​
Add credentials

  1. Create a new pipeline or open an existing pipeline.
  2. Expand the left side of your screen to view the file browser.
  3. Scroll down and click on a file named io_config.yaml.
  4. Enter the following keys and values under the key named default (you can have multiple profiles, add it under whichever is relevant to you)
version: 0.1.1
default:
  MYSQL_DATABASE: ...
  MYSQL_HOST: ...
  MYSQL_PASSWORD: ...
  MYSQL_PORT: 3306
  MYSQL_USER: root

​
Using SQL block

  1. Create a new pipeline or open an existing pipeline.
  2. Add a data loader, transformer, or data exporter block.
  3. Select SQL.
  4. Under the Data provider/Connection dropdown, select Mysql.
  5. Under the Profile dropdown, select default (or the profile you added credentials underneath).
  6. Enter the optional table name of the table to write to.
  7. Under the Write policy dropdown, select Replace or Append (please see SQL blocks guide for more information on write policies).
  8. Enter in this test query: SELECT 1.
  9. Run the block.

​
Using Python block

​
Using MySQL connector

import mysql.connector

conn = mysql.connector.connect(
    host='...',
    password='...',
    port=3306,
    user='root',
    database='...',
)

sql = """
SELECT
  id
  , email
FROM auth_user
"""


cursor = conn.cursor()
cursor.execute(sql)

rows = cursor.fetchall()

import pandas as pd

df = pd.DataFrame(rows, columns=['id', 'email'])
df.to_csv('default_repo/users.csv', index=False)

​
Using Mage’s MySQL python blocks

  1. Create a Data Loader block from the MySQL Template

Example snippet:

from mage_ai.settings.repo import get_repo_path
from mage_ai.io.config import ConfigFileLoader
from mage_ai.io.mysql import MySQL
from os import path

@data_loader
def load_data_from_mysql(*args, **kwargs):
    """
    Template for loading data from a MySQL database.
    Specify your configuration settings in 'io_config.yaml'.

    Docs: https://docs.mage.ai/design/data-loading#mysql
    """
    query = 'Your MySQL query'  # Specify your SQL query here
    config_path = path.join(get_repo_path(), 'io_config.yaml')
    config_profile = 'default'

    with MySQL.with_config(ConfigFileLoader(config_path, config_profile)) as loader:
        return loader.load(query)
  1. Create a Data Exporter block from the MySQL Template

Example snippet:

from mage_ai.settings.repo import get_repo_path
from mage_ai.io.config import ConfigFileLoader
from mage_ai.io.mysql import MySQL
from pandas import DataFrame
from os import path

if 'data_exporter' not in globals():
    from mage_ai.data_preparation.decorators import data_exporter


@data_exporter
def export_data_to_mysql(df: DataFrame, **kwargs) -> None:
    """
    Template for exporting data to a MySQL database.
    Specify your configuration settings in 'io_config.yaml'.

    Docs: https://docs.mage.ai/design/data-loading#mysql
    """
    table_name = 'your_table_name'  # Specify the name of the table to export data to
    config_path = path.join(get_repo_path(), 'io_config.yaml')
    config_profile = 'default'

    with MySQL.with_config(ConfigFileLoader(config_path, config_profile)) as loader:
        loader.export(
            df,
            None,
            table_name,
            index=False,  # Specifies whether to include index in exported table
            if_exists='replace',  # Specify resolution policy if table name already exists
        )
  1. Custom types

To overwrite a column type when running a python export block, simply specify the column name and type in the overwrite_types dict in data exporter config

Here is an example code snippet:

from mage_ai.settings.repo import get_repo_path
from mage_ai.io.config import ConfigFileLoader
from mage_ai.io.mysql import MySQL
from pandas import DataFrame
from os import path

if 'data_exporter' not in globals():
    from mage_ai.data_preparation.decorators import data_exporter


@data_exporter
def export_data_to_mysql(df: DataFrame, **kwargs) -> None:
    """
    Template for exporting data to a MySQL database.
    Specify your configuration settings in 'io_config.yaml'.

    Docs: https://docs.mage.ai/design/data-loading#mysql
    """
    table_name = 'your_table_name'  # Specify the name of the table to export data to
    config_path = path.join(get_repo_path(), 'io_config.yaml')
    config_profile = 'default'
    overwrite_types = {'column_name': 'VARCHAR(255)'}

    with MySQL.with_config(ConfigFileLoader(config_path, config_profile)) as loader:
        loader.export(
            df,
            None,
            table_name,
            index=False,  # Specifies whether to include index in exported table
            if_exists='replace',  # Specify resolution policy if table name already exists
            overwrite_types=overwrite_types,
        )

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