def prepare_metrics(obj,
org_metric_lookup,
valid_levels=[],
parent_obj='ContentItem',
check_timeseries=True):
"""
Validate a metric.
"""
# check if metrics exist and are properly formatted.
obj.update(obj.pop('metrics', {}))
for k in obj.keys():
m = org_metric_lookup.get(k)
if not m:
raise RequestError(
"Metric '{}' does not exist at this level.".format(k))
if m['faceted'] and not isinstance(obj[k], list):
raise RequestError(
"Metric '{}' is faceted but was not passed in as a list.".
format(k))
if m['faceted'] and not set(
obj[k][0].keys()) == set(METRIC_FACET_KEYS):
raise RequestError(
"Metric '{}' is faceted, but it\'s elements are not properly formatted. "
"Each facet must be a dictionary of '{\"facet\":\"facet_name\", \"value\": 1234}"
.format(k))
# parse number
obj[k] = stats.parse_number(obj[k])
return obj
def prepare_metrics(
obj,
org_metric_lookup,
valid_levels=[],
parent_obj='ContentItem',
check_timeseries=True
):
"""
Validate a metric.
"""
# check if metrics exist and are properly formatted.
obj.update(obj.pop('metrics', {}))
for k in obj.keys():
m = org_metric_lookup.get(k)
if not m:
raise RequestError(
"Metric '{}' does not exist at this level."
.format(k))
if m['faceted'] and not isinstance(obj[k], list):
raise RequestError(
"Metric '{}' is faceted but was not passed in as a list."
.format(k))
if m['faceted'] and not set(obj[k][0].keys()) == set(METRIC_FACET_KEYS):
raise RequestError(
"Metric '{}' is faceted, but it\'s elements are not properly formatted. "
"Each facet must be a dictionary of '{\"facet\":\"facet_name\", \"value\": 1234}"
.format(k))
# parse number
obj[k] = stats.parse_number(obj[k])
return obj
def _prepare_metrics(obj, metrics_lookup):
"""
Given a lookup of all metrics this object can contain,
validate the object and prepare for ingest.
"""
# check if metrics exist and are properly formatted.
obj.update(obj.pop('metrics', {}))
for k in obj.keys():
if k == 'datetime':
continue
# fetch from lookup
m = metrics_lookup.get(k)
if not m:
raise RequestError(
"Metric '{}' does not exist at this level."
.format(k))
# validate facet formatting.
if m['faceted'] and not isinstance(obj[k], list):
raise RequestError(
"Metric '{}' is faceted but was not passed in as a list."
.format(k))
if m['faceted'] and len(obj[k]) \
and not set(obj[k][0].keys()) == set(METRIC_FACET_KEYS):
raise RequestError(
"Metric '{}' is faceted, but it\'s elements are not properly formatted. "
"Each facet must be a dictionary of '{\"facet\":\"facet_name\", \"value\": 1234}"
.format(k))
# remove empty facets
if m['faceted'] and not len(obj[k]):
obj.pop(k)
# parse numbers.
if not m['faceted']:
obj[k] = stats.parse_number(obj[k])
# parse facet values.
else:
for i, v in enumerate(obj[k]):
obj[k][i]['value'] = \
stats.parse_number(obj[k][i]['value'])
return obj
def _prepare_metrics(obj, metrics_lookup):
"""
Given a lookup of all metrics this object can contain,
validate the object and prepare for ingest.
"""
# check if metrics exist and are properly formatted.
obj.update(obj.pop('metrics', {}))
for k in obj.keys():
if k == 'datetime':
continue
# fetch from lookup
m = metrics_lookup.get(k)
if not m:
raise RequestError(
"Metric '{}' does not exist at this level.".format(k))
# validate facet formatting.
if m['faceted'] and not isinstance(obj[k], list):
raise RequestError(
"Metric '{}' is faceted but was not passed in as a list.".
format(k))
if m['faceted'] and len(obj[k]) \
and not set(obj[k][0].keys()) == set(METRIC_FACET_KEYS):
raise RequestError(
"Metric '{}' is faceted, but it\'s elements are not properly formatted. "
"Each facet must be a dictionary of '{\"facet\":\"facet_name\", \"value\": 1234}"
.format(k))
# remove empty facets
if m['faceted'] and not len(obj[k]):
obj.pop(k)
# parse numbers.
if not m['faceted']:
obj[k] = stats.parse_number(obj[k])
# parse facet values.
else:
for i, v in enumerate(obj[k]):
obj[k][i]['value'] = \
stats.parse_number(obj[k][i]['value'])
return obj
def valid_numeric(self, key, opt):
"""
Validate a numeric option.
