How does python interpreter works?
Python is an interpreted language.The interpreter takes source code of
the program line by line , check each line for the syntax error and then
executes it. But Python interpreter does not work as the interpreters of
other languages do.
There are some nuisances in python interpreter internal working.
Please note that there are several implemnetation of python
interpreter . However this article describes the cpython implementation.
At first, Python interpreter takes your source code, and it compiles the
whole source code into the bytecode. Python interpreter acts as a
compiler at this phase. During this phase, source code is analysed for
lexical and syntactical analysis . Bytecode, then goes into the execution
phase where the bytecode is converted into the machine code.
Why bytecode ? What is it? Why two phases for python interpreter?
Bytecode is the intermediate form of conversion of source code into the
lower-level code that is platform-independent. This bytcode is
understood by what is known as Python Virtual machine(PVM). This is
the PVM that takes this bytecode and converts each bytecode
instructions sequentially into the machine code for execution.
This structure of python interpreter makes python , a portable language
as the bytecode are platform independent that can be ported into any
machine that has a compatible PVM. This makes Python a portable
language so that your source code can run on different platforms.
If your source code has imported modules, then the bytecode of these
modules gets saved as a .pyc file
under __pycache__ directory. __pycache__ directory resides in the
same directory as the .py file. Next time when the same script is run, it
checks the timestamp of the .pyc file against the source code. If no
change is made in the source code since its last compilation, it fetches
the stored bytecode and does not recreate it — thus providing the faster
performance.
how does __pycache__ directory looks if ls command is issued on it.
Please note that no bytecode is saved for lines other than
import statement.
Concluding, python interpreter boosts performace speed of the
execution of the code having many imported modules as it avoids
repeated compilation.
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