calliostro/last-fm-client-bundle
Symfony bundle that integrates the modern calliostro/lastfm-client with autowiring and Guzzle. Configure your API key, secret, session key, user agent, and optional rate limiter to access Last.fm music data and scrobbling.
429) and server overload (503), with auto_retry enabled by default and configurable max_retries. This reduces failed requests for user-facing features like live DJ sets, trending charts, and social feeds.calliostro_lastfm configuration rather than building custom backoff/sleep logic. This lowers maintenance burden and makes resilience a configuration decision, not a bespoke engineering project.429 and 503 responses, with the ability to tune or disable retries via auto_retry and max_retries.For Executives: “v2.1.0 makes our Last.fm integration more reliable under real traffic. It now automatically retries when Last.fm rate-limits or overloads requests, with configurable limits, so user-facing music features are less likely to fail during peak usage. We get stronger compatibility across PHP 8.1–8.6 and Symfony 6.4–8.2, plus 100% test coverage. This is a low-risk upgrade that reduces custom reliability work and supports scaling music features without adding engineering overhead.”
For Engineering:
“v2.1.0 upgrades to calliostro/lastfm-client v2.1 with built-in retry resilience for Last.fm 429 and 503 responses. New configuration options auto_retry (default true) and max_retries (default 3) remove the need for manual backoff/sleep logic. Tests maintain 100% coverage, and CI now covers PHP 8.1–8.6 plus Symfony 6.4 LTS, 7.x, 8.0–8.2. Tooling is also tightened with root phpstan.neon.dist at Level 8 and PSR-12 .php-cs-fixer.dist.php. Migration from v2.0.0 should be low-friction; review retry defaults against your traffic profile and Last.fm API limits.”
For Product: “This unlocks data-driven music features with less operational risk: users get more reliable ‘Your Top Artists,’ ‘Fans of this artist,’ and scrobble-driven recommendation experiences, even when Last.fm is slow or rate-limiting. We can tune retries without new engineering work, which means fewer broken states in high-traffic features and faster iteration on discovery and personalization.”
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