Data exporter templates

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


@data_exporter
def export_data(*args, **kwargs):
    """
    Exports data to some source

    Args:
        args: The input variables from upstream blocks

    Output (optional):
        Optionally return any object and it'll be logged and
        displayed when inspecting the block run.
    """
    # Specify your data exporting logic here

from mage_ai.io.file import FileIO
from pandas import DataFrame

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


@data_exporter
def export_data_to_file(df: DataFrame, **kwargs) -> None:
    """
    Template for exporting data to filesystem.

    Docs: /design/data-loading#fileio
    """
    filepath = 'path/to/write/dataframe/to.csv'
    FileIO().export(df, filepath)

from mage_ai.settings.repo import get_repo_path
from mage_ai.io.azure_blob_storage import AzureBlobStorage
from mage_ai.io.config import ConfigFileLoader
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_azure_blob_storage(df: DataFrame, **kwargs) -> None:
    """
    Template for exporting data to a Azure Blob Storage.
    Specify your configuration settings in 'io_config.yaml'.

    Docs: /design/data-loading
    """
    config_path = path.join(get_repo_path(), 'io_config.yaml')
    config_profile = 'default'

    container_name = 'your_container_name'
    blob_path = 'your_blob_path'

    AzureBlobStorage.with_config(ConfigFileLoader(config_path, config_profile)).export(
        df,
        container_name,
        blob_path,
    )

from mage_ai.settings.repo import get_repo_path
from mage_ai.io.bigquery import BigQuery
from mage_ai.io.config import ConfigFileLoader
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_big_query(df: DataFrame, **kwargs) -> None:
    """
    Template for exporting data to a BigQuery warehouse.
    Specify your configuration settings in 'io_config.yaml'.

    Docs: /design/data-loading#bigquery
    """
    table_id = 'your-project.your_dataset.your_table_name'
    config_path = path.join(get_repo_path(), 'io_config.yaml')
    config_profile = 'default'

    BigQuery.with_config(ConfigFileLoader(config_path, config_profile)).export(
        df,
        table_id,
        if_exists='replace',  # Specify resolution policy if table name already exists
    )

from mage_ai.settings.repo import get_repo_path
from mage_ai.io.config import ConfigFileLoader
from mage_ai.io.google_cloud_storage import GoogleCloudStorage
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_google_cloud_storage(df: DataFrame, **kwargs) -> None:
    """
    Template for exporting data to a Google Cloud Storage bucket.
    Specify your configuration settings in 'io_config.yaml'.

    Docs: /design/data-loading#googlecloudstorage
    """
    config_path = path.join(get_repo_path(), 'io_config.yaml')
    config_profile = 'default'

    bucket_name = 'your_bucket_name'
    object_key = 'your_object_key'

    GoogleCloudStorage.with_config(ConfigFileLoader(config_path, config_profile)).export(
        df,
        bucket_name,
        object_key,
    )

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: /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
        )

from mage_ai.settings.repo import get_repo_path
from mage_ai.io.config import ConfigFileLoader
from mage_ai.io.postgres import Postgres
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_postgres(df: DataFrame, **kwargs) -> None:
    """
    Template for exporting data to a PostgreSQL database.
    Specify your configuration settings in 'io_config.yaml'.

    Docs: /design/data-loading#postgresql
    """
    schema_name = 'your_schema_name'  # Specify the name of the schema to export data to
    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 Postgres.with_config(ConfigFileLoader(config_path, config_profile)) as loader:
        loader.export(
            df,
            schema_name,
            table_name,
            index=False,  # Specifies whether to include index in exported table
            if_exists='replace',  # Specify resolution policy if table name already exists
        )

from mage_ai.settings.repo import get_repo_path
from mage_ai.io.config import ConfigFileLoader
from mage_ai.io.redshift import Redshift
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_redshift(df: DataFrame, **kwargs) -> None:
    """
    Template for exporting data to a Redshift cluster.
    Specify your configuration settings in 'io_config.yaml'.

    Docs: /design/data-loading#redshift
    """
    table_name = 'your_table_name'
    config_path = path.join(get_repo_path(), 'io_config.yaml')
    config_profile = 'default'

    with Redshift.with_config(ConfigFileLoader(config_path, config_profile)) as loader:
        loader.export(
            df,
            table_name,
            if_exists='replace',  # Specify resolution policy if table already exists
        )

from mage_ai.settings.repo import get_repo_path
from mage_ai.io.config import ConfigFileLoader
from mage_ai.io.s3 import S3
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_s3(df: DataFrame, **kwargs) -> None:
    """
    Template for exporting data to a S3 bucket.
    Specify your configuration settings in 'io_config.yaml'.

