def time_range(self, **kwargs: Any) -> FlaskResponse:
"""Get actually time range from human readable string or datetime expression"""
time_range = kwargs["rison"]
try:
since, until = get_since_until(time_range)
result = {
"since": since.isoformat() if since else "",
"until": until.isoformat() if until else "",
"timeRange": time_range,
}
return self.json_response({"result": result})
except ValueError as error:
error_msg = {"message": f"Unexpected time range: {error}"}
return self.json_response(error_msg, 400)
def _get_dttms(
self,
time_range: Optional[str],
time_shift: Optional[str],
extras: Dict[str, Any],
) -> Tuple[Optional[datetime], Optional[datetime]]:
return get_since_until(
relative_start=extras.get(
"relative_start", self._config["DEFAULT_RELATIVE_START_TIME"]),
relative_end=extras.get("relative_end",
self._config["DEFAULT_RELATIVE_END_TIME"]),
time_range=time_range,
time_shift=time_shift,
)
def time_range(self, **kwargs: Any) -> FlaskResponse:
"""Get actually time range from human readable string or datetime expression"""
time_range = kwargs["rison"]
try:
since, until = get_since_until(time_range)
result = {
"since": since.isoformat() if since else "",
"until": until.isoformat() if until else "",
"timeRange": time_range,
}
return self.json_response({"result": result})
except (ValueError, TimeRangeParseFailError,
TimeRangeUnclearError) as error:
error_msg = {"message": f"Ошибка в фильтре по времени: {error}"}
return self.json_response(error_msg, 400)
def __init__(
self,
datasource: Optional[DatasourceDict] = None,
result_type: Optional[ChartDataResultType] = None,
annotation_layers: Optional[List[Dict[str, Any]]] = None,
applied_time_extras: Optional[Dict[str, str]] = None,
apply_fetch_values_predicate: bool = False,
granularity: Optional[str] = None,
metrics: Optional[List[Union[Dict[str, Any], str]]] = None,
groupby: Optional[List[str]] = None,
filters: Optional[List[Dict[str, Any]]] = None,
time_range: Optional[str] = None,
time_shift: Optional[str] = None,
is_timeseries: Optional[bool] = None,
timeseries_limit: int = 0,
row_limit: Optional[int] = None,
row_offset: Optional[int] = None,
timeseries_limit_metric: Optional[Metric] = None,
order_desc: bool = True,
extras: Optional[Dict[str, Any]] = None,
columns: Optional[List[str]] = None,
orderby: Optional[List[OrderBy]] = None,
post_processing: Optional[List[Optional[Dict[str, Any]]]] = None,
is_rowcount: bool = False,
**kwargs: Any,
):
columns = columns or []
groupby = groupby or []
extras = extras or {}
annotation_layers = annotation_layers or []
self.is_rowcount = is_rowcount
self.datasource = None
if datasource:
self.datasource = ConnectorRegistry.get_datasource(
str(datasource["type"]), int(datasource["id"]), db.session)
self.result_type = result_type
self.apply_fetch_values_predicate = apply_fetch_values_predicate or False
self.annotation_layers = [
layer for layer in annotation_layers
# formula annotations don't affect the payload, hence can be dropped
if layer["annotationType"] != "FORMULA"
]
self.applied_time_extras = applied_time_extras or {}
self.granularity = granularity
self.from_dttm, self.to_dttm = get_since_until(
relative_start=extras.get("relative_start",
config["DEFAULT_RELATIVE_START_TIME"]),
relative_end=extras.get("relative_end",
config["DEFAULT_RELATIVE_END_TIME"]),
time_range=time_range,
time_shift=time_shift,
)
# is_timeseries is True if time column is in either columns or groupby
# (both are dimensions)
self.is_timeseries = (is_timeseries if is_timeseries is not None else
DTTM_ALIAS in columns + groupby)
self.time_range = time_range
self.time_shift = parse_human_timedelta(time_shift)
self.post_processing = [
post_proc for post_proc in post_processing or [] if post_proc
]
