Wrapper for sqlalchemy engine that provides functions for handoff with pandas
Project description
SQLBear is a lightweight wrapper around SQLAlchemy and Pandas to simplify SQL interactions.
Installation
pip install sqlbear
Usage
from sqlbear import SQLBear
from datetime import datetime
# Connects to sqlite database
connection_str = "sqlite:///example.db"
sqlbear = SQLBear(connection_str)
# Query account and user tables
df = sqlbear.read_sql_query("SELECT * FROM users JOIN account ON users.account = account.id WHERE lastUpdated > DATE_SUB(CURRENT_DATE(), INTERVAL 1 DAY)")
# Perform some transformation
df['added_to_report'] = datetime.now()
# Write to new or existing sql table, handling new columns, mismatched sql types, timezone issues if present, and duplicates across the user_id column
nob_bear.put_table(
'account_users',
'user_id',
df,
['id','user_id']
)
Features
Efficient SQL querying with progress bars
Automatic handling of time zones and schema updates
Simple table insertion and schema validation
Project details
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