve it manually print(val1 <= val2 or val1 < val3 and val1 <= val3 and val1 == val2 or val2==val3 or val1 != val2)
# Bitwise operator : & | >> << print(bin(50)) #bin() convert into binary numbers # 50 = 0b 110010 print(int(0b110010)) #int() will convert into decimal number print(oct(50)) # Octal number system: 0o62 print(hex(50)) #hexadecimal: 0x32 # Assignments (3 programs) – refer below
total_marks = 150 if total_marks>=200: print(“Congratulations! You have passed the exam”) print(“You have 7 days to reserve your admission”) else: print(“Sorry, You have not cleared the exam”) print(“Try again after 3 months”)
print(“Thank you”) # marks = 75 ”’ >=85: Grade A >=75: B >=60: C >=50: D <50: E ”’ if marks>=85: print(“Grade A”) elif marks>=75: print(“Grade B”) elif marks>=60: print(“Grade C”) elif marks>=50: print(“Grade D”) else: print(“Grade E”)
print(“Done”) ###. marks = 85 ”’ >=85: Grade A >=75: B >=60: C >=50: D <50: E ”’ if marks>=85: print(“Grade A”)
if marks>=75 and marks<85: print(“Grade B”) if marks>=60 and marks<75: print(“Grade C”) if marks>=50 and marks<60: print(“Grade D”) if marks<50: print(“Grade E”)
print(“Done”) ### NEST IF marks = 98.0001 ”’ >=85: Grade A >=75: B >=60: C >=50: D <50: E >90: award them with medal ”’ if marks>=85: print(“Grade A”) if marks >= 90: print(“You win the medal”) if marks>98: print(“Your photo will be on the wall of fame”) elif marks>=75: print(“Grade B”) elif marks>=60: print(“Grade C”) elif marks>=50: print(“Grade D”) else: print(“Grade E”)
”’ Practice basic programs from here: https://www.scribd.com/document/669472691/Flowchart-and-C-Programs ”’ # check if a number is odd or even num1 = int(input(“Enter the number: “)) if num1<0: print(“Its neither Odd or Even”) else: if num1%2==0: print(“Its Even”) else: print(“Its Odd”)
## check the greater of the given two numbers: num1, num2 = 20,20 if num1>num2: print(f”{num1} is greater than {num2}“) elif num2>num1: print(f”{num2} is greater than {num1}“) else: print(“They are equal”)
## check the greater of the given three numbers: num1, num2,num3 = 29,49,29 if num1>num2: # n1 > n2 if num1>num3: print(f”{num1} is greater”) else: print(f”{num3} is greater”) else: # n2 is greater or equal to if num2 > num3: print(f”{num2} is greater”) else: print(f”{num3} is greater”) ## #enter 3 sides of a triangle and check if they are: #equilateral, isoceles, scalene, right angled triangle side1,side2,side3 = 90,60,30 if side1==side2: if side1 == side3: print(“Equilateral”) else: print(“Isoceles”) else: if side1==side3: print(“Isoceles”) else: if side2==side3: print(“Isoceles”) else: print(“Scalene”)
#modify the above code to handle Right Angled triangle logic
# loops – # FOR : know how many times you need to repeat # WHILE : dont know how many times but you have the condition # range(start, stop,step): starts with start, goes upto stop (not including) # step: each time value is increasesd by step # range(10,34,6): 10, 16, 22, 28 # range(start, stop) : default step is 1 # range(10,17): 10,11,12,13,14,15,16 # range(stop): default start is zero, default step is 1 # range(5): 0,1,2,3,4 # generate values from 1 to 10 for counter in range(1,11): # 1,2,3…10 print(counter,end=“, “) print() print(“Thank You”)
# generate first 10 odd numbers for odd_num in range(1,11,2): # 1,2,3…10 print(odd_num,end=“, “) print() print(“———-“) for counter in range(10): print(2*counter+1,end=“, “) print() print(“———-“) # generate even numbers till 50 for even_num in range(0,50,2): # 1,2,3…10 print(even_num,end=“, “) print() ############## # WHILE: is always followed by a condition and only if the condition is true, u get in # WAP to print hello till user says so user = “y” while user==“y”: print(“Hello”) user = input(“Enter y to continue or anyother key to stop: “) ## print(“method 2”)
while True: user = input(“Enter y to continue or anyother key to stop: “) if user!=“y”: break print(“Hello”)
print(“Thank you”) count = int(input(“How many times you want to print: “)) while count >0: print(“Hello”) count-=1 #count = count-1
# For loops ”’ * * * * * * * * * * * * * * * * * * * * * * * * * ”’ n=5 for j in range(n): for i in range(n): print(“*”,end=” “) print()
”’ * * * * * * * * * * * * * * * ”’ n=5 num_stars=1 for j in range(n): for i in range(num_stars): print(“*”,end=” “) print() num_stars+=1 # n=5 for j in range(n): for i in range(j+1): print(“*”,end=” “) print()
”’ * * * * * * * * * * * * * * * ”’ for j in range(n): for i in range(n-j): print(“*”,end=” “) print()
”’ * * * * * * * * * * * * * * * ”’ for j in range(n): for k in range(j): print(“”, end=” “) for i in range(n-j): print(“*”,end=” “) print()
”’ Print prime numbers between 5000 and 10,000 10 – prime or not 2 10%2==0 => not a prime 3 4 ”’ for num in range(5000,10000): isPrime = True for i in range(2,num//2+1): if num%i==0: isPrime = False break if isPrime: print(num,end=“, “) ”’ num = 11 isPrime =T i in range(2,6) isPrime =F ”’