# Support metric reference/definition in the format of
# 1. 'metric_name' - name of predefined metric
# 2. { label: 'label_name' } - legacy format for a predefined metric
# 3. { expressionType: 'SIMPLE' | 'SQL', ... } - adhoc metric
self.metrics = metrics and [
x if isinstance(x, str) or is_adhoc_metric(x) else
x["label"] # type: ignore
for x in metrics
]
self.row_limit = config["ROW_LIMIT"] if row_limit is None else row_limit
self.row_offset = row_offset or 0
self.filter = filters or []
self.timeseries_limit = timeseries_limit
self.timeseries_limit_metric = timeseries_limit_metric
self.order_desc = order_desc
self.extras = extras
if config["SIP_15_ENABLED"]:
self.extras["time_range_endpoints"] = get_time_range_endpoints(
form_data=self.extras)
self.columns = columns
self.groupby = groupby or []
self.orderby = orderby or []
# rename deprecated fields
for field in DEPRECATED_FIELDS:
if field.old_name in kwargs:
logger.warning(
"The field `%s` is deprecated, please use `%s` instead.",
field.old_name,
field.new_name,
)
value = kwargs[field.old_name]
if value:
if hasattr(self, field.new_name):
logger.warning(
"The field `%s` is already populated, "
"replacing value with contents from `%s`.",
field.new_name,
field.old_name,
)
setattr(self, field.new_name, value)
# move deprecated extras fields to extras
for field in DEPRECATED_EXTRAS_FIELDS:
if field.old_name in kwargs:
logger.warning(
"The field `%s` is deprecated and should "
"be passed to `extras` via the `%s` property.",
field.old_name,
field.new_name,
)
value = kwargs[field.old_name]
if value:
if hasattr(self.extras, field.new_name):
logger.warning(
"The field `%s` is already populated in "
"`extras`, replacing value with contents "
"from `%s`.",
field.new_name,
field.old_name,
)
self.extras[field.new_name] = value
def test_get_since_until() -> None:
result: Tuple[Optional[datetime], Optional[datetime]]
expected: Tuple[Optional[datetime], Optional[datetime]]
result = get_since_until()
expected = None, datetime(2016, 11, 7)
assert result == expected
result = get_since_until(" : now")
expected = None, datetime(2016, 11, 7, 9, 30, 10)
assert result == expected
result = get_since_until("yesterday : tomorrow")
expected = datetime(2016, 11, 6), datetime(2016, 11, 8)
assert result == expected
result = get_since_until("2018-01-01T00:00:00 : 2018-12-31T23:59:59")
expected = datetime(2018, 1, 1), datetime(2018, 12, 31, 23, 59, 59)
assert result == expected
result = get_since_until("Last year")
expected = datetime(2015, 11, 7), datetime(2016, 11, 7)
assert result == expected
result = get_since_until("Last quarter")
expected = datetime(2016, 8, 7), datetime(2016, 11, 7)
assert result == expected
result = get_since_until("Last 5 months")
expected = datetime(2016, 6, 7), datetime(2016, 11, 7)
assert result == expected
result = get_since_until("Last 1 month")
expected = datetime(2016, 10, 7), datetime(2016, 11, 7)
assert result == expected
result = get_since_until("Next 5 months")
expected = datetime(2016, 11, 7), datetime(2017, 4, 7)
assert result == expected
result = get_since_until("Next 1 month")
expected = datetime(2016, 11, 7), datetime(2016, 12, 7)
assert result == expected
result = get_since_until(since="5 days")
expected = datetime(2016, 11, 2), datetime(2016, 11, 7)
assert result == expected
result = get_since_until(since="5 days ago", until="tomorrow")
expected = datetime(2016, 11, 2), datetime(2016, 11, 8)
assert result == expected
result = get_since_until(time_range="yesterday : tomorrow", time_shift="1 day")
expected = datetime(2016, 11, 5), datetime(2016, 11, 7)
assert result == expected
result = get_since_until(time_range="5 days : now")
expected = datetime(2016, 11, 2), datetime(2016, 11, 7, 9, 30, 10)
assert result == expected
result = get_since_until("Last week", relative_end="now")
expected = datetime(2016, 10, 31), datetime(2016, 11, 7, 9, 30, 10)
