Python Source Code Analysis

This column takes you deep into the source code of Python 3, revealing the principles of the Python virtual machine and the ingenious design!

I have been a Python developer for many years. I started studying the Python source code as early as the Python 2 era, when I read Chen Ru’s Python Source Code Analysis book, which is a great resource for understanding the internal design of Python.

However, Python has entered the 3 era, and many internal designs have changed. For example, dict and str objects are no longer the same as in the Python 2 era.

Since there is no dedicated source code analysis material for Python 3, I decided to study the source code of Python 3 again, and write it down as a column. This is the origin of this column, a kind of fate, indescribable.

The column takes Python 3.7.4 as the research object and explains it in the following sections:

1. Introduction . Discuss the important significance of source code learning on improving development capabilities, and introduce the growth journey of Python engineers through the experience of me, a total newbie.

2. Object Model . Introduce the theoretical system of Python object-oriented programming, clarify the representation of “Class” and “Object” in Python. Analyze the memory layout of objects through source code, study the lifecycle of objects, and uncover the mystery of objects.

3. Built-in Objects . Cover the implementation details of built-in objects such as float , int , bytes , str , list , dict , etc. Focus on the data structure and algorithmic ideas behind each object, and combine engineering practices to explain the amazing usage these of built-in objects.

4. Virtual Machine . First introduce the execution process of Python programs and the structure of bytecode; then introduce the running mechanism of the Python virtual machine , and the name space and other runtime contexts; finally, explain the impact of the GIL global lock on the virtual machine and explore countermeasures.

5. Function Mechanism . Explore each step from code to function object, and simulate this process with Python code. Focus on the nested functions , closures , and decorators , which are frequently asked in interviews, and combine engineering practices to introduce the advanced usage of functional programming and decorators.

6. Class Mechanism . Explore all steps from code to class object to create instance objects, and simulate this process with Python code. Focus on the inheritance mechanism , attribute lookup , and magic methods , which are frequently asked in interviews, and combine engineering practices to introduce the advanced usage of magic methods and metaclasses.

7. Generator and Coroutine . Discuss the advanced usage of generators, and explain its running principles with bytecode. Based on generators, design a coroutine library, deepen the understanding of the coroutine running mechanism. Combine engineering practices to introduce the techniques of building high-concurrency applications with asyncio.

8. Memory Management Mechanism . Combine the features of Python to comprehensively explain the key technologies of memory pool , reference counting , mark-and-sweep , generation collection , etc. Combine theory with practice, and use a real case to introduce the methodological approach to figure out and solve memory leak problems.

9. Summary . Review the content of the column, pursue code design techniques with a Python style based on understanding the Python source code.

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