Connect to data¶
Once you have a Data Context, you’ll want to connect to data. In Great Expectations, Datasources simplify connections, by managing configuration and providing a consistent, cross-platform API for referencing data.
Let’s configure your first Datasource: a connection to the data directory we’ve provided in the repo. This could also be a database connection, but for now we’re just using a simple file store.
Start by running the following command:
great_expectations --v3-api datasource new
What data would you like Great Expectations to connect to? 1. Files on a filesystem (for processing with Pandas or Spark) 2. Relational database (SQL) : 1 What are you processing your files with? 1. Pandas 2. PySpark : 1 Enter the path of the root directory where the data files are stored. If files are on local disk enter a path relative to your current working directory or an absolute path. : data
This will now open up a new Jupyter notebook to complete the Datasource configuration.
datasource new notebook¶
The Jupyter notebook contains some boilerplate code to configure your new Datasource. You can run the entire notebook as-is, but we recommend changing at least the Datasource name to something more specific.
Edit the second code cell as follows:
datasource_name = "data__dir"
Then execute all cells in the notebook in order to save the new Datasource. If successful, the last cell will print a list of all Datasources, including the one you just created.
Before continuing, let’s stop and unpack what just happened.
When you completed those last few steps, you told Great Expectations that:
You want to create a new Datasource called
You want to use Pandas to read the data from CSV.
Based on that information, the CLI added the following entry into your
great_expectations.yml file, under the
name: my_datasource class_name: Datasource execution_engine: class_name: PandasExecutionEngine data_connectors: my_datasource_example_data_connector: class_name: InferredAssetFilesystemDataConnector datasource_name: my_datasource base_directory: ../data default_regex: group_names: - data_asset_name pattern: (.*)
This datasource does not require any credentials. However, if you were to connect to a database that requires connection credentials,
those would be stored in
In the future, you can modify or delete your configuration by editing your
config_variables.yml files directly.
For now, let’s move on to creating your first Expectations.