assert result == expected
result = get_since_until("Last week", relative_start="now")
expected = datetime(2016, 10, 31, 9, 30, 10), datetime(2016, 11, 7)
assert result == expected
result = get_since_until("Last week", relative_start="now", relative_end="now")
expected = datetime(2016, 10, 31, 9, 30, 10), datetime(2016, 11, 7, 9, 30, 10)
assert result == expected
result = get_since_until("previous calendar week")
expected = datetime(2016, 10, 31, 0, 0, 0), datetime(2016, 11, 7, 0, 0, 0)
assert result == expected
result = get_since_until("previous calendar month")
expected = datetime(2016, 10, 1, 0, 0, 0), datetime(2016, 11, 1, 0, 0, 0)
assert result == expected
result = get_since_until("previous calendar year")
expected = datetime(2015, 1, 1, 0, 0, 0), datetime(2016, 1, 1, 0, 0, 0)
assert result == expected
with pytest.raises(ValueError):
get_since_until(time_range="tomorrow : yesterday")
def __init__(
self,
annotation_layers: Optional[List[Dict[str, Any]]] = None,
applied_time_extras: Optional[Dict[str, str]] = None,
granularity: Optional[str] = None,
metrics: Optional[List[Union[Dict[str, Any], str]]] = None,
groupby: Optional[List[str]] = None,
filters: Optional[List[Dict[str, Any]]] = None,
time_range: Optional[str] = None,
time_shift: Optional[str] = None,
is_timeseries: Optional[bool] = None,
timeseries_limit: int = 0,
row_limit: Optional[int] = None,
row_offset: Optional[int] = None,
timeseries_limit_metric: Optional[Metric] = None,
order_desc: bool = True,
extras: Optional[Dict[str, Any]] = None,
columns: Optional[List[str]] = None,
orderby: Optional[List[List[str]]] = None,
post_processing: Optional[List[Optional[Dict[str, Any]]]] = None,
**kwargs: Any,
):
annotation_layers = annotation_layers or []
metrics = metrics or []
extras = extras or {}
is_sip_38 = is_feature_enabled("SIP_38_VIZ_REARCHITECTURE")
self.annotation_layers = [
layer
for layer in annotation_layers
# formula annotations don't affect the payload, hence can be dropped
if layer["annotationType"] != "FORMULA"
]
self.applied_time_extras = applied_time_extras or {}
self.granularity = granularity
self.from_dttm, self.to_dttm = get_since_until(
relative_start=extras.get(
"relative_start", config["DEFAULT_RELATIVE_START_TIME"]
),
relative_end=extras.get(
"relative_end", config["DEFAULT_RELATIVE_END_TIME"]
),
time_range=time_range,
time_shift=time_shift,
)
# is_timeseries is True if time column is in groupby
self.is_timeseries = (
is_timeseries
if is_timeseries is not None
else (DTTM_ALIAS in groupby if groupby else False)
)
self.time_range = time_range
self.time_shift = parse_human_timedelta(time_shift)
self.post_processing = [
post_proc for post_proc in post_processing or [] if post_proc
]
if not is_sip_38:
self.groupby = groupby or []
# Support metric reference/definition in the format of
# 1. 'metric_name' - name of predefined metric
# 2. { label: 'label_name' } - legacy format for a predefined metric
# 3. { expressionType: 'SIMPLE' | 'SQL', ... } - adhoc metric
self.metrics = [
metric
if isinstance(metric, str) or "expressionType" in metric
else metric["label"] # type: ignore
for metric in metrics
]
self.row_limit = row_limit or config["ROW_LIMIT"]
self.row_offset = row_offset or 0
self.filter = filters or []
self.timeseries_limit = timeseries_limit
self.timeseries_limit_metric = timeseries_limit_metric
self.order_desc = order_desc
self.extras = extras
if config["SIP_15_ENABLED"] and "time_range_endpoints" not in self.extras:
self.extras["time_range_endpoints"] = get_time_range_endpoints(form_data={})
self.columns = columns or []
if is_sip_38 and groupby:
self.columns += groupby
logger.warning(
"The field `groupby` is deprecated. Viz plugins should "
"pass all selectables via the `columns` field"
)
self.orderby = orderby or []
