def onModuleEncounter(self, module_filename, module_name, module_kind):
if module_name.hasNamespace("mpl_toolkits"):
return True, "Needed by matplotlib"
# some special handling for matplotlib:
# depending on whether 'tk-inter' resp. 'qt-plugins' are enabled,
# their matplotlib backends are included.
if hasActivePlugin("tk-inter"):
if module_name in (
"matplotlib.backends.backend_tk",
"matplotlib.backends.backend_tkagg",
"matplotlib.backend.tkagg",
):
return True, "Needed for tkinter matplotplib backend"
if getActiveQtPlugin() is not None:
# Note, their code tries everything behind that name, the qt5 is
# misleading therefore, PySide will work there too.
if module_name in (
"matplotlib.backends.backend_qt5",
"matplotlib.backends.backend_qt5.py",
"matplotlib.backends.backend_qt5cairo.py",
"matplotlib.backend.backend_qt5.py",
):
return True, "Needed for Qt matplotplib backend"
if module_name == "matplotlib.backends.backend_agg":
return True, "Needed as standard matplotplib backend"
def onModuleEncounter(self, module_filename, module_name, module_kind):
# pylint: disable=too-many-branches,too-many-return-statements
if not self.scipy and module_name.hasOneOfNamespaces(
"scipy", "sklearn", "skimage"):
return False, "Omit unneeded components"
if not self.matplotlib and module_name.hasOneOfNamespaces(
"matplotlib", "skimage"):
return False, "Omit unneeded components"
if module_name == "scipy.sparse.csgraph._validation":
return True, "Replicate implicit import"
if self.matplotlib and module_name.hasNamespace("mpl_toolkits"):
return True, "Needed by matplotlib"
if module_name in ("cv2", "cv2.cv2", "cv2.data"):
return True, "Needed for OpenCV"
sklearn_mods = [
"sklearn.utils.sparsetools._graph_validation",
"sklearn.utils.sparsetools._graph_tools",
"sklearn.utils.lgamma",
"sklearn.utils.weight_vector",
"sklearn.utils._unittest_backport",
"sklearn.externals.joblib.externals.cloudpickle.dumps",
"sklearn.externals.joblib.externals.loky.backend.managers",
]
if isWin32Windows():
sklearn_mods.extend([
"sklearn.externals.joblib.externals.loky.backend.synchronize",
"sklearn.externals.joblib.externals.loky.backend._win_wait",
"sklearn.externals.joblib.externals.loky.backend._win_reduction",
"sklearn.externals.joblib.externals.loky.backend.popen_loky_win32",
])
else:
sklearn_mods.extend([
"sklearn.externals.joblib.externals.loky.backend.synchronize",
"sklearn.externals.joblib.externals.loky.backend.compat_posix",
"sklearn.externals.joblib.externals.loky.backend._posix_reduction",
"sklearn.externals.joblib.externals.loky.backend.popen_loky_posix",
])
if self.scipy and module_name in sklearn_mods:
return True, "Needed by sklearn"
# some special handling for matplotlib:
# depending on whether 'tk-inter' resp. 'qt-plugins' are enabled,
# matplotlib backends are included.
if self.matplotlib:
if hasActivePlugin("tk-inter"):
if module_name in (
"matplotlib.backends.backend_tk",
"matplotlib.backends.backend_tkagg",
"matplotlib.backend.tkagg",
):
return True, "Needed for tkinter matplotplib backend"
if hasActivePlugin("qt-plugins"):
if module_name in (
"matplotlib.backends.backend_qt5",
"matplotlib.backends.backend_qt5.py",
"matplotlib.backends.backend_qt5cairo.py",
"matplotlib.backend.backend_qt5.py",
):
return True, "Needed for Qt5 matplotplib backend"
if module_name == "matplotlib.backends.backend_agg":
return True, "Needed as standard matplotplib backend"