def gpd_to_values(data):
"""Replace a GeoDataFrame by a data model with values.
For ``geopandas.GeoDataFrame`` columns values are stored as Foreign Members
of GeoJSON feature objects. For all other types uses function
:py:func:`altair.to_values`."""
if isinstance(data, gpd.GeoDataFrame):
data = alt.utils.sanitize_dataframe(data)
values = geopandas_to_dict(data)
return {'values': json.dumps(values)}
else:
return alt.to_values(data)
def test_gpd_to_values_pd():
data = pd.DataFrame(pd.np.arange(3), columns=['param'])
assert gpdvega.gpd_to_values(data) == alt.to_values(data)
def execute_query(parameters: dict):
injected_span: object = parameters.pop("span")
with tracer.start_active_span(
"queryibis",
references=[
opentracing.child_of(
(tracer.extract(opentracing.Format.TEXT_MAP,
injected_span)))
],
) as scope:
scope.span.log_kv(parameters)
name: str = parameters.pop("name")
transforms: typing.Optional[str] = parameters.pop("transform", None)
if name not in _expr_map:
raise ValueError(f"{name} is not an expression known to us!")
expr = _expr_map[name]
sql = expr.compile()
scope.span.log_kv({"sql:initial": sql})
debug(
"query:initial",
{
"transforms": transforms,
"parameters": parameters,
"sql": sql
},
)
if transforms:
# Replace all string instances of data references with value in schema
for k, v in parameters.items():
# All data items are added to parameters as `:<data name>`.
# They also should be in the `data` paramater, but you have to call
# this with a tuple which I am not sure where to get from
# https://github.com/vega/vega/blob/65fe7cb2485be90e16298d9dff87bf56045afb8d/packages/vega-transforms/src/Filter.js#L48
if not k.startswith(":"):
continue
k = k[1:]
res = json.dumps(v)
for t in transforms:
if t["type"] == "filter" or t["type"] == "formula":
t["expr"] = _patch_vegaexpr(t["expr"], k, res)
try:
expr = apply(expr, transforms)
except Exception as e:
raise ValueError(
f"Failed to convert {transforms} with error message message '{e}'"
)
with tracer.start_span("ibis:execute") as execute_span:
sql = expr.compile()
execute_span.log_kv({"sql": sql})
if ENABLE_MULTIPROCESSING:
data = execute_new_client(expr)
else:
data = expr.execute()
values = altair.to_values(data)["values"]
debug("query:result", {
"transforms": transforms,
"sql": sql,
"values": values
})
return values