Arpit's Newsletter read by 38000+ engineers
Weekly essays on real-world system design, distributed systems, or a deep dive into some super-clever algorithm.
Open-source projects are a treasure trove of knowledge and a great opportunity for engineers to enhance their skills. However, delving into a complex codebase can be overwhelming, especially when trying to find the starting point. In this article, I will guide you through the process I follow to navigate massive open-source code bases and locate the initial entry point. To demonstrate the methodology, I will use CPython as a reference, which is the C implementation of Python.
To begin, clone the CPython repository, which contains the entire source code of Python. Though it may take some time due to the size of the code base, the effort is worthwhile. In the repository’s readme file, you will typically find setup instructions. For CPython, the necessary commands to set up the project locally are ./configure
and make
. These two commands are common across most C-based open source projects.
Once you have the code base set up locally, you can build the Python executable by running the make
command. The resulting python
binary is specific to the version and source code you have. By executing ./python
, you can verify the version and see that it matches the one mentioned in the readme file.
When working with a large code base, understanding where the execution begins is crucial. Since CPython is implemented in C, we know that it should have a main
function, as execution typically starts there. To locate the main
function, a common approach is to use a text search within the repository.
By searching for main
in a case-sensitive manner, and filtering for files where main
is followed by an opening brace, we can narrow down the results. Scrolling through the list of files, we can identify the most relevant ones. In the case of CPython, the main.c
file under the Modules
folder seems promising.
Examining the main.c
file, we discover the presence of Py_Main
and Py_BytesMain
functions, which serve as entry points for both Windows and UNIX platforms. Clicking on Py_Main
, we find the exact location where the main
function is defined. Understanding the conditional compilation, we see that Py_Main
is invoked for Windows, while Py_BytesMain
is used for UNIX.
To make our first change, let’s add a printf
statement to the main
function, indicating that this is our version of CPython. We add the statement in the main.c
file, right after the function’s opening brace. Alternatively, we could have added it in the python.c
file where the main
function is defined.
After making the modification, we can compile and build the binary by running the make
command again. This process takes a few seconds and generates the updated python
executable. Running ./python
now reveals that our custom printf
statement appears as the first output, confirming the successful incorporation of our changes.
Navigating and understanding a massive open-source code base may seem daunting at first. However, with time and familiarity, it becomes an achievable task. By gradually exploring the code, locating the entry point, and making small modifications, you can gain confidence and deepen your understanding of the project.
Now that you have successfully grasped the process of navigating a large code base like CPython, you can use this knowledge to explore other open-source projects. Remember, it takes time and persistence to become comfortable with complex code bases. Embrace the opportunity to learn from and
Here's the video ⤵
Super practical courses, with a no-nonsense approach, are designed to spark engineering curiosity and help you ace your career.
An in-depth, self-paced, and on-demand course that for early engineers to become great at designing scalable, available, and extensible systems at scale.
A masterclass that helps experienced engineers become great at designing scalable, fault-tolerant, and highly available systems.
A course that helps covers Redis internals by reimplementing its core features like - event loop, serialization protocol, pipelining, eviction, and transactions.
Arpit's Newsletter read by 38000+ engineers
Weekly essays on real-world system design, distributed systems, or a deep dive into some super-clever algorithm.