def test_process_orgs_generates_org_cats_link_table(
self, valid_org_data, no_existing_orgs, valid_cat_groups,
valid_org_descs):
_, org_cats, _ = process_orgs(valid_org_data, no_existing_orgs,
valid_cat_groups, valid_org_descs)
expected_result = [{
'organization_id': '1-1',
'category_name': 'data'
}, {
'organization_id': '1-1',
'category_name': 'digital'
}, {
'organization_id': '1-1',
'category_name': 'cats'
}, {
'organization_id': '2-2',
'category_name': 'science'
}, {
'organization_id': '2-2',
'category_name': 'cats'
}, {
'organization_id': '3-3',
'category_name': 'data'
}]
assert org_cats == expected_result
def test_process_orgs_returns_missing_cat_groups(self, invalid_org_data,
no_existing_orgs,
valid_cat_groups,
valid_org_descs):
_, org_cats, missing_cat_groups = process_orgs(invalid_org_data,
no_existing_orgs,
valid_cat_groups,
valid_org_descs)
expected_org_cats = [{
'organization_id': '1-1',
'category_name': 'data'
}, {
'organization_id': '1-1',
'category_name': 'digital'
}, {
'organization_id': '1-1',
'category_name': 'dogs'
}, {
'organization_id': '2-2',
'category_name': 'science'
}, {
'organization_id': '2-2',
'category_name': 'cats'
}, {
'organization_id': '2-2',
'category_name': 'goats'
}]
missing_cats = {c['category_name'] for c in missing_cat_groups}
expected_missing_cat_groups = {'dogs', 'goats'}
assert org_cats == expected_org_cats
assert missing_cats == expected_missing_cat_groups
def test_process_orgs_removes_redundant_category_columns(
self, valid_org_data, no_existing_orgs, valid_cat_groups,
valid_org_descs):
processed_orgs, _, _ = process_orgs(valid_org_data, no_existing_orgs,
valid_cat_groups, valid_org_descs)
processed_orgs = pd.DataFrame(processed_orgs)
assert 'category_list' not in processed_orgs
assert 'category_group_list' not in processed_orgs
def test_process_orgs_removes_country_code_column(self, valid_org_data,
no_existing_orgs,
valid_cat_groups,
valid_org_descs):
processed_orgs, _, _ = process_orgs(valid_org_data, no_existing_orgs,
valid_cat_groups, valid_org_descs)
processed_orgs = pd.DataFrame(processed_orgs)
assert 'country_code' not in processed_orgs
def test_process_orgs_renames_uuid_column(self, valid_org_data,
no_existing_orgs,
valid_cat_groups,
valid_org_descs):
processed_orgs, _, _ = process_orgs(valid_org_data, no_existing_orgs,
valid_cat_groups, valid_org_descs)
processed_orgs = pd.DataFrame(processed_orgs)
assert 'id' in processed_orgs
assert 'uuid' not in processed_orgs
def test_process_orgs_correctly_applies_country_name(
self, valid_org_data, no_existing_orgs, valid_cat_groups,
valid_org_descs):
processed_orgs, _, _ = process_orgs(valid_org_data, no_existing_orgs,
valid_cat_groups, valid_org_descs)
processed_orgs = pd.DataFrame(processed_orgs)
expected_result = pd.Series(['France', 'Germany', 'United Kingdom'])
assert_series_equal(processed_orgs['country'],
expected_result,
check_names=False)
def test_process_orgs_removes_existing_orgs(self, valid_org_data,
existing_orgs,
valid_cat_groups,
valid_org_descs):
processed_orgs, _, _ = process_orgs(valid_org_data, existing_orgs,
valid_cat_groups, valid_org_descs)
processed_orgs = pd.DataFrame(processed_orgs)
expected_result = pd.Series(['1-1'])
assert_series_equal(processed_orgs['id'],
expected_result,
check_names=False)
def test_process_orgs_inserts_none_if_composite_key_fails(
self, invalid_org_data, no_existing_orgs, valid_cat_groups,
valid_org_descs):
processed_orgs, _, _ = process_orgs(invalid_org_data, no_existing_orgs,
valid_cat_groups, valid_org_descs)
processed_orgs = pd.DataFrame(processed_orgs)
expected_result = pd.Series(
