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Posted to commits@superset.apache.org by jo...@apache.org on 2020/07/06 21:07:43 UTC
[incubator-superset] 01/01: chore: Cleaning up types and names for
SQLA models
This is an automated email from the ASF dual-hosted git repository.
johnbodley pushed a commit to branch john-bodley--cleanup-sqla-models
in repository https://gitbox.apache.org/repos/asf/incubator-superset.git
commit 05f194b566d812189823333e9e93463d8384eabc
Author: John Bodley <45...@users.noreply.github.com>
AuthorDate: Mon Jul 6 14:07:19 2020 -0700
chore: Cleaning up types and names for SQLA models
---
superset/connectors/sqla/models.py | 54 ++++++++++++++++++++------------------
1 file changed, 29 insertions(+), 25 deletions(-)
diff --git a/superset/connectors/sqla/models.py b/superset/connectors/sqla/models.py
index 8cfae24..631fb2c 100644
--- a/superset/connectors/sqla/models.py
+++ b/superset/connectors/sqla/models.py
@@ -685,13 +685,13 @@ class SqlaTable( # pylint: disable=too-many-public-methods,too-many-instance-at
return self.get_sqla_table()
def adhoc_metric_to_sqla(
- self, metric: Dict[str, Any], cols: Dict[str, Any]
+ self, metric: Dict[str, Any], columns_by_name: Dict[str, Any]
) -> Optional[Column]:
"""
Turn an adhoc metric into a sqlalchemy column.
:param dict metric: Adhoc metric definition
- :param dict cols: Columns for the current table
+ :param dict columns_by_name: Columns for the current table
:returns: The metric defined as a sqlalchemy column
:rtype: sqlalchemy.sql.column
"""
@@ -700,7 +700,7 @@ class SqlaTable( # pylint: disable=too-many-public-methods,too-many-instance-at
if expression_type == utils.ADHOC_METRIC_EXPRESSION_TYPES["SIMPLE"]:
column_name = metric["column"].get("column_name")
- table_column = cols.get(column_name)
+ table_column = columns_by_name.get(column_name)
if table_column:
sqla_column = table_column.get_sqla_col()
else:
@@ -780,8 +780,10 @@ class SqlaTable( # pylint: disable=too-many-public-methods,too-many-instance-at
# Database spec supports join-free timeslot grouping
time_groupby_inline = db_engine_spec.time_groupby_inline
- cols: Dict[str, Column] = {col.column_name: col for col in self.columns}
- metrics_dict: Dict[str, SqlMetric] = {m.metric_name: m for m in self.metrics}
+ columns_by_name: Dict[str, TableColumn] = {
+ col.column_name: col for col in self.columns
+ }
+ metrics_by_name: Dict[str, SqlMetric] = {m.metric_name: m for m in self.metrics}
if not granularity and is_timeseries:
raise Exception(
@@ -800,9 +802,9 @@ class SqlaTable( # pylint: disable=too-many-public-methods,too-many-instance-at
for metric in metrics:
if utils.is_adhoc_metric(metric):
assert isinstance(metric, dict)
- metrics_exprs.append(self.adhoc_metric_to_sqla(metric, cols))
- elif isinstance(metric, str) and metric in metrics_dict:
- metrics_exprs.append(metrics_dict[metric].get_sqla_col())
+ metrics_exprs.append(self.adhoc_metric_to_sqla(metric, columns_by_name))
+ elif isinstance(metric, str) and metric in metrics_by_name:
+ metrics_exprs.append(metrics_by_name[metric].get_sqla_col())
else:
raise Exception(_("Metric '%(metric)s' does not exist", metric=metric))
if metrics_exprs:
@@ -822,8 +824,8 @@ class SqlaTable( # pylint: disable=too-many-public-methods,too-many-instance-at
select_exprs = []
for selected in groupby:
- if selected in cols:
- outer = cols[selected].get_sqla_col()
+ if selected in columns_by_name:
+ outer = columns_by_name[selected].get_sqla_col()
else:
outer = literal_column(f"({selected})")
