sqlalchemy-helper-tool 1.4.11

Package to work with mysql database from python

sqlalchemy_helper_tool

A lightweight Python utility class for simplified interaction with MySQL databases using SQLAlchemy and Pandas. It provides convenient methods to read, write, and modify data or schema with minimal boilerplate.

Features

• Easy connection setup to a MySQL database using SQLAlchemy
• Execute raw SQL queries
• Inspect tables and columns
• Read SQL results into Pandas DataFrames
• Append, replace, or ignore duplicate rows when writing
• Dynamically add or remove columns
• Parameterized queries
• Auto-handle nulls in inserts
• Safe "replace" of data while preserving table schema

Installation

Install via pip (requires sqlalchemy, pymysql, and pandas):

pip install sqlalchemy_helper_tool

Clone this repository if needed:

git clone https://github.com/anakings/sqlalchemy_helper_tool.git

Usage

from sqlalchemy_helper_tool import DbApi

db = DbApi(
    server='localhost',
    database='my_db',
    username='user',
    password='pass'
)

# Run a SQL query
result = db.execute_query("SELECT COUNT(*) FROM users")

# Read a SQL query as DataFrame
df = db.read_sql("SELECT * FROM users LIMIT 10")

# Check if a table exists
exists = db.table_in_db("users")

# Add a new column after an existing one
db.add_column("users", "new_col", "existing_col")

# Write DataFrame ignoring duplicates
db.write_sql_key(df, "users")

# Append rows to an existing table
db.write_sql_df_append(df, "users")

# Replace all data in a table but keep schema
db.write_sql_df_replace(df, "users")

# Replace values in a specific column using a key
db.replace_sql_values(df, "users", column_replace="status", columns_key="id")

# Delete all rows in a table
db.delete_table("users")

# Drop a column
db.delete_column("users", "new_col")

Class: DbApi

Initialization

DbApi(server, database, username, password, dict_params=None)

Key Methods

Method	Description
execute_query(query)	Executes a raw SQL query
read_sql(query, dict_params=None)	Executes a SQL query and returns a DataFrame
table_in_db(table_name)	Checks if table exists
table_info(table_name)	Returns column metadata
read_columns_table_db(table_name)	Returns column names as list
add_column(table_name, column_name, after_column)	Adds a column
delete_column(table_name, column_name)	Removes a column
delete_table(table_name)	Deletes all rows in a table
write_sql_key(df, table_name)	Inserts ignoring duplicates
write_sql_key2(df, table_name)	Like above, but handles nulls and escapes column names
write_sql_df_append(df, table_name)	Appends to table
write_sql_df_replace(df, table_name)	Deletes all rows and inserts new ones, preserving schema
replace_sql_values(df, table_name, column_replace, columns_key)	Replaces specific values via ON DUPLICATE KEY UPDATE

Requirements

• Python 3.6+
• SQLAlchemy
• pymysql
• pandas

License

MIT License

Author

Anabel Reyes