One of the most widely used programming languages nowadays is Python, which is generally suggested for being easy to learn, adaptable, and simple. Especially in the field of Data Science, Python is a must-know programming language to excel in the domain. Because of its easy coding and readability, it is used to build ML models in an easy way. However, the upcoming learners are mostly confused by the frequently asked question like “Is Python code compiled or interpreted?”. The solution to this problem is not as simple as you may think, because producing effective and efficient code requires a grasp of how Python execution works. This blog post will unbox the real story of how Python executes your code, the functions of the Python interpreter and compiler, and what actually occurs when you hit the run button.
Question in our Brain: Is Python Compiled or Interpreted?
The short answer to the above question is that Python is both compiled and interpreted.
When you build a Python program, it is first compiled into bytecode, which the Python Virtual Machine (PVM) interprets. The advantages of compilation and interpretation are combined in this hybrid execution architecture.
Let’s examine it in detail.
Understanding the difference between Compiled and Interpreted Languages
Before we get to know about the specifics of Python, it is vital to figure out what “compiled” and “interpreted” languages are in programming.
Compiled Languages: Compiled languages like C or C++ use a compiler that converts the source code into machine code before the program runs. This machine code is customized for specific hardware, allowing the program to execute on its own from the original source code or the compiler.
Interpreted Languages: In this, early versions of BASIC or JavaScript are processed line-by-line by an interpreter. The interpreter reads the source code and executes the instructions directly, which results in slower performance.
How Python Executes Code: Compilation and Interpretation
- Parsing the Source Code
The Python interpreter reads and breaks down the source code of a Python script (a.py file) before transforming it into an internal data structure called an Abstract Syntax Tree (AST) and examining it for syntax mistakes.
- Bytecode Compilation
The AST is then converted into bytecode, a lower-level, platform-neutral representation of the code, by Python. This bytecode is a collection of instructions for the Python Virtual Machine (PVM), not machine code. Evidence of this step is frequently visible in the __pycache__ directory, where .pyc files are stored.
- Bytecode Interpretation
Ultimately, the bytecode is interpreted and run instruction by instruction by the Python Virtual Machine. The PVM reads the bytecode, executes the operations, and controls memory, exceptions, and other runtime duties. This is where Python’s interpreted nature really shines.
Why Is This Hybrid Method Used in Python?
The execution model of Python has the following benefits:
- Dynamic Typing
You don’t have to declare data types ahead of time. This speeds up development but requires careful coding practices.
- Platform Independence:
Python applications can run on any operating system with a suitable interpreter thanks to Bytecode’s platform independence.
- Ease of Development:
Developers can write and run code without a separate compilation step, enabling rapid prototyping and interactive development.
- Extensive Standard Library
Python has a comprehensive library that handles everything from file management to web development, minimizing the need for extra libraries for many common tasks.
- Object-Oriented and Functional Programming
There is support for both object-oriented programming and functional programming paradigms, giving developers flexibility in how they structure their code.
Compilers vs. Interpreters: A Quick Comparison
| Feature | Compiled Languages | Interpreted Languages | Python’s Approach |
| Translation | The whole program at once | Line by line | Source to bytecode, then line-by-line execution |
| Output | Machine code | No intermediate output | Bytecode (.pyc files) |
| Speed | Fast execution | Slower execution | Moderate (can be optimized) |
| Platform Dependency | Platform-dependent | Platform-independent | Platform-independent bytecode |
| Error Reporting | All errors at once | Errors per line | Syntax errors at compile, runtime errors during execution |
Common Misconceptions
- “Python is only interpreted.”
[ Not quite. Python always compiles code to bytecode before interpreting it.]
- “Python code runs directly on the CPU.”
[ No. Bytecode is executed by the Python Virtual Machine, not directly by the hardware. ]
- “Compiled code means no need for the interpreter.”
[ With Python, you still need the interpreter (PVM) to execute the bytecode]
Conclusion: The Real Story of How Python Works
So, is Python interpreted or compiled? In real terms, Python is both. After converting the source code to bytecode, it uses the Python Virtual Machine to interpret the bytecode. Python’s versatility, portability, and user-friendliness stem from its hybrid execution theory, which makes it a popular choice for both beginners and experts.
Developers may write more effective code, debug more successfully, and appreciate Python’s strength and clarity by discovering this execution mechanism. Understanding the reality of Python execution enables you to fully utilize this amazing language, regardless of your level of programming experience.
