Author: A thoroughly awakened backend engineer

I first met it on a sultry afternoon in a college dorm.

That day, a roommate casually tossed me a copy of Python Crash Course and said, "Learn this, and you can write a web scraper in three days."
I opened the first page, saw that line of print("Hello, World!") as clean as poetry, and somewhere inside my heart, I quietly caved.

From that moment on, I knew I was in love.

For the first two years we were together, our life was extravagantly lavish.

I wrapped the entire data processing pipeline in Python—Pandas, NumPy, scikit-learn, FastAPI, Celery, SQLAlchemy... My requirements.txt alone spanned three pages, like dowries we prepared together, every single line a meticulously chosen token of commitment.

I still remember the tactile feel of writing code back then: smooth as flowing water, refreshing as a spring breeze.
A List Comprehension solved three layers of nested loops, and a @decorator gracefully hid away all cross-cutting logic.
In the quiet of deep, lost nights, it would whisper softly: "Dynamic typing. You don't need to declare anything; I understand what you mean."

Back then, I thought we would go on like this until the servers retired.

What remains most unforgettable to me was the early morning of a stress test.

When concurrency hit 3,000, it gently pushed me away.
Not because of a lack of love—because of the GIL.

In a tone I can never forget, it explained:

"I only have one lock. At any given moment, only a single thread can truly run globally. This is not my fault; it is my destiny."

I remained silent for a long time, reached for a profiling tool from my desk, and began to profile its bottlenecks piece by piece.
For two full hours, we sat like that in the dark workstation, looking at flame graphs line by line, as if giving each other a final medical checkup.

Just as I was about to give up, it suddenly raised its head and said in a tone both nonchalant yet heavy with consequence:

"If I'm ever gone, there will never be another language that lets you process a CSV in a single line of code while casually writing a poem."

I stared at those words, silent for a very, very long time.

However, as the scale of the system grew larger, it changed.

It began to demand more and more from me:

• I wanted async—so I gave it asyncio, but it nested async with await and turned my call stack into a plate of spaghetti;
• I wanted type safety—so I gave it mypy, but its error messages were like riddles, forcing me to guess every time CI failed;
• I wanted high concurrency—so together we introduced Gunicorn, uWSGI, Gevent, multi-process workers... The overhead of inter-process communication alone pointlessly drained 5,000 RMB from my extra monthly cloud bill;
• I wanted lightweight deployment—it handed me a Docker container with an 800MB base image, carrying all of its past inside.

I stared at the Grafana monitoring dashboard, watching the P99 latency hang high at 800ms, and something inside my heart began to shatter, piece by piece.

It was a Thursday late at night when the boss forwarded the performance report of a competing service in the group chat: API P99 latency at 12ms, memory consumption less than a tenth of ours.

I sat alone at my workstation, facing the dual-monitor setup, my heart aching with anguish.

I opened Claude.

I fed it everything all at once: our technical debt from the past three years, the memory profile of the Python service, the GC pause logs, and that competitor's performance report, and then I typed out these words:

"I've been with Python for three years. Do you think I should keep investing?"

Five seconds later, Claude delivered its calm and brutal analysis—

Claude's Analysis Report (Excerpt):

• Python's GIL forms a hard bottleneck in CPU-bound scenarios, which cannot be fundamentally eliminated through engineering means;

• Thread-switching overhead in the current concurrent architecture accounts for approximately 23% of total CPU time;

• Memory usage efficiency is about 4-6 times lower than an equivalent Go implementation;

• Considering comprehensive maintenance costs, the performance ceiling, and team migration costs, the recommendation is: Migrate core pipelines to Go to stop the bleed of current architectural premiums.

I stared at the words on the screen and slowly closed my eyes.

Outside the window, the late autumn night breeze of Beijing blew in through the half-open glass door of the cubicle.

The next day, I opened JIRA and created a new ticket:

Title: [P0] Core Service Migration Python → Go
Priority: Highest
Estimated Timeline: 12 weeks
Assignee: Myself
Remarks: Let Benchmarks and Code Reviews judge everything.

The first line of Go code looked like this:

package main

import "fmt"

func main() {
    fmt.Println("Hello, new life.")
}

That was the moment I realized—Go has no GIL, no implicit type conversions, no runtime surprises, and no gentle magic.

It just stands quietly there, compiling, running, exit code 0.

As calm as someone who would never message you at two in the morning.

Twelve weeks later, the new service went live.

P99 Latency: Dropped from 800ms to 18ms.
Memory Footprint: Dropped from 12GB to 1.8GB.
Docker Image: Dropped from 800MB to 23MB (a single static binary).
Cloud Bill: Saved about 40,000 RMB per month.

I stood in front of the new Grafana dashboard, looking at that latency curve as smooth and pretty as a calm lake, feeling unsure whether it was relief or some nameless weight in my heart.

I thought of that saying:
"If I'm ever gone, there will never be another language that lets you process a CSV in a single line of code while casually writing a poem."

It was right.

Go doesn't write poems. Go just routes traffic, handles requests, closes channels, and exits.

But sometimes, what you need isn't someone who can write poetry, but someone who can hold their ground against a 3 AM traffic peak in production.

I heard that Python later learned asyncio, went GIL-free (Python 3.13's experimental proposal), and even got a Cython certification.

I'm happy for it.

But I know that's already someone else's story.

As for me and Claude—

It analyzed Python for me and told me to leave; yet it was reportedly trained using Python itself.

Some debts of gratitude in this world can never be fully repaid.

Disclaimer: The architectural migration process in this article is purely fictional. Any resemblance to real events is purely coincidental, except for the fact that you've probably lived through them too.

This article is a poor imitation of Brother Sun's writing style for clout.

This article was co-created with Claude (Anthropic). As for conflicts of interest, they have been referred to the ethics committee for review.