From Scratch: A Step-by-Step Guide to Creating a Python Project

mkdir todo-list-project
cd todo-list-project

mkdir todo
mkdir tests

touch todo/__init__.py
touch todo/cli.py
touch todo/storage.py
touch tests/test_storage.py
touch requirements.txt
touch README.md
touch .gitignore

Step 3: Isolate Your Project with a Virtual Environment

This is non-negotiable. A virtual environment creates a self-contained space for your project’s dependencies. It prevents version conflicts between different projects.

1. Create the environment: From your project root (todo-list-project), run:bash

python -m venv venv

This creates a folder called venv that contains a clean Python installation.
2. Activate it:On macOS/Linux: source venv/bin/activate
3. On Windows (Command Prompt): venv\Scripts\activate.bat
4. On Windows (PowerShell): venv\Scripts\Activate.ps1You’ll know it worked when you see (venv) at the beginning of your terminal prompt.

Why it matters: Imagine you install a library for a project in first year, and another for a project in third year that requires a newer version. Without virtual environments, your system Python would get confused. With them, each project lives in its own happy bubble.

Step 4: Write Your First Module (The Code)

Now for the fun part. Let’s write the core logic. Open todo/storage.py. This module will handle saving and loading tasks from a simple file.

import json
from pathlib import Path

# Define the path to the file where tasks will be stored
TASKS_FILE = Path.home() / ".todo_tasks.json"

def load_tasks():
    """Load tasks from the JSON file. Returns an empty list if file doesn't exist."""
    if TASKS_FILE.exists():
        with open(TASKS_FILE, 'r') as f:
            try:
                return json.load(f)
            except json.JSONDecodeError:
                # If the file is corrupted, start fresh
                return []
    return []

def save_tasks(tasks):
    """Save the list of tasks to the JSON file."""
    with open(TASKS_FILE, 'w') as f:
        json.dump(tasks, f, indent=4)

def add_task(description):
    """Add a new task to the list."""
    tasks = load_tasks()
    # Create a simple task structure
    new_task = {
        "id": len(tasks) + 1,
        "description": description,
        "done": False
    }
    tasks.append(new_task)
    save_tasks(tasks)
    return new_task

Step 5: Create the User Interface (CLI)

Now, let’s build the command-line interface in todo/cli.py that will use our storage functions.

import argparse
from todo import storage

def main():
    parser = argparse.ArgumentParser(description="A simple to-do list manager.")
    subparsers = parser.add_subparsers(dest="command", help="Available commands")

    # Parser for the "add" command
    parser_add = subparsers.add_parser("add", help="Add a new task")
    parser_add.add_argument("description", type=str, help="Description of the task")

    # Parser for the "list" command
    parser_list = subparsers.add_parser("list", help="List all tasks")

    args = parser.parse_args()

    if args.command == "add":
        task = storage.add_task(args.description)
        print(f"✅ Added task: {task['description']}")
    elif args.command == "list":
        tasks = storage.load_tasks()
        if not tasks:
            print("📭 No tasks found. Add one with `python run.py add <task>`")
        else:
            for task in tasks:
                status = "✅" if task['done'] else "⬜"
                print(f"{status} {task['id']}: {task['description']}")
    else:
        parser.print_help()

if __name__ == "__main__":
    main()

Step 6: Create a Run File and Install as a Package

Having to run python todo/cli.py is a bit awkward. Let’s create a top-level runner and turn our project into an installable package.

First, create a file called run.py in your project root (todo-list-project/run.py):

# run.py
from todo.cli import main

if __name__ == "__main__":
    main()

# setup.py
from setuptools import setup, find_packages

setup(
    name="todo",
    version="0.1",
    packages=find_packages(),
    entry_points={
        "console_scripts": [
            "todo=run:main",
        ],
    },
)

Finally, while your virtual environment is activated, install your project in editable mode:

pip install -e .

Now, you can run your project from anywhere (while the venv is active) by simply typing todo in your terminal!

todo add "Finish programming assignment"
todo list

 

💡 Pro Tip: Add pycache/, venv/, and .DS_Store (on Mac) to your .gitignore file. This prevents temporary files and your virtual environment from being committed to GitHub, keeping your repository clean.
Ready to go deeper? Join our expert sessions

 

4. Common Mistakes Students Make When Creating a Python Project

Even with a guide, it’s easy to fall into these traps. Watch out for them.