# WAP to create a menu option to perform arithmetic operations ”’ Before you use while loop, decide: 1. Should the loop run atleast once (Exit Controlled), or 2. Should we check the condition even before running the loop (Entry controlled) ”’ # method 1: Exit controlled while True: num1 = int(input(“Enter first number: “)) num2 = int(input(“Enter second number: “)) print(“Your Option: “) print(“1. Add”) print(“2. Subtract”) print(“3. Multiply”) print(“4. Divide”) print(“5. Exit”) ch = input(“Enter your choice: “) if ch==“1”: print(“Addition = “,num1 + num2) elif ch==“2”: print(“Difference = “, num1 – num2) elif ch==“3”: print(“Multiplication = “, num1 * num2) elif ch==“4”: print(“Division = “,num1 / num2) elif ch==“5”: break else: print(“Invalid Option”)
# # Generate odd numbers from 1 till user wants to continue num1 = 1 while True: print(num1) num1+=2 ch=input(“Enter y to generate next number or anyother key to stop: “) if ch!=‘y’: break # Generate fibonacci numbers from 1 till user wants to continue num1 = 0 num2 = 1 while True: num3 =num1 +num2 print(num3) num1,num2 = num2,num3 ch=input(“Enter y to generate next number or anyother key to stop: “) if ch!=‘y’: break # Generate fibonacci numbers from 1 till user wants to continue print(“Hit Enter key to continue or anyother key to stop! “) num1 = 0 num2 = 1 while True: num3 =num1 +num2 print(num3,end=“”) num1,num2 = num2,num3 ch=input() if ch!=”: break
import random print(random.random()) print(random.randint(100,1000))
from random import randint print(randint(100,1000))
# guess the number game – computer (has the number) v human (attempting) from random import randint
num = randint(1,100) attempt=0 while True: guess = int(input(“Guess the number (1-100): “)) if guess<1 or guess>100: print(“Invalid attempt!!!”) continue attempt+=1 #attempt=attempt+1 if guess ==num: print(f”Congratulations! You got it right in {attempt} attempts.”) break elif guess < num: print(“Sorry, that’s incorrect. Please try again with a higher number!”) else: print(“Sorry, that’s incorrect. Please try again with a lower number!”)
### ### # guess the number game – computer (has the number) v computer (attempting) from random import randint start,stop = 1,100 num = randint(1,100) attempt=0 while True: #guess = int(input(“Guess the number (1-100): “)) guess = randint(start,stop) if guess<1 or guess>100: print(“Invalid attempt!!!”) continue attempt+=1 #attempt=attempt+1 if guess ==num: print(f”Congratulations! You got it right in {attempt} attempts.”) break elif guess < num: print(f”Sorry, {guess} that’s incorrect. Please try again with a higher number!”) start=guess+1 else: print(f”Sorry, {guess} that’s incorrect. Please try again with a lower number!”) stop=guess-1 ## # guess the number game – computer (has the number) v computer (attempting) from random import randint total_attempts = 0 for i in range(10000): start,stop = 1,100 num = randint(1,100) attempt=0 while True: #guess = int(input(“Guess the number (1-100): “)) guess = randint(start,stop) if guess<1 or guess>100: print(“Invalid attempt!!!”) continue attempt+=1 #attempt=attempt+1 if guess ==num: print(f”Congratulations! You got it right in {attempt} attempts.”) total_attempts+=attempt break elif guess < num: print(f”Sorry, {guess} that’s incorrect. Please try again with a higher number!”) start=guess+1 else: print(f”Sorry, {guess} that’s incorrect. Please try again with a lower number!”) stop=guess-1 print(“========================================”) print(“Average number of attempts = “,total_attempts/10000) print(“========================================”)
”’ Multi line text of comments which can go into multiple lines ”’ # Strings str1 = ‘Hello’ str2 = “Hello there” print(type(str1), type(str2)) str3 = ”’How are you? Where are you from? Where do you want to go?”’ str4 = “””I am fine I live here I am going there””” print(type(str3), type(str4)) print(str3) print(str4) # one line of comment ”’ Multi line text of comments which can go into multiple lines ”’ # what’s your name? print(‘what\’s your name?’)
# counting in Python starts from zero str1 = ‘Hello there how are you?’ print(“Number of characters in str1 is”,len(str1)) print(“First character: “,str1[0], str1[-len(str1)]) print(“Second character: “,str1[1]) print(“Last character: “,str1[len(str1)-1]) print(“Last character: “,str1[-1]) print(“Second Last character: “,str1[-2]) print(“5th 6th 7th char: “,str1[4:7]) print(“First 4 char: “,str1[0:4],str1[:4]) print(“first 3 alternate char: “,str1[1:5:2]) print(“last 3 characters:”,str1[-3:]) print(“last 4 but one characters:”,str1[-4:-1]) print(str1[5:1:-1])
txt1 = “HiiH” txt2=txt1[-1::-1] #reversing the text print(txt2) txt2=str1[-1:-7:-1] #reversing the text print(txt2) if txt2 == txt1: print(“Its palindrome”) else: print(“Its not a palindrome”) var1 = 5 #print(var1[0]) # ‘int’ object is not subscriptable # add two strings print(“Hello”+“, “+“How are you?”) print(“Hello”,“How are you?”) print((“Hello”+” “)*5) print(“* “*5)
# for loop – using strings str1 = “hello” for i in str1: print(i)
for i in range(len(str1)): print(i, str1[i])
print(type(str1)) # <class ‘str’> str2 = “HOW Are You?” up_count, lo_count,sp_count = 0,0,0 for i in str2: if i.islower(): lo_count+=1 if i.isupper(): up_count+=1 if i.isspace(): sp_count+=1 print(f”Number of spaces={sp_count}, uppercase letters={up_count} and lower case letters={lo_count}“)
#input values: val1 = input(“Enter a number: “) if val1.isdigit(): val1 = int(val1) print(val1 * 5) else: print(“Invalid value”)
str3 = “123af ds” print(str3.isalnum())
