File Handling in Python

# CHAPTER 9

File Handling in Python #

1. Chapter Introduction #

2. Reading Text Files #

Python has a built-in open() function. We use the with statement because it automatically closes the file when the block finishes, preventing memory leaks and locked files.

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

# Alternatively, read line by line (better for massive files)
with open('data.txt', 'r') as file:
    for line in file:
        print(line.strip()) # strip() removes the invisible newline character

3. Writing Text Files #

To save your results, you open a file in Write ('w') or Append ('a') mode.

report = "Analysis Complete: 500 rows processed."

# 'w' mode (Write): OVERWRITES the file completely
with open('report.txt', 'w') as file:
    file.write(report)
    
# 'a' mode (Append): Adds to the end of the file
with open('report.txt', 'a') as file:
    file.write("\nNo errors detected.")

4. Working with CSV Files #

While you will eventually use Pandas for CSVs, it is important to know how the built-in csv module works for basic scripting.

import csv

# Writing a CSV
header = ['Name', 'Age', 'Department']
data = [
    ['Alice', 28, 'Sales'],
    ['Bob', 35, 'IT']
]

with open('employees.csv', 'w', newline='') as file:
    writer = csv.writer(file)
    writer.writerow(header)
    writer.writerows(data)

# Reading a CSV
with open('employees.csv', 'r') as file:
    reader = csv.reader(file)
    for row in reader:
        print(row) # Outputs lists: ['Alice', '28', 'Sales']

5. Working with JSON Files #

JSON (JavaScript Object Notation) is the standard format for web data. It looks exactly like Python nested Dictionaries and Lists. The json module translates JSON strings into Python Dictionaries.

import json

# Python Dictionary
user_data = {
    "id": 101,
    "name": "Jane",
    "is_active": True
}

# 1. Write Dictionary to a JSON file
with open('user.json', 'w') as file:
    # json.dump serializes the dictionary to text
    json.dump(user_data, file, indent=4)

# 2. Read JSON file back into a Dictionary
with open('user.json', 'r') as file:
    loaded_data = json.load(file)
    print(loaded_data['name']) # Output: Jane

6. File Paths #

You must tell Python where the file is.

• Relative Path: Looks relative to where the script is running. (e.g., data/sales.csv). *This is preferred!*

• Absolute Path: The full path (e.g., C:/Users/Name/Documents/data/sales.csv).

import os

# Check if a file exists before trying to open it
if os.path.exists("employees.csv"):
    print("File found!")
else:
    print("File missing!")

7. Mini Project: Notes Manager System #

Let's build a simple script that logs daily notes and timestamps them.

import os
from datetime import datetime

filename = "daily_log.txt"

def add_log(note):
    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
    log_entry = f"[{timestamp}] {note}\n"
    
    # Use 'a' to append, so we don't overwrite yesterday's notes
    with open(filename, 'a') as file:
        file.write(log_entry)
    print("Log saved.")

def view_logs():
    if not os.path.exists(filename):
        print("No logs found.")
        return
        
    with open(filename, 'r') as file:
        print("--- DAILY LOGS ---")
        print(file.read())

# Simulate usage
add_log("Started data cleaning phase.")
view_logs()

8. Common Mistakes #

• FileNotFoundError: You type open('data.csv'), but your script is in a different folder. Always double-check your Current Working Directory (os.getcwd()).

• Overwriting Data: Opening an existing file in 'w' mode instantly wipes it clean. Use 'a' if you want to keep the historical data and add to it.

• Forgetting newline='' in CSVs: On Windows, writing CSVs without newline='' often results in blank rows between every line of data.

9. MCQs #

10. Interview Questions #

• Q: Explain the difference between opening a file in 'w' mode versus 'a' mode.

• Q: When sharing code with a team, why is it better to use relative paths (data/file.csv) instead of absolute paths (C:/Users/Dave/data/file.csv)?

11. Summary #

12. Next Chapter Recommendation #