When you run Python code from an Editor, like Visual Studio Code or any other IDE, a series of steps occur from when you hit "run" to when the CPU executes your code. Let's break down the process:
1. Writing the Code
You write your Python code in an editor (like VSCode, PyCharm, Sublime Text, etc.). This code is typically in plain text and follows Python's syntax and grammar. The file is usually saved with a .py extension.
2. Running the Code
When you execute or "run" your Python script, several things happen. The key step is that the Python interpreter is invoked to process the code.
3. Python Interpreter Execution
• Python Virtual Machine (PVM) is responsible for executing Python code. The Python interpreter (CPython by default) interprets your Python code.
• The Python interpreter consists of two parts:
1. Compiler (to convert Python code to bytecode)
2. Interpreter (to execute bytecode)
4. From Python Code to Bytecode
When you run your Python code:
1. The Python interpreter (which is typically CPython) reads the Python source file (.py).
2. The compiler part of the interpreter converts your Python code into an intermediate form known as bytecode.
3. This bytecode is stored in .pyc files (Python Compiled files), which are placed in a special directory (__pycache__) by default.
5. Running the Bytecode in Python Virtual Machine (PVM)
• PVM is responsible for running the bytecode. The bytecode is essentially a set of instructions that are closer to machine code but not yet ready for the CPU.
• The Python Virtual Machine is part of the interpreter that takes the bytecode and executes it. PVM translates these bytecode instructions into lower-level machine instructions that the CPU can understand.
6. Machine Instructions and Execution on the CPU
• The CPU executes the machine instructions.
• The Operating System (OS) manages how the CPU accesses memory and other resources.
• If your code interacts with hardware (e.g., I/O operations, file systems, network requests), those operations are handled by the OS, which then uses the CPU to interact with the underlying hardware.
7. Libraries and C Extensions (if any)
• If your Python script uses external libraries or C extensions (e.g., NumPy, pandas), these are often written in low-level languages like C and are already compiled into machine code, and Python calls these compiled binaries.
• These libraries provide optimized performance because they execute faster than Python code (since they are precompiled). When you use them, Python will interface with these C libraries via a special API, which is faster than running pure Python code.
8. Execution Flow (Summary)
1. Write Python code: You write .py code in your editor.
2. Run Python code: The Python interpreter is called.
3. Convert to Bytecode: The interpreter compiles the Python code to bytecode.
4. Execute Bytecode: The Python Virtual Machine interprets and runs the bytecode.
5. Machine Code: The bytecode gets converted to machine code by the operating system, ultimately executed on the CPU.
9. Interaction with the CPU
• The CPU executes the machine code instructions, which could include performing calculations, accessing data in memory, or interacting with I/O devices.
• For CPU to perform the actions, it depends on the instruction set architecture (ISA) (like x86, ARM, etc.) and operates with basic instructions that the processor understands (like addition, subtraction, memory access, conditional jumps, etc.).
• Memory: The CPU interacts with the system's memory (RAM) to retrieve variables, functions, and other data. The OS manages this process through system calls.
In Summary:
1. You write Python code in an editor.
2. When you run the code, the Python interpreter compiles the code to bytecode.
3. The bytecode is executed by the Python Virtual Machine (PVM), which translates the bytecode into machine code.
4. The OS and CPU manage the execution of these machine instructions.
5. If external libraries or C extensions are used, they are precompiled into machine code and called by the interpreter.
This whole process ensures that your high-level Python code eventually gets executed on the CPU in the form of low-level machine code, even though Python itself doesn't directly compile to machine code like C or C++.