File Handling and Notebook Management

# CHAPTER 9

File Handling and Notebook Management #

1. Chapter Introduction #

2. Understanding File Paths in Jupyter #

When you launch Jupyter, it opens a specific directory (folder) on your computer. This is your Current Working Directory (CWD).

Cell 1:

import os

# Check where Jupyter is currently looking
print("Current Directory:", os.getcwd())

# List all files in this directory
print("Files:", os.listdir())

When you try to open a file, you must tell Jupyter where it is.

• Relative Path: Looks for the file *relative* to where the notebook is saved. (e.g., data.csv assumes the file is in the exact same folder as the notebook).

• Absolute Path: The full path from the root of your hard drive. (e.g., C:/Users/Name/Documents/data.csv).

*Best Practice:* Always keep your data files in a folder named data right next to your notebook, and use relative paths like data/my_file.csv. This ensures your code works if you email the project to a colleague.

3. Reading from Text Files #

Python has a built-in open() function to read files. We use the with statement because it automatically closes the file when we are done, freeing up computer memory.

Cell 2: *(Assuming you have a file named sample.txt in the same folder)*

# 'r' stands for Read mode
with open('sample.txt', 'r') as file:
    # Read the entire file into a single string
    content = file.read()
    print(content)

4. Writing to Text Files #

To save your analytical results, you write to a file.

Cell 3:

report = "Analysis Complete: 500 records processed."

# 'w' stands for Write mode. 
# WARNING: 'w' will overwrite the file if it already exists!
with open('report.txt', 'w') as file:
    file.write(report)
    
print("File saved successfully.")

# 'a' stands for Append mode. 
# It adds text to the end of an existing file.
with open('report.txt', 'a') as file:
    file.write("\nAppended note: No errors found.")

5. Jupyter Notebook Files (.ipynb) #

When you save a notebook, it is saved as a .ipynb file. If you try to open this file in a normal text editor (like Notepad), you will see a massive, messy JSON file. Do not edit .ipynb files in a standard text editor! It will corrupt the notebook. You can only safely open and edit them inside the Jupyter interface or VS Code.

6. The Power of Checkpoints #

Jupyter auto-saves your notebook every 120 seconds. However, it also has a feature called Checkpoints.

When you click the "Save" icon (or press Ctrl+S), Jupyter explicitly creates a Checkpoint. A checkpoint is a hidden backup of your file at that exact moment.

How to use Checkpoints: If you write some code that breaks your notebook, and you want to go back in time:

1. 1. Go to the top menu.

1. 2. Click File -> Revert to Checkpoint.

1. 3. Select the timestamp you want to revert to.

*Note:* Jupyter only keeps the *single most recent* checkpoint by default.

7. Mini Project: File Analyzer #

Let's build a quick notebook tool that reads a text file and counts the words.

Cell 4:

# First, let's create a dummy file to analyze
with open('dummy_data.txt', 'w') as f:
    f.write("Data science is the sexiest job of the 21st century. Data is everywhere.")

# Now, let's analyze it
def analyze_file(filepath):
    try:
        with open(filepath, 'r') as file:
            text = file.read()
            words = text.split()
            word_count = len(words)
            return f"The file has {word_count} words."
    except FileNotFoundError:
        return "Error: File does not exist!"

print(analyze_file('dummy_data.txt'))
print(analyze_file('missing_file.txt'))

8. Common Mistakes #

• FileNotFoundError: You type open('data.csv'), but you get an error. 99% of the time, the file is in your "Downloads" folder, but your Jupyter Notebook is saved in your "Documents" folder. Move the CSV to the exact same folder as the notebook.

• Forgetting to close files: If you don't use the with open() syntax and instead do f = open('file.txt'), the file remains "locked" in memory. Other programs won't be able to edit it.

9. MCQs #

10. Interview Questions #

• Q: Explain the difference between an Absolute Path and a Relative Path. Why are relative paths preferred in data science projects?

• Q: Why is it dangerous to open a file in 'w' mode? What should you use instead if you want to keep historical log data?

11. Summary #

12. Next Chapter Recommendation #