# str1 =“How are You” # docs.python.org help(str.isascii)
help(help)
str1 = “HOw are YOU today?” print(str1.upper()) print(str1.lower()) print(str1.title()) #str1 = str1.title() # strings are immutable – you cant edit #str1[3] = “A” #TypeError: ‘str’ object does not support item assignment str1= str1[0:3]+“A”+str1[4:] print(str1) cnt = str1.lower().count(‘o’) print(cnt) cnt = str1.count(‘O’,3,15) # x,start,end print(cnt)
# Strings – method str1 = “Hello how are you doing today” var1 = str1.split() print(“Var 1 =”,var1) var2 = str1.split(‘o’) print(“Var 2 =”,var2) str2 = “1,|Sachin,|Mumbai,|Cricket” var3 = str2.split(‘,|’) print(var3) str11 = ” “.join(var1) print(“Str11 = “,str11) str11 = “”.join(var2) print(“Str11 = “,str11) str11= “–“.join(var3) print(“Str11 = “,str11) # Strings – method str1 = “Hello how are you doing today” str2 = str1.replace(‘o’,‘ooo’) print(str2) cnt = str1.count(‘z’) print(“Number of z in the str1 =”,cnt) find_cnt = str1.find(‘ow’) if find_cnt==-1: print(“Given substring is not in the main string”) else: print(“Substring in the str1 found at =”,find_cnt)
find_cnt = str1.find(‘o’,5,6) print(“Substring in the str1 found at =”,find_cnt)
str2 = str1.replace(‘z’,‘ooo’,3) print(str2)
################ ## LIST = Linear Ordered Mutable Collection l1 = [55, ‘Hello’,False,45.9,[2,4,6]] print(“type of l1 = “,type(l1)) print(“Number of members in the list=”,len(l1)) print(l1[0],l1[4],l1[-1]) print(“type of l1 =”,type(l1[0])) print(“type of l1 =”,type(l1[-1])) l2 = l1[-1] print(l2[0], l1[-1][0], type(l1[-1][0])) l1[0] = 95 print(“L1 =”,l1) ## LIST = Linear Ordered Mutable Collection l1 = [55, ‘Hello’,False,45.9,[2,4,6]]
for member in l1: print(member)
print(l1+l1) print(l1*2)
print(“count = “,l1.count(False)) print(“count = “,l1.count(‘Hello’)) # remove second last member – pop takes position l1.pop(-2) print(“L1 after Pop: “,l1) l1.pop(-2) print(“L1 after Pop: “,l1) # delete the element – remove takes value cnt = l1.count(‘Helloo’) if cnt>0: l1.remove(‘Helloo’) print(“L1 after Remove: “,l1) else: print(“‘Helloo’ not in the list”)
# Collections – Lists – linear mutable ordered collection l1 = [10,50,90,20,90] # add and remove members l1.append(25) #append will add at the end l1.append(45) print(“L1 after append: “,l1) #insert takes position and the value to add l1.insert(2,35) l1.insert(2,65) print(“L1 after insert: “,l1) l1.remove(35) #takes value to delete l1.remove(90) print(“L1 after remove: “,l1) cnt_90 = l1.count(90) print(“Number of 90s: “,cnt_90) l1.pop(2) #index at which you want to delete print(“L1 after pop: “,l1)
# Collections – Lists – linear mutable ordered collection l1 = [10,50,90,20,90] l2 = l1.copy() #shallow – photocopy l3 = l1 # deepcopy – same list with two names print(“1. L1 = “,l1) print(“1. L2 = “,l2) print(“1. L3 = “,l3) l1.append(11) l2.append(22) l3.append(33) print(“2. L1 = “,l1) print(“2. L2 = “,l2) print(“2. L3 = “,l3) print(“Index of 90:”,l1.index(90,3,7))
# Extend: l1 = l1+l2 l2=[1,2,3] l1.extend(l2) print(“L1 after extend:”,l1) l1.reverse() print(“L1 after reverse: “,l1) l1.sort() #sort in ascending order print(“L1 after sort: “,l1) l1.sort(reverse=True) #sort in descending order print(“L1 after reverse sort: “,l1) l1.clear() print(“L1 after clear: “,l1)
######## question from Vivek: ########### l1 = [9,5,7,2] target = 12 l2=l1.copy() l2.sort() #[2,5,7,19] for i in range(len(l2)-1): if l2[i]+l2[i+1] == target #l1.index(l2[i]), l1.index(l2[i+1]) break else: > target: stop <target: check with i+1 with i+2
#t1[1] = 14 TypeError: ‘tuple’ object does not support item assignment print(“Index of 2 =”,t1.index(2)) print(“Count of 2 =”,t1.count(2)) print(t1, type(t1)) t1=list(t1) t1[1] = 14 t1 = tuple(t1) print(t1, type(t1)) for i in t1: print(i)
# Dictionary ”’ WAP to input marks of three students in three subjects marks = {‘Sachin’: [78, 87, 69], ‘Kapil’: [59, 79, 49], ‘Virat’: [88, 68, 78]} ”’ students = [‘Sachin’,‘Kapil’,‘Virat’] subjects = [‘Maths’,‘Science’,‘English’] marks = {} #marks_list = [] num_students, num_subjects = 3,3 for i in range(num_students): marks_list = [] for j in range(num_subjects): m = int(input(“Enter the marks in subject ” + subjects[j]+” : “)) marks_list.append(m) temp = {students[i]:marks_list} marks.update(temp) #marks_list.clear() print(“Marks entered are: “,marks)
# Dictionary ”’ WAP to input marks of three students in three subjects. calculate total and average of marks for all the 3 students find who is the highest scorer in total and also for each subject marks = {‘Sachin’: [78, 87, 69], ‘Kapil’: [59, 79, 49], ‘Virat’: [88, 68, 78]} ”’ students = [‘Sachin’, ‘Kapil’, ‘Virat’] subjects = [‘Maths’, ‘Science’, ‘English’] marks = {‘Sachin’: [78, 87, 69], ‘Kapil’: [59, 79, 49], ‘Virat’: [88, 68, 78]} topper = {‘Total’: –1, ‘Name’: []} subject_highest = [-1, –1, –1]
num_students, num_subjects = 3, 3 for i in range(num_students): tot, avg = 0, 0 key = students[i] for j in range(num_subjects): tot = tot + marks[key][j] # checking the highest values for each subject # … avg = tot / 3 print(f”Total marks obtained by {students[i]} is {tot} and average is {avg:.1f}“) # check highest total if tot >= topper[‘Total’]: topper[‘Total’] = tot topper[‘Name’].append(key)
print(f”{topper[‘Name’]} has topped the class with total marks of {topper[‘Total’]}“)
