send a usage statistics message.

Calculate summary statistics for the validation results and return ``ExpectationStatistics``.

Convert a (pandas) dataframe to a great_expectations dataset, with (optional) expectation_suite Args: df: the DataFrame object to co

Args: expectation_configuration: The ExpectationConfiguration to add or update match_type: The criteria used to dete

Obtain domain and value keys for metrics and proceeds to add these metrics to the validation graph until all metrics have been added.

Assertions to check if a store backend is handling reading and writing a store_backend_id appropriately. Args: store_backend: Instanc

Expect the column median to be between a minimum value and a maximum value. expect_column_median_to_be_between is a \ :func:`column_a

Expect specific provided column quantiles to be between provided minimum and maximum values. ``quantile_ranges`` must be a dictionary with tw

Expect column values to not be null. To be counted as an exception, values must be explicitly null or missing, such as a NULL in PostgreSQL o

Get exactly one batch, based on a variety of flexible input types. The method `get_batch` is the main user-facing method for getting batches;

Get a list of configured site names.

This is a simple helper utility that can be used to parse a string result_format into the dict format used internally by great_expectations. It is

Generates a JSON-formatted report describing the outcome of all expectations. Use the default expectation_suite=None to validate the expectat

Get list of column names. If expect_table_columns_to_match_ordered_list EVR is present, use it as the list, including the order.

Get a list of examples from the object's `examples` member variable. :param return_only_gallery_examples: if True, include only test

Create a project config for an in-code data context. Not a fixture because we want to control when this is built (after the expectation store

Expect the number of rows to equal a value. expect_table_row_count_to_equal is a :func:`expectation \ <great_expectations.data_asset.

Parse a parameter expression to identify dependencies including GE URNs. Args: parameter_expression: the parameter to parse Returns:

Read the project setup.cfg file to determine Versioneer config.

Returns _expectation_config as a JSON object, and perform some cleaning along the way. Args: discard_failed_expectations (boolean

Return the URL of the HTML document that renders a resource (e.g., an expectation suite or a validation result). :param reso

Get the project root directory. We require that all commands are run from the project root, i.e. the directory that contains setup.py, setup.

Get the project version from whatever source is available. Returns dict with two keys: 'version' and 'full'.

Obtains validation dependencies for each metric using the implementation of their associated expectation, then proceeds to add these dependenc

Return True if ``obj`` is a collection type, e.g list, tuple, queryset.

Helper function to convert a dict object to one that is serializable Args: test_obj: an object to attempt to convert a corresponding

Call the given command(s).

Mark decorated function as a hook to be picked up later. You should not need to use this method directly. .. note:: Currently only wo

Substitute all config variables of the form ${SOME_VARIABLE} in a dictionary-like config object for their values. The method traverses t

If value is an array, test element-wise for NaN and return result as a boolean array. If value is a scalar, return boolean. A

Format the value or raise a :exc:`ValidationError` if an error occurs.

Add a new ValidationOperator to the DataContext and (for convenience) return the instantiated object. Args: validation_operator_n

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