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pylastfm Documentation |  |
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pylastfm Documentation | |
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>>> import lastfm
>>> lastfm.config.update({"cache.on", True})
The update function will automatically reload all related modules, including the caching module with the new configuration options.
pylastfm provides two caching backends: The first is an In-Memory-Cache - which
is the default, the second one is a filesystem based cache which keeps it's
information accross sessions on a per user basis. You can choose between both
backends by setting the "cache.backend" option. Here's a complete
example:
>>> import lastfm
>>> lastfm.config.update({"cache.on" : True, "cache.backend" : "filesystem"})
>>> artists = lastfm.user.top_artists("RJ")
2007-02-20 12:22:08,280 DEBUG Retrieving 'http://ws.audioscrobbler.com/1.0/user/RJ/profile.xml'
2007-02-20 12:22:08,526 DEBUG Retrieving 'http://ws.audioscrobbler.com/1.0/user/RJ/topartists.xml'
>>> # Let's do it again!
>>> artists = lastfm.user.top_artists("RJ")
2007-02-20 12:22:17,300 DEBUG Retrieving 'http://ws.audioscrobbler.com/1.0/user/RJ/profile.xml'
2007-02-20 12:22:17,301 DEBUG Cached 'http://ws.audioscrobbler.com/1.0/user/RJ/profile.xml'
2007-02-20 12:22:17,302 DEBUG Retrieving 'http://ws.audioscrobbler.com/1.0/user/RJ/topartists.xml'
2007-02-20 12:22:17,302 DEBUG Cached 'http://ws.audioscrobbler.com/1.0/user/RJ/topartists.xml'
>>>
As you can see, calling the top_artists function a second time with the same parameters returns the information from the filesystem cache.
You can easily write your own cache backend by subclassing
lastfm.lib.cache.BaseCache and setting the "cache.backend" to an
import path (i.e. "mymodule.MyCachingClass"). pylastfm will dynamically
import your class and use it as it's caching backend.
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pylastfm Documentation | |
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