From 1ade3a6ea6f976cf017373c27d3d74c3c1f41949 Mon Sep 17 00:00:00 2001
From: Martin Bauer <martin.bauer@fau.de>
Date: Thu, 11 Jan 2018 12:37:52 +0100
Subject: [PATCH] Removed joblib.cached-sphinx workaround / Caching fix
- sphinx detection is not reliable, e.g. jupyter notebooks have sphinx
imported at startup -> no caching from notebooks
- explicitly added cached functions via autofunction to docs
- some functions do not support memory cache, because memory cache can't
handle non-hashable parameters -> introduced diskcacheNoFallback
decorator for these functions
---
cache.py | 31 ++-----------------------------
1 file changed, 2 insertions(+), 29 deletions(-)
diff --git a/cache.py b/cache.py
index 78a7c56a8..261e76231 100644
--- a/cache.py
+++ b/cache.py
@@ -15,36 +15,9 @@ try:
else:
cacheDir = user_cache_dir('pystencils')
diskcache = Memory(cachedir=cacheDir, verbose=False).cache
+ diskcacheNoFallback = diskcache
except ImportError:
# fallback to in-memory caching if joblib is not available
diskcache = memorycache(maxsize=64)
+ diskcacheNoFallback = lambda o: o
-
-# joblibs Memory decorator does not play nicely with sphinx autodoc (decorated functions do not occur in autodoc)
-# -> if this script is imported by sphinx we use functools instead
-import sys
-calledBySphinx = 'sphinx' in sys.modules
-if calledBySphinx:
- diskcache = memorycache(maxsize=64)
-
-
-# ------------------------ Helper classes to JSON serialize sympy objects ----------------------------------------------
-
-
-class SympyJSONEncoder(json.JSONEncoder):
- def default(self, obj):
- if isinstance(obj, sp.Basic):
- return {"_type": "sp", "str": str(obj)}
- else:
- super(SympyJSONEncoder, self).default(obj)
-
-
-class SympyJSONDecoder(json.JSONDecoder):
- def __init__(self, *args, **kwargs):
- json.JSONDecoder.__init__(self, object_hook=self.object_hook, *args, **kwargs)
-
- def object_hook(self, obj):
- if '_type' in obj:
- return sp.sympify(obj['str'])
- else:
- return obj
\ No newline at end of file
--
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