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Most Pump.fun API endpoints that return lists support pagination through offset and limit parameters. This guide covers best practices for paginating through large result sets.

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Basic pagination

The standard pagination pattern uses two parameters:
  • limit - Number of items to return (page size)
  • offset - Number of items to skip (starting position)

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Simple pagination example

# Get first page (items 0-49)
curl -X GET "https://frontend-api-v3.pump.fun/coins/search?limit=50&offset=0&searchTerm=&sort=created_timestamp&order=desc&includeNsfw=false" \
  -H "Authorization: Bearer <your_token>" \
  -H "Accept: application/json"

# Get second page (items 50-99)
curl -X GET "https://frontend-api-v3.pump.fun/coins/search?limit=50&offset=50&searchTerm=&sort=created_timestamp&order=desc&includeNsfw=false" \
  -H "Authorization: Bearer <your_token>" \
  -H "Accept: application/json"

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Iterate through all pages

Automatically paginate through all available results:
Python
import requests
from typing import List, Dict, Any

def fetch_all_results(url: str, headers: Dict[str, str], 
                      params: Dict[str, Any], page_size: int = 100) -> List[Dict]:
    """
    Fetch all results by paginating through pages
    """
    all_results = []
    offset = 0
    
    while True:
        # Update pagination parameters
        params["limit"] = page_size
        params["offset"] = offset
        
        # Fetch page
        response = requests.get(url, headers=headers, params=params)
        
        if response.status_code != 200:
            print(f"Error: {response.status_code}")
            break
        
        results = response.json()
        
        # Stop if no results returned
        if not results:
            break
        
        all_results.extend(results)
        
        # Stop if we got fewer results than requested (last page)
        if len(results) < page_size:
            break
        
        # Move to next page
        offset += page_size
    
    return all_results

# Usage
url = "https://frontend-api-v3.pump.fun/coins/search"
headers = {"Authorization": "Bearer <your_token>", "Accept": "application/json"}
params = {
    "searchTerm": "DOGE",
    "sort": "market_cap",
    "order": "desc",
    "includeNsfw": False
}

all_coins = fetch_all_results(url, headers, params, page_size=100)
print(f"Total results: {len(all_coins)}")
Detect the last page by checking if the returned results are fewer than your requested limit.

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Pagination with rate limiting

Implement pagination with proper rate limiting handling:
Python
import requests
import time
from typing import List, Dict, Any, Optional

class PaginatedFetcher:
    def __init__(self, token: str, delay: float = 0.5):
        self.headers = {
            "Authorization": f"Bearer {token}",
            "Accept": "application/json"
        }
        self.delay = delay  # Delay between requests
    
    def fetch_paginated(self, url: str, params: Dict[str, Any], 
                       page_size: int = 100, max_results: Optional[int] = None) -> List[Dict]:
        """
        Fetch paginated results with rate limiting
        """
        all_results = []
        offset = 0
        
        while True:
            # Check if we've reached max_results
            if max_results and len(all_results) >= max_results:
                break
            
            # Update pagination params
            params["limit"] = page_size
            params["offset"] = offset
            
            try:
                response = requests.get(url, headers=self.headers, params=params)
                
                # Handle rate limiting
                if response.status_code == 429:
                    retry_after = int(response.headers.get('Retry-After', 60))
                    print(f"Rate limited. Waiting {retry_after}s...")
                    time.sleep(retry_after)
                    continue
                
                if response.status_code != 200:
                    print(f"Error {response.status_code}: {response.text}")
                    break
                
                results = response.json()
                
                if not results:
                    break
                
                all_results.extend(results)
                print(f"Fetched {len(results)} results (total: {len(all_results)})")
                
                # Check if last page
                if len(results) < page_size:
                    break
                
                offset += page_size
                
                # Respectful delay between requests
                time.sleep(self.delay)
                
            except Exception as e:
                print(f"Error: {e}")
                break
        
        return all_results

# Usage
fetcher = PaginatedFetcher("your_token", delay=0.5)
url = "https://frontend-api-v3.pump.fun/coins/search"
params = {
    "searchTerm": "",
    "sort": "created_timestamp",
    "order": "desc",
    "includeNsfw": False
}

coins = fetcher.fetch_paginated(url, params, page_size=100, max_results=500)
Always implement delays between paginated requests to avoid rate limiting. A 0.5-1 second delay is recommended.

