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Standardized DB Connections.

Project description

Description

A Python library by Dire Analytics to standardize database connections across platforms for more efficient data engineering.

Installation

pip install dbharbor
pip install git+https://github.com/edire/dbharbor.git

Code

import os
import dbharbor

# Microsoft SQL Server
from dbharbor.sql import SQL
con = SQL(
    server=os.getenv('SQL_SERVER'),
    db=os.getenv('SQL_DB'),
    uid=os.getenv('SQL_UID'),
    pwd=os.getenv('SQL_PWD'),
    driver='ODBC Driver 17 for SQL Server'
)

# MySQL Server
from dbharbor.mysql import SQL
con = SQL(
    server=os.getenv('MYSQL_SERVER'),
    db=os.getenv('MYSQL_DB'),
    uid=os.getenv('MYSQL_UID'),
    pwd=os.getenv('MYSQL_PWD'),
    port=3306
)

# BigQuery
from dbharbor.bigquery import SQL
con = SQL(
    credentials_filepath = os.getenv('BIGQUERY_CRED')
)

# To request additional database connections please reach out to eric.dire@direanalytics.com

# Read
df = con.read("select * from [table]")

# Run
con.run("drop table if exists [table]")

# Clean Dataframe before inserting into database
df = dbharbor.clean(df)

# Write DataFrame to table
con.to_sql(df, "[table]", schema="dbo", index=False, if_exists='fail')

# Or use the connection directly with pandas dataframe for SQL or MySQL
df.to_sql("[table]", con=con.con, schema="dbo", index=False, if_exists='fail')

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

License

MIT License

Updates

09/09/2024 - Update SQL Varchar datatype to use max when greater than 8000 characters.
08/12/2024 - Added datetime_us datatype and Bigquery storage library to setup for faster API.
11/06/2023 - Fixed dtype missing lower function in sql and mysql and now use python tempfile module.
11/03/2023 - fixed index name bigquery to_sql issue.
11/03/2023 - added clean_dtypes function and updated create_table dtypes.
10/20/2023 - Updated clean tool for empty column names, replaced empty strings with NaN.
10/04/2023 - Updated Bigquery data type mapping.
09/19/2023 - Added port option for MySQL.
08/12/2023 - Update for applymap deprecation and upper env vars.
07/07/2023 - Reverted MSSQL and MySQL Run logic in order to pick up proc errors.
06/29/2023 - Reverted MySQL engine to con.
06/16/2023 - Updated SQL and MySQL modules for SQLAlchemy 2.0.
04/23/2023 - Updated bigquery to remove string length restrictions. Added pyarrow to required libraries for bigquery to_dataframe function. Added db-dtypes to required libraries for bigquery.
03/27/2023 - Updated clean column function to convert to string before cleaning.
03/14/2023 - Updated data type amounts for float columns in sql and mysql.
03/13/2023 - Added **kwargs to create_table function across all to eliminate error of passing missing variables.
02/23/2023 - Updated class names for consistency.
02/22/2023 - Fixed run logic in SQL and MySQL to use autocommit appropriately. Removed parameters in SQL class.
02/20/2023 - Updated bigquery module to allow connections from cloud resources.
02/17/2023 - Updated MySQL for reading multiple statement queries into DataFrame.
02/10/2023 - Added full functionality to BigQuery module.
02/06/2023 - Updated MySQL connector to automatically password parse if necessary.
01/31/2023 - Added option to not drop columns in clean function.
01/09/2023 - Added openpyxl to dependencies on install.
01/08/2023 - Fixed duplicate RowLoadDateTime issue in create_table function for sql and mysql.
01/06/2023 - Added BigQuery module with read function. Updated MySQL RowLoadDateTime for new and old MySQL server versions.
01/05/2023 - Adjusted env variable default names for multiple connection types.
01/04/2023 - Added password parse option to MySQL.
12/31/2022 - Added SSAS module.
12/22/2022 - Added clean_string function to tools.
12/14/2022 - Added mysql module.

Project details


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