[None, 'berlin_germany', 'london_united-kingdom'])
assert_series_equal(processed_orgs.location_id,
expected_result,
check_names=False)
def test_process_orgs_generates_location_id_composite_keys(
self, valid_org_data, no_existing_orgs, valid_cat_groups,
valid_org_descs):
processed_orgs, _, _ = process_orgs(valid_org_data, no_existing_orgs,
valid_cat_groups, valid_org_descs)
processed_orgs = pd.DataFrame(processed_orgs)
expected_result = pd.Series(
['paris_france', 'berlin_germany', 'london_united-kingdom'])
assert_series_equal(processed_orgs.location_id,
expected_result,
check_names=False)
def test_process_orgs_inserts_none_for_unfound_long_descriptions(
self, valid_org_data, no_existing_orgs, valid_cat_groups,
invalid_org_descs):
processed_orgs, _, _ = process_orgs(valid_org_data, no_existing_orgs,
valid_cat_groups,
invalid_org_descs)
processed_orgs = pd.DataFrame(processed_orgs)
expected_result = pd.DataFrame({
'id': ['1-1', '2-2', '3-3'],
'long_description': [None, 'org two', 'org three']
})
assert_frame_equal(processed_orgs[['id', 'long_description']],
expected_result,
check_like=True)
def run(self):
"""Collect and process organizations, categories and long descriptions."""
# database setup
database = 'dev' if self.test else 'production'
logging.warning(f"Using {database} database")
self.engine = get_mysql_engine(self.db_config_env, 'mysqldb', database)
try_until_allowed(Base.metadata.create_all, self.engine)
# collect files
nrows = 200 if self.test else None
cat_groups, orgs, org_descriptions = get_files_from_tar(
['category_groups', 'organizations', 'organization_descriptions'],
nrows=nrows)
# process category_groups
cat_groups = rename_uuid_columns(cat_groups)
insert_data(self.db_config_env,
'mysqldb',
database,
Base,
CategoryGroup,
cat_groups.to_dict(orient='records'),
low_memory=True)
# process organizations and categories
with db_session(self.engine) as session:
existing_orgs = session.query(Organization.id).all()
existing_orgs = {org[0] for org in existing_orgs}
logging.info("Summary of organisation data:")
logging.info(f"Total number of organisations:\t {len(orgs)}")
logging.info(
f"Number of organisations already in the database:\t {len(existing_orgs)}"
)
logging.info(f"Number of category groups and text descriptions:\t"
f"{len(cat_groups)}, {len(org_descriptions)}")
processed_orgs, org_cats, missing_cat_groups = process_orgs(
orgs, existing_orgs, cat_groups, org_descriptions)
# Insert CatGroups
insert_data(self.db_config_env, 'mysqldb', database, Base,
CategoryGroup, missing_cat_groups)
# Insert orgs in batches
n_batches = round(len(processed_orgs) / self.insert_batch_size)
logging.info(
f"Inserting {n_batches} batches of size {self.insert_batch_size}")
for i, batch in enumerate(
split_batches(processed_orgs, self.insert_batch_size)):
if i % 100 == 0:
logging.info(f"Inserting batch {i} of {n_batches}")
insert_data(self.db_config_env,
'mysqldb',
database,
Base,
Organization,
batch,
low_memory=True)
# link table needs to be inserted via non-bulk method to enforce relationship
logging.info("Filtering duplicates...")
org_cats, existing_org_cats, failed_org_cats = filter_out_duplicates(
self.db_config_env,
'mysqldb',
database,
Base,
OrganizationCategory,
org_cats,
low_memory=True)
logging.info(
f"Inserting {len(org_cats)} org categories "
f"({len(existing_org_cats)} already existed and {len(failed_org_cats)} failed)"
)
#org_cats = [OrganizationCategory(**org_cat) for org_cat in org_cats]
with db_session(self.engine) as session:
session.add_all(org_cats)
# mark as done
self.output().touch()