This is a workaround to help identify Windows and adjust the prompts accordingly since hidden prompts may freeze in certain Windows terminals

requested_metrics is a dictionary like this: requested_metrics: *: # The asterisk here matches *any* expectat

Add a new datasource to the data context, with configuration provided as kwargs. Args: name: the name for the new datasource to ad

Helper function to assert presence or non-presence of how-to buttons and related content in various Data Docs pages.

Subclasses can override this method if the respective data source (e.g., Redshift) supports "approximate" mode. In certain cases (e.g

Build a Checkpoint.

Builds batch_spec from batch_definition by generating batch_spec params and adding any pass_through params Args: batch_d

Build BatchSpec from batch_definition by calling DataConnector's build_batch_spec function. Args: batch_definition (Batc

If we can't reflect the table, use a query to at least get column names.

Serialize an object to native Python data types according to this Schema's fields. :param obj: The object to serialize. :para

Wrap subprocess command in a try/except block to provide a convenient method for pip installing dependencies. :param command: bash command -

Execute a shell (bash in the present case) command from inside Python program with polling (to enable progress bar). :param command: bash co

Expect values in column A to be greater than column B. Args: column_A (str): The first column name column_B

Expect the number of unique values to be between a minimum value and a maximum value. expect_column_unique_value_count_to_be_between is a \

Expect column entries to be strings with length equal to the provided value. This expectation only works for string-type values. Invoking it

Checks to see if a file specified by the user actually exists Args: filepath (str or None): \ The filepa

Manages configuration and running of expectation objects. Expectation builds and saves a new expectation configuration to the DataAsset objec

Helper method that raises a `ValidationError` with an error message from ``self.error_messages``. .. deprecated:: 3.0.0 U

This base implementation naively passes arguments on to the real constructor, which is suitable really when a constructor knows to take its ow

Applies the current _partitioner to the batches available on data_asset_name and returns a list of valid partition_id strings that ca

Note: this method should *not* be used when getting a Batch from a BatchRequest, since it does not capture BatchRequest metadata.

Get binned values of series. Args: Series (pd.Series): Input series bins (list): Bins for th

Returns: int, table column count

Returns: int

Return a list of column map expectations.

Get a histogram of column values Args: column: the column for which to generate the histogram bins (tuple): the bins t

Returns: Any

Returns: int

This utility function takes a string with strftime format elements and substitutes those elements using either the provided datetime_obj or c

List file names, relative to base_directory_path one level deep, with expansion specified by glob_directive. :param base_directory_path -- ba

Utility to create datasets for json-formatted tests.

Utility to create datasets for json-formatted tests.

Return True if ``obj`` is an iterable object that isn't a string.

Really basic sanity checking.

Tests whether a given object is a valid continuous or categorical partition object. :param partition_object: The partition_object to evaluate

Returns a list of all expectations available to the validator

List the contents of an s3 bucket as a set of strings given bucket name and prefix Args: bucket: s3 bucket prefix: prefix for

For InferredAssetS3DataConnector, we take bucket and prefix and search for files using RegEx at and below the level specified by that bucket

List currently-configured Stores on this context