fix: Move rpc stuff to its own file

src/sentry/snuba/spans_eap.py

@@ -1,14 +1,12 @@
 import logging
 from collections.abc import Mapping, Sequence
 from datetime import timedelta
-from typing import Any
 
 import sentry_sdk
 from snuba_sdk import Column, Condition
 
 from sentry.discover.arithmetic import categorize_columns
 from sentry.models.organization import Organization
-from sentry.search.eap.types import SearchResolverConfig
 from sentry.search.events.builder.spans_indexed import (
     SpansEAPQueryBuilder,
     TimeseriesSpanEAPIndexedQueryBuilder,
@@ -19,7 +17,6 @@
 from sentry.snuba.dataset import Dataset
 from sentry.snuba.metrics.extraction import MetricSpecType
 from sentry.snuba.query_sources import QuerySource
-from sentry.snuba.referrer import Referrer
 from sentry.utils.snuba import SnubaTSResult, bulk_snuba_queries
 
 logger = logging.getLogger(__name__)
@@ -293,91 +290,3 @@ def top_events_timeseries(
             )
 
     return top_events_results
-
-
-"""The run_*_query functions below will replace the ones above, and are the ones which will call the RPC instead of
-snql"""
-
-
-def run_table_query(
-    params: SnubaParams,
-    query_string: str,
-    selected_columns: list[str],  # Aggregations & Fields?
-    orderby: list[str],
-    offset: int,
-    limit: int,
-    referrer: Referrer,
-    config: SearchResolverConfig,
-) -> Any:
-    pass
-    """Make the query"""
-    # maker = SearchResolver(params)
-    # columns, contexts = maker.resolve_columns(selected_columns)
-    # query = maker.resolve_query(query_string)
-
-    """Run the query"""
-    # rpc = table_RPC(columns=[column.proto_definition for column in columns], query=query)
-    # result = rpc.run()
-
-    """Process the results"""
-    # for row in result:
-    #     for column in columns:
-    #         column.process(row)
-    # return result
-
-
-def run_timeseries_query(
-    params: SnubaParams,
-    query_string: str,
-    y_axes: list[str],
-    groupby: list[str],
-) -> Any:
-    pass
-    """Make the query"""
-    # maker = SearchResolver(params)
-    # groupby, contexts = maker.resolve_columns(groupby)
-    # yaxes = maker.resolve_aggregate(y_axes)
-    # query = maker.resolve_query(query_string)
-
-    """Run the query"""
-    # rpc = timeseries_RPC(columns=[column.proto_definition for column in groupby], query=query)
-    # result = rpc.run()
-
-    """Process the results"""
-    # return _process_timeseries(result, columns)
-
-
-def run_top_events_timeseries_query(
-    params: SnubaParams,
-    query_string: str,
-    y_axes: list[str],
-    groupby: list[str],
-    orderby: list[str],
-) -> Any:
-    """We intentionally duplicate run_timeseries_query code here to reduce the complexity of needing multiple helper
-    functions that both would call
-    This is because at time of writing, the query construction is very straightforward, if that changes perhaps we can
-    change this"""
-    pass
-    """Make the query"""
-    # maker = SearchResolver(params)
-    # top_events = run_table_query() with process_results off
-    # new_conditions = construct conditions based on top_events
-    # resolved_query = And(new_conditions, maker.resolve_query(query_string))
-    # groupby, contexts = maker.resolve_columns(groupby)
-    # yaxes = maker.resolve_aggregate(y_axes)
-
-    """Run the query"""
-    # rpc = timeseries_RPC(columns=[column.proto_definition for column in groupby], query=query)
-
-    """Process the results"""
-    # result = rpc.run()
-    # return _process_timeseries(result, columns)
-
-
-def _process_timeseries(result, columns):
-    pass
-    # for row in result:
-    #     for column in columns:
-    #         column.process(row)
-    # return result

src/sentry/snuba/spans_rpc.py

@@ -0,0 +1,89 @@
+from typing import Any
+
+from sentry.search.eap.types import SearchResolverConfig
+from sentry.search.events.types import SnubaParams
+from sentry.snuba.referrer import Referrer
+
+
+def run_table_query(
+    params: SnubaParams,
+    query_string: str,
+    selected_columns: list[str],  # Aggregations & Fields?
+    orderby: list[str],
+    offset: int,
+    limit: int,
+    referrer: Referrer,
+    config: SearchResolverConfig,
+) -> Any:
+    pass
+    """Make the query"""
+    # maker = SearchResolver(params)
+    # columns, contexts = maker.resolve_columns(selected_columns)
+    # query = maker.resolve_query(query_string)
+
+    """Run the query"""
+    # rpc = table_RPC(columns=[column.proto_definition for column in columns], query=query)
+    # result = rpc.run()
+
+    """Process the results"""
+    # for row in result:
+    #     for column in columns:
+    #         column.process(row)
+    # return result
+
+
+def run_timeseries_query(
+    params: SnubaParams,
+    query_string: str,
+    y_axes: list[str],
+    groupby: list[str],
+) -> Any:
+    pass
+    """Make the query"""
+    # maker = SearchResolver(params)
+    # groupby, contexts = maker.resolve_columns(groupby)
+    # yaxes = maker.resolve_aggregate(y_axes)
+    # query = maker.resolve_query(query_string)
+
+    """Run the query"""
+    # rpc = timeseries_RPC(columns=[column.proto_definition for column in groupby], query=query)
+    # result = rpc.run()
+
+    """Process the results"""
+    # return _process_timeseries(result, columns)
+
+
+def run_top_events_timeseries_query(
+    params: SnubaParams,
+    query_string: str,
+    y_axes: list[str],
+    groupby: list[str],
+    orderby: list[str],
+) -> Any:
+    """We intentionally duplicate run_timeseries_query code here to reduce the complexity of needing multiple helper
+    functions that both would call
+    This is because at time of writing, the query construction is very straightforward, if that changes perhaps we can
+    change this"""
+    pass
+    """Make the query"""
+    # maker = SearchResolver(params)
+    # top_events = run_table_query() with process_results off
+    # new_conditions = construct conditions based on top_events
+    # resolved_query = And(new_conditions, maker.resolve_query(query_string))
+    # groupby, contexts = maker.resolve_columns(groupby)
+    # yaxes = maker.resolve_aggregate(y_axes)
+
+    """Run the query"""
+    # rpc = timeseries_RPC(columns=[column.proto_definition for column in groupby], query=query)
+
+    """Process the results"""
+    # result = rpc.run()
+    # return _process_timeseries(result, columns)
+
+
+def _process_timeseries(result, columns):
+    pass
+    # for row in result:
+    #     for column in columns:
+    #         column.process(row)
+    # return result