# Dictionary ”’ WAP to input marks of three students in three subjects. calculate total and average of marks for all the 3 students find who is the highest scorer in total and also for each subject marks = {‘Sachin’: [78, 87, 69], ‘Kapil’: [59, 79, 49], ‘Virat’: [88, 68, 78]} ”’ students = [‘Sachin’,‘Kapil’,‘Virat’] subjects = [‘Maths’,‘Science’,‘English’] marks = {‘Sachin’: [78, 87, 69], ‘Kapil’: [59, 79, 49], ‘Virat’: [88, 68, 78]} topper = {‘Total’:-1, ‘Name’:[]} subject_highest = [-1,-1,-1]
num_students, num_subjects = 3,3 for i in range(num_students): tot,avg = 0,0 key = students[i] for j in range(num_subjects): tot = tot + marks[key][j] #checking the highest values for each subject if marks[key][j] > subject_highest[j]: subject_highest[j] = marks[key][j]
avg = tot / 3 print(f”Total marks obtained by {students[i]} is {tot} and average is {avg:.1f}“) # check highest total if tot >=topper[‘Total’]: topper[‘Total’] = tot topper[‘Name’].append(key)
print(f”{topper[‘Name’]} has topped the class with total marks of {topper[‘Total’]}“) print(f”Highest marks for subjects {subjects} is {subject_highest}“)
# sets, lists, tuples -> they are convertible in each others form l1 = [‘Apple’,‘Apple’,‘Apple’,‘Apple’,‘Apple’] l1 = list(set(l1)) print(l1) s1 = {4,2,3} print(s1)
# Functions def smile(): txt=”’ A smile, a curve that sets all right, Lighting days and brightening the night. In its warmth, hearts find their flight, A silent whisper of pure delight.”’ print(txt)
smile()
smile()
smile()
#================== # function to calculate gross pay def calc_grosspay(): basic_salary = 5000 hra = 0.1 * basic_salary da = 0.4 * basic_salary gross_pay = basic_salary + hra + da print(“Your gross pay is”,gross_pay)
def calc_grosspay_withreturn(): basic_salary = 5000 hra = 0.1 * basic_salary da = 0.4 * basic_salary gross_pay = basic_salary + hra + da return gross_pay
def calc_grosspay_return_input(basic_salary): hra = 0.1 * basic_salary da = 0.4 * basic_salary gross_pay = basic_salary + hra + da return gross_pay
bp_list = [3900,5000,6500,9000] gp_1 = calc_grosspay_return_input(bp_list[3]) print(“Gross Pay for this month is”,gp_1)
gp = calc_grosspay_withreturn() print(“Total gross pay for ABC is”,gp) gp_list=[] gp_list.append(gp) calc_grosspay()
# function to check prime numbers ”’ 10 = 2 to 5 7 = 2, 9 = 2,3 ”’ def gen_prime(num): ”’ This function takes a parameter and checks if its a prime number or not :param num: number (int) :return: True/False (True for prime number) ”’ isPrime = True for i in range(2,num//2): if num%i ==0: isPrime = False break return isPrime
if __name__ ==“__main__”: num = 11 print(num,” : “,gen_prime(num)) num = 100 print(num,” : “,gen_prime(num))
# generate prime numbers between given range start,end = 1000, 5000 for i in range(start,end): check = gen_prime(i) if check: print(i,end=“, “)
# doc string: multi line comment added at the beginning of the function help(gen_prime)
#import infy_apr as ia from infy_apr import gen_prime
def product_val(n1,n2): return n1 * n2
if __name__==“__main__”: num1 = 1 num2 = 3 print(“Sum of two numbers is”,num2+num1) # generate prime numbers between 50K to 50.5K for i in range(50000,50500): check = gen_prime(i) if check: print(i,end=“, “)
res = calculate(5,10,plus) print(“1. Result = “,res) res = calculate(5,10,diff) print(“2. Result = “,res) ############### # in-built functions() # user defined functions() # anonymous / one line /lambda def myfunc1(a,b): return a**b #above myfunc1() can also be written as: myfunc2 = lambda a,b: a**b print(“5 to power of 4 is”,myfunc2(5,4))
”’ map: apply same logic on all the values of the list: multiply all the values by 76 filter: filter out values in a list based on a condition: remove -ve values reduce: reduce multiple values in a list to a single value ”’ # a= 11, b = 12, c = 13… calc = 0 list1 = [‘a’,‘b’,‘c’,‘d’] word = input() for i in word: calc = calc+list1.index(i) + 11 # 11 + 13+14 print(calc)
res = calculate(5,10,plus) print(“1. Result = “,res) res = calculate(5,10,diff) print(“2. Result = “,res) ############### # in-built functions() # user defined functions() # anonymous / one line /lambda def myfunc1(a,b): return a**b #above myfunc1() can also be written as: myfunc2 = lambda a,b: a**b print(“5 to power of 4 is”,myfunc2(5,4))
”’ map: apply same logic on all the values of the list: multiply all the values by 76 filter: filter out values in a list based on a condition: remove -ve values reduce: reduce multiple values in a list to a single value ”’ # a= 11, b = 12, c = 13… calc = 0 list1 = [‘a’,‘b’,‘c’,‘d’] word = input() for i in word: calc = calc+list1.index(i) + 11 # 11 + 13+14 print(calc)
”’ map: apply same logic on all the values of the list: multiply all the values by 76 filter: filter out values in a list based on a condition: remove -ve values reduce: reduce multiple values in a list to a single value ”’ value_usd = [12.15,34.20,13,8,9,12,45,87,56,78,54,34] value_inr = [] # 1 usd = 78 inr for v in value_usd: value_inr.append(v*78) print(“Value in INR: “,value_inr)
value_inr =list(map(lambda x: 78*x,value_usd)) print(“Value in INR: “,value_inr)
