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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)

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Standard connection

version: 0.1.1
default:
  MYSQL_DATABASE: ...
  MYSQL_HOST: ...
  MYSQL_PASSWORD: ...
  MYSQL_PORT: 3306
  MYSQL_USER: root

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SSH tunnel connection

If your MySQL database is in a private network and you need to connect via an SSH bastion host, Mage Pro supports configuring an SSH tunnel directly in io_config.yaml: 
version: 0.1.1
default:
  MYSQL_DATABASE: ...
  MYSQL_HOST: ...
  MYSQL_PASSWORD: ...
  MYSQL_PORT: 3306
  MYSQL_USER: root

  # Pro only: SSH tunnel settings
  MYSQL_SSH_HOST: bastion.example.com
  MYSQL_SSH_PORT: 22
  MYSQL_SSH_USERNAME: ec2-user
  # Use one of the following for authentication:
  MYSQL_SSH_PKEY: /path/to/private/key.pem   # path to SSH private key
  MYSQL_SSH_PASSWORD: your_ssh_password      # only if using password auth
  • MYSQL_SSH_HOST: Hostname or IP of the SSH bastion.
  • MYSQL_SSH_PORT: SSH port (default 22).
  • MYSQL_SSH_USERNAME: SSH user to log in as.
  • MYSQL_SSH_PKEY: Path to private key file (preferred).
  • MYSQL_SSH_PASSWORD: Password for SSH user (alternative to key).
⚠️ You only need either MYSQL_SSH_PKEY or MYSQL_SSH_PASSWORD, not both.

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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.

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Using Python block

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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)

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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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Method arguments

Field nameDescriptionExample values
allow_reserved_wordsWhether to allow using reserved words as column names.True/False (default: False)
auto_clean_nameWhether to automatically clean the column name (replace the empty space with underscore, avoid using number as the prefix of the column name)True/False (default: True)
case_sensitiveWhether to support case sensitive columnsTrue/False (default: False)
drop_table_on_replaceWhether to drop the table when “if_exists” param is set to “replace”.True/False (default: False)
if_existsSpecify resolution policy if table name already exists”fail”/“replace”/“append” (default: “replace”)
overwrite_typesOverwrite the column types{'column1': 'INTEGER', 'column2': 'VARCHAR(255)'}
unique_conflict_methodHow to handle the conflict on unique constraints. Use ‘UPDATE’ for UPSERT (update existing rows, insert new ones) or ‘IGNORE’ to skip duplicates.‘UPDATE’ or ‘IGNORE’ (default: None)
unique_constraintsThe unique constraints of the table. Used with unique_conflict_method for UPSERT operations.[‘col1’, ‘col2’] (default: None)
Example: Using UPSERT (UPDATE or INSERT) 
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 with UPSERT support.
    Specify your configuration settings in 'io_config.yaml'.

    Docs: https://docs.mage.ai/design/data-loading#mysql
    """
    table_name = 'your_table_name'
    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,
            if_exists='append',  # Use 'append' with UPSERT
            unique_constraints=['user_id', 'email'],  # Columns that form unique constraint
            unique_conflict_method='UPDATE',  # Update existing rows, insert new ones
        )