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Pagination for trades

Paginate through trade history for a specific coin:
Python
import requests
from typing import List, Dict

def fetch_all_trades(mint: str, minimum_size: int = 0, page_size: int = 100) -> List[Dict]:
    """
    Fetch all trades for a coin with pagination
    """
    url = f"https://frontend-api-v3.pump.fun/trades/all/{mint}"
    headers = {
        "Authorization": "Bearer <your_token>",
        "Accept": "application/json"
    }
    
    all_trades = []
    offset = 0
    
    while True:
        params = {
            "limit": page_size,
            "offset": offset,
            "minimumSize": minimum_size
        }
        
        response = requests.get(url, headers=headers, params=params)
        trades = response.json()
        
        if not trades:
            break
        
        all_trades.extend(trades)
        print(f"Fetched {len(trades)} trades (total: {len(all_trades)})")
        
        if len(trades) < page_size:
            break
        
        offset += page_size
    
    return all_trades

# Usage
mint = "CxLHsqvjfisgPAGwcZJsTn6nzZXJLxmVYM7v9pump"
trades = fetch_all_trades(mint, minimum_size=1000000, page_size=100)
print(f"Total trades with size >= 1M: {len(trades)}")

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Efficient pagination patterns

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Calculate total pages

While most endpoints don’t return total counts, you can implement page counting:
Python
import math

def estimate_total_pages(first_page_results: List, page_size: int) -> str:
    """
    Estimate total pages based on first page results
    """
    if len(first_page_results) < page_size:
        return "1 page (last page)"
    else:
        return "Multiple pages (exact count unknown)"

# Usage
results = fetch_page(url, headers, params, limit=100, offset=0)
print(estimate_total_pages(results, 100))

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Resume pagination

Save progress to resume pagination later:
Python
import json
import os

class ResumablePagination:
    def __init__(self, cache_file: str = "pagination_state.json"):
        self.cache_file = cache_file
    
    def save_state(self, offset: int, total_results: int):
        """Save pagination state"""
        state = {
            "offset": offset,
            "total_results": total_results
        }
        with open(self.cache_file, 'w') as f:
            json.dump(state, f)
    
    def load_state(self) -> tuple:
        """Load pagination state"""
        if os.path.exists(self.cache_file):
            with open(self.cache_file, 'r') as f:
                state = json.load(f)
                return state["offset"], state["total_results"]
        return 0, 0
    
    def fetch_with_resume(self, url: str, headers: dict, params: dict, page_size: int = 100):
        """Fetch with ability to resume"""
        offset, total_results = self.load_state()
        all_results = []
        
        print(f"Resuming from offset {offset} (already fetched {total_results} items)")
        
        while True:
            params["limit"] = page_size
            params["offset"] = offset
            
            response = requests.get(url, headers=headers, params=params)
            results = response.json()
            
            if not results:
                break
            
            all_results.extend(results)
            offset += len(results)
            
            # Save progress
            self.save_state(offset, total_results + len(all_results))
            
            if len(results) < page_size:
                break
        
        return all_results

# Usage
pagination = ResumablePagination()
results = pagination.fetch_with_resume(url, headers, params)

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Common pagination endpoints

Endpoints that support offset/limit pagination:
  • GET /coins - All coins with filtering
  • GET /coins/search - Search results
  • GET /coins/featured/{timeWindow} - Featured coins
  • GET /coins/currently-live - Live coins
  • GET /coins/for-you - Personalized recommendations
  • GET /coins/user-created-coins/{userId} - User’s created coins
  • GET /trades/all/{mint} - All trades for a coin
  • GET /trades/followsUserId/{mint} - Trades from followed users
  • GET /replies - All replies
  • GET /replies/{mint} - Replies for a coin
  • GET /replies/user-replies/{address} - User’s replies
  • GET /notifications - User notifications
  • GET /moderation/logs - Moderation logs
  • GET /bookmarks/{id} - Bookmark items

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Best practices

1

Choose appropriate page sizes

Use 50-100 items per page for most use cases. Smaller for real-time updates, larger for bulk processing.
2

Implement exponential backoff

When encountering rate limits, use exponential backoff before retrying.
3

Add delays between pages

Wait 0.5-1 second between page requests to be respectful of API resources.
4

Handle empty results

Always check for empty arrays to detect the last page.
5

Cache results locally

Store fetched data locally to avoid re-fetching the same pages.
6

Monitor progress

Log progress during pagination to help with debugging and resumption.
The maximum recommended limit is 100. Larger values may result in timeouts or degraded performance.

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