🟡 Advanced Python · Lesson 28

API Requests in Python

In this lesson: Call REST APIs in Python with the requests library — GET, POST, JSON, headers and error handling — with output. In Hindi & English.

What is an API?

An API (Application Programming Interface) lets one program ask another program for data or actions over the internet. A weather app asks a weather API for today’s temperature; a shop app asks the server for products and sends orders back. Most web APIs speak HTTP and reply with JSON.

HTTP method	Meaning	Example
GET	Read data	List of products
POST	Create something	Place an order
PUT / PATCH	Update	Change address
DELETE	Remove	Cancel order

In this lesson we use the free CodingEasily practice API for a sweet shop: https://codingeasily.in/api/sweets/. It is real, needs no key and never stores your data, so you can experiment freely.

Terminal – install once (inside your venv)

pip install requests

Your first GET request

Python – get_products.py

import requests

URL = "https://codingeasily.in/api/sweets/"

response = requests.get(URL, timeout=10)
print("status :", response.status_code)
print("type   :", response.headers["Content-Type"])

products = response.json()           # JSON text → Python list of dicts
print("items  :", len(products))
for p in products[:3]:
    print(f"{p['id']}. {p['name']:<14} ₹{p['price']}/{p['unit']}  stock {p['stock']}")

status : 200 type : application/json; charset=utf-8 items : 8 1. Kaju Katli ₹900/kg stock 25 2. Malai Ghewar ₹650/kg stock 8 3. Rasmalai ₹700/kg stock 12

status_code 200 means OK.
.json() converts the reply into Python lists and dicts.
Always pass timeout=; without it a dead server can freeze your program forever.

Query parameters

Do not build URLs by joining strings. Pass a dictionary to params and requests encodes it correctly (spaces, Hindi, &).

Python – params.py

import requests

URL = "https://codingeasily.in/api/sweets/"

r = requests.get(URL, params={"category": "box"}, timeout=10)
print(r.url)
print([p["name"] for p in r.json()])

r = requests.get(URL, params={"q": "kaju"}, timeout=10)
print([p["name"] for p in r.json()])

https://codingeasily.in/api/sweets/?category=box ['Classic Gift Box', 'Assorted Gift Box'] ['Kaju Katli']

Status codes and errors

Code	Meaning	What your program should do
200 / 201	OK / Created	Use the data
400 / 422	Your request is wrong	Show the server’s message to the user
401 / 403	Not logged in / not allowed	Ask for login or a valid API key
404	Not found	Show “not found”
429	Too many requests	Wait and retry
500–599	Server problem	Retry later; log the error

Python – errors.py

import requests

URL = "https://codingeasily.in/api/sweets/"

def get_product(product_id):
    try:
        r = requests.get(URL, params={"id": product_id}, timeout=5)
        r.raise_for_status()                 # turns 4xx/5xx into an exception
        return r.json()
    except requests.exceptions.HTTPError:
        return f"HTTP {r.status_code}: {r.json().get('error')}"
    except requests.exceptions.Timeout:
        return "Server is too slow, try again"
    except requests.exceptions.ConnectionError:
        return "No internet connection"

print(get_product(2)["name"])
print(get_product(99))

Malai Ghewar HTTP 404: Product not found

⚠️ requests does not raise on 404 by itself

A 404 or 500 response is still a “successful” call. Call raise_for_status() or check r.ok before using the data.

Timeouts in practice

The practice API can simulate a slow server with ?delay= (milliseconds). Here the server needs 2 seconds but we wait only 1:

Python – timeout.py

import requests

URL = "https://codingeasily.in/api/sweets/"

try:
    requests.get(URL, params={"delay": 2000}, timeout=1)
except requests.exceptions.Timeout:
    print("Timed out after 1 second – show a friendly message instead of freezing")

r = requests.get(URL, params={"delay": 500}, timeout=5)
print("with a longer timeout:", r.status_code)

Timed out after 1 second – show a friendly message instead of freezing with a longer timeout: 200

POST: sending JSON (placing an order)

Python – post_order.py

import requests

URL = "https://codingeasily.in/api/sweets/"

order = {
    "name": "Aarti Gupta",
    "phone": "9829012345",
    "items": [{"id": 1, "qty": 0.5}, {"id": 7, "qty": 2}],
    "coupon": "SWEET10",
    "mode": "pickup",
}
r = requests.post(URL, json=order, timeout=10)     # json= sets the header and encodes for you
print(r.status_code)
data = r.json()
for item in data["items"]:
    print(f"  {item['name']:<17} x{item['qty']:<4} ₹{item['amount']}")
print("subtotal", data["subtotal"], "| discount", data["discount"], "| delivery", data["delivery"], "| total", data["total"])

bad = requests.post(URL, json={"name": "A", "phone": "12345", "items": []}, timeout=10)
print(bad.status_code, bad.json()["fields"])

201 Kaju Katli x0.5 ₹450 Classic Gift Box x2 ₹960 subtotal 1410 | discount 141 | delivery 0 | total 1269 422 {'name': 'Name must have at least 2 letters.', 'phone': 'Enter a valid 10-digit Indian mobile number.', 'items': 'Cart is empty.'}

The server validates everything and calculates the prices itself – the client only sends ids and quantities. That is how real e-commerce APIs protect against fake prices.