• Mistake #1: Writing All Code in One Giant FileWhat it looks like: A single main.py that’s 500+ lines long with functions for file I/O, user input, and data processing all mixed together.
• Why students make it: It feels faster at the start.
• How to avoid it: As soon as your file gets past 100-150 lines, ask yourself, “Can I group some of these functions into a separate module?” like we did with storage.py.
  Mistake #2: Forgetting to Activate the Virtual Environment
• What it looks like: You install a library (e.g., requests) but when you run your program, you get a ModuleNotFoundError.
• Why students make it: It’s easy to forget you have multiple terminal windows open, and the venv might only be active in one.
• How to avoid it: Make it a habit to check for the (venv) prefix in your terminal prompt before running pip install or python run.py.
  Mistake #3: Committing Sensitive Information
• What it looks like: You push your project to GitHub, and later realize your API keys, database passwords, or secret keys are publicly visible.
• Why students make it: Hardcoding credentials is quick and easy.
• How to avoid it: Use environment variables or a .env file (and make sure .env is in your .gitignore!). Never hardcode secrets.
  Mistake #4: Ignoring the init.py File
• What it looks like: You create a folder with .py files, but when you try to import them, Python can’t find the module.
• Why students make it: It seems like an unnecessary file.
• How to avoid it: In Python versions before 3.3, init.py was required to make a folder a package. Even now, it’s a best practice to include it to signal that the folder is a Python package.
  Mistake #5: Not Updating requirements.txt
• What it looks like: You share your project with a friend, and they can’t run it because they get import errors for libraries they don’t have.
• Why students make it: Forgetting to document your dependencies.
• How to avoid it: After installing any new library with pip, immediately run pip freeze > requirements.txt to update the list.

5. Frequently Asked Questions (FAQ)

Q: What is the best IDE for creating a Python project from scratch?
 

A: There’s no single “best” IDE, but VS Code is an excellent, free, and popular choice for students. It has fantastic Python support, a built-in terminal, and Git integration. PyCharm is another powerful option, especially its free Community Edition.

Q: My professor just wants the .py file. Do I still need a full project structure?
 

A: Even for a single-file submission, the principles apply. You can still use a virtual environment for dependencies. Inside your single file, you should still organize your code into functions and classes. The project structure is for you to manage your work effectively, even if the final submission is just one file.

Q: I’m getting a “ModuleNotFoundError” even though I installed the library. Help!
 

A: This is almost always a virtual environment issue. First, check if you have (venv) in your terminal. If not, activate it. Then, run pip list to see if the library is installed in this environment. If it’s not there, install it. If it is there and you’re still getting the error, make sure you’re running the script from the same terminal where the venv is active.

Q: What is the if name == “main”: block for?
 

A: That block allows a Python file to be both reusable as a module and runnable as a script. Any code inside that block will only run when you execute the file directly (e.g., python run.py). If you import that file into another script, the code inside the block won’t run automatically, preventing unwanted side effects.

Q: How do I choose good names for my files and folders?
 

A: Follow Python’s PEP 8 style guide. Use snake_case for file and module names (e.g., storage_manager.py, data_utils.py). Names should be descriptive and tell you what’s inside. Avoid generic names like utils.py if possible; be specific, like file_utils.py or string_utils.py.

Q: Is it okay to use pip install without a virtual environment?
 

A: For quick, one-off experiments, it might be okay. However, for any project you plan to keep, submit, or build upon, always use a virtual environment. It’s a professional habit that will save you from major headaches down the line.

Q: My project is getting huge. How do I manage multiple folders?
 

A: The principles remain the same. You can create sub-packages by adding more folders with their own init.py files. For example, you might have todo/models/, todo/views/, and todo/controllers/ if you’re following an MVC pattern. The key is to keep related code grouped together.

6. Conclusion: From Blank Slate to Python Pro

Starting with a blinking cursor is intimidating, but it doesn’t have to be. By following this structured approach to creating a Python project from scratch, you transform that empty space into a organized, professional, and functional application. You’ve moved beyond just writing code to building real software. 

You now have a blueprint you can use for every assignment, personal project, and hackathon from here on out. Remember, every expert was once a beginner who just took the first step. Now, go build something amazing.

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