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How to Read and Write Files in Python

How to Read and Write Files in Python

How to Read and Write Files in Python

File handling is a fundamental concept in Python that lets you work with files on your computer—be it reading configuration files, logs, or saving user data. Python’s open() function, along with methods like read(), write(), and the with statement, provides an easy-to-use and safe interface for working with files. This article shows you the standard approaches, key patterns, and best practices for reading and writing files in Python.

Table of Content

Why Work with Files in Python?

  • Persistence: Store data so it’s available between program runs.
  • Data Exchange: Read configuration, save results, or share data with other programs.
  • Logging: Keep a record of program actions or errors.
  • Automation: Batch process files for data cleaning, reporting, etc.

Syntax & Structure

# Open a file
file_obj = open("filename.txt", "mode")
# ... read or write using file_obj
file_obj.close()

# Recommended: Use with statement (auto-closes the file)
with open("filename.txt", "mode") as file_obj:
    # read or write using file_obj
  • open(filename, mode): Opens a file; returns a file object.
  • filename: Name (and path) of the file to open.
  • mode: 'r' (read), 'w' (write), 'a' (append), 'b' (binary), 'x' (exclusive create), 't' (text, default).
  • Always call close() or use the with statement, which does this for you.

Basic Examples: Reading Files

1. Read Entire File as String

with open("example.txt", "r") as file:
    content = file.read()
    print(content)

2. Read File Line by Line

with open("example.txt", "r") as file:
    for line in file:
        print(line.strip())

3. Read File into a List of Lines

with open("example.txt", "r") as file:
    lines = file.readlines()
    print(lines)

Writing to Files

1. Write Text to a File (Overwrites Existing Content or Creates New)

with open("output.txt", "w") as file:
    file.write("Hello, world!\n")

2. Append to an Existing File

with open("output.txt", "a") as file:
    file.write("Adding another line.\n")

3. Write a List of Lines

lines = ["First line\n", "Second line\n", "Third line\n"]
with open("lines.txt", "w") as file:
    file.writelines(lines)

File Modes Explained

Mode Description Best For
'r' Read text file (default mode) Reading existing files
'w' Write (overwrites file or creates new) Start new file or replace old
'a' Append (creates file if not exists) Adding logs, new lines
'b' Binary mode (add to other mode: e.g. 'rb', 'wb') Images, non-text data
'x' Create file, fail if file already exists One-time writes, exclusive output
't' Text mode (default if omitted) Regular text file work

Comparison Table: File Reading & Writing Patterns

Pattern Example Code Best For
Read full file as string 
with open("data.txt", "r") as file:
    content = file.read()
Small text/config files
Process file line-by-line 
with open("log.txt", "r") as file:
    for line in file:
        process_line(line)
Large files, parsing logs
Write output (overwrite) 
with open("out.txt", "w") as file:
    file.write("result\n")
Reports, config outputs
Append output 
with open("log.txt", "a") as file:
    file.write("new event\n")
Logging, adding to files
Binary read 
with open("img.jpg", "rb") as file:
    data = file.read()
Images, PDF, binary data

Useful Tips

  • Use with: Always use the with statement. Automatically closes files, even if there’s an error.
  • Be explicit: Specify the correct mode ('r', 'w', 'a', 'b') for your purpose.
  • Don’t read large files at once: For big files, process line by line to save memory.
  • Handle errors: Use try/except to catch file not found, permission errors, etc.
  • Writing lists: Add \n at the end of each line if using writelines().
  • Path management: For cross-platform code, use os.path or pathlib to build file paths.

Conclusion

Python’s file handling is simple and powerful. Just remember to use the with statement, pick the right mode for your task, and process files efficiently for your use case. These examples and patterns will help you reliably manage files in scripts, applications, or data processing pipelines.

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