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Imagine scrolling through endless search results or retrieving an unmanageable amount of data with a single API call. Chaos, right? That’s where API Pagination becomes your unsung hero.
Let’s simplify this essential concept and discover the best pagination methods for your needs.
1. Time-based Pagination
Best for real-time data updates.
Orders results using timestamps (e.g., `updated_at`).
Perfect for tracking changes over time.
🔑 Use case: Activity feeds or logs.
2. Hybrid Pagination
Combines two methods (e.g., time-based + cursor-based).
Offers balance: real-time accuracy + efficient navigation.
🔑 Use case: Applications needing flexible, robust data retrieval.
3. Keyset-based Pagination
Uses a unique identifier (like id) to fetch data efficiently.
Faster than offsets for large datasets.
🔑 Use case: Large databases with frequent updates.
4. Page-based Pagination
Breaks data into numbered pages (`?page=2`).
Simple and widely used.
🔑 Use case: User-facing applications (e.g., e-commerce).
5. Cursor-based Pagination
Relies on pointers (e.g., `next_cursor`).
Ensures accuracy but can be tricky to implement.
🔑 Use case: Social media feeds or endless scrolling.
6. Offset-based Pagination
Uses offsets to skip records (`?offset=100`).
Easy to set up but slower for large datasets.
🔑 Use case: Small-scale apps or datasets with stable records.
You Should Know:
Linux & API Pagination Commands
– `curl` with Pagination:
curl -X GET "https://api.example.com/data?page=2&limit=10" -H "Authorization: Bearer TOKEN"
– Using `jq` to Process Paginated JSON:
curl -s "https://api.example.com/data" | jq '.results[] | {id, name}'
– Automating Pagination with `while` Loop (Bash):
next_page=1 while [ $next_page -ne 0 ]; do response=$(curl -s "https://api.example.com/data?page=$next_page") echo "$response" | jq '.data[]' next_page=$(echo "$response" | jq -r '.next_page // 0') done
Database Pagination (SQL)
- MySQL:
SELECT FROM users ORDER BY id LIMIT 10 OFFSET 20;
- PostgreSQL:
SELECT FROM logs ORDER BY created_at DESC LIMIT 50;
- MongoDB (Cursor-based):
db.collection.find().sort({ _id: 1 }).limit(10).skip(10);
Python (Requests + Pagination Handling)
import requests
url = "https://api.example.com/data"
params = {"page": 1, "limit": 50}
while True:
response = requests.get(url, params=params).json()
for item in response["results"]:
print(item["id"])
if not response.get("next_page"):
break
params["page"] = response["next_page"]
What Undercode Say:
API pagination is crucial for performance and user experience. Time-based and cursor-based methods excel in real-time apps, while offset-based is simple but inefficient at scale. Always test pagination under heavy loads—keyset pagination often outperforms offsets in large datasets.
For Linux sysadmins, automate pagination with curl + jq. Developers should optimize SQL queries with `LIMIT-OFFSET` or keyset techniques. Pythonistas can streamline API calls with loops and dynamic params.
🔗 Further Reading:
Expected Output:
A structured API response with pagination metadata:
{
"data": [...],
"next_page": 2,
"total_records": 1000,
"limit": 50
}
References:
Reported By: Ashsau Api – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
