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Why Python is Interpreted Language?

Updated on 21/01/20258,441 Views

An interpreted language is one where the code is executed line-by-line by an interpreter, while a compiled language is transformed into machine code that the computer can directly execute. The question of whether python is interpreted language or compiled often comes up among learners.

This distinction matters because it affects how Python programs are executed, their performance, and their overall efficiency.

In this guide, you’ll look at why Python is not compiled language and how that impacts its flexibility and ease of use.

By the end, you’ll have a clearer understanding of Python's execution model. Let’s dive in!

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What Does It Mean for a Language to Be Interpreted or Compiled?

When discussing programming languages, one of the key distinctions is whether they are compiled or interpreted. Let’s look at them in detail:

Compilation

In compiled languages, the source code is converted into machine code before execution. This process happens once, and the output is a standalone executable file.

This file can then be run directly on any machine that is compatible with the machine code generated, which generally leads to faster execution.

Advantages of Compilation:

  • Faster Execution: There’s no need for the interpreter to translate the code line-by-line during execution.
  • Platform-Specific: Once compiled, the executable can run directly on a system without needing the original source code or an interpreter.

Interpretation

In interpreted languages, the source code is translated and executed line-by-line by an interpreter. Rather than creating a standalone executable, the interpreter reads the source code and performs operations directly from the code, meaning that the code is interpreted in real-time during execution.

Advantages of Interpretation:

  • Portability: The same code can run on any system that has the interpreter installed, regardless of the underlying platform.
  • Flexibility: Changes can be made to the code without needing a recompile.

Also Read: Compiler vs Interpreter: Difference Between Compiler and Interpreter

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Python's Hybrid Nature: Interpreted and Compiled

Although Python is interpreted language or compiled, it actually features a hybrid approach, blending both compilation and interpretation processes to execute code efficiently.

  • Python first compiles the source code into bytecode, which is a lower-level, platform-independent representation of your code. This bytecode is stored in .pyc files.
  • Bytecode is not machine code, but it’s an intermediate representation that can be efficiently interpreted by the Python Virtual Machine (PVM).

This process of compiling the source code into bytecode happens automatically when you run a Python program.

The bytecode is saved in .pyc files within the __pycache__ directory. This means that Python doesn’t have to compile the source code every time it runs the program, improving performance on subsequent runs.

Here’s a simple example to illustrate how Python compiles the code into bytecode:

# example.py
def greet(name):
    return f"Hello, {name}!"
greeting = greet("Alice")
print(greeting)

Explanation:

  • When you run example.py using the command python example.py, Python will first compile the source code into bytecode.
  • The compiled bytecode is stored in a .pyc file, which is placed in the __pycache__ directory.
  • You can check the __pycache__ folder in your project directory after running the code, and you'll see a file named something like example.cpython-39.pyc, where 39 represents the version of Python you’re using.

Python Execution Flow:

  • Compilation Step: Python reads your .py file, compiles it into bytecode, and stores it in a .pyc file (if it doesn’t already exist).
  • Interpretation Step: The bytecode is interpreted by the Python Virtual Machine (PVM), which executes the instructions.

Also Read: High-Level Programming Languages: Key Concepts Explained

Role of Python Virtual Machine (PVM)

After the source code is compiled into bytecode, the PVM interprets it at runtime and executes the bytecode instructions step-by-step.

Since Python is compiled into bytecode before execution, this helps optimize performance by not requiring re-compilation every time the code runs.

However, since Python is interpreted language or compiled, it still relies on the Python Virtual Machine (PVM) to interpret the bytecode, making Python primarily an interpreted language.

Let’s see how Python creates a .pyc file:

# example.py
def multiply(x, y):
    return x * y
result = multiply(10, 5)
print(result)

Output:

50

After running the above code (python example.py), check your project folder for the __pycache__ directory. Inside, you should see a file like example.cpython-39.pyc.

  • This .pyc file contains the bytecode representation of the example.py script.
  • On subsequent runs, Python will use this bytecode for faster execution instead of recompiling the source code.

After running the code, the output shows 50 as expected since the function multiply(10, 5) returns the product of 10 and 5. Python also creates the .pyc file to improve performance on the next run.

By understanding Python’s hybrid approach, you can better grasp how Python handles code execution and why it's both fast and portable.

FAQs

1: Why Python is interpreted language or compiled?

A: Python is called an interpreted language because it reads and executes code line-by-line using the Python interpreter, rather than compiling the entire code into machine code before execution.

2: Why Python is not compiled language?

A: Python is not a compiled language because it doesn't convert source code into machine code ahead of time. Instead, Python code is compiled to bytecode and then interpreted at runtime by the Python Virtual Machine (PVM).

3: Does Python compile the code before interpreting it?

A: Yes, Python first compiles the source code into bytecode, and then the bytecode is interpreted by the Python Virtual Machine (PVM) at runtime, making Python a hybrid language.

4: What is bytecode in Python?

A: Bytecode is an intermediate, platform-independent representation of Python code. Python compiles the source code into bytecode, which is then interpreted by the Python Virtual Machine (PVM).

5: What are the benefits of Python not being a compiled language?

A: Some benefits include better portability (as the bytecode can be interpreted on any machine with a Python interpreter), flexibility for rapid development, and easier debugging, which is why Python is not compiled language but rather interpreted at runtime.

6: Can Python be considered both interpreted and compiled?

A: Yes, Python can be considered both interpreted and compiled. While it is interpreted at runtime, the code is first compiled into bytecode. This dual process is one of the reasons why Python is not compiled language in the traditional sense.

7: How does the Python Virtual Machine (PVM) work?

A: The PVM is responsible for executing Python bytecode. After Python compiles the source code into bytecode, the PVM reads and executes the bytecode instructions line-by-line at runtime.

8: Is Python slower than compiled languages?

A: Yes, Python is generally slower than fully compiled languages because the interpreter executes the bytecode line-by-line rather than running machine code directly.

9: Does Python need an interpreter on every machine to run?

A: Yes, Python requires an interpreter on every machine where the code is run. This is one of the reasons Python is so portable—any system with the Python interpreter can run Python code.

10: How can I improve Python performance despite being interpreted?

A: You can improve Python performance by using tools like Cython, PyPy, or optimizing your code for faster execution. Additionally, using efficient libraries can significantly speed up your Python programs.

11: Can I distribute Python programs like compiled languages?

A: Yes, you can package Python code into executables using tools like PyInstaller or cx_Freeze, but it still requires an interpreter for execution. However, these tools bundle the interpreter along with the code for easier distribution.

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