def fetch_cube(dataset, dimensions, weight=None, filter=None, **measures):
"""Return a shoji.View containing a crunch:cube.
The dataset entity is used to look up its views.cube URL.
The dimensions must be a list of either strings, which are assumed to be
URL's of variable Entities to be fetched and analyzed according to type,
or objects, which are assumed to be complete variable expressions.
The weight, if sent, should be the URL of a valid weight variable
If applying a filter, it should be a filter expression or filter URL.
>>> dataset = session.site.datasets.by('name')['my dataset'].entity
>>> variables = dataset.variables.by('alias')
>>> dimensions = [
... {"each": variables['CA'].entity_url},
... {"variable": variables['CA'].entity_url}
... ]
>>> weight = variables['weight_var'].entity_url
>>> count = {
... "function": "cube_count",
... "args": []
... }
>>> filter = {
... "function": "!=",
... "args": [
... {"variable": variables['categorical_var'].entity_url},
... {"value": 3},
... ]
... }
>>> fetch_cube(dataset, dimensions, weight=weight, filter=filter, count=count)
"""
dims = DimensionsPreparer(dataset).prepare_dimensions(dimensions)
cube_query = elements.JSONObject(dimensions=dims, measures=measures)
if weight is not None:
cube_query['weight'] = weight
params = {"query": cube_query.json}
if filter is not None:
params['filter'] = elements.JSONObject(filter).json
return dataset.session.get(dataset.views.cube, params=params).payload
def by(self, attr):
"""Return the Tuples of self.index indexed by the given 'attr' instead.
If a given Tuple does not contain the specified attribute,
it is not included. If more than one does, only one will be
included (which one is undefined).
The specified attr is not popped from the Tuple; it is merely
copied to the output keys. Due to restrictions on Python dicts,
specifying attrs which are not hashable will raise an error.
"""
return elements.JSONObject(**dict(
(tupl[attr], tupl) for tupl in six.itervalues(self.index)
if attr in tupl))
def cast(variable, type, format=None, offset=None, resolution=None):
"""Alter the given variable Entity to a new type.
Various parameters may need to be sent to properly convert from one type
to another. Datetime is particularly demanding.
"""
payload = elements.JSONObject(cast_as=type)
if format is not None:
payload['format'] = format
if offset is not None:
payload['offset'] = offset
if resolution is not None:
payload['resolution'] = resolution
return variable.cast.post(data=payload.json)
def fetch_cube(dataset, dimensions, weight=None, **measures):
"""Return a shoji.View containing a crunch:cube.
The dataset entity is used to look up its views.cube URL.
The dimensions must be a list of either strings, which are assumed to be
URL's of variable Entities to be fetched and analyzed according to type,
or objects, which are assumed to be complete variable expressions.
"""
dims = []
for d in dimensions:
if isinstance(d, dict):
# This is already a Crunch expression.
dims.append(d)
elif isinstance(d, six.string_types):
ref = {'variable': d}
# A URL of a variable entity. GET it to find its type.
v = dataset.session.get(d).payload
if v.body.type == "numeric":
dims.append({"function": "bin", "args": [ref]})
elif v.body.type == "datetime":
rollup_res = v.body.view.get("rollup_resolution", None)
dims.append({
"function": "rollup",
"args": [ref, {
"value": rollup_res
}]
})
elif v.body.type == "categorical_array":
dims.append(ref)
dims.append({"each": d})
elif v.body.type == "multiple_response":
dims.append({"function": "selected_array", "args": [ref]})
dims.append({"each": d})
else:
dims.append(ref)
else:
raise TypeError(
"dimensions must be URL strings or Crunch expression objects.")
q = elements.JSONObject(dimensions=dims, measures=measures)
if weight is not None:
q['weight'] = weight
return dataset.session.get(dataset.views.cube, params={
"query": q.json
}).payload
def fetch_cube(dataset, dimensions, weight=None, filter=None, **measures):
"""Return a shoji.View containing a crunch:cube.
The dataset entity is used to look up its views.cube URL.
The dimensions must be a list of either strings, which are assumed to be
URL's of variable Entities to be fetched and analyzed according to type,
or objects, which are assumed to be complete variable expressions.
The weight, if sent, should be the URL of a valid weight variable
If applying a filter, it should be a filter expression or filter URL.
>>> dataset = session.site.datasets.by('name')['my dataset'].entity
>>> variables = dataset.variables.by('alias')
>>> dimensions = [
... {"each": variables['CA'].entity_url},
... {"variable": variables['CA'].entity_url}
... ]
>>> weight = variables['weight_var'].entity_url
>>> count = {
... "function": "cube_count",
... "args": []
... }
>>> filter = {
... "function": "!=",
... "args": [
... {"variable": variables['categorical_var'].entity_url},
... {"value": 3},
... ]
... }
>>> fetch_cube(dataset, dimensions, weight=weight, filter=filter, count=count)
"""
dims = []
for d in dimensions:
if isinstance(d, dict):
# This is already a Crunch expression.
dims.append(d)
elif isinstance(d, six.string_types):
ref = {'variable': d}
# A URL of a variable entity. GET it to find its type.
v = dataset.session.get(d).payload
if v.body.type == "numeric":
dims.append({"function": "bin", "args": [ref]})
elif v.body.type == "datetime":
rollup_res = v.body.view.get("rollup_resolution", None)
dims.append({
"function": "rollup",
"args": [ref, {
"value": rollup_res
}]
})
elif v.body.type == "categorical_array":
dims.append({"each": d})
dims.append(ref)
elif v.body.type == "multiple_response":
dims.append({"each": d})
dims.append({"function": "as_selected", "args": [ref]})
else:
dims.append(ref)
else:
raise TypeError(
"dimensions must be URL strings or Crunch expression objects.")
q = elements.JSONObject(dimensions=dims, measures=measures)
if weight is not None:
q['weight'] = weight
params = {"query": q.json}
if filter is not None:
params['filter'] = elements.JSONObject(filter).json
return dataset.session.get(dataset.views.cube, params=params).payload