Use Cases

from aioarxiv.client.arxiv_client import ArxivClient from aioarxiv.models import SortCriterion, SortOrder async def search_papers(): async with ArxivClient() as client: # Simple keyword search result = await client.search("quantum computing") # Search with multiple keywords result = await client.search("machine learning AND neural networks") # Search with sorting result = await client.search( "quantum computing", sort_by=SortCriterion.LAST_UPDATED, sort_order=SortOrder.DESCENDING )

from aioarxiv.client.arxiv_client import ArxivClient async def search_specific_papers(): async with ArxivClient() as client: # Search for specific papers by their arXiv IDs result = await client.search( id_list=["2103.00020", "2103.00021"] )

from pathlib import Path from aioarxiv.client.arxiv_client import ArxivClient async def download_paper(): download_dir = Path("./papers") async with ArxivClient( enable_downloader=True, download_dir=download_dir ) as client: # Search and download a specific paper result = await client.search(id_list=["2103.00020"]) paper = result.papers[0] # Download with default filename await client.download_paper(paper) # Download with custom filename await client.download_paper(paper, "quantum_paper.pdf")

from pathlib import Path from aioarxiv.client.arxiv_client import ArxivClient async def batch_download(): download_dir = Path("./papers") async with ArxivClient( enable_downloader=True, download_dir=download_dir ) as client: # Search for papers result = await client.search( "quantum computing", max_results=5 ) # Download all papers from search result tracker = await client.download_search_result(result) # Check download statistics print(f"Total: {tracker.total}") print(f"Completed: {tracker.completed}") print(f"Failed: {tracker.failed}")

from aioarxiv.client.arxiv_client import ArxivClient from aioarxiv.config import ArxivConfig async def custom_client(): # Create custom configuration config = ArxivConfig( timeout=60.0, max_retries=5, rate_limit_calls=2, rate_limit_period=6.0, proxy="http://proxy.example.com:8080" ) # Initialize client with custom config async with ArxivClient(config=config) as client: result = await client.search("quantum computing")

from aioarxiv.client.arxiv_client import ArxivClient from aioarxiv.exception import ( HTTPException, QueryBuildError, PaperDownloadException ) async def handle_errors(): try: async with ArxivClient(enable_downloader=True) as client: # Search with invalid query result = await client.search("quantum computing") # Try to download papers await client.download_search_result(result) except HTTPException as e: print(f"HTTP error: {e.status_code}") except QueryBuildError as e: print(f"Query error: {e}") except PaperDownloadException as e: print(f"Download error: {e}")

from aioarxiv.client.arxiv_client import ArxivClient async def paginated_search(): async with ArxivClient() as client: # Get first page result = await client.search( "quantum computing", max_results=10, start=0 ) # Get second page if result.has_next: next_result = await client.search( "quantum computing", max_results=10, start=10 )

from aioarxiv.client.arxiv_client import ArxivClient async def process_papers(): async with ArxivClient() as client: result = await client.search("quantum computing") for paper in result.papers: # Access paper information print(f"Title: {paper.info.title}") print(f"Authors: {', '.join(a.name for a in paper.info.authors)}") print(f"Published: {paper.info.published}") print(f"Updated: {paper.info.updated}") print(f"Summary: {paper.info.summary}") # Access additional information if paper.doi: print(f"DOI: {paper.doi}") if paper.journal_ref: print(f"Journal: {paper.journal_ref}") if paper.pdf_url: print(f"PDF URL: {paper.pdf_url}")