Make some dependencies optional: pandas, wendelin

product/ERP5Type/patches/Restricted.py

@@ -402,8 +402,7 @@ ModuleSecurityInfo('os').declarePublic('urandom')
 #
 # backport from wendelin
 #
-# we neeed to allow access to numpy's internal types
-import pandas as pd
+# we need to allow access to numpy's internal types
 import numpy as np
 allow_module('numpy')
 allow_module('numpy.lib.recfunctions')
@@ -427,55 +426,66 @@ allow_type(np.timedelta64)
 allow_type(type(np.c_))
 allow_type(type(np.dtype('int16')))
 
-allow_module('pandas')
+# Modify 'safetype' dict in full_write_guard function of RestrictedPython
+# (closure) directly to allow  write access to ndarray
+# (and pandas DataFrame below).
 
-allow_type(pd.Series)
-allow_type(pd.Timestamp)
-allow_type(pd.DatetimeIndex)
-# XXX: pd.DataFrame has its own security thus disable until we can fully integrate it
-#allow_type(pd.DataFrame)
-allow_type(pd.MultiIndex)
-allow_type(pd.indexes.range.RangeIndex)
-allow_type(pd.indexes.numeric.Int64Index)
-allow_type(pd.core.groupby.DataFrameGroupBy)
-allow_type(pd.core.groupby.SeriesGroupBy)
-allow_class(pd.DataFrame)
+from RestrictedPython.Guards import full_write_guard
+safetype = full_write_guard.func_closure[1].cell_contents.__self__
+safetype.update(dict.fromkeys((
+  np.ndarray,
+  np.core.records.recarray,
+  np.core.records.record,
+), True))
 
 def restrictedMethod(s,name):
   def dummyMethod(*args, **kw):
     raise Unauthorized(name)
   return dummyMethod
 
-# Note: These black_list methods are for pandas 0.19.2
-series_black_list = ['to_csv', 'to_json', 'to_pickle', 'to_hdf',
-                     'to_sql', 'to_msgpack']
-series_black_list_dict = {m: restrictedMethod for m in series_black_list}
-ContainerAssertions[pd.Series] = _check_access_wrapper(pd.Series,
-                                                       series_black_list_dict)
-
-pandas_black_list = ['read_csv', 'read_json', 'read_pickle', 'read_hdf', 'read_fwf',
+try:
+  import pandas as pd
+except ImportError:
+  pass
+else:
+  allow_module('pandas')
+  allow_type(pd.Series)
+  allow_type(pd.Timestamp)
+  allow_type(pd.DatetimeIndex)
+  # XXX: pd.DataFrame has its own security thus disable
+  #      until we can fully integrate it
+  #allow_type(pd.DataFrame)
+  allow_type(pd.MultiIndex)
+  allow_type(pd.indexes.range.RangeIndex)
+  allow_type(pd.indexes.numeric.Int64Index)
+  allow_type(pd.core.groupby.DataFrameGroupBy)
+  allow_type(pd.core.groupby.SeriesGroupBy)
+  allow_class(pd.DataFrame)
+
+  # Note: These black_list methods are for pandas 0.19.2
+  ContainerAssertions[pd.Series] = _check_access_wrapper(
+    pd.Series, dict.fromkeys((
+      'to_csv', 'to_json', 'to_pickle', 'to_hdf', 'to_sql', 'to_msgpack',
+    ), restrictedMethod))
+
+  ModuleSecurityInfo('pandas').declarePrivate(
+    'read_csv', 'read_json', 'read_pickle', 'read_hdf', 'read_fwf',
     'read_excel', 'read_html', 'read_msgpack',
-                     'read_gbq', 'read_sas', 'read_stata']
-ModuleSecurityInfo('pandas').declarePrivate(*pandas_black_list)
-
-dataframe_black_list = ['to_csv', 'to_json', 'to_pickle', 'to_hdf',
-                        'to_excel', 'to_html', 'to_sql', 'to_msgpack',
-                        'to_latex', 'to_gbq', 'to_stata']
-dataframe_black_list_dict = {m: restrictedMethod for m in dataframe_black_list}
-ContainerAssertions[pd.DataFrame] = _check_access_wrapper(
-                                      pd.DataFrame, dataframe_black_list_dict)
-
-# Modify 'safetype' dict in full_write_guard function
-# of RestrictedPython (closure) directly to allow
-# write access to ndarray and pandas DataFrame.
-from RestrictedPython.Guards import full_write_guard
-full_write_guard.func_closure[1].cell_contents.__self__[np.ndarray] = True
-full_write_guard.func_closure[1].cell_contents.__self__[np.core.records.recarray] = True
-full_write_guard.func_closure[1].cell_contents.__self__[np.core.records.record] = True
-full_write_guard.func_closure[1].cell_contents.__self__[pd.DataFrame] = True
-full_write_guard.func_closure[1].cell_contents.__self__[pd.Series] = True
-full_write_guard.func_closure[1].cell_contents.__self__[pd.tseries.index.DatetimeIndex] = True
-full_write_guard.func_closure[1].cell_contents.__self__[pd.core.indexing._iLocIndexer] = True
-full_write_guard.func_closure[1].cell_contents.__self__[pd.core.indexing._LocIndexer] = True
-full_write_guard.func_closure[1].cell_contents.__self__[pd.MultiIndex] = True
-full_write_guard.func_closure[1].cell_contents.__self__[pd.Index] = True
+    'read_gbq', 'read_sas', 'read_stata',
+  )
+
+  ContainerAssertions[pd.DataFrame] = _check_access_wrapper(
+    pd.DataFrame, dict.fromkeys((
+      'to_csv', 'to_json', 'to_pickle', 'to_hdf', 'to_excel', 'to_html',
+      'to_sql', 'to_msgpack', 'to_latex', 'to_gbq', 'to_stata',
+    ), restrictedMethod))
+
+  safetype.update(dict.fromkeys((
+    pd.DataFrame,
+    pd.Series,
+    pd.tseries.index.DatetimeIndex,
+    pd.core.indexing._iLocIndexer,
+    pd.core.indexing._LocIndexer,
+    pd.MultiIndex,
+    pd.Index,
+  ), True))

product/ERP5Type/patches/pylint.py

@@ -335,12 +335,16 @@ for filename in os.listdir(os.path.dirname(lxml.__file__)):
 # with `No name 'bigarray' in module 'wendelin' (no-name-in-module)`.
 #
 # -> Teach pylint to properly understand wendelin package nature.
-import wendelin
-def wendelin_transform(node):
+try:
+    import wendelin
+except ImportError:
+    pass
+else:
+    def wendelin_transform(node):
         m = AstroidBuilder(MANAGER).string_build('__path__ = %r' % wendelin.__path__)
         m.package = True
         return m
-MANAGER.register_transform(Module, wendelin_transform, lambda node: node.name == 'wendelin')
+    MANAGER.register_transform(Module, wendelin_transform, lambda node: node.name == 'wendelin')
 
 # Properly search for namespace packages: original astroid (as of 1.3.8) only
 # checks at top-level and it doesn't work for Shared.DC.ZRDB (defined in