# filter: filter out the values new_list=[12,7,0,-5,-6,15,18,21,-44,-90,-34,56,43,12,7,0,-5,-6,15,18,21,-44,-90,-34,56,43] output_list = list(filter(lambda x: x>=0,new_list)) print(“Filtered: “,output_list)
output_list = list(filter(lambda x: x%3==0 and x>=0,new_list)) print(“Filtered: “,output_list)
################################## ## class & objects ”’ car – class number of wheels – 4, color, make driving parking ”’ class Book: number_of_books = 0 def reading(self): print(“I am reading a book”)
b1 = Book() #creating object of class Book b2 = Book() b3 = Book() b4 = Book() print(b1.number_of_books) b1.reading() ”’ class level variables and methods object level variables and methods ”’
”’ __init__() : will automatically called when object is created ”’ class Book: book_count = 0 # class level variable def __init__(self,title): # object level method self.title=title # object level variable total = 0 #normal variable Book.book_count+=1 @classmethod def output(cls): print(“Total book now available = “, Book.book_count)
def check_prime(self): # check if n1 is prime or not self.checkPrime = True for i in range(2, self.n1//2+1): if self.n1 % i==0: self.checkPrime=False m1 = MyMathOp(15,10) print(m1.n1) m1.check_prime() print(m1.checkPrime)
s1 = Shape() #s1.myarea() #s1.myarea(10) #s1.area(10,20) as1 = AnotherShape() as1.test1() ”’ public: anyone can call public members of a class protected (_var): (concept exists but practically it doesnt exist) – behaves like public concept: only the derived class call private (__var): available only within the given class ”’ #s1.__dummy3() #r1.__dummy3() s1.dummy4()
# logical error # runtime errors – exceptions a = 50 try: b = int(input(“Enter the denominator: “)) except ValueError: print(“You have provided invalid value for B, changing the value to 1”) b = 1 try: print(a/b) # ZeroDivisionError print(“A by B is”,a/b) except ZeroDivisionError: print(“Sorry, we cant perform the analysis as denominator is zero”)
print(“thank you”)
################ a = 50 b = input(“Enter the denominator: “) try: print(“A by B is”, a / int(b)) # ZeroDivisionError & ValueError except ValueError: print(“You have provided invalid value for B, changing the value to 1”) b = 1 except ZeroDivisionError: print(“Sorry, we cant perform the analysis as denominator is zero”)
except Exception: print(“An error has occurred, hence skipping this section”)
else: print(“So we got the answer now!”)
finally: print(“Not sure if there was an error but we made it through”) print(“thank you”)
# File handling ”’ Working with Text files: 1. read: read(), readline(), readlines() 2. write: write(), writelines() 3. append Modes: r,r+, w, w+, a, a+ Accessing the file: 1. Absolute path: 2. Relative path: ”’ path=“C:/Folder1/Folder2/txt1.txt” path=“C:\\Folder1\\Folder2\\txt1.txt” path=“ptxt1.txt” content=”’Twinkle twinkle little star How I wonder what you are Up above the world so high like a diamond in the sky ”’ file_obj = open(path,“a+”)
file_obj.write(content)
file_obj.seek(0) # go to the beginning of the content read_cnt = file_obj.read() file_obj.close()
file_obj = open(path,“w”) write_nt = [‘Hello how are you?\n‘,‘I am fine\n‘,‘Where are you going\n‘,‘sipdfjisdjisdjf\n‘] file_obj.writelines(write_nt) file_obj.close()
Python is a high level computer programming language and famous for its plainness. Late in the 1980s Rossum shaped python and unconfined in 1991. Python ropes several programming paradigms, as well as ritual object-oriented and purposeful programming. Python is very vast and regular collection which provides numerous correspondence, framework and many practical relevance like web development, data analysis AI (artificial intelligence) scientific computing and much more.
I. Introduction
Why learn Python?
There are several reasons to learn Python:
effortlessness of Learning: Python’s straightforward and sparkling syntax makes it reachable for beginners.
resourcefulness: It’s applicable in diverse domains like web development, data analysis, machine learning, artificial intelligence, scientific computing, etc.
Large Community and Libraries: Python has a massive community that contributes to its ecosystem by creating libraries and frameworks, allowing developers to accomplish tasks more efficiently.
Career Opportunities: Python is widely used across industries, and proficiency in Python opens up job opportunities in software development, data science, machine learning, and more.
High Demand: Due to its versatility and ease of use, Python developers are in high demand in the job market.
C. Brief history and popularity
History: Python was conceived in the late 1980s by Guido van Rossum, and its implementation began in December 1989. It was officially released in 1991 as Python 0.9. Python 2.x and Python 3.x are the two major versions coexisting for some time, with Python 2.x being officially discontinued in 2020 in favor of Python 3.x.
Popularity: Python’s popularity has surged over the years due to its simplicity, readability, versatility, and an extensive community-driven ecosystem. It’s used by both beginners and experienced developers for various purposes, contributing to its widespread adoption across industries. Its popularity is evident in fields like web development (Django, Flask), data science (Pandas, NumPy), machine learning (TensorFlow, PyTorch), and more.
