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db_utils.py
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db_utils.py
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import json
from unidecode import unidecode
import pandas as pd
UNMODIFIED = 0
INSERT = 1
UPDATE = 2
def normalize_entity_name(entity_name):
return unidecode(entity_name.lower().strip())
class NotOne(ValueError):
pass
class DBUtils:
# TODO create bulk inserts for every create? what type should they return?
def __init__(self, cursor):
self.cursor = cursor
self.counts = {
"tags_inserted": 0,
"tags_updated": 0,
"entities_inserted": 0,
"datasets_inserted": 0,
"datasets_updated": 0,
"namespaces_inserted": 0,
"namespaces_updated": 0,
"variables_inserted": 0,
"variables_updated": 0,
"sources_inserted": 0,
"sources_updated": 0,
}
self.entity_id_by_normalised_name = {}
def get_counts(self):
return self.counts
def get_entity_cache(self):
return self.entity_id_by_normalised_name
def fetch_one_or_none(self, *args, **kwargs):
self.cursor.execute(*args, **kwargs)
rows = self.cursor.fetchall()
if len(rows) > 1:
raise NotOne("Expected 1 or 0 rows but received %d" % (len(rows)))
elif len(rows) == 1:
return rows[0]
else:
return None
def fetch_one(self, *args, **kwargs):
result = self.fetch_one_or_none(*args, **kwargs)
if result is None:
raise NotOne("Expected 1 row but received 0")
else:
return result
def fetch_many(self, *args, **kwargs):
self.cursor.execute(*args, **kwargs)
return self.cursor.fetchall()
def insert_one(self, *args, **kwargs):
self.cursor.execute(*args, **kwargs)
return self.cursor.lastrowid
def upsert_one(self, *args, **kwargs):
self.cursor.execute(*args, **kwargs)
if self.cursor.rowcount == 0:
return UNMODIFIED
if self.cursor.rowcount == 1:
return INSERT
if self.cursor.rowcount == 2:
return UPDATE
return None
def upsert_many(self, query, tuples):
self.cursor.executemany(query, tuples)
def execute_until_empty(self, *args, **kwargs):
first = True
while first or self.cursor.rowcount > 0:
first = False
self.cursor.execute(*args, **kwargs)
def __fetch_parent_tag(self, name):
(tag_id,) = self.fetch_one(
"""
SELECT id FROM tags
WHERE name = %s
AND isBulkImport = TRUE
AND parentId IS NULL
LIMIT 1
""",
[name],
)
return tag_id
def upsert_parent_tag(self, name):
try:
return self.__fetch_parent_tag(name)
except NotOne:
self.upsert_one(
"""
INSERT INTO tags (name, createdAt, updatedAt, isBulkImport)
VALUES (%s, NOW(), NOW(), TRUE)
""",
[name],
)
self.counts["tags_inserted"] += 1
return self.__fetch_parent_tag(name)
def upsert_tag(self, name, parent_id):
operation = self.upsert_one(
"""
INSERT INTO
tags (name, parentId, createdAt, updatedAt, isBulkImport)
VALUES
(%s, %s, NOW(), NOW(), TRUE)
ON DUPLICATE KEY UPDATE
updatedAt = VALUES(updatedAt),
isBulkImport = VALUES(isBulkImport)
""",
[name, parent_id],
)
if operation == INSERT:
self.counts["tags_inserted"] += 1
elif operation == UPDATE:
self.counts["tags_updated"] += 1
(tag_id,) = self.fetch_one(
"""
SELECT id FROM tags
WHERE name = %s
AND parentId = %s
""",
[name, parent_id],
)
return tag_id
def associate_dataset_tag(self, dataset_id, tag_id):
self.upsert_one(
"""
INSERT INTO dataset_tags
(datasetId, tagId)
VALUES
(%s, %s)
ON DUPLICATE KEY UPDATE
tagId = VALUES(tagId)
""",
[dataset_id, tag_id],
)
# ON DUPLICATE here only avoids error, it intentionally updates nothing
def upsert_dataset(
self,
name,
namespace,
user_id,
tag_id=None,
description="This is a dataset imported by the automated fetcher",
):
operation = self.upsert_one(
"""
INSERT INTO datasets
