Project

This guide outlines the steps to create an Ascend Project.

Before you begin

New to Ascend? We recommend starting with:

• Quickstart guides to build your first data pipeline
• Otto's Expeditions for a guided sample Project experience with your preferred Git provider

If you're already set up with Ascend and just want to create a new Project, you've come to the right place.

Prerequisites

• Ascend Instance
• Either a managed Repository or a manually created Repository

Create an Ascend Project

1. In the Ascend UI, click the Instance settings button (top right, showing your Instance name and user icon)
2. Navigate to the Projects tab
3. Click Add Project
4. Enter a Title for your Project
5. Select your Repository from the dropdown
6. Set Project root to the folder path containing your Project code
7. Click Save

Ascend-managed options

When using an Ascend-managed Repository, choose one of these Project root paths based on your needs:

• projects/default/duckdb - simplified single Flow showcasing core features
• projects/ottos-expeditions/duckdb - comprehensive sample Project with advanced features
• projects/default/minimal/duckdb - minimal Project with basic features only

Data Plane alternatives

You can replace duckdb in the Project root with other Data Planes like bigquery, snowflake, or databricks based on your infrastructure preference. DuckDB is recommended for getting started since it requires no additional setup in Ascend.

Configure your Project

Ascend Projects use a dual configuration approach:

• ascend_project.yaml - defines Data Plane settings and default Flow specifications
• pyproject.toml - manages Python package dependencies

The examples below show ascend_project.yaml configurations for different Data Planes, based on the Otto's Expeditions Project. See this guide for pyproject.toml setup.

DuckLake

project:
  # only alphanumeric characters, dashes, and underscores are allowed for the Project name
  name: ottos-expeditions
  # in Ascend, parameters are a core concept.
  # Think of parameters as a key:value mapping (dictionary, map, etc.) of variables
  # you can use in your Flows. The hierarchy of parameters is:
  # Project > Profile > Flow > Flow run.
  # The parameters below are the top-level variables -- you can think of them as a default
  # -- for all Flows in this Project. Profiles are typically used to override parameters
  parameters:
    data_planes:
      ducklake:
        component_concurrency: 1
        data_connection_name: <your-object-store-connection-name>
        metadata_connection_name: <your-postgres-instance-connection-name>
  # defaults are typically used to specify the default Data Plane Connection
  # used for Flows, specified by a regex pattern on the Flow name
  defaults:
    - kind: Flow
      name:
        regex: .*
      spec:
        data_plane:
          connection_name: data_plane_ducklake

BigQuery

project:
  # only alphanumeric characters, dashes, and underscores are allowed for the Project name
  name: ottos-expeditions
  # in Ascend, parameters are a core concept.
  # Think of parameters as a key:value mapping (dictionary, map, etc.) of variables
  # you can use in your Flows. The hierarchy of parameters is:
  # Project > Profile > Flow > Flow run.
  # The parameters below are the top-level variables -- you can think of them as a default
  # -- for all Flows in this Project. Profiles are typically used to override parameters
  parameters:
    data_planes:
      gcp:
        project_id: <your-gcp-project-id>
      bigquery:
        dataset: OTTOS_EXPEDITIONS_DEVELOPMENT
        location: US
  # defaults are typically used to specify the default Data Plane Connection
  # used for Flows, specified by a regex pattern on the Flow name
  defaults:
    - kind: Flow
      name:
        regex: .*
      spec:
        data_plane:
          connection_name: data_plane_bigquery

Snowflake

project:
  # only alphanumeric characters, dashes, and underscores are allowed for the Project name
  name: ottos-expeditions
  # in Ascend, parameters are a core concept.
  # Think of parameters as a key:value mapping (dictionary, map, etc.) of variables
  # you can use in your Flows. The hierarchy of parameters is:
  # Project > Profile > Flow > Flow run.
  # The parameters below are the top-level variables -- you can think of them as a default
  # -- for all Flows in this Project. Profiles are typically used to override parameters
  parameters:
    data_planes:
      snowflake:
        account: <your-snowflake-account>
        user: <your-snowflake-user>
        role: <your-snowflake-role>
        warehouse: <your-snowflake-warehouse>
        database: OTTOS_EXPEDITIONS_DEVELOPMENT
        schema: DEFAULT
        max_concurrent_queries: 20
  # defaults are typically used to specify the default Data Plane Connection
  # used for Flows, specified by a regex pattern on the Flow name
  defaults:
    - kind: Flow
      name:
        regex: .*
      spec:
        data_plane:
          connection_name: data_plane_snowflake

Databricks

project:
  # only alphanumeric characters, dashes, and underscores are allowed for the Project name
  name: ottos-expeditions
  # additional packages to install from PyPI
  # https://pypi.org/project/ottos-expeditions/
  # you can use a Flow bootstrap command to install private packages
  # in Ascend, parameters are a core concept.
  # Think of parameters as a key:value mapping (dictionary, map, etc.) of variables
  # you can use in your Flows. The hierarchy of parameters is:
  # Project > Profile > Flow > Flow run.
  # The parameters below are the top-level variables -- you can think of them as a default
  # -- for all Flows in this Project. Profiles are typically used to override parameters
  parameters:
    data_planes:
      databricks:
        workspace_url: "<your-databricks-workspace-url>"
        client_id: <your-databricks-client-id>
        cluster_id: <your-databricks-cluster-id>
        cluster_http_path: <your-databricks-cluster-http-path>
        warehouse_http_path: <your-databricks-warehouse-http-path>
        catalog: OTTOS_EXPEDITIONS_DEVELOPMENT
        schema: DEFAULT
  # defaults are typically used to specify the default Data Plane Connection
  # used for Flows, specified by a regex pattern on the Flow name
  defaults:
    - kind: Flow
      name:
        regex: .*
      spec:
        data_plane:
          connection_name: data_plane_databricks

Next steps

• Set up your Workspace to start developing in Ascend