Skip to main content

A DQ package

Project description

Requirements

pip install -r requirements.txt

Env

.env File

API_KEY=xyz
API_URL=xyz

Or Export variables

export API_KEY=xyz
export API_URL=xyz

Database User

GRANT USAGE on schema "validation" to anon;
GRANT SELECT, INSERT, UPDATE, DELETE ON ALL TABLES IN SCHEMA "validation" TO anon;
GRANT ALL ON SEQUENCE validation.rule_output_rule_output_id_seq TO anon;
GRANT ALL ON SEQUENCE validation. connections_connection_id_seq TO anon;
GRANT ALL ON SEQUENCE validation.owlcheck_q_job_id_seq TO anon;
GRANT ALL ON SEQUENCE validation.job_log_log_id_seq TO anon;
GRANT ALL ON SEQUENCE validation.assignment_q_id_seq TO anon;

Examples

"""
# Invididual Usage Examples 

#Client instantiation
api = APIClient(api_client)

engine = duckdb.connect(':memory:')
engine.sql(" select * from read_csv_auto('./data/fake_customers.csv') limit 10").show()
engine.close()

# owl_check_history, Delete, Insert, Read
api.delete_owl_check_history("test")
api.insert_owl_check_history("test", "2024-09-16")
rs = api.get_owl_check_history("test")
print(rs)

# owl_catalog, Delete, Insert, Read
api.delete_owl_catalog("test")
api.insert_owl_catalog("test")
rs = api.get_owl_catalog("test")
print(rs)

# dataset_schema, Delete, Insert, Read
api.delete_dataset_schema("test")
api.insert_dataset_schema("test")
rs = api.get_dataset_schema("test")
print(rs)

# dataset_field, Delete, Insert, Read
api.delete_dataset_field("test", "2024-09-16")
api.insert_dataset_field("test", "2024-09-16")
rs = api.get_dataset_field("test", "2024-09-16")
print(rs)

# Print the result
df = pd.DataFrame(rs.data)
print(df[['dataset','run_id','rc']])

# run rules 
api.delete_rule_output("test", "2024-09-16")
api.run_rules("test", "2024-09-16")

# scoring
rule_output = api.get_rule_output("test", "2024-09-16")
rule_score = 0
for r in rule_output.data:
    rule_score += r['score']
print(rule_score)

# dataset_scan, Delete, Insert, Read
delete_record = api.delete_dataset_scan("test", "2024-09-16")
add_record = api.insert_dataset_scan("test", "2024-09-16", 100, 100 - rule_score)

Register

dataset = 'test' 

# opt_spark
api.delete_opt_spark(dataset)
api.insert_opt_spark(dataset)
rs = api.get_opt_spark(dataset)
print(rs)
df = pd.DataFrame(rs.data)
display(df)

# opt_pushdown
api.delete_opt_pushdown(dataset)
api.insert_opt_pushdown(dataset)
rs = api.get_opt_pushdown(dataset)
print(rs)
df = pd.DataFrame(rs.data)
display(df)

# opt_profile
api.delete_opt_profile(dataset)
api.insert_opt_profile(dataset)
rs = api.get_opt_profile(dataset)
print(rs)
df = pd.DataFrame(rs.data)
display(df)

# opt_load
api.delete_opt_load(dataset)
api.insert_opt_load(dataset)
rs = api.get_opt_load(dataset)
print(rs)
df = pd.DataFrame(rs.data)
display(df)

# opt_profile
api.delete_opt_profile(dataset)
api.insert_opt_profile(dataset)
rs = api.get_opt_profile(dataset)
print(rs)
df = pd.DataFrame(rs.data)
display(df)

# opt_env
api.delete_opt_env(dataset)
api.insert_opt_env(dataset)
rs = api.get_opt_env(dataset)
print(rs)
df = pd.DataFrame(rs.data)
display(df)

# opt_owl
api.delete_opt_owl(dataset)
api.insert_opt_owl(dataset)
rs = api.get_opt_owl(dataset)
print(rs)
df = pd.DataFrame(rs.data)
display(df)

Job

dataset = 'test' 
run_id = '2024-09-20'
conn.sql(f"create table if not exists {dataset} as select * from read_csv_auto('./data/fake_customers.csv') ")

# owl_check_history, 
# Delete, Insert, Read
api.delete_owl_check_history(dataset)
api.insert_owl_check_history(dataset, run_id)
rs = api.get_owl_check_history(dataset)
print(rs)

# owl_catalog, 
# Delete, Insert, Read
api.delete_owl_catalog(dataset)
api.insert_owl_catalog(dataset)
rs = api.get_owl_catalog(dataset)
print(rs)

# dataset_schema, 
# Delete, Insert, Read
api.delete_dataset_schema(dataset)
api.insert_dataset_schema(dataset)
rs = api.get_dataset_schema(dataset)
print(rs)

# dataset_field, 
# Delete, Insert, Read
api.delete_dataset_field(dataset, run_id)
api.insert_dataset_field(dataset, run_id)
rs = api.get_dataset_field(dataset, run_id)
print(rs)

# run rules 
api.delete_rule_output(dataset, run_id)
api.run_rules(dataset, run_id)

# scoring
rule_output = api.get_rule_output(dataset, run_id)
print(rule_output.data)

rule_score = 0
for r in rule_output.data:
    rule_score += r['score']
print(str(rule_score))

# dataset_scan, 
# Delete, Insert, Read
delete_record = api.delete_dataset_scan(dataset, run_id)
add_record = api.insert_dataset_scan(dataset, run_id, 100, 100 - rule_score)
rs = api.get_dataset_scan(dataset, run_id)
print(rs.data)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

duckdq-0.0.3.tar.gz (2.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

duckdq-0.0.3-py3-none-any.whl (2.2 kB view details)

Uploaded Python 3

File details

Details for the file duckdq-0.0.3.tar.gz.

File metadata

  • Download URL: duckdq-0.0.3.tar.gz
  • Upload date:
  • Size: 2.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.4

File hashes

Hashes for duckdq-0.0.3.tar.gz
Algorithm Hash digest
SHA256 5b31fdfb05cdec8399d17fae82879fe1342941488739cad247a6a920a1912061
MD5 691bf0ff309a5065e6e11797e153c792
BLAKE2b-256 5eeb1a1f0c1e0a8a148c738f1a8cf99701ee975b1f97809aefe60d8fb924af04

See more details on using hashes here.

File details

Details for the file duckdq-0.0.3-py3-none-any.whl.

File metadata

  • Download URL: duckdq-0.0.3-py3-none-any.whl
  • Upload date:
  • Size: 2.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.4

File hashes

Hashes for duckdq-0.0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 8a3dc60333c89443a46694c620316a7b197ea046e88101ced17219864e14832c
MD5 133601b02b39769acb9d7a984109c014
BLAKE2b-256 ebc31612cc070f95349418f63c87459e638339fe26c1ac2ffdbeee0a93f7ba9c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page