II. Setting Up Python
A. Installing Python:
Download Python: Visit the official Python website at python.org,
navigate to the Downloads section, and select the version of Python suitable for your operating system (Windows, macOS, or Linux).
Install Python: Run the installer and follow the installation instructions. Make sure to check the box that says “Add Python to PATH” during installation on Windows. This makes it easier to run Python from the command line.
B. Using Integrated Development Environments (IDEs) or Text Editors:
IDEs: Integrated Development Environments like PyCharm, VSCode with Python extensions, Jupyter Notebook, or Spyder provide an all-in-one solution with features like code highlighting, debugging tools, and project management. Install an IDE of your choice by downloading it from the respective website and follow the setup instructions.
Text Editors: Text editors like Sublime Text, Atom, or Notepad++ are simpler compared to IDEs but still support Python development. You write code and execute it separately. After installing a text editor, create a new file and save it with a .py extension (e.g., hello.py) to write Python code.
C. Running the First Python Program (Hello, World!):
Using IDEs:
Open your IDE.
Create a new Python file.
Type the following code:
python
print(“Hello, World!”)
Save the file.
Run the code using the “Run” or “Execute” button in the IDE. You should see “Hello, World!” printed in the output console.
Using Text Editors:
Open your chosen text editor.
Create a new file and type:
print(“Hello, World!”)
Save the file with a .py extension (e.g., hello.py).
Open a command line or terminal.
Navigate to the directory where your Python file is saved using cd (change directory) command.
Type python hello.py (replace hello.py with your file name) and press Enter.
You should see “Hello, World!” printed in the terminal.
Congratulations! You’ve successfully installed Python, chosen an environment to write code (IDE or text editor), and executed your first Python program displaying “Hello, World!”
III. Basics of Python Programming
A. Syntax and Indentation:
Syntax: Python’s syntax is clear and readable. It uses indentation to define blocks of code instead of using curly braces {} or keywords like end in other languages. Proper indentation (usually four spaces) is crucial for Python to understand the code structure correctly.
Example:
if 5 > 2: print(“Five is greater than two”)
B. Variables and Data Types:
Variables: In Python, variables are used to store data. They can be assigned different data types and values during the program’s execution.
Data Types: Python has several data types:
Integers (int): Whole numbers without decimals.
Floats (float): Numbers with decimals.
Strings (str): Ordered sequences of characters enclosed in single (‘ ‘) or double (” “) quotes.
Arithmetic Operators: Used for basic mathematical operations such as addition, subtraction, multiplication, division, etc.
python
# Examples of arithmetic operators a = 10 b = 5 print(a + b) # Addition print(a – b) # Subtraction print(a * b) # Multiplication print(a / b) # Division print(a % b) # Modulus (remainder) print(a ** b) # Exponentiation
Comparison Operators: Used to compare values and return True or False.
python
# Examples of comparison operators x = 10 y = 5 print(x == y) # Equal to print(x != y) # Not equal to print(x > y) # Greater than print(x < y) # Less than print(x >= y) # Greater than or equal to print(x <= y) # Less than or equal to
Logical Operators: Used to combine conditional statements.
python
# Examples of logical operators p = True q = False print(p and q) # Logical AND print(p or q) # Logical OR print(not p) # Logical NOT
D. Control Structures:
Conditionals (if, elif, else): Used to make decisions in the code based on certain conditions.
python
# Example of conditional statements age = 18 if age >= 18: print(“You are an adult”) elif age >= 13: print(“You are a teenager”) else: print(“You are a child”)
Loops (for, while): Used for iterating over a sequence (for loop) or executing a block of code while a condition is True (while loop).
python
# Example of loops # For loop for i in range(5): print(i) # While loop count = 0 while count < 5: print(count) count += 1
IV. Data Structures in Python
A. Lists:
Definition: Lists are ordered collections of items or elements in Python. They are mutable, meaning the elements within a list can be changed or modified after the list is created.
Syntax: Lists are created by enclosing elements within square brackets [], separated by commas.
Example:
python
# Creating a list my_list = [1, 2, 3, 4, 5]
B. Tuples:
Definition: Tuples are similar to lists but are immutable, meaning the elements cannot be changed once the tuple is created.
Syntax: Tuples are created by enclosing elements within parentheses (), separated by commas.
Example:
python
# Creating a tuple my_tuple = (1, 2, 3, 4, 5)
C. Dictionaries:
Definition: Dictionaries are unordered collections of key-value pairs. They are mutable and indexed by unique keys. Each key is associated with a value, similar to a real-life dictionary where words (keys) have definitions (values).
Syntax: Dictionaries are created by enclosing key-value pairs within curly braces {}, separated by commas and using a colon : to separate keys and values.
Definition: Sets are unordered collections of unique elements. They do not allow duplicate elements.
Syntax: Sets are created by enclosing elements within curly braces {}, separated by commas.
Example:
python
# Creating a set my_set = {1, 2, 3, 4, 5}
Key Points:
Lists and tuples are ordered collections, but lists are mutable while tuples are immutable.
Dictionaries use key-value pairs to store data, allowing quick retrieval of values using their associated keys.
Sets are unordered collections of unique elements; they are useful for mathematical set operations like union, intersection, etc., and do not allow duplicate elements.
These data structures provide flexibility in storing and manipulating data in Python, each with its own characteristics and best-use cases. Understanding how to use them effectively can greatly enhance your ability to work with data in Python programs.
V. Functions and Modules
A. Defining Functions:
Definition: Functions in Python are blocks of reusable code designed to perform a specific task. They improve code modularity and reusability.
Syntax: Functions are defined using the def keyword, followed by the function name and parentheses containing optional parameters. The block of code inside the function is indented.
