Disadvantages of Interpretation
Interpreted languages like Python offer numerous disadvantages:
- Slower Execution : Interpreted languages like Python typically run slower compared to compiled languages because the interpreter translates the source code into intermediate code during runtime. This overhead can result in slower execution speeds, especially for performance-critical applications.
- Dependency on Interpreter : Python code requires the presence of the Python interpreter to run, which adds an extra layer of dependency. Users need to have the appropriate version of the interpreter installed on their systems to execute Python programs.
- Difficulty in Hiding Source Code : Since Python code is distributed as source files, it can be easier for others to access and view the source code. While tools like obfuscation can be used to make the code less readable, it’s inherently more difficult to protect Python code compared to compiled languages.
Why Python is Called Interpreted Language
Python is frequently categorized as an interpreted language, but What does that suggest exactly? To apprehend why Python is called an interpreted language, it’s essential to discover the concepts of interpretation and compilation, in addition to the execution model of Python code.
Python is called an interpreted language because it executes code logic directly, line by line, without the need for a separate compilation step. In methods to compiled languages like C or C++, where the source code is translated into machine code before execution, Python code is translated into intermediate code by the Python interpreter.
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