What are .pyc files in Python?

In Python, .pyc files are compiled bytecode files that are generated by the Python interpreter when a Python script is imported or executed. The .pyc files contain compiled bytecode that can be executed directly by the interpreter, without the need to recompile the source code every time the script is run. This can result in faster script execution times, especially for large scripts or modules.

.pyc files are created by the Python interpreter when a .py file is imported. They contain the "compiled bytecode" of the imported module/program so that the "translation" from source code to bytecode (which only needs to be done once) can be skipped on subsequent imports if the .pyc is newer than the corresponding .py file, thus speeding startup a little. But it's still interpreted. Once the *.pyc file is generated, there is no need of *.py file, unless you edit it.

Key points to keep in mind about .pyc files

Here are some key points to keep in mind about .pyc files:

• .pyc files are generated automatically by the Python interpreter when a Python script is imported or executed.
• The .pyc files are stored in the same directory as the corresponding .py files, and have the same name as the .py files, except with a .pyc extension instead of .py.
• The .pyc files are specific to the version of Python that was used to generate them. If you try to run a .pyc file with a different version of Python, you may encounter errors or unexpected behavior.

How .pyc files are generated

Here are some examples of how .pyc files are generated and used in Python:

Example:

Importing a Python module generates a .pyc file:

# my_module.py
def my_function():
    print("Hello, world!")

# main.py
import my_module

# When main.py is executed, Python will generate a my_module.pyc file

Example:

Running a Python script generates a .pyc file:

# my_script.py
def my_function():
    print("Hello, world!")

my_function()

# When my_script.py is executed, Python will generate a my_script.pyc file

Output

Hello world!
 

Example:

If a .pyc file already exists and is up-to-date, Python will use it instead of recompiling the source code:

# my_module.py
def my_function():
    print("Hello, world!")

# main.py
import my_module

# This will use the existing my_module.pyc file, if it is up-to-date

Example:

If the source code for a script or module changes, Python will recompile the bytecode and generate a new .pyc file:

# my_module.py
def my_function():
    print("Hello, world!")

# main.py
import my_module

# This will cause Python to recompile my_module.py and generate a new my_module.pyc file
# the next time main.py is run

By using .pyc files, Python can avoid the overhead of recompiling the same source code every time a script is run. This can result in faster script execution times and a more efficient use of system resources. However, it's important to keep in mind that .pyc files are specific to the version of Python that generated them, and should not be used across different versions of Python.

About optimizing .pyc files

If a Python script is run with the -O option, the .pyc files will be optimized:

# my_module.py
def my_function():
    print("Hello, world!")

# main.py
import my_module

# When main.py is run with the -O option, Python will generate a my_module.pyc file that is optimized

The -O option tells the Python interpreter to generate optimized bytecode, which can result in faster script execution times. The optimized bytecode is stored in .pyo files instead of .pyc files.

Note that not all Python interpreters support the -O option, and that the optimizations may not always result in faster execution times, depending on the specifics of the script and the system it is run on.

If you want to delete all .pyc files in a directory, you can use the find and rm commands:

$ find . -name '*.pyc' -delete

This will find all .pyc files in the current directory and its subdirectories, and delete them.

Note that deleting .pyc files is usually not necessary, as the Python interpreter will regenerate them as needed. However, in some cases it may be useful to delete the files to force the interpreter to recompile the source code.

To summarize, .pyc files are a useful feature of Python that can help improve the performance of scripts and modules. By understanding how they are generated and used, you can optimise your Python code and ensure that it runs efficiently on your system.