Scrapingbee Pagination for CSV Exports and APIs

Data is the key to success. When you have the right tools with the correct guide, it becomes much easier to collect the data and use it at the right time and right place. Be more efficient and productive with the ScrapingBee pagination for CSV export and APIs. This simply helps you gather information from every page and export it to a CSV file with minimal effort and achieve appreciable results.

It is important to get on with the rules and to learn how to send the first data collecting request, find the signal for the next page, and continue till the last page. The steps are simple, easy to follow, and repeatable for other APIs with just a few changes.

Table of Contents

What “Pagination” Means in Practice

The Game Plan That Works Everywhere

Data Shaping: From JSON To Stable Columns

Python Walkthrough

JavaScript Walkthrough

Reading Pagination Signals

Handling Rate Limits and Errors

Building One Clean CSV

When The API Uses Tokens

When The API Uses Cursors

CSV Performance Tips

Security, Compliance, and Responsible Use

Troubleshooting Guide

Quick Checklist

Scrapingbee Pagination for CSV Exports and APIs

Conclusion

What “Pagination” Means in Practice

APIs split large lists into small parts so each request stays quick and stable. You will see three common styles:

Page numbers such as page=2, page=3.
Offset and limit, for example, offset=100, limit=50.
A cursor or a token, such as next_cursor.

Scrapingbee helps you call these endpoints in a steady way. Your task is simple. Read the response, find the next page hint, and continue until it ends. For quick browser trials, you can also review ScrapingBee extension alternatives that handle small page tasks.

To keep the work useful, aim for one final file. It should hold all rows from all pages. The phrase export paginated API to CSV states this goal clearly.

The Game Plan That Works Everywhere

A reliable plan uses six small steps:

Create the CSV and write the headers.
Send the first request with your base query and page fields.
Extract the records and write the rows.
Find the next page value and set up the next call.
Respect limits and retry on transient errors.
Stop when there is no next page.

For broader patterns and trade-offs, see pagination guidance for list APIs that explains page numbers, offsets, and cursors.

If the API returns a token, keep it safe and pass it forward. The phrase Scrapingbee pagination next-page token names this handoff. If the API uses a cursor, treat it like a bookmark for your next call. That is the idea in cursor-based pagination with Scrapingbee.

Data Shaping: From JSON To Stable Columns

Most APIs return nested JSON. A CSV needs flat columns. Build a small mapper that picks fields in a fixed order. When a field is missing, write an empty value or a default. This keeps your CSV stable and friendly to spreadsheets and BI tools.

Here is a helpful habit. Write rows as you go. Do not keep all pages in memory. The approach of appending rows to CSV during scraping is fast and safe for big jobs. For stable access and region control, you can route calls through the ScrapingBee premium proxy when a site is strict.

Python Walkthrough

Below is a small Python flow you can reuse. It shows a cursor loop, gentle backoff, and streaming writes.

import csv, time, requests

API_URL = "https://app.scrapingbee.com/api/v1/"
API_KEY = "YOUR_SCRAPINGBEE_KEY"

def fetch_page(params):
    # Scrapingbee proxying a JSON API endpoint
    r = requests.get(
        API_URL,
        params={
            "api_key": API_KEY,
            "url": "https://example.com/api/items",
            "params": params,              # forward query params to target API
            "render_js": "false",
            "country_code": "us"
        },
        timeout=60
    )
    r.raise_for_status()
    return r.json()

def normalize(item):
    return {
        "id": item.get("id", ""),
        "title": item.get("title", ""),
        "price": item.get("price", ""),
        "category": item.get("category", ""),
        "updated": item.get("updated_at", "")
    }

def run():
    outfile = "items.csv"
    with open(outfile, "w", newline="", encoding="utf-8") as f:
        writer = csv.DictWriter(f, fieldnames=["id","title","price","category","updated"])
        writer.writeheader()

        params = {"limit": 100}
        cursor = None
        attempts = 0

        while True:
            if cursor:
                params["cursor"] = cursor

            try:
                data = fetch_page(params)
                attempts = 0  # reset on success
            except requests.HTTPError as e:
                if e.response is not None and e.response.status_code in (429, 500, 502, 503, 504):
                    attempts += 1
                    wait = min(60, 2 ** attempts)
                    time.sleep(wait)
                    continue
                raise

            items = data.get("items", [])
            for item in items:
                writer.writerow(normalize(item))

            cursor = data.get("next_cursor")
            if not cursor:
                break

if __name__ == "__main__":
    run()

This script shows a Python Scrapingbee CSV pagination script. It writes headers once, streams rows, waits on common errors, and stops when there is no cursor.

JavaScript Walkthrough

Some teams prefer Node.js. The pattern stays the same. You fetch, you loop, and you write. For step-by-step practice, you can follow a Scrapingbee JavaScript tutorial that shows pagination and CSV export.

