Python splitlines() Method: Full Guide, Usage & Examples

1. Introduction

2. What is the splitlines() Method

Overview and Use Cases

• Works regardless of the type of newline code; supports all.
• You can control whether to keep the newline characters using the optional argument keepends.
• If the input string is empty, it returns an empty list.

• Processing text files: Split text data into lines and manipulate it as a list.
• Log analysis: Process each line of a log file individually.
• Data organization: Split multi-line input data and structure it.

Differences between splitlines() and split()

Code Example

# Test string
text = "line1
line2
line3"

# Example of splitlines() usage
lines = text.splitlines()
print(lines)  # Output: ['line1', 'line2', 'line3']

# When specifying newline with split()
lines_split = text.split('
')
print(lines_split)  # Output: ['line1', 'line2
', 'line3']

3. Using splitlines()

Basic Syntax

string.splitlines(keepends=False)

• string: The string to be split.
• keepends: Optional argument that specifies whether to include newline characters in the list elements.
• The default value is False (newline characters are not included).
• Specifying True includes newline characters in each element.

Behavior of the keepends argument

text = "line1
line2
line3"

# keepends=False (default) case
print(text.splitlines(keepends=False))
# Output: ['line1', 'line2', 'line3']

# keepends=True case
print(text.splitlines(keepends=True))
# Output: ['line1\n', 'line2\n', 'line3']

• When keepends=False, newline characters are removed and only the line strings are stored in the list.
• When keepends=True, newline characters are retained at the end of each line.

Example: Basic Usage

# Sample string
sample_text = "Hello
Python
Programming"

# When not preserving newline characters
lines = sample_text.splitlines()
print(lines)
# Output: ['Hello', 'Python', 'Programming']

# When preserving newline characters
lines_with_ends = sample_text.splitlines(keepends=True)
print(lines_with_ends)
# Output: ['Hello\n', 'Python\n', 'Programming']

Example: Empty String

empty_text = ""
print(empty_text.splitlines())
# Output: []

Example: No Newline Characters

single_line = "Python is fun"
print(single_line.splitlines())
# Output: ['Python is fun']

4. Concrete examples of splitlines()

1. Processing a text file line by line

# Convert the file contents into a list of lines
with open("sample.txt", "r", encoding="utf-8") as file:
    content = file.read()
    lines = content.splitlines()

# Output each line
for line in lines:
    print(line)

• Search for specific keywords within the file.
• Parse data line by line.

2. Formatting user input

# Multiple-line input from the user
user_input = """Name: Sato
Age: 25
Occupation: Engineer"""

# Split the input into lines
lines = user_input.splitlines()

# Formatted output
for line in lines:
    key, value = line.split(": ")
    print(f"{key} is {value}.")

Name is Sato.
Age is 25.
Occupation is Engineer.

3. Organizing data in web scraping

import requests

# Retrieve a sample web page
url = "https://example.com"
response = requests.get(url)

# Split the page text into lines
lines = response.text.splitlines()

# Verify the retrieved data (display the first 10 lines as an example)
for line in lines[:10]:
    print(line)

• Preprocess scraped data.
• Analyze HTML or log data.

4. Analyzing log files

# Sample log
log_data = """2025-01-24 10:00:00 INFO User logged in
2025-01-24 10:05:00 ERROR Connection failed
2025-01-24 10:10:00 INFO User logged out"""

# Split into lines
log_lines = log_data.splitlines()

# Extract only error lines
for line in log_lines:
    if "ERROR" in line:
        print(line)

2025-01-24 10:05:00 ERROR Connection failed

5. When preserving newline characters is required

# Example of preserving newline characters
text = "Line1
Line2
Line3"

# Preserve newline characters
lines = text.splitlines(keepends=True)
print(lines)
# Output: ['Line1\\n', 'Line2\\r\\n', 'Line3']

• When you need to analyze the types of newline characters.
• When you need to manipulate data while preserving the original formatting.