Example:
python
# Defining a function def greet(): print(“Hello, welcome!”)
B. Passing Arguments and Returning Values:
Arguments: Functions can accept parameters (arguments) to perform their tasks dynamically.
Positional Arguments: Defined based on the order they are passed.
Keyword Arguments: Defined by specifying the parameter name when calling the function.
Return Values: Functions can return values using the return statement.
Example:
python
# Function with arguments and return value def add(a, b): return a + b result = add(3, 5) # Passing arguments print(“Result:”, result) # Output: Result: 8
C. Working with Modules and Libraries:
Modules: Python modules are files containing Python code, which can define functions, classes, and variables. They can be imported into other Python scripts to reuse the code.
Libraries: Libraries are collections of modules that provide pre-written functionalities to ease development tasks.
Importing Modules/Libraries: Use the import keyword to import modules and libraries in your Python script.
Example:
python
# Importing a module import math # Importing the math module # Using functions from the imported module print(math.sqrt(16)) # Output: 4.0 (square root function from math module)
Creating and Using Your Own Modules: You can create your own modules by writing Python code in a separate file and importing it into your script.
VI. File Handling in Python
A. Reading from and Writing to Files:
Reading from Files (open() and read()):
To read from a file, you can use the open() function in Python, which opens a file and returns a file object. The read() method is used to read the contents of the file.
Syntax for Reading:
python
# Reading from a file file = open(‘file.txt’, ‘r’) # Opens the file in read mode (‘r’) content = file.read() # Reads the entire file content print(content) file.close() # Close the file after reading
Writing to Files (open() and write()):
To write to a file, open it with the appropriate mode (‘w’ for write, ‘a’ for append). The write() method is used to write content to the file.
Syntax for Writing:
python
# Writing to a file file = open(‘file.txt’, ‘w’) # Opens the file in write mode (‘w’) file.write(‘Hello, World!\n’) # Writes content to the file file.close() # Close the file after writing
B. File Modes and Operations:
File Modes:
Read Mode (‘r’): Opens a file for reading. Raises an error if the file does not exist.
Write Mode (‘w’): Opens a file for writing. Creates a new file if it doesn’t exist or truncates the file if it exists.
Append Mode (‘a’): Opens a file for appending new content. Creates a new file if it doesn’t exist.
Read and Write Mode (‘r+’): Opens a file for both reading and writing.
Binary Mode (‘b’): Used in conjunction with other modes (e.g., ‘rb’, ‘wb’) to handle binary files.
File Operations:
read(): Reads the entire content of the file or a specified number of bytes.
readline(): Reads a single line from the file.
readlines(): Reads all the lines of a file and returns a list.
write(): Writes content to the file.
close(): Closes the file when finished with file operations.
Using with Statement (Context Manager):
The with statement in Python is used to automatically close the file when the block of code is exited. It’s a good practice to use it to ensure proper file handling.
Syntax:
python
with open(‘file.txt’, ‘r’) as file: content = file.read() print(content) # File is automatically closed outside the ‘with’ block
VII. Object-Oriented Programming (OOP) Basics
A. Classes and Objects:
Classes:
Classes are blueprints for creating objects in Python. They encapsulate data (attributes) and behaviors (methods) into a single unit.
Syntax for Class Declaration:
python
# Class declaration class MyClass: # Class constructor (initializer) def __init__(self, attribute1, attribute2): self.attribute1 = attribute1 self.attribute2 = attribute2 # Class method def my_method(self): return “This is a method in MyClass”
Objects:
Objects are instances of classes. They represent real-world entities and have attributes and behaviors defined by the class.
Creating Objects from a Class:
python
# Creating an object of MyClass obj = MyClass(“value1”, “value2”)
B. Inheritance and Polymorphism:
Inheritance:
Inheritance allows a class (subclass/child class) to inherit attributes and methods from another class (superclass/parent class).
Syntax for Inheritance:
python
# Parent class class Animal: def sound(self): return “Some sound” # Child class inheriting from Animal class Dog(Animal): def sound(self): # Overriding the method return “Woof!”
Polymorphism:
Polymorphism allows objects of different classes to be treated as objects of a common superclass. It enables the same method name to behave differently for each class.
Example of Polymorphism:
python
# Polymorphism example def animal_sound(animal): return animal.sound() # Same method name, different behaviors # Creating instances of classes animal1 = Animal() dog = Dog() # Calling the function with different objects print(animal_sound(animal1)) # Output: “Some sound” print(animal_sound(dog)) # Output: “Woof!”
VIII. Error Handling (Exceptions)
A. Understanding Exceptions:
What are Exceptions?
Exceptions are errors that occur during the execution of a program, disrupting the normal flow of the code.
Examples include dividing by zero, trying to access an undefined variable, or attempting to open a non-existent file.
Types of Exceptions:
Python has built-in exception types that represent different errors that can occur during program execution, like ZeroDivisionError, NameError, FileNotFoundError, etc.
B. Using Try-Except Blocks:
Handling Exceptions with Try-Except Blocks:
Try-except blocks in Python provide a way to handle exceptions gracefully, preventing the program from crashing when errors occur.
Syntax:
python
try: # Code that might raise an exception result = 10 / 0 # Example: Division by zero except ExceptionType as e: # Code to handle the exception print(“An exception occurred:”, e)
Handling Specific Exceptions:
You can catch specific exceptions by specifying the exception type after the except keyword.
Example:
python
try: file = open(‘nonexistent_file.txt’, ‘r’) except FileNotFoundError as e: print(“File not found:”, e)
Using Multiple Except Blocks:
You can use multiple except blocks to handle different types of exceptions separately.
Example:
python
try: result = 10 / 0 except ZeroDivisionError as e: print(“Division by zero error:”, e) except Exception as e: print(“An exception occurred:”, e)
Handling Exceptions with Else and Finally:
The else block runs if no exceptions are raised in the try block, while the finally block always runs, whether an exception is raised or not.
