# Query ## *class* Query Used to execute a SQL query against table(s) in Redivis, using the [Redivis SQL query syntax](https://docs.redivis.com/reference/projects/transform-nodes/raw-sql), and read out the results. ## Constructors
MethodDescription
redivis.query(query_string)Execute a SQL query within the current default scope (either a dataset or workflow).

In a Redivis notebook, the default scope will always be the notebook's workflow, and the notebook's source table can be referenced via the _source_ identifier.

If no default scope is specified, all tables in the query must be fully qualified. Consult the referencing resources documentation to learn more.
Dataset.query(query_string)Execute a SQL query scoped to a specific dataset. Tables referenced by the query do not need to be fully qualified, since the table lookup is already scoped to the dataset.

Consult the referencing resources documentation to learn more.
Workflow.query(query_string)Execute a SQL query scoped to a specific workflow. Tables referenced by the query do not need to be fully qualified, since the table lookup is already scoped to the dataset.

Consult the referencing resources documentation to learn more.
## Examples {% tabs %} {% tab title="Basics" %} ```python # Execute any SQL query and read the results query = redivis.query("SELECT 1 + 1 AS two, 'foo' AS bar") query.to_pandas_dataframe() # two bar # 0 2 foo # The query can reference any table on Redivis query = redivis.query(""" SELECT * FROM demo.iris_species.iris WHERE SepalLengthCm > 5 """) query.to_pandas_dataframe() # Id SepalLengthCm SepalWidthCm PetalLengthCm PetalWidthCm Species # 0 33 5.2 4.1 1.5 0.1 Iris-setosa # ... # Other methods to read data: # query.to_arrow_batch_iterator() # query.to_arrow_dataset() # query.to_arrow_dataset() # query.to_geopandas_dataframe() # query.to_dask_dataframe() # query.to_polars_lazyframe() ``` {% endtab %} {% tab title="Scoped queries" %} ```python # To simplify table references, execute a query scoped to a dataset or workflow dataset = redivis.organization("Demo").dataset("CMS 2014 Medicare Data") query = dataset.query(""" SELECT hospice_providers.name, inpatient_charges.drg_definition -- The tables inpatient_chargers, hospice_providers are assumed to be -- within the scoped dataset FROM inpatient_charges INNER JOIN hospice_providers ON hospice_providers.provider_id = inpatient_charges.provider_id """) # In a notebook, all queries are scoped to the current workflow. # Additionally, the notebooks source table can simply be referenced as _source_ query = redivis.query("SELECT * FROM _source_ LIMIT 10") ``` {% endtab %} {% endtabs %} ## Attributes | **`properties`** | A dict containing the [API resource representation of the query](/api/resource-definitions/query.md). This will always be populated after the query has been created, and can be refreshed by calling `query.get()` | | ---------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ## Methods
Query.file(name, *, [...])Reference a File within query results that contain a file_id variable.
Query.get()Fetch query metadata. Once called, the properties attribute on the query will be fully populated.
Query.list_files([max_results, *, ...])Return a list of File instances for query results containing a file_id variable.
Query.list_variables([max_results, *, ...])Return a list of Variable instances associated with this query's output.
Query.to_*([max_results, *, ...])Various methods to read query results. Mirrors the various Table.to_* methods (e.g., table.to_pandas_dataframe()
Query.variable(name)Reference a Variable within the query's output.
--- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.redivis.com/api/client-libraries/redivis-python/reference/query.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.