5. Scenarios for Using splitlines()

1. Data Analysis

Example: Log Data Analysis

log_data = """2025-01-24 10:00:00 INFO Starting process
2025-01-24 10:05:00 ERROR Failed to connect to database
2025-01-24 10:10:00 INFO Process completed"""

# Split into lines
log_lines = log_data.splitlines()

# Extract error lines
error_logs = [line for line in log_lines if "ERROR" in line]
print("Error lines:", error_logs)

• Extract errors and warnings from log files.
• Perform line-by-line statistics and classification of data.

2. Text File Manipulation

Example: Configuration File Processing

# Sample configuration file content
config_data = """[Database]
host = localhost
port = 5432

[User]
name = admin
password = secret"""

# Split configuration into lines
config_lines = config_data.splitlines()

# Exclude comments and empty lines
filtered_lines = [line for line in config_lines if line.strip() and not line.startswith("#")]
print(filtered_lines)

• Automatic analysis of configuration files and scripts.
• Extract useful information from documents.

3. Use in Web Development

Example: Formatting User Input

# Example user input
user_input = """Line1
Line2
Line3"""

# Split by line
lines = user_input.splitlines()

# Formatted output
formatted_output = "n".join(f"Line {i+1}: {line}" for i, line in enumerate(lines))
print(formatted_output)

Line 1: Line1
Line 2: Line2
Line 3: Line3

• Validation and formatting of input data.
• Preprocessing after collecting data from users.

4. Data Organization in Web Scraping

Example: Splitting HTML Text into Lines

import requests

# Sample HTML data
html_content = """<html>
<head><title>Example</title></head>
<body>
<p>This is an example.</p>
</body>
</html>"""

# Split HTML into lines
html_lines = html_content.splitlines()

# Output each line's content
for line in html_lines:
    print(line.strip())

• Parsing HTML or JSON data.
• Data formatting after scraping.

5. Use During Debugging

Example: Splitting Error Messages

error_message = """Traceback (most recent call last):
File "main.py", line 10, in <module>
ValueError: invalid literal for int() with base 10: 'abc'"""

# Split into lines
error_lines = error_message.splitlines()

# Output each line with a number
for i, line in enumerate(error_lines, start=1):
    print(f"{i}: {line}")

• Improving readability of error logs.
• Analyzing multi-line error messages.

6. Points to Note and Best Practices

Considerations

1. Behavior with mixed line endings splitlines() automatically recognizes various line-ending codes such as \r, \n, \r\n, etc., and splits accordingly. This behavior is usually convenient, but if you need to split on a specific line-ending code, you must use another method such as split(' '). Example:

   text = "line1
line2
line3"
   print(text.splitlines())
   # Output: ['line1', 'line2', 'line3']

2. Handling of empty lines splitlines() also retains empty lines as list elements. If you need to exclude empty lines, additional filtering is required. Example: Excluding empty lines:

   text = "line1

line2
"
   lines = text.splitlines()
   filtered_lines = [line for line in lines if line.strip()]
   print(filtered_lines)
   # Output: ['line1', 'line2']

3. Processing large datasets When processing large amounts of data, using splitlines() can increase memory consumption. For large files or strings, you need to carefully design how you use the split data.
4. Whether to retain line endings If you don’t specify the argument keepends=True, line endings are removed, which is unsuitable when you need to preserve the original formatting.