"""
try:
return parse_number(opt)
except:
return RecipeSchemaError(
"{} is an 'numeric' field but was passed '{}'."
.format(key, opt))
def valid_numeric(self, key, opt):
"""
Validate a numeric option.
"""
try:
return parse_number(opt)
except:
return RecipeSchemaError(
"{} is an 'numeric' field but was passed '{}'."
.format(key, opt))
def list_metrics(user, org):
# optionally filter by type/level/category
include_recipes, exclude_recipes = \
arg_list('recipes', default=[], typ=str, exclusions=True)
include_sous_chefs, exclude_sous_chefs = \
arg_list('sous_chefs', default=[], typ=str, exclusions=True)
include_types, exclude_types = \
arg_list('types', default=[], typ=str, exclusions=True)
include_content_levels, exclude_content_levels = \
arg_list('content_levels', default=[], typ=str, exclusions=True)
include_org_levels, exclude_org_levels = \
arg_list('org_levels', default=[], typ=str, exclusions=True)
sort_field, direction = arg_sort('sort', default='display_name')
faceted = arg_bool('faceted', default=None)
# base query
metric_query = Metric.query.join(Recipe).join(SousChef)
# validate sort fields are part of Recipe object.
if sort_field:
validate_fields(Metric, fields=[sort_field], suffix='to sort by')
# filter by recipes
if len(include_recipes):
slugs = []
ids = []
for r in include_recipes:
try:
i = parse_number(r)
ids.append(i)
except:
slugs.append(r)
metric_query = metric_query\
.filter(or_(Recipe.id.in_(ids), Recipe.slug.in_(slugs)))
if len(exclude_recipes):
slugs = []
ids = []
for r in exclude_recipes:
try:
i = parse_number(r)
ids.append(i)
except:
slugs.append(r)
metric_query = metric_query\
.filter(~or_(Recipe.id.in_(ids), Recipe.slug.in_(slugs)))
# filter by sous-chefs
if len(include_sous_chefs):
slugs = []
ids = []
for r in include_sous_chefs:
try:
i = parse_number(r)
ids.append(i)
except:
slugs.append(r)
metric_query = metric_query\
.filter(or_(SousChef.id.in_(ids), SousChef.slug.in_(slugs)))
if len(exclude_sous_chefs):
slugs = []
ids = []
for r in exclude_sous_chefs:
try:
i = parse_number(r)
ids.append(i)
except:
slugs.append(r)
metric_query = metric_query\
.filter(~or_(SousChef.id.in_(ids), SousChef.slug.in_(slugs)))
# filter by levels
if len(include_types):
metric_query = metric_query\
.filter(Metric.type.in_(include_types))
if len(exclude_types):
metric_query = metric_query\
.filter(~Metric.type.in_(exclude_types))
# filter by levels
if len(include_content_levels):
metric_query = metric_query\
.filter(Metric.content_levels.contains(include_content_levels))
if len(exclude_content_levels):
metric_query = metric_query\
.filter(~Metric.content_levels.contains(exclude_content_levels))
if len(include_org_levels):
metric_query = metric_query\
.filter(Metric.org_levels.contains(include_org_levels))
if len(exclude_org_levels):
metric_query = metric_query\
.filter(~Metric.org_levels.contains(exclude_org_levels))
# filter by faceted
if faceted is not None:
metric_query = metric_query\
.filter(Metric.faceted == faceted)
if sort_field:
sort_obj = eval('Metric.{}.{}'.format(sort_field, direction))
metric_query = metric_query.order_by(sort_obj())
facets = defaultdict(Counter)
metrics = []
for m in metric_query.all():
facets['recipes'][m.recipe.slug] += 1
facets['types'][m.type] += 1
if 'faceted' in facets:
if m.faceted:
facets['faceted'] += 1
else:
facets['faceted'] = 0
for cl in m.content_levels:
facets['content_levels'][cl] += 1
for cl in m.org_levels:
facets['org_levels'][cl] += 1
metrics.append(m.to_dict())
resp = {
'metrics': metrics,
'facets': facets
}
return jsonify(resp)
