DataSae 0.4.0

Data Quality Framework provides by Jabar Digital Service

DataSae

Data Quality Framework provides by Jabar Digital Service

Converter

https://github.com/jabardigitalservice/DataSae/blob/46ef80072b98ca949084b4e1ae50bcf23d07d646/tests/data/config.json#L1-L183

https://github.com/jabardigitalservice/DataSae/blob/46ef80072b98ca949084b4e1ae50bcf23d07d646/tests/data/config.yaml#L1-L120

Local Computer

pip install 'DataSae[converter]'

from datasae.converter import Config

# From JSON
config = Config('DataSae/tests/data/config.json')

# From YAML
config = Config('DataSae/tests/data/config.yaml')

# Local computer file to DataFrame
local = config('test_local')

df = local('path/file_name.csv', sep=',')
df = local('path/file_name.json')
df = local('path/file_name.parquet')
df = local('path/file_name.xlsx', sheet_name='Sheet1')

df = local('path/file_name.csv')  # Default: sep = ','
df = local('path/file_name.json')
df = local('path/file_name.parquet')
df = local('path/file_name.xlsx')  # Default: sheet_name = 'Sheet1'

Google Spreadsheet

https://github.com/jabardigitalservice/DataSae/blob/4308324d066c6627936773ab2d5b990adaa60100/tests/data/creds.json#L1-L12

pip install 'DataSae[converter,gsheet]'

from datasae.converter import Config

# From JSON
config = Config('DataSae/tests/data/config.json')

# From YAML
config = Config('DataSae/tests/data/config.yaml')

# Google Spreadsheet to DataFrame
gsheet = config('test_gsheet')
df = gsheet('Sheet1')
df = gsheet('Sheet1', 'gsheet_id')

S3

pip install 'DataSae[converter,s3]'

from datasae.converter import Config

# From JSON
config = Config('DataSae/tests/data/config.json')

# From YAML
config = Config('DataSae/tests/data/config.yaml')

# S3 object to DataFrame
s3 = config('test_s3')

df = s3('path/file_name.csv', sep=',')
df = s3('path/file_name.json')
df = s3('path/file_name.parquet')
df = s3('path/file_name.xlsx', sheet_name='Sheet1')

df = s3('path/file_name.csv', 'bucket_name')  # Default: sep = ','
df = s3('path/file_name.json', 'bucket_name')
df = s3('path/file_name.parquet', 'bucket_name')
df = s3('path/file_name.xlsx', 'bucket_name')  # Default: sheet_name = 'Sheet1'

SQL

pip install 'DataSae[converter,sql]'

MariaDB or MySQL

from datasae.converter import Config

# From JSON
config = Config('DataSae/tests/data/config.json')

# From YAML
config = Config('DataSae/tests/data/config.yaml')

# MariaDB or MySQL to DataFrame
mariadb_or_mysql = config('test_mariadb_or_mysql')
df = mariadb_or_mysql('select 1 column_name from schema_name.table_name;')
df = mariadb_or_mysql('path/file_name.sql')

PostgreSQL

from datasae.converter import Config

# From JSON
config = Config('DataSae/tests/data/config.json')

# From YAML
config = Config('DataSae/tests/data/config.yaml')

# PostgreSQL to DataFrame
postgresql = config('test_postgresql')
df = postgresql('select 1 column_name from schema_name.table_name;')
df = postgresql('path/file_name.sql')

Checker for Data Quality

from datasae.converter import Config

# From JSON
config = Config('DataSae/tests/data/config.json')

# From YAML
config = Config('DataSae/tests/data/config.yaml')

# Check all data qualities on configuration
config.checker  # dict result

# Check data quality by config name
config('test_local').checker  # list of dict result
config('test_gsheet').checker  # list of dict result
config('test_s3').checker  # list of dict result
config('test_mariadb_or_mysql').checker  # list of dict result
config('test_postgresql').checker  # list of dict result

Example results: https://github.com/jabardigitalservice/DataSae/blob/46ef80072b98ca949084b4e1ae50bcf23d07d646/tests/data/checker.json#L1-L432