outer = self.make_sqla_column_compatible(outer, selected)
@@ -833,8 +835,8 @@ class SqlaTable( # pylint: disable=too-many-public-methods,too-many-instance-at
elif columns:
for selected in columns:
select_exprs.append(
- cols[selected].get_sqla_col()
- if selected in cols
+ columns_by_name[selected].get_sqla_col()
+ if selected in columns_by_name
else self.make_sqla_column_compatible(literal_column(selected))
)
metrics_exprs = []
@@ -843,7 +845,7 @@ class SqlaTable( # pylint: disable=too-many-public-methods,too-many-instance-at
time_range_endpoints = extras.get("time_range_endpoints")
groupby_exprs_with_timestamp = OrderedDict(groupby_exprs_sans_timestamp.items())
if granularity:
- dttm_col = cols[granularity]
+ dttm_col = columns_by_name[granularity]
time_grain = extras.get("time_grain_sqla")
time_filters = []
@@ -859,7 +861,7 @@ class SqlaTable( # pylint: disable=too-many-public-methods,too-many-instance-at
and self.main_dttm_col != dttm_col.column_name
):
time_filters.append(
- cols[self.main_dttm_col].get_time_filter(
+ columns_by_name[self.main_dttm_col].get_time_filter(
from_dttm, to_dttm, time_range_endpoints
)
)
@@ -892,7 +894,7 @@ class SqlaTable( # pylint: disable=too-many-public-methods,too-many-instance-at
continue
col = flt["col"]
op = flt["op"].upper()
- col_obj = cols.get(col)
+ col_obj = columns_by_name.get(col)
if col_obj:
is_list_target = op in (
utils.FilterOperator.IN.value,
@@ -977,9 +979,9 @@ class SqlaTable( # pylint: disable=too-many-public-methods,too-many-instance-at
for col, ascending in orderby:
direction = asc if ascending else desc
if utils.is_adhoc_metric(col):
- col = self.adhoc_metric_to_sqla(col, cols)
- elif col in cols:
- col = cols[col].get_sqla_col()
+ col = self.adhoc_metric_to_sqla(col, columns_by_name)
+ elif col in columns_by_name:
+ col = columns_by_name[col].get_sqla_col()
if isinstance(col, Label):
label = col._label # pylint: disable=protected-access
@@ -1026,7 +1028,7 @@ class SqlaTable( # pylint: disable=too-many-public-methods,too-many-instance-at
ob = inner_main_metric_expr
if timeseries_limit_metric:
ob = self._get_timeseries_orderby(
- timeseries_limit_metric, metrics_dict, cols
+ timeseries_limit_metric, metrics_by_name, columns_by_name
)
direction = desc if order_desc else asc
subq = subq.order_by(direction(ob))
@@ -1046,7 +1048,9 @@ class SqlaTable( # pylint: disable=too-many-public-methods,too-many-instance-at
orderby = [
(
self._get_timeseries_orderby(
- timeseries_limit_metric, metrics_dict, cols
+ timeseries_limit_metric,
+ metrics_by_name,
+ columns_by_name,
),
False,
)
@@ -1090,17 +1094,17 @@ class SqlaTable( # pylint: disable=too-many-public-methods,too-many-instance-at
def _get_timeseries_orderby(
self,
timeseries_limit_metric: Metric,
- metrics_dict: Dict[str, SqlMetric],
- cols: Dict[str, Column],
+ metrics_by_name: Dict[str, SqlMetric],
+ columns_by_name: Dict[str, TableColumn],
) -> Optional[Column]:
if utils.is_adhoc_metric(timeseries_limit_metric):
assert isinstance(timeseries_limit_metric, dict)
- ob = self.adhoc_metric_to_sqla(timeseries_limit_metric, cols)
+ ob = self.adhoc_metric_to_sqla(timeseries_limit_metric, columns_by_name)
elif (
isinstance(timeseries_limit_metric, str)
- and timeseries_limit_metric in metrics_dict
+ and timeseries_limit_metric in metrics_by_name
):
- ob = metrics_dict[timeseries_limit_metric].get_sqla_col()
+ ob = metrics_by_name[timeseries_limit_metric].get_sqla_col()
else:
raise Exception(
_("Metric '%(metric)s' does not exist", metric=timeseries_limit_metric)