def explore_json(
self, datasource_type: str | None = None, datasource_id: int | None = None
) -> FlaskResponse:
"""Serves all request that GET or POST form_data
This endpoint evolved to be the entry point of many different
requests that GETs or POSTs a form_data.
`self.generate_json` receives this input and returns different
payloads based on the request args in the first block
TODO: break into one endpoint for each return shape"""
response_type = ChartDataResultFormat.JSON.value
responses: list[ChartDataResultFormat | ChartDataResultType] = list(
ChartDataResultFormat
)
responses.extend(list(ChartDataResultType))
for response_option in responses:
if request.args.get(response_option) == "true":
response_type = response_option
break
# Verify user has permission to export CSV file
if (
response_type == ChartDataResultFormat.CSV
and not security_manager.can_access("can_csv", "Superset")
):
return json_error_response(
_("You don't have the rights to download as csv"),
status=403,
)
form_data = get_form_data()[0]
try:
datasource_id, datasource_type = get_datasource_info(
datasource_id, datasource_type, form_data
)
force = request.args.get("force") == "true"
# TODO: support CSV, SQL query and other non-JSON types
if (
is_feature_enabled("GLOBAL_ASYNC_QUERIES")
and response_type == ChartDataResultFormat.JSON
):
# First, look for the chart query results in the cache.
with contextlib.suppress(CacheLoadError):
viz_obj = get_viz(
datasource_type=cast(str, datasource_type),
datasource_id=datasource_id,
form_data=form_data,
force_cached=True,
force=force,
)
payload = viz_obj.get_payload()
# If the chart query has already been cached, return it immediately.
if payload is not None:
return self.send_data_payload_response(viz_obj, payload)
# Otherwise, kick off a background job to run the chart query.
# Clients will either poll or be notified of query completion,
# at which point they will call the /explore_json/data/<cache_key>
# endpoint to retrieve the results.
try:
async_channel_id = (
async_query_manager.parse_channel_id_from_request(request)
)
job_metadata = async_query_manager.submit_explore_json_job(
async_channel_id, form_data, response_type, force, get_user_id()
)
except AsyncQueryTokenException:
return json_error_response("Not authorized", 401)
return json_success(json.dumps(job_metadata), status=202)
viz_obj = get_viz(
datasource_type=cast(str, datasource_type),
datasource_id=datasource_id,
form_data=form_data,
force=force,
)
return self.generate_json(viz_obj, response_type)
except SupersetException as ex:
return json_error_response(utils.error_msg_from_exception(ex), 400)解释代码
本文探讨了Superset平台在实际应用中遇到的问题，包括页面加载速度慢、模板定制困难、视图数据处理限制及代码结构不清晰等问题，并提出了可能的优化方向。
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