    Docs: /design/data-loading#s3
    """
    config_path = path.join(get_repo_path(), 'io_config.yaml')
    config_profile = 'default'

    bucket_name = 'your_bucket_name'
    object_key = 'your_object_key'

    S3.with_config(ConfigFileLoader(config_path, config_profile)).export(
        df,
        bucket_name,
        object_key,
    )

from mage_ai.settings.repo import get_repo_path
from mage_ai.io.config import ConfigFileLoader
from mage_ai.io.snowflake import Snowflake
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_snowflake(df: DataFrame, **kwargs) -> None:
    """
    Template for exporting data to a Snowflake warehouse.
    Specify your configuration settings in 'io_config.yaml'.

    Docs: /design/data-loading#snowflake
    """
    table_name = 'your_table_name'
    database = 'your_database_name'
    schema = 'your_schema_name'
    config_path = path.join(get_repo_path(), 'io_config.yaml')
    config_profile = 'default'

    with Snowflake.with_config(ConfigFileLoader(config_path, config_profile)) as loader:
        loader.export(
            df,
            table_name,
            database,
            schema,
            if_exists='replace',  # Specify resolution policy if table already exists
        )

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


@data_exporter
def export_data(df, *args, **kwargs):
    """
    Export data to a Delta Table

    Docs: https://delta-io.github.io/delta-rs/python/usage.html#writing-delta-tables
    """
    storage_options = {
        'AWS_ACCESS_KEY_ID': '',
        'AWS_SECRET_ACCESS_KEY': '',
        'AWS_REGION': '',
        'AWS_S3_ALLOW_UNSAFE_RENAME': 'true',
    }

    uri = 's3://[bucket]/[key]'

    write_deltalake(
        uri,
        data=df,
        mode='append',          # append or overwrite
        overwrite_schema=False, # set True to alter the schema when overwriting
        partition_by=[],
        storage_options=storage_options,
    )

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


@data_exporter
def export_data(df, *args, **kwargs):
    """
    Export data to a Delta Table

    Docs: https://delta-io.github.io/delta-rs/python/usage.html#writing-delta-tables
    """
    storage_options = {
        'AZURE_STORAGE_ACCOUNT_NAME': '',
        'AZURE_STORAGE_ACCOUNT_KEY': '',
        'AZURE_STORAGE_ACCESS_KEY': '',
        'AZURE_STORAGE_MASTER_KEY': '',
        'AZURE_STORAGE_CLIENT_ID': '',
        'AZURE_STORAGE_CLIENT_SECRET': '',
        'AZURE_STORAGE_TENANT_ID': '',
        'AZURE_STORAGE_SAS_KEY': '',
        'AZURE_STORAGE_TOKEN': '',
        'AZURE_STORAGE_USE_EMULATOR': '',
    }

    uri = 'az://[container]/[key]'

    write_deltalake(
        uri,
        data=df,
        mode='append',          # append or overwrite
        overwrite_schema=False, # set True to alter the schema when overwriting
        partition_by=[],
        storage_options=storage_options,
    )

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


@data_exporter
def export_data(df, *args, **kwargs):
    """
    Export data to a Delta Table

    Docs: https://delta-io.github.io/delta-rs/python/usage.html#writing-delta-tables
    """
    storage_options = {
        'GOOGLE_SERVICE_ACCOUNT': '',
        'GOOGLE_SERVICE_ACCOUNT_PATH': '',
        'GOOGLE_SERVICE_ACCOUNT_KEY': '',
        'GOOGLE_BUCKET': '',
    }

    uri = 'gs://[bucket]/[key]'

    write_deltalake(
        uri,
        data=df,
        mode='append',          # append or overwrite
        overwrite_schema=False, # set True to alter the schema when overwriting
        partition_by=[],
        storage_options=storage_options,
    )

from mage_ai.orchestration.triggers.api import trigger_pipeline
if 'data_exporter' not in globals():
    from mage_ai.data_preparation.decorators import data_exporter


@data_exporter
def trigger(*args, **kwargs):
    """
    Trigger another pipeline to run.

    Documentation: /orchestration/triggers/trigger-pipeline
    """

    trigger_pipeline(
        'pipeline_uuid',        # Required: enter the UUID of the pipeline to trigger
        variables={},           # Optional: runtime variables for the pipeline
        check_status=False,     # Optional: poll and check the status of the triggered pipeline
        error_on_failure=False, # Optional: if triggered pipeline fails, raise an exception
        poll_interval=60,       # Optional: check the status of triggered pipeline every N seconds
        poll_timeout=None,      # Optional: raise an exception after N seconds
        verbose=True,           # Optional: print status of triggered pipeline run
    )