Headers, API keys and sessions

Python – session_headers.py

import os
import requests

session = requests.Session()                       # reuses the connection → faster
session.headers.update({
    "User-Agent": "school-report/1.0 (contact@example.com)",
    "Authorization": f"Bearer {os.environ.get('MY_API_KEY', 'demo-key')}",
})
r = session.get("https://codingeasily.in/api/sweets/", params={"id": 3}, timeout=10)
print(r.status_code, r.json()["name"])
print("sent header:", r.request.headers["User-Agent"])

200 Rasmalai sent header: school-report/1.0 (contact@example.com)

🔐 Never write API keys in code

Keep keys in environment variables or a .env file that is not committed to Git. A key pushed to GitHub is found by bots within minutes.

Automatic retries for unreliable servers

Python – retries.py

import requests
from requests.adapters import HTTPAdapter
from urllib3.util.retry import Retry

retry = Retry(total=3, backoff_factor=0.5, status_forcelist=[429, 500, 502, 503, 504])
session = requests.Session()
session.mount("https://", HTTPAdapter(max_retries=retry))
session.mount("http://", HTTPAdapter(max_retries=retry))

try:
    session.get("https://codingeasily.in/api/sweets/", params={"fail": 1}, timeout=5)
except requests.exceptions.RetryError:
    print("Gave up after 3 retries – the server keeps returning 500")

Gave up after 3 retries – the server keeps returning 500

?fail=1 makes the practice API return HTTP 500. The session retries 3 times with growing waits (0.5 s, 1 s, 2 s) before giving up.

Mini project: low-stock report

Python – low_stock_report.py

import csv
import requests

URL = "https://codingeasily.in/api/sweets/"

products = requests.get(URL, timeout=10).json()
low = sorted((p for p in products if p["stock"] < 15), key=lambda p: p["stock"])

with open("reorder.csv", "w", newline="", encoding="utf-8-sig") as f:
    w = csv.writer(f)
    w.writerow(["Product", "Stock", "Status"])
    for p in low:
        w.writerow([p["name"], p["stock"], "OUT OF STOCK" if p["stock"] == 0 else "Reorder"])

print(open("reorder.csv", encoding="utf-8-sig").read())

Product,Stock,Status Kalakand,0,OUT OF STOCK Malai Ghewar,8,Reorder Rasmalai,12,Reorder

Common mistakes

Mistake	Fix
No timeout	Always `timeout=10` (or a tuple `(3, 10)`)
Using data without checking status	`r.raise_for_status()` or `if r.ok:`
`data=` instead of `json=` for JSON APIs	Use `json=payload`
Building URLs with + and f-strings	Use `params={...}`
API key in code / GitHub	Environment variable or .env (git-ignored)
Calling an API in a tight loop	Respect rate limits; use sleep, caching or batch endpoints

Practice tasks

Print all milk sweets (?category=milk) sorted by rating.
Ask the user for a product id with input() and print its details or “not found”.
Place a delivery order without a coupon and print the delivery charge returned by the server.
Try a coupon on an order below ₹500 and print the server’s error message for the coupon field.

Summary

requests.get(url, params=…, timeout=…) reads; requests.post(url, json=…) sends JSON.
r.json() gives Python data; check r.status_code / raise_for_status().
Handle Timeout and ConnectionError; add retries for flaky servers.
Sessions reuse connections and headers; keep API keys out of code.

Frequently Asked Questions

Is requests built into Python?

No. Install it with pip install requests. The built-in alternative is urllib.request, which works but needs more code. requests is the most popular HTTP library for Python.

Why do I get an SSL error?

Usually the computer’s date/time is wrong, an office proxy intercepts HTTPS, or certificates are outdated. Fix the clock or update certifi with pip install --upgrade certifi. Do not use verify=False in real projects.

requests or httpx?

requests is simple and stable for normal scripts. httpx has a very similar API and also supports async and HTTP/2, which helps when you make many requests at the same time.

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