google.cloud.bigquery.table.RowIterator#
Methods
|
[Beta] Create a class:pyarrow.Table by loading all pages of a table or query. |
|
Create a pandas DataFrame by loading all pages of a query. |
Attributes
Iterator of pages in the response. |
|
The subset of columns to be read from the table. |
|
The total number of rows in the table. |
-
class
google.cloud.bigquery.table.
RowIterator
(client, api_request, path, schema, page_token=None, max_results=None, page_size=None, extra_params=None, table=None, selected_fields=None)[source]# Bases:
google.api_core.page_iterator.HTTPIterator
A class for iterating through HTTP/JSON API row list responses.
- Parameters
client (google.cloud.bigquery.Client) – The API client.
api_request (Callable[google.cloud._http.JSONConnection.api_request]) – The function to use to make API requests.
path (str) – The method path to query for the list of items.
page_token (str) – A token identifying a page in a result set to start fetching results from.
max_results (int, optional) – The maximum number of results to fetch.
page_size (int, optional) – The maximum number of rows in each page of results from this request. Non-positive values are ignored. Defaults to a sensible value set by the API.
extra_params (Dict[str, object]) – Extra query string parameters for the API call.
table (Union[
Table
,TableReference
, ]) – Optional. The table which these rows belong to, or a reference to it. Used to call the BigQuery Storage API to fetch rows.selected_fields (Sequence[ google.cloud.bigquery.schema.SchemaField, ]) – Optional. A subset of columns to select from this table.
-
property
pages
# Iterator of pages in the response.
- Returns
- A
generator of page instances.
- Return type
types.GeneratorType[google.api_core.page_iterator.Page]
- Raises
ValueError – If the iterator has already been started.
-
property
schema
# The subset of columns to be read from the table.
- Type
-
to_arrow
(progress_bar_type=None, bqstorage_client=None)[source]# [Beta] Create a class:pyarrow.Table by loading all pages of a table or query.
- Parameters
progress_bar_type (Optional[str]) –
If set, use the tqdm library to display a progress bar while the data downloads. Install the
tqdm
package to use this feature.Possible values of
progress_bar_type
include:None
No progress bar.
'tqdm'
Use the
tqdm.tqdm()
function to print a progress bar tosys.stderr
.'tqdm_notebook'
Use the
tqdm.tqdm_notebook()
function to display a progress bar as a Jupyter notebook widget.'tqdm_gui'
Use the
tqdm.tqdm_gui()
function to display a progress bar as a graphical dialog box.
bqstorage_client (google.cloud.bigquery_storage_v1beta1.BigQueryStorageClient) –
Beta Feature Optional. A BigQuery Storage API client. If supplied, use the faster BigQuery Storage API to fetch rows from BigQuery. This API is a billable API.
This method requires the
pyarrow
andgoogle-cloud-bigquery-storage
libraries.Reading from a specific partition or snapshot is not currently supported by this method.
- Returns
- pyarrow.Table
A
pyarrow.Table
populated with row data and column headers from the query results. The column headers are derived from the destination table’s schema.
- Raises
ValueError – If the
pyarrow
library cannot be imported.
..versionadded:: 1.17.0
-
to_dataframe
(bqstorage_client=None, dtypes=None, progress_bar_type=None)[source]# Create a pandas DataFrame by loading all pages of a query.
- Parameters
bqstorage_client (google.cloud.bigquery_storage_v1beta1.BigQueryStorageClient) –
Beta Feature Optional. A BigQuery Storage API client. If supplied, use the faster BigQuery Storage API to fetch rows from BigQuery. This API is a billable API.
This method requires the
pyarrow
andgoogle-cloud-bigquery-storage
libraries.Reading from a specific partition or snapshot is not currently supported by this method.
Caution: There is a known issue reading small anonymous query result tables with the BQ Storage API. When a problem is encountered reading a table, the tabledata.list method from the BigQuery API is used, instead.
dtypes (Map[str, Union[str, pandas.Series.dtype]]) – Optional. A dictionary of column names pandas
dtype``s. The provided ``dtype
is used when constructing the series for the column specified. Otherwise, the default pandas behavior is used.progress_bar_type (Optional[str]) –
If set, use the tqdm library to display a progress bar while the data downloads. Install the
tqdm
package to use this feature.Possible values of
progress_bar_type
include:None
No progress bar.
'tqdm'
Use the
tqdm.tqdm()
function to print a progress bar tosys.stderr
.'tqdm_notebook'
Use the
tqdm.tqdm_notebook()
function to display a progress bar as a Jupyter notebook widget.'tqdm_gui'
Use the
tqdm.tqdm_gui()
function to display a progress bar as a graphical dialog box.
..versionadded:: 1.11.0
- Returns
A
DataFrame
populated with row data and column headers from the query results. The column headers are derived from the destination table’s schema.- Return type
- Raises
ValueError – If the
pandas
library cannot be imported, or thegoogle.cloud.bigquery_storage_v1beta1
module is required but cannot be imported.