(name, description, namespace, createdAt, createdByUserId, updatedAt, metadataEditedAt, metadataEditedByUserId, dataEditedAt, dataEditedByUserId)
VALUES
(%s, %s, %s, NOW(), %s, NOW(), NOW(), %s, NOW(), %s)
ON DUPLICATE KEY UPDATE
name = VALUES(name),
description = VALUES(description),
namespace = VALUES(namespace),
updatedAt = VALUES(updatedAt),
metadataEditedAt = VALUES(metadataEditedAt),
metadataEditedByUserId = VALUES(metadataEditedByUserId),
dataEditedAt = VALUES(dataEditedAt),
dataEditedByUserId = VALUES(dataEditedByUserId)
""",
[name, description, namespace, user_id, user_id, user_id],
)
(dataset_id,) = self.fetch_one(
"""
SELECT id FROM datasets
WHERE name = %s
AND namespace = %s
""",
[name, namespace],
)
if operation == INSERT:
self.counts["datasets_inserted"] += 1
if operation == UPDATE:
self.counts["datasets_updated"] += 1
if tag_id is not None:
self.associate_dataset_tag(dataset_id, tag_id)
return dataset_id
def upsert_namespace(self, name, description):
operation = self.upsert_one(
"""
INSERT INTO namespaces
(name, description)
VALUES
(%s, %s)
ON DUPLICATE KEY UPDATE
name = VALUES(name),
description = VALUES(description)
""",
[name, description],
)
(namespace_id,) = self.fetch_one(
"""
SELECT id FROM namespaces
WHERE name = %s
""",
[name],
)
if operation == INSERT:
self.counts["namespaces_inserted"] += 1
if operation == UPDATE:
self.counts["namespaces_updated"] += 1
return namespace_id
def upsert_source(self, name, description, dataset_id):
# There is no UNIQUE key constraint we can rely on to prevent duplicates
# so we have to do a SELECT before INSERT...
desc_json = json.loads(description)
query = """
SELECT id FROM sources
WHERE name = %(name)s
AND IF(%(dataPublishedBy)s IS NULL, description->>"$.dataPublishedBy" IS NULL OR description->>"$.dataPublishedBy" = 'null', description->"$.dataPublishedBy" = %(dataPublishedBy)s)
AND IF(%(dataPublisherSource)s IS NULL, description->>"$.dataPublisherSource" IS NULL OR description->>"$.dataPublisherSource" = 'null', description->"$.dataPublisherSource" = %(dataPublisherSource)s)
AND IF(%(additionalInfo)s IS NULL, description->>"$.additionalInfo" IS NULL OR description->>"$.additionalInfo" = 'null', description->"$.additionalInfo" = %(additionalInfo)s)
"""
if pd.isnull(dataset_id):
query += "AND datasetId IS NULL"
else:
query += f"AND datasetId = {dataset_id}"
row = self.fetch_one_or_none(
query,
{
"name": name,
"dataPublishedBy": desc_json.get("dataPublishedBy"),
"dataPublisherSource": desc_json.get("dataPublisherSource"),
"additionalInfo": desc_json.get("additionalInfo"),
},
)
if row is None:
if pd.isnull(dataset_id):
self.upsert_one(
"""
INSERT INTO sources (name, description, createdAt, updatedAt)
VALUES (%s, %s, NOW(), NOW())
""",
[name, description],
)
else:
self.upsert_one(
"""
INSERT INTO sources (name, description, datasetId, createdAt, updatedAt)
VALUES (%s, %s, %s, NOW(), NOW())
""",
[name, description, dataset_id],
)
self.counts["sources_inserted"] += 1
row = self.fetch_one(
query,
{
"name": name,
"dataPublishedBy": desc_json.get("dataPublishedBy"),
"dataPublisherSource": desc_json.get("dataPublisherSource"),
"additionalInfo": desc_json.get("additionalInfo"),
},
)
else:
self.cursor.execute(
"""
UPDATE sources
SET updatedAt = NOW(),
description = %(description)s
WHERE id = %(id)s
""",
{"description": description, "id": row[0]},
)
self.counts["sources_updated"] += 1
return row[0]
def upsert_variable(
self,
name,
code,
unit,
short_unit,
source_id,
dataset_id,
description=None,
timespan="",
coverage="",
display=None,
original_metadata=None,
):
if display is None or display == "":
display = {}
