Go vs Python for Backend: A Practical Comparison in 2024

Online Python Trainer for Beginners

Learn Python easily without overwhelming theory. Solve practical tasks with automatic checking, get hints in Russian, and write code directly in your browser — no installation required.

Start Course

Go vs Python: What to Choose for Backend in Practice?

In the world of backend development, two programming languages hold a special place: Python and Go (Golang). Python is known for its simplicity and vast number of libraries, while Go is known for its performance and built-in concurrency support. But which one should you choose for a real project? In this article, we will break down the practical aspects of comparing Go and Python, focusing on Go's strengths: speed, parallelism, and reliability.

1. Performance: Go is Faster Out of the Box

Python is an interpreted language, which makes it slower than the compiled Go. In backend development, where every millisecond counts, Go provides a tangible boost. Let's look at a simple HTTP server example.

Example in Go:

package main

import (    "fmt"    "net/http")

func handler(w http.ResponseWriter, r *http.Request) {    fmt.Fprintf(w, "Hello, backend in Go!")}

func main() {    http.HandleFunc("/", handler)    http.ListenAndServe(":8080", nil)}

This code compiles into a single binary file and runs instantly. In Python, similar tasks often use Flask or Django, which adds overhead.

Example in Python (Flask):

from flask import Flaskapp = Flask(__name__)

@app.route('/')def hello():    return "Hello, backend in Python!"

if __name__ == '__main__':    app.run(port=8080)

In practice, a Go server handles 10-20 times more requests per second with the same resources. For high-load projects (e.g., APIs for mobile applications), this is critical.

2. Concurrency: Goroutines vs Python Threads

One of Go's main advantages is lightweight goroutines. Unlike Python threads (limited by the GIL — Global Interpreter Lock), goroutines consume only a few kilobytes of memory and can be launched by the thousands.

Example of a concurrent handler in Go:

package main

import (    "fmt"    "net/http"    "time")

func slowHandler(w http.ResponseWriter, r *http.Request) {    // Simulating a long operation    time.Sleep(2 * time.Second)    fmt.Fprintf(w, "Data processed")}

func main() {    http.HandleFunc("/slow", slowHandler)    http.ListenAndServe(":8080", nil)}

Each request to /slow is automatically handled in a separate goroutine. In Python, you would have to use asyncio or multithreading, which is more complex and less efficient.

Why is this important for backend? Imagine a service that simultaneously processes 1000 requests to fetch data from a database. Go will handle this without performance loss, while Python will start to slow down due to the GIL.

3. Ease of Deployment and DevOps

Go compiles into a static binary that does not require an interpreter or dependencies to be installed. This makes deployment extremely simple:

One file — copy it to the server and run it.
Minimal Docker image — you can use scratch (empty image) with a size of 5-10 MB.
Cross-platform — compile for Linux, Windows, macOS with a single command.

Example Dockerfile for a Go application:

FROM golang:1.22 AS builderWORKDIR /appCOPY go.mod go.sum ./RUN go mod downloadCOPY . .RUN go build -o server .

FROM scratchCOPY --from=builder /app/server /EXPOSE 8080CMD ["/server"]

For a Python application, you will need an image with an interpreter (usually ~100-200 MB) and installation of all dependencies via pip. This increases deployment time and the risk of errors.