Performance

vlrdevapi is optimized for speed and efficiency.

Built-in Optimizations

HTTP Connection Pooling & HTTP/2

Managed by the shared httpx clients with automatic keep-alive and HTTP/2 support.

  • Impact: Lower latency from multiplexed requests and persistent sessions

  • Shared across the process for consistent performance

In-Memory Caching

Responses cached in memory to avoid redundant requests.

  • Impact: Orders-of-magnitude faster for repeated requests within a session

  • Cache is in-memory only; call vlr.fetcher.clear_cache() for fresh data

Fast HTML Parser

Uses lxml (C-based) instead of Python’s html.parser.

  • Impact: 50-100% faster HTML parsing

  • Installed automatically as a dependency

Brotli & Gzip Compression

httpx transparently negotiates Brotli (br) and gzip compression with VLR.gg.

  • Impact: Smaller payloads and faster decompression

  • Enabled by default; no additional configuration needed

Best Practices

Cache Management

Clear cache when you need fresh data:

import vlrdevapi as vlr

# Clear cache for fresh data
vlr.fetcher.clear_cache()

# Now fetch fresh data
results = vlr.search.search("nrg")

Connection Cleanup

Close connections on application shutdown:

import vlrdevapi as vlr
# At application exit
vlr.fetcher.close_connections()

Controlled Fetches

Minimize API calls by batching or paginating operations:

import vlrdevapi as vlr
# Efficient: Request a larger batch once
matches = vlr.matches.upcoming(limit=5)

import vlrdevapi as vlr
# Paginate when you need historical data
page1 = vlr.matches.completed(limit=5, page=1)
page2 = vlr.matches.completed(limit=5, page=2)