# rename deprecated fields
for field in DEPRECATED_FIELDS:
if field.old_name in kwargs:
logger.warning(
"The field `%s` is deprecated, please use `%s` instead.",
field.old_name,
field.new_name,
)
value = kwargs[field.old_name]
if value:
if hasattr(self, field.new_name):
logger.warning(
"The field `%s` is already populated, "
"replacing value with contents from `%s`.",
field.new_name,
field.old_name,
)
setattr(self, field.new_name, value)
# move deprecated extras fields to extras
for field in DEPRECATED_EXTRAS_FIELDS:
if field.old_name in kwargs:
logger.warning(
"The field `%s` is deprecated and should "
"be passed to `extras` via the `%s` property.",
field.old_name,
field.new_name,
)
value = kwargs[field.old_name]
if value:
if hasattr(self.extras, field.new_name):
logger.warning(
"The field `%s` is already populated in "
"`extras`, replacing value with contents "
"from `%s`.",
field.new_name,
field.old_name,
)
self.extras[field.new_name] = value
def test_get_since_until(self):
result = get_since_until()
expected = None, datetime(2016, 11, 7)
self.assertEqual(result, expected)
result = get_since_until(" : now")
expected = None, datetime(2016, 11, 7, 9, 30, 10)
self.assertEqual(result, expected)
result = get_since_until("yesterday : tomorrow")
expected = datetime(2016, 11, 6), datetime(2016, 11, 8)
self.assertEqual(result, expected)
result = get_since_until("2018-01-01T00:00:00 : 2018-12-31T23:59:59")
expected = datetime(2018, 1, 1), datetime(2018, 12, 31, 23, 59, 59)
self.assertEqual(result, expected)
result = get_since_until("Last year")
expected = datetime(2015, 11, 7), datetime(2016, 11, 7)
self.assertEqual(result, expected)
result = get_since_until("Last quarter")
expected = datetime(2016, 8, 7), datetime(2016, 11, 7)
self.assertEqual(result, expected)
result = get_since_until("Last 5 months")
expected = datetime(2016, 6, 7), datetime(2016, 11, 7)
self.assertEqual(result, expected)
result = get_since_until("Last 1 month")
expected = datetime(2016, 10, 7), datetime(2016, 11, 7)
self.assertEqual(result, expected)
result = get_since_until("Next 5 months")
expected = datetime(2016, 11, 7), datetime(2017, 4, 7)
self.assertEqual(result, expected)
result = get_since_until("Next 1 month")
expected = datetime(2016, 11, 7), datetime(2016, 12, 7)
self.assertEqual(result, expected)
result = get_since_until(since="5 days")
expected = datetime(2016, 11, 2), datetime(2016, 11, 7)
self.assertEqual(result, expected)
result = get_since_until(since="5 days ago", until="tomorrow")
expected = datetime(2016, 11, 2), datetime(2016, 11, 8)
self.assertEqual(result, expected)
result = get_since_until(time_range="yesterday : tomorrow",
time_shift="1 day")
expected = datetime(2016, 11, 5), datetime(2016, 11, 7)
self.assertEqual(result, expected)
result = get_since_until(time_range="5 days : now")
expected = datetime(2016, 11, 2), datetime(2016, 11, 7, 9, 30, 10)
self.assertEqual(result, expected)
result = get_since_until("Last week", relative_end="now")
expected = datetime(2016, 10, 31), datetime(2016, 11, 7, 9, 30, 10)
self.assertEqual(result, expected)
result = get_since_until("Last week", relative_start="now")
expected = datetime(2016, 10, 31, 9, 30, 10), datetime(2016, 11, 7)
self.assertEqual(result, expected)
result = get_since_until("Last week",
relative_start="now",
relative_end="now")
expected = datetime(2016, 10, 31, 9, 30,
10), datetime(2016, 11, 7, 9, 30, 10)
self.assertEqual(result, expected)
result = get_since_until("previous calendar week")
expected = datetime(2016, 10, 31, 0, 0,
0), datetime(2016, 11, 7, 0, 0, 0)
self.assertEqual(result, expected)
result = get_since_until("previous calendar month")
expected = datetime(2016, 10, 1, 0, 0,
0), datetime(2016, 11, 1, 0, 0, 0)
self.assertEqual(result, expected)
result = get_since_until("previous calendar year")
