def build_object(cls, document_type: str, left_schema: Schema,
right_schema: Schema):
# Check if field exists under different name in schema.
# Field also can have small schema changes in the same time
# So we try to get similarity percentage and if it more than
# threshold then we're consider such change as rename/alter.
# Otherwise it is drop/create
match = document_type in left_schema and document_type not in right_schema
if not match:
return
is_left_embedded = document_type.startswith(
flags.EMBEDDED_DOCUMENT_NAME_PREFIX)
left_document_schema = left_schema[document_type]
candidates = []
for right_document_type, right_document_schema in right_schema.items():
matches = 0
compares = 0
# Skip collections which apparently was not renamed
if right_document_type in left_schema:
continue
# Prevent adding to 'candidates' a right document, which
# could have same/similar schema but has another type
# (embedded and usual and vice versa)
is_right_embedded = right_document_type.startswith(
flags.EMBEDDED_DOCUMENT_NAME_PREFIX)
if is_left_embedded != is_right_embedded:
continue
# Exact match, collection was just renamed. We found it
if left_document_schema == right_document_schema:
candidates = [(right_document_type, right_document_schema)]
break
# Count of equal fields and parameters items and then
# divide it on whole compared fields/parameters count
items = ((left_document_schema, right_document_schema),
(left_document_schema.parameters,
right_document_schema.parameters))
for left, right in items:
all_keys = left.keys() | right.keys()
compares += len(all_keys)
# FIXME: keys can be functions (default for instance)
# they will not be equal then dispite they hasn't change
matches += sum(left.get(k) == right.get(k) for k in all_keys)
if compares > 0 and (matches / compares *
100) >= cls.similarity_threshold:
candidates.append((right_document_type, right_document_schema))
if len(candidates) == 1:
return cls(document_type=document_type, new_name=candidates[0][0])
def build_object(cls, document_type: str, left_schema: Schema,
right_schema: Schema):
# Check if field exists under different name in schema.
# Field also can have small schema changes in the same time
# So we try to get similarity percentage and if it more than
# threshold then we're consider such change as rename/alter.
# Otherwise it is drop/create
match = document_type in left_schema and document_type not in right_schema
if not match:
return
left_document_schema = left_schema[document_type]
candidates = []
matches = 0
compares = 0
for right_document_type, right_document_schema in right_schema.items():
# Skip collections which was not renamed
if right_document_type in left_schema:
continue
# Exact match, collection was just renamed
if left_document_schema == right_document_schema:
candidates = [(right_document_type, right_document_schema)]
break
# Try to find collection by its schema similarity
# Compares are counted as every field schema comparing
common_fields = left_document_schema.keys(
) | right_document_schema.keys()
for field_name in common_fields:
left_field_schema = left_document_schema.get(field_name, {})
right_field_schema = right_document_schema.get(field_name, {})
common_keys = left_field_schema.keys(
) & right_field_schema.keys()
compares += len(common_keys)
matches += sum(left_field_schema[k] == right_field_schema[k]
for k in common_keys)
if compares > 0 and (matches / compares *
100) >= cls.similarity_threshold:
candidates.append((right_document_type, right_document_schema))
if len(candidates) == 1:
return cls(document_type=document_type, new_name=candidates[0][0])
def _verify_schema(self, schema: Schema):
# Check if all derived documents have the same collection as
# their parents.
# E.g. user could comment/remove AlterDocument(collection=...)
# for any derived document, but leave for base one)
collections = {} # {top_level_document: collection}
for document_type, doc_schema in schema.items():
if 'collection' not in doc_schema.parameters:
continue
col = doc_schema.parameters['collection']
top_lvl_doc = document_type.split(
runtime_flags.DOCUMENT_NAME_SEPARATOR)[0]
if top_lvl_doc in collections and collections[top_lvl_doc] != col:
log.warning(
f'The collection in derived document {document_type} ({col}) '
f'is differ than its base document {top_lvl_doc} '
f'({collections[top_lvl_doc]}). Please fix collection name and rerun '
f'an affected migration')
collections.setdefault(top_lvl_doc, col)