Why are .pyc files created?
In this article let’s try to demystify these *.pyc files!
But before we start, I recommend you to read this article for a better understanding of how Python runs: How Python runs?
After reading the article given below, you will be able to understand:
So, let’s get started!
pyc files are simply the compiled python files which contain the bytecode representation of your source code.
Whenever a Python script is executed, the byte code is generated in memory and simply discarded when program exits.
But, if a Python module is imported, a .pyc file for the module is generated (by default) which contains its bytecode. Thus, when the module is imported next time, the byte code from .pyc file is used. This makes loading of Python modules much faster because the compilation phase can be bypassed!
Here is a flowchart which clears the concept:
Let’s try to understand this by an example.
Consider two python scripts, namely, myadd.py and test.py. The add function of myadd.py has been imported in test.py.
Now, if we try to execute test.py, a folder named __pycache__ gets created in the current directory. It contains the following file:
Here, myadd.cpython-36.pyc is the name of generated pyc file. cpython-36 is the specification of the interpreter which created this pyc file. First few bytes of a pyc file specify the interpreter version (also called magic number).
Of course, you can run pyc files!
In a CPython interpreter, bytecode is fed to PVM (Python Virtual Machine) which is responsible for running your code.
Since, pyc files contain nothing but bytecode representation of your source code, we can execute them directly (just like the normal py files):
Note: A pyc file generated by a Python3 compiler can’t be executed using a Python2 compiler and will throw the error: RuntimeError: Bad magic number in .pyc file
If you need to create a pyc file for a module that is not imported, you can use the py_compile module.
The py_compile module can manually compile any module. One way is to use the py_compile.compile function in that module interactively:
This will write the .pyc in the __pycache__ folder in the same location as myadd.py.
You can also automatically compile all files in a directory or directories using the compileall module.
Yes, pyc files can be decompiled but the generated source code may or may not be totally identical to your original source code.
Also, there is no built-in module for decompilation. For this purpose, you can use a 3rd party python package uncompyle6 .
Simply install it using:
Now, using the terminal, you can decompile any pyc file as:
The obtained output looks something like this:
Since pyc files can be generated automatically when you import python modules, it is useless to add them to git repositories.
In order to not share your pyc files with others, you would add the entries:
in .gitignore file and git will start ignoring any new pyc files and __pycache__ folders in the repo.
But what about those files that are already being tracked by git? To fix this, we need to ask git to remove these paths from it’s index by running the git rm command with the --cached option.
So, this was all about pyc files! If you have any doubts or find anything incorrect, please share in the comments section below. Thanks for reading! 🙂
What are .pyc files when Python is interpreted/interpreter language? Well, this often confuses a lot of people. They consider the .pyc files to be the compiled version of the .py file, which is not true. In this article, we will learn why python generates the .pyc files if it claims to be an interpreted language.
Python is a popular high-level interpreted language, meaning that code is executed by an interpreter rather than compiled into machine code. It is faster for development, but Python code can be slower to execute than compiled languages like C or Java.
To speed up the execution of Python code, we can use .pyc files. These are compiled bytecode files. They are generated by the Python interpreter so that the interpreter can load them to speed up the execution of Python code.
Let’s see what these types of files mean and how python generates these files with examples
When you execute a Python script, the interpreter reads the source code and translates it into bytecode (.pyc files), the bytecode is not human-readable, but it is faster to execute than the source code.
Python interpreter does not save the bytecode to disk. However, it can be configured to generate and save compiled bytecode files with a .pyc extension. These .pyc files are binary files that contain the bytecode for the corresponding .py source file. The main purpose of .pyc files is to improve the performance of Python scripts.
If you are familiar with Java, .pyc files are similar to .class files in Java.
The Python interpreter generates .pyc files automatically when a .py file is imported or executed. When a Python script is executed, the interpreter first checks if there is a corresponding .pyc file for that script.
If there is the .pyc file, and the modification time of the .pyc file is later than that of the .py file, then the interpreter loads the bytecode from the .pyc file instead of recompiling the .py file. If there is no .pyc file or existing .pyc file modification time is not later than .py file, then the interpreter compiles the .py file into bytecode which ideally creates a .pyc file.
Python generate theses .pyc files for a few reasons:
Though python creates the .pyc files automatically, however, we can also manually generate the python .pyc files for a python .py files.
To create a compiled .pyc file for a module that hasn’t been imported yet, you can use the py_compile and compileall modules in Python. The py_compile module provides a way to manually compile any module, including one that hasn’t been imported yet. To use this module, you can call the py_compile.compile() function and specify the name of the module you want to compile as an argument.
You can also use the compileall module to automatically compile all Python files in a directory or directories.
You can also use this method via the command prompt:
You now know the reason why Python creates .pyc files while python is being interpreted/interpreter language. I hope this article was helpful. If you have any questions please feel free to put them in the comment section.
pyc files are created automatically by the GraalVM Python runtime when no or an invalid . pyc file is found matching the desired . py file. When a Python source file (module) is imported during an execution for the first time, the appropriate .
What are .pyc files when Python is interpreted/interpreter language? Well, this often confuses a lot of people. They consider the .pyc files to be the compiled version of the .py file, which is not true. In this article, we will learn why python generates the .pyc files if it claims to be an interpreted language.
Python is a popular high-level interpreted language, meaning that code is executed by an interpreter rather than compiled into machine code. It is faster for development, but Python code can be slower to execute than compiled languages like C or Java.
To speed up the execution of Python code, we can use .pyc files. These are compiled bytecode files. They are generated by the Python interpreter so that the interpreter can load them to speed up the execution of Python code.
Let’s see what these types of files mean and how python generates these files with examples
When you execute a Python script, the interpreter reads the source code and translates it into bytecode (.pyc files), the bytecode is not human-readable, but it is faster to execute than the source code.
Python interpreter does not save the bytecode to disk. However, it can be configured to generate and save compiled bytecode files with a .pyc extension. These .pyc files are binary files that contain the bytecode for the corresponding .py source file. The main purpose of .pyc files is to improve the performance of Python scripts.
If you are familiar with Java, .pyc files are similar to .class files in Java.
The Python interpreter generates .pyc files automatically when a .py file is imported or executed. When a Python script is executed, the interpreter first checks if there is a corresponding .pyc file for that script.
If there is the .pyc file, and the modification time of the .pyc file is later than that of the .py file, then the interpreter loads the bytecode from the .pyc file instead of recompiling the .py file. If there is no .pyc file or existing .pyc file modification time is not later than .py file, then the interpreter compiles the .py file into bytecode which ideally creates a .pyc file.
Python generate theses .pyc files for a few reasons:
Though python creates the .pyc files automatically, however, we can also manually generate the python .pyc files for a python .py files.
To create a compiled .pyc file for a module that hasn’t been imported yet, you can use the py_compile and compileall modules in Python. The py_compile module provides a way to manually compile any module, including one that hasn’t been imported yet. To use this module, you can call the py_compile.compile() function and specify the name of the module you want to compile as an argument.
You can also use the compileall module to automatically compile all Python files in a directory or directories.
You can also use this method via the command prompt:
You now know the reason why Python creates .pyc files while python is being interpreted/interpreter language. I hope this article was helpful. If you have any questions please feel free to put them in the comment section.
Happy Learning!