Best Practices

1. Use keepends=True when you need to retain line endings When you need to keep line endings, specifying keepends=True allows you to split without damaging the format. Example:

   text = "line1
line2
line3"
   lines = text.splitlines(keepends=True)
   print(lines)
   # Output: ['line1
', 'line2
', 'line3']

2. Use list comprehensions to exclude empty lines To efficiently exclude empty lines, using a list comprehension is a simple and fast method. Example:

   lines = ["line1", "", "line2", " "]
   filtered = [line for line in lines if line.strip()]
   print(filtered)
   # Output: ['line1', 'line2']

3. Appropriately use split() as an alternative to splitlines() If you want to split by a specific line ending or character, choosing split() is more appropriate. Example:

   text = "line1
line2
line3"
   print(text.split('
'))
   # Output: ['line1', 'line2
', 'line3']

4. Processing large data with generators When reading large files, instead of processing everything at once, using a a time can reduce memory usage. Example:

   def read_lines(file_path):
       with open(file_path, 'r', encoding='utf-8') as file:
           for line in file:
               yield line.strip()

   for line in read_lines("large_file.txt"):
       print(line)

5. Incorporate error handling Considering that input data may be in an unexpected format, incorporating error handling is also important. Example:

   try:
       text = None  # Incorrect input
       lines = text.splitlines()
   except AttributeError as e:
       print("Error: Invalid input -", e)

7. Frequently Asked Questions (FAQ)

Q1: splitlines() and split(‘

text = "line1
line2
line3"

# when using splitlines()
print(text.splitlines())  
# Output: ['line1', 'line2', 'line3']

# when using split('\n')
print(text.split('\n'))  
# Output: ['line1', 'line2\n', 'line3']

Q2: How does splitlines() handle empty lines?

text = "line1

line2"
lines = text.splitlines()
filtered_lines = [line for line in lines if line.strip()]
print(filtered_lines)
# Output: ['line1', 'line2']

Q3: Does splitlines() distinguish case?

Q4: Can splitlines() be used with byte strings?

text = b"line1
line2
line3"
lines = text.splitlines()
print(lines)
# Output: [b'line1', b'line2', b'line3']

Q5: When should you use the keepends option of splitlines()?

text = "line1
line2
line3"
lines = text.splitlines(keepends=True)
print(lines)
# Output: ['line1\n', 'line2\n', 'line3']

Q6: Since which Python version is splitlines() available?

Q7: What happens when splitlines() processes a string without newline characters?

text = "Python is fun"
lines = text.splitlines()
print(lines)
# Output: ['Python is fun']

Q8: In what situations should you use splitlines()?

• Processing a text file line by line.
• Organizing multi‑line input from users.
• Handling data where newline characters are mixed.
• Analyzing log data or HTML text.

Q9: How performant is splitlines()?

Q10: What are the most important points when using splitlines()?

• The main benefit is simplifying newline handling.
• If you need to be aware of empty lines or formatting, add extra processing.
• Consider combining it with other splitting methods as needed.

8. Summary

Article recap

1. splitlines() method overview

• splitlines() is a method that splits a string at line‑break characters and returns a list. It automatically recognizes multiple types of line‑break codes (, , ).

1. Basic usage

• By using the keepends argument, you can control whether line‑break characters are retained. This allows flexible usage according to your needs.

1. Specific use cases and application scenarios

• It can be used for a wide range of tasks such as processing text files and log data, web scraping, and formatting user input.

1. Cautions and best practices

• Understanding the cautions when handling empty lines or large datasets, as well as how to choose between this and other string manipulation methods, improves code efficiency.

1. Frequently Asked Questions (FAQ)

• We covered everything from common beginner questions to advanced points, illustrating with concrete examples.

Benefits of using splitlines()

• Efficient string manipulation: You can easily split complex data that includes line‑break characters.
• Support for diverse data formats: It can be used with CSVs, log files, scraped data, and various other formats.
• Flexibility and ease of use: By combining the keepends argument with list comprehensions, you can handle a variety of processing tasks.

Next steps

1. Try the code yourself Experience how to use splitlines() by running the sample code presented in the article.
2. Learn other string manipulation methods Python offers various string methods such as split(), join(), strip(), etc. Hone your skill in selecting the appropriate one for each use case.
3. Apply it in projects By using splitlines() in real projects like log analysis or data formatting, you’ll gain deeper understanding and practical ability.