Example:
python
try: result = 10 / 2 except ZeroDivisionError as e: print(“Division by zero error:”, e) else: print(“No exceptions occurred!”) finally: print(“Finally block always executes”)
IX. Introduction to Python Libraries
A. Overview of Popular Libraries:
NumPy:
Description: NumPy is a fundamental package for scientific computing in Python. It provides support for arrays, matrices, and mathematical functions to operate on these data structures efficiently.
Key Features:
Multi-dimensional arrays and matrices.
Mathematical functions for array manipulation.
Linear algebra, Fourier transforms, and random number capabilities.
Example:
python
import numpy as np # Creating a NumPy array arr = np.array([1, 2, 3, 4, 5])
Pandas:
Description: Pandas is a powerful library for data manipulation and analysis. It provides data structures like Series and DataFrame, making it easy to handle structured data.
Key Features:
Data manipulation tools for reading, writing, and analyzing data.
Data alignment, indexing, and handling missing data.
Time-series functionality.
Example:
python
import pandas as pd # Creating a DataFrame data = {‘Name’: [‘Alice’, ‘Bob’, ‘Charlie’], ‘Age’: [25, 30, 35]} df = pd.DataFrame(data)
Matplotlib:
Description: Matplotlib is a comprehensive library for creating static, interactive, and animated visualizations in Python. It provides functionalities to visualize data in various formats.
Key Features:
Plotting 2D and 3D graphs, histograms, scatter plots, etc.
Customizable visualizations.
Integration with Jupyter Notebook for interactive plotting.
Example:
python
import matplotlib.pyplot as plt # Plotting a simple line graph x = [1, 2, 3, 4, 5] y = [2, 4, 6, 8, 10] plt.plot(x, y) plt.xlabel(‘X-axis’) plt.ylabel(‘Y-axis’) plt.title(‘Simple Line Graph’) plt.show()
B. Installing and Importing Libraries:
Installing Libraries using pip:
Open a terminal or command prompt and use the following command to install libraries:
pip install numpy pandas matplotlib
Importing Libraries in Python:
Once installed, import the libraries in your Python script using import statements:
Python import numpy as np import pandas as pd import matplotlib.pyplot as plt
After importing, you can use the functionalities provided by these libraries in your Python code.
X. Real-life Examples and Projects
A. Simple Projects for Practice:
To-Do List Application:
Create a command-line to-do list application that allows users to add tasks, mark them as completed, delete tasks, and display the list.
Temperature Converter:
Build a program that converts temperatures between Celsius and Fahrenheit or other temperature scales.
Web Scraper:
Develop a web scraper that extracts information from a website and stores it in a structured format like a CSV file.
Simple Calculator:
Create a basic calculator that performs arithmetic operations such as addition, subtraction, multiplication, and division.
Hangman Game:
Implement a command-line version of the Hangman game where players guess letters to reveal a hidden word.
Address Book:
Develop an address book application that stores contacts with details like name, phone number, and email address.
File Organizer:
Write a script that organizes files in a directory based on their file extensions or other criteria.
B. Exploring Python’s Applications in Different Fields:
Web Development (Django, Flask):
Python is widely used for web development. Explore frameworks like Django or Flask to build web applications, REST APIs, or dynamic websites.
Data Science and Machine Learning:
Use libraries like NumPy, Pandas, Scikit-learn, or TensorFlow to perform data analysis, create machine learning models, or work on predictive analytics projects.
Scientific Computing:
Python is used extensively in scientific computing for simulations, modeling, and solving complex mathematical problems. Use libraries like SciPy or SymPy for scientific computations.
Natural Language Processing (NLP):
Explore NLP with Python using libraries like NLTK or spaCy for text processing, sentiment analysis, or language translation tasks.
Game Development:
Develop simple games using Python libraries like Pygame, allowing you to create 2D games and learn game development concepts.
Automation and Scripting:
Create scripts to automate repetitive tasks like file manipulation, data processing, or system administration using Python’s scripting capabilities.
IoT (Internet of Things) and Raspberry Pi Projects:
Experiment with Python for IoT projects by controlling sensors, actuators, or devices using Raspberry Pi and Python libraries like GPIO Zero.
XI. Conclusion
A. Recap of Key Points:
Python Basics: Python is a high-level, versatile programming language known for its simplicity, readability, and vast ecosystem of libraries and frameworks.
Core Concepts: Understanding Python’s syntax, data types, control structures, functions, and handling exceptions is crucial for effective programming.
Popular Libraries: Libraries like NumPy, Pandas, Matplotlib, etc., offer specialized functionalities for data manipulation, scientific computing, visualization, and more.
Project Ideas: Simple projects, such as to-do lists, calculators, web scrapers, etc., provide practical experience and reinforce learning.
Real-world Applications: Python’s applications span diverse fields like web development, data science, machine learning, scientific computing, automation, IoT, and more.
B. Encouragement for Further Exploration:
Continuous Learning: Python’s versatility and vast ecosystem offer endless opportunities for learning and growth.
Practice and Projects: Build upon your knowledge by working on more complex projects, contributing to open-source, and experimenting with different libraries and domains.
Community Engagement: Engage with the Python community through forums, meetups, conferences, and online platforms to learn, share experiences, and collaborate.
Stay Curious: Python evolves continuously, and exploring new libraries, updates, or trends keeps your skills up-to-date and opens doors to new possibilities.
Persistence: Embrace challenges as learning opportunities. Persistence and dedication in learning Python will yield rewarding results in the long run.
C. Final Thoughts:
Python is an exceptional programming language renowned for its simplicity, readability, and versatility. Its applications span across numerous fields, from web development to scientific computing, data analysis, machine learning, and beyond. Whether you’re a beginner starting your programming journey or an experienced developer seeking new avenues, Python offers a rich ecosystem and a supportive community to aid your exploration and growth.