import fs from "fs";
import fetch from "node-fetch";

const API_URL = "https://app.scrapingbee.com/api/v1/";
const API_KEY = process.env.SCRAPINGBEE_KEY;

function toCsvRow(obj, columns) {
  return columns.map(c => (obj[c] ?? "").toString().replace(/"/g, '""')).join(",");
}

async function fetchPage(params) {
  const url = new URL(API_URL);
  url.searchParams.set("api_key", API_KEY);
  url.searchParams.set("url", "https://example.com/api/items");
  url.searchParams.set("params", JSON.stringify(params));
  url.searchParams.set("render_js", "false");

  const res = await fetch(url.toString());
  if (!res.ok) {
    throw new Error(`HTTP ${res.status}`);
  }
  return res.json();
}

async function run() {
  const file = fs.createWriteStream("items.csv", { encoding: "utf8" });
  const columns = ["id","title","price","category","updated"];
  file.write(columns.join(",") + "\n");

  let cursor = undefined;
  let params = { limit: 100 };

  while (true) {
    if (cursor) params.cursor = cursor;

    let data;
    try {
      data = await fetchPage(params);
    } catch (err) {
      const message = String(err.message || "");
      if (message.includes("HTTP 429") || message.includes("HTTP 5")) {
        await new Promise(r => setTimeout(r, 4000));
        continue;
      }
      throw err;
    }

    for (const item of (data.items || [])) {
      const row = {
        id: item.id ?? "",
        title: item.title ?? "",
        price: item.price ?? "",
        category: item.category ?? "",
        updated: item.updated_at ?? ""
      };
      file.write(toCsvRow(row, columns) + "\n");
    }

    cursor = data.next_cursor;
    if (!cursor) break;
  }

  file.end();
}

run().catch(err => {
  console.error(err);
  process.exit(1);
});

This code shows JavaScript Scrapingbee fetch pagination. It streams rows, retries when needed, and finishes when there is no next_cursor. When you need to create or update records, send a ScrapingBee POST request with a JSON body and the target API URL.

Reading Pagination Signals

Where should you look for the next page? Some APIs place it in the body. Others use headers. You may see a field such as X-Next-Page or a link that uses rel=”next”. That case is the Scrapingbee pagination headers example. Parse it once, test it, and then move forward.

If the API uses page numbers, keep going until page * limit reaches total. This path is simple and works well. Many modern APIs choose cursors, since cursor flows scale better.

Handling Rate Limits and Errors

APIs set limits to protect their systems. You should follow the rules. Add a short delay between calls. When you see 429 or a common 5xx code, wait a little and try again. The habit of rate-limit-friendly pagination loop keeps your job stable.

In live runs, write clear logs. Save the time, the request, and the status. If a job fails, start again from the last cursor. With idempotent writes and steady cursors, you can finish long runs with confidence. For quick browser checks, you can follow a ScrapingBee Playwright guide to test pagination steps before long runs.

Building One Clean CSV

Aim for one file and stable columns. The phrase combine paginated results into one file tells the goal. Use a fixed list of column names and write the headers once. If new fields appear later, add them on purpose and in order so charts and reports do not break.

Helpful checks:

Count rows and compare with the expected total.
Look for blank ID fields.
Check date formats in the updated column.
Validate numbers before loading them into a warehouse.

When The API Uses Tokens

Some APIs return a next_page_token in the body. Others include it in a header. Treat the token like a black box. Pass it back as you received it. That is the idea of Scrapingbee pagination next-page token. Tokens may expire quickly, so avoid long pauses. Before production, install ScrapingBee and run a quick auth check to ensure requests succeed.

When The API Uses Cursors

A cursor points to where you left off. The server may sign it or encode it. You do not need to know the details. Just pass it back for the next page. That is the core of cursor-based pagination with Scrapingbee.

CSV Performance Tips

Open the file once and flush from time to time.
Do not store all records in memory.
Keep the mapper small and quick.
Use UTF-8 and quote fields that contain commas.

If the export is huge, split it by row count or by a time window. You can merge parts later if needed. For field targeting and paths, you can use ScrapingBee extract rules to define what each page should capture.

Security, Compliance, and Responsible Use

Only scrape what you are allowed to access. Follow robots, terms, and limits. Hide secrets in logs. Keep API keys in environment variables or a secure vault, not in code or repos.

Troubleshooting Guide

CSV is empty: Check the field name for items.
Duplicate rows: Track seen IDs or use unique keys during load.
Last page is missing: Stop only when there is no next token or cursor.
Bad characters: Always open files with explicit UTF-8 settings.

For community-built examples, you may review ScrapingBee’s open source tools that mirror these steps.

Quick Checklist

Find the page style: page, offset, or cursor.
Build a safe loop with retries.
Map JSON to a flat shape.
Write the CSV with headers first.
Stop when there is no next hint.
Check totals and sample rows.

Scrapingbee Pagination for CSV Exports and APIs

Step	What to do	Key fields or params	Quick tip
Goal	Export all pages to one CSV	filename, headers	Plan columns before you start
Find pagination type	Check if it is page, offset, or cursor	`page`, `offset`, `limit`, `next_cursor`, `next_page_token`	Read the API docs first
First request	Send the first call with base params	base URL, auth, query	Log the status code and URL
Write headers	Open CSV and write column names	id, title, price, category, updated	Keep column order fixed
Loop and fetch	Get items from each response	`items` or list field name	Append rows as you go
Next page signal	Read the next value and pass it back	`page+1`, `offset+limit`, `next_cursor`, token	Stop only when no next value
Handle limits	Wait and retry on common errors	HTTP 429, 500, 502, 503, 504	Use short delays and backoff
Map fields	Flatten JSON to simple columns	id, title, price, category, updated_at	Fill blanks with empty strings
Quality checks	Verify counts and formats	total rows, id not blank, dates, numbers	Sample a few rows by hand
Finish	Close file and report summary	row count, runtime	Keep logs for future runs

Conclusion

Scrapingbee Pagination becomes clear when you follow a short loop. You request a page, write the rows, pick up the next hint, and continue until the data ends. Keep parameters simple and logs clean. Treat tokens as opaque values that you pass forward without change. If this stack is not a fit, you can compare Scrapingbee alternatives that offer similar pagination and CSV export steps.

With these steps, you can export full catalogs, job feeds, and listings into one neat CSV. Begin with the small script. Then add retries, checks, and logs so long jobs finish well and your files work for dashboards and reports.