expected = datetime(2015, 1, 1, 0, 0, 0), datetime(2016, 1, 1, 0, 0, 0)
self.assertEqual(result, expected)
with self.assertRaises(ValueError):
get_since_until(time_range="tomorrow : yesterday")
def __init__( # pylint: disable=too-many-arguments,too-many-locals
self,
query_context: "QueryContext",
annotation_layers: Optional[List[Dict[str, Any]]] = None,
applied_time_extras: Optional[Dict[str, str]] = None,
apply_fetch_values_predicate: bool = False,
columns: Optional[List[str]] = None,
datasource: Optional[DatasourceDict] = None,
extras: Optional[Dict[str, Any]] = None,
filters: Optional[List[QueryObjectFilterClause]] = None,
granularity: Optional[str] = None,
is_rowcount: bool = False,
is_timeseries: Optional[bool] = None,
metrics: Optional[List[Metric]] = None,
order_desc: bool = True,
orderby: Optional[List[OrderBy]] = None,
post_processing: Optional[List[Optional[Dict[str, Any]]]] = None,
result_type: Optional[ChartDataResultType] = None,
row_limit: Optional[int] = None,
row_offset: Optional[int] = None,
series_columns: Optional[List[str]] = None,
series_limit: int = 0,
series_limit_metric: Optional[Metric] = None,
time_range: Optional[str] = None,
time_shift: Optional[str] = None,
**kwargs: Any,
):
columns = columns or []
extras = extras or {}
annotation_layers = annotation_layers or []
self.time_offsets = kwargs.get("time_offsets", [])
self.inner_from_dttm = kwargs.get("inner_from_dttm")
self.inner_to_dttm = kwargs.get("inner_to_dttm")
if series_columns:
self.series_columns = series_columns
elif is_timeseries and metrics:
self.series_columns = columns
else:
self.series_columns = []
self.is_rowcount = is_rowcount
self.datasource = None
if datasource:
self.datasource = ConnectorRegistry.get_datasource(
str(datasource["type"]), int(datasource["id"]), db.session)
self.result_type = result_type or query_context.result_type
self.apply_fetch_values_predicate = apply_fetch_values_predicate or False
self.annotation_layers = [
layer for layer in annotation_layers
# formula annotations don't affect the payload, hence can be dropped
if layer["annotationType"] != "FORMULA"
]
self.applied_time_extras = applied_time_extras or {}
self.granularity = granularity
self.from_dttm, self.to_dttm = get_since_until(
relative_start=extras.get("relative_start",
config["DEFAULT_RELATIVE_START_TIME"]),
relative_end=extras.get("relative_end",
config["DEFAULT_RELATIVE_END_TIME"]),
time_range=time_range,
time_shift=time_shift,
)
# is_timeseries is True if time column is in either columns or groupby
# (both are dimensions)
self.is_timeseries = (is_timeseries if is_timeseries is not None else
DTTM_ALIAS in columns)
self.time_range = time_range
self.time_shift = parse_human_timedelta(time_shift)
self.post_processing = [
post_proc for post_proc in post_processing or [] if post_proc
]
# Support metric reference/definition in the format of
# 1. 'metric_name' - name of predefined metric
# 2. { label: 'label_name' } - legacy format for a predefined metric
# 3. { expressionType: 'SIMPLE' | 'SQL', ... } - adhoc metric
self.metrics = metrics and [
x if isinstance(x, str) or is_adhoc_metric(x) else
x["label"] # type: ignore
for x in metrics
]
default_row_limit = (config["SAMPLES_ROW_LIMIT"]
if self.result_type == ChartDataResultType.SAMPLES
else config["ROW_LIMIT"])
self.row_limit = apply_max_row_limit(row_limit or default_row_limit)
self.row_offset = row_offset or 0
self.filter = filters or []
self.series_limit = series_limit
self.series_limit_metric = series_limit_metric
self.order_desc = order_desc
self.extras = extras
if config["SIP_15_ENABLED"]:
self.extras["time_range_endpoints"] = get_time_range_endpoints(
form_data=self.extras)
self.columns = columns
self.orderby = orderby or []
self._rename_deprecated_fields(kwargs)
self._move_deprecated_extra_fields(kwargs)