if original_metadata is None or original_metadata == "":
original_metadata = {}
if not isinstance(display, str):
display = json.dumps(display)
if not isinstance(original_metadata, str):
original_metadata = json.dumps(original_metadata)
operation = self.upsert_one(
"""
INSERT INTO variables (
name, code, description, unit, shortUnit, timespan, coverage,
display, originalMetadata, sourceId, datasetId, createdAt,
updatedAt
)
VALUES
(%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, NOW(), NOW())
ON DUPLICATE KEY UPDATE
name = VALUES(name),
code = VALUES(code),
description = VALUES(description),
unit = VALUES(unit),
shortUnit = VALUES(shortUnit),
timespan = VALUES(timespan),
coverage = VALUES(coverage),
display = VALUES(display),
originalMetadata = VALUES(originalMetadata),
datasetId = VALUES(datasetId),
sourceId = VALUES(sourceId),
datasetId = VALUES(datasetId),
updatedAt = VALUES(updatedAt)
""",
[
name,
code,
description,
unit,
short_unit,
timespan,
coverage,
display,
original_metadata,
source_id,
dataset_id,
],
)
if operation == INSERT:
self.counts["variables_inserted"] += 1
elif operation == UPDATE:
self.counts["variables_updated"] += 1
(var_id,) = self.fetch_one(
"""
SELECT id FROM variables
WHERE (name = %s OR code = %s)
AND datasetId = %s
AND sourceId = %s
""",
[name, code, dataset_id, source_id],
)
return var_id
def touch_variable(self, var_id):
self.cursor.execute(
"""
UPDATE variables
SET updatedAt = NOW()
WHERE id = %s
""",
[var_id],
)
self.counts["variables_updated"] += self.cursor.rowcount
def note_import(self, import_type, import_notes, import_state):
self.upsert_one(
"""
INSERT INTO importer_importhistory (import_type, import_time, import_notes, import_state)
VALUES (%s, NOW(), %s, %s)
""",
[import_type, import_notes, import_state],
)
def __get_cached_entity_id(self, name):
normalised_name = normalize_entity_name(name)
if normalised_name in self.entity_id_by_normalised_name:
return self.entity_id_by_normalised_name[normalised_name]
else:
return None
def get_or_create_entity(self, name):
# Serve from cache if available
entity_id = self.__get_cached_entity_id(name)
if entity_id is not None:
return entity_id
# Populate cache from database
self.prefill_entity_cache([name])
entity_id = self.__get_cached_entity_id(name)
if entity_id is not None:
return entity_id
# If still not in cache, it's a new entity and we have to insert it
else:
self.upsert_one(
"""
INSERT INTO entities
(name, displayName, validated, createdAt, updatedAt)
VALUES
(%s, '', FALSE, NOW(), NOW())
""",
[name],
)
self.counts["entities_inserted"] += 1
(entity_id,) = self.fetch_one(
"""
SELECT id FROM entities
WHERE name = %s
""",
[name],
)
# Cache the newly created entity
self.entity_id_by_normalised_name[normalize_entity_name(name)] = entity_id
return entity_id
def prefill_entity_cache(self, names):
rows = self.fetch_many(
"""
SELECT
LOWER(country_name),
LOWER(entities.name),
entities.id AS id
FROM entities
LEFT JOIN
country_name_tool_countrydata
ON country_name_tool_countrydata.owid_name = entities.name
LEFT JOIN
country_name_tool_countryname
ON country_name_tool_countryname.owid_country = country_name_tool_countrydata.id
WHERE
LOWER(country_name) IN %(country_names)s
OR LOWER(entities.name) IN %(country_names)s
ORDER BY entities.id ASC
""",
{"country_names": [normalize_entity_name(x) for x in names]},
)
# Merge the two dicts
self.entity_id_by_normalised_name.update(
{
# entityName → entityId
**dict((row[1], row[2]) for row in rows if row[1]),
# country_tool_name → entityId
# the country tool name should take precedence
**dict((row[0], row[2]) for row in rows if row[0]),
}
)