Reading files line by line is a fundamental task in Python programming, crucial for handling large datasets or text processing. Inefficient methods can lead to performance bottlenecks. This blog post explores several techniques for reading files line by line in Python, focusing on efficiency and best practices.

**Method 1: Using a `for` loop**
This is the simplest and often most efficient approach for smaller files. The `for` loop iterates directly over the file object, reading one line at a time:
“`python
file = open(‘my_file.txt’, ‘r’)
for line in file:
# Process each line
print(line.strip())
file.close()
“`
Note the use of `.strip()` to remove leading/trailing whitespace.

**Method 2: Using `readline()`**
The `readline()` method provides more granular control. You can read lines one by one explicitly:
“`python
file = open(‘my_file.txt’, ‘r’)
line = file.readline()
while line:
# Process each line
print(line.strip())
line = file.readline()
file.close()
“`
This is useful when you need to conditionally process lines or handle specific line numbers.

**Method 3: Using `readlines()` (Less Efficient)**
While `readlines()` reads all lines into a list, it’s generally less efficient for very large files, as it loads the entire file into memory. Avoid this for massive files.

**Best Practices and Context Managers**
Always close files using `file.close()` or, better yet, use a `with` statement (context manager) to ensure automatic closure even if exceptions occur:
“`python
with open(‘my_file.txt’, ‘r’) as file:
for line in file:
# Process each line
print(line.strip())
“`
This is the recommended approach for its robustness and clarity.

Choosing the right method depends on file size and processing needs. For smaller files, the simple `for` loop is often sufficient; for larger files, the `readline()` approach or other memory-efficient strategies become essential.