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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

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