Effective File Reading Techniques in Python
There are four common methods for reading files in Python. 1. Use open() and read() to suit small text files and read all content at once; 2. Read by line is suitable for large files, and processed line by line to avoid excessive memory usage; 3. readlines() can obtain a list of all lines at once, which is convenient for line by line but is not suitable for large files; 4. Specify encoding parameters to solve encoding problems. Common encodings include utf-8, gbk, etc. to ensure the correct parsing of the file content. Choosing the right method and paying attention to using with and encoding settings can improve code efficiency and stability.
Reading files is one of the most common operations in Python programming. If you just want to read a text file quickly, the method is actually very simple, but when facing different formats, sizes and scenarios, using the right method becomes very critical.

1. Basic reading: use open()
and read()
This is the most basic and most commonly used reading method. Suitable for small text files, such as logs, configuration files, etc.

with open('example.txt', 'r') as file: content = file.read() print(content)
-
with
is a good habit, it automatically closes files. -
'r'
means opening the file in read-only mode. - If the file is not large, it is okay to directly
read()
the entire content; but if the file is large, loading it at one time may take up too much memory.
2. Read by line: suitable for large file processing
For larger files, such as logs or data files of several hundred MB, it is recommended to read them one by one:
with open('large_file.txt', 'r') as file: for line in file: print(line.strip())
- This will not load the entire file into memory at once.
-
for line in file
is the standard writing method for line-by-line iteration. -
strip()
can remove newlines and spaces at the end of each line and use them depending on the situation.
This method is very practical when dealing with log analysis and data cleaning, especially when you only need to focus on certain specific rows.

3. Use readlines()
to get a list of all rows
If you really need to process each line and want to get everything as a list at once, you can use this method:
with open('data.txt', 'r') as file: lines = file.readlines() for line in lines: print(line.strip())
-
readlines()
returns a list containing all rows. - Each item retains newlines and usually needs to be processed with
strip()
. - Pay attention to memory issues, it is also not suitable for particularly large files.
4. What should I do if I have different coding? Specify encoding parameters
Many beginners encounter Chinese garbled code because they do not specify the correct encoding format. Especially on Windows, it is not UTF-8 by default.
with open('chinese.txt', 'r', encoding='utf-8') as file: content = file.read() print(content)
- If you are not sure about the encoding of the file, you can try common options such as
utf-8
,gbk
, andlatin1
. - It also applies when opening CSV, JSON, or HTML files.
- If an error is still reported, you may need to read in binary mode and decode manually (advanced skills).
Basically these commonly used methods. Just choose the right method according to the file size, format and your processing needs. What is not complicated but easy to ignore is: don't forget to add with
, and don't easily ignore the encoding problem.
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