# Define an empty list to store tasks
tasks = []

# Define a function to add tasks to the list
def add_task():
    task = input("Enter the task description: ")
    tasks.append(task)
    print("Task added successfully!")

# Define a function to display the list of tasks
def display_tasks():
    if not tasks:
        print("No tasks found!")
    else:
        print("Task List:")
        for i, task in enumerate(tasks, start=1):
            print(f"{i}. {task}")

# Define a function to mark tasks as completed
def complete_task():
    display_tasks()
    if not tasks:
        return

    try:
        task_index = int(input("Enter the task number to mark as completed: "))
        if 1 <= task_index <= len(tasks):
            completed_task = tasks.pop(task_index - 1)
            print(f"Task '{completed_task}' marked as completed!")
        else:
            print("Invalid task number! Please enter a valid task number.")
    except ValueError:
        print("Invalid input! Please enter a number.")

# Define a function to update task descriptions
def update_task():
    display_tasks()
    if not tasks:
        return

    try:
        task_index = int(input("Enter the task number to update: "))
        if 1 <= task_index <= len(tasks):
            new_task = input("Enter the new task description: ")
            tasks[task_index - 1] = new_task
            print("Task updated successfully!")
        else:
            print("Invalid task number! Please enter a valid task number.")
    except ValueError:
        print("Invalid input! Please enter a number.")

# Define a function to remove tasks from the list
def remove_task():
    display_tasks()
    if not tasks:
        return

    try:
        task_index = int(input("Enter the task number to remove: "))
        if 1 <= task_index <= len(tasks):
            removed_task = tasks.pop(task_index - 1)
            print(f"Task '{removed_task}' removed successfully!")
        else:
            print("Invalid task number! Please enter a valid task number.")
    except ValueError:
        print("Invalid input! Please enter a number.")

# Define a function to display the menu of options
def display_menu():
    print("To-Do List Application")
    print("---------------------")
    print("1. Add Task")
    print("2. Display Tasks")
    print("3. Mark Task as Completed")
    print("4. Update Task")
    print("5. Remove Task")
    print("6. Exit")

# Define the main function to run the application
def main():
    while True:
        display_menu()
        try:
            choice = int(input("Enter your choice: "))
            if choice == 1:
                add_task()
            elif choice == 2:
                display_tasks()
            elif choice == 3:
                complete_task()
            elif choice == 4:
                update_task()
            elif choice == 5:
                remove_task()
            elif choice == 6:
                print("Exiting...")
                break
            else:
                print("Invalid choice! Please enter a number between 1 and 6.")
        except ValueError:
            print("Invalid input! Please enter a number.")

if __name__ == "__main__":
    main()
 

Python Online Compiler

Write, Run & Share Python code online using OneCompiler's Python online compiler for free. It's one of the robust, feature-rich online compilers for python language, supporting both the versions which are Python 3 and Python 2.7. Getting started with the OneCompiler's Python editor is easy and fast. The editor shows sample boilerplate code when you choose language as Python or Python2 and start coding.

Taking inputs (stdin)

OneCompiler's python online editor supports stdin and users can give inputs to programs using the STDIN textbox under the I/O tab. Following is a sample python program which takes name as input and print your name with hello.

import sys
name = sys.stdin.readline()
print("Hello "+ name)

About Python

Python is a very popular general-purpose programming language which was created by Guido van Rossum, and released in 1991. It is very popular for web development and you can build almost anything like mobile apps, web apps, tools, data analytics, machine learning etc. It is designed to be simple and easy like english language. It's is highly productive and efficient making it a very popular language.

Tutorial & Syntax help

Loops

1. If-Else:

When ever you want to perform a set of operations based on a condition IF-ELSE is used.

if conditional-expression
    #code
elif conditional-expression
    #code
else:
    #code

Note:

Indentation is very important in Python, make sure the indentation is followed correctly

2. For:

For loop is used to iterate over arrays(list, tuple, set, dictionary) or strings.

Example:

mylist=("Iphone","Pixel","Samsung")
for i in mylist:
    print(i)

3. While:

While is also used to iterate a set of statements based on a condition. Usually while is preferred when number of iterations are not known in advance.

while condition  
    #code 

Collections

There are four types of collections in Python.

1. List:

List is a collection which is ordered and can be changed. Lists are specified in square brackets.

Example:

mylist=["iPhone","Pixel","Samsung"]
print(mylist)

2. Tuple:

Tuple is a collection which is ordered and can not be changed. Tuples are specified in round brackets.

Example:

myTuple=("iPhone","Pixel","Samsung")
print(myTuple)

Below throws an error if you assign another value to tuple again.

myTuple=("iPhone","Pixel","Samsung")
print(myTuple)
myTuple[1]="onePlus"
print(myTuple)

3. Set:

Set is a collection which is unordered and unindexed. Sets are specified in curly brackets.

Example:

myset = {"iPhone","Pixel","Samsung"}
print(myset)

4. Dictionary:

Dictionary is a collection of key value pairs which is unordered, can be changed, and indexed. They are written in curly brackets with key - value pairs.

Example:

mydict = {
    "brand" :"iPhone",
    "model": "iPhone 11"
}
print(mydict)

Supported Libraries

Following are the libraries supported by OneCompiler's Python compiler

NameDescription
NumPyNumPy python library helps users to work on arrays with ease
SciPySciPy is a scientific computation library which depends on NumPy for convenient and fast N-dimensional array manipulation
SKLearn/Scikit-learnScikit-learn or Scikit-learn is the most useful library for machine learning in Python
PandasPandas is the most efficient Python library for data manipulation and analysis
DOcplexDOcplex is IBM Decision Optimization CPLEX Modeling for Python, is a library composed of Mathematical Programming Modeling and Constraint Programming Modeling