superset country_map 源码
superset country_map 代码
文件路径:/superset/examples/country_map.py
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
import datetime
import pandas as pd
from sqlalchemy import BigInteger, Date, inspect, String
from sqlalchemy.sql import column
import superset.utils.database as database_utils
from superset import db
from superset.connectors.sqla.models import SqlMetric
from superset.models.slice import Slice
from superset.utils.core import DatasourceType
from .helpers import (
get_example_url,
get_slice_json,
get_table_connector_registry,
merge_slice,
misc_dash_slices,
)
def load_country_map_data(only_metadata: bool = False, force: bool = False) -> None:
"""Loading data for map with country map"""
tbl_name = "birth_france_by_region"
database = database_utils.get_example_database()
engine = database.get_sqla_engine()
schema = inspect(engine).default_schema_name
table_exists = database.has_table_by_name(tbl_name)
if not only_metadata and (not table_exists or force):
url = get_example_url("birth_france_data_for_country_map.csv")
data = pd.read_csv(url, encoding="utf-8")
data["dttm"] = datetime.datetime.now().date()
data.to_sql(
tbl_name,
engine,
schema=schema,
if_exists="replace",
chunksize=500,
dtype={
"DEPT_ID": String(10),
"2003": BigInteger,
"2004": BigInteger,
"2005": BigInteger,
"2006": BigInteger,
"2007": BigInteger,
"2008": BigInteger,
"2009": BigInteger,
"2010": BigInteger,
"2011": BigInteger,
"2012": BigInteger,
"2013": BigInteger,
"2014": BigInteger,
"dttm": Date(),
},
index=False,
)
print("Done loading table!")
print("-" * 80)
print("Creating table reference")
table = get_table_connector_registry()
obj = db.session.query(table).filter_by(table_name=tbl_name).first()
if not obj:
obj = table(table_name=tbl_name, schema=schema)
obj.main_dttm_col = "dttm"
obj.database = database
obj.filter_select_enabled = True
if not any(col.metric_name == "avg__2004" for col in obj.metrics):
col = str(column("2004").compile(db.engine))
obj.metrics.append(SqlMetric(metric_name="avg__2004", expression=f"AVG({col})"))
db.session.merge(obj)
db.session.commit()
obj.fetch_metadata()
tbl = obj
slice_data = {
"granularity_sqla": "",
"since": "",
"until": "",
"viz_type": "country_map",
"entity": "DEPT_ID",
"metric": {
"expressionType": "SIMPLE",
"column": {"type": "INT", "column_name": "2004"},
"aggregate": "AVG",
"label": "Boys",
"optionName": "metric_112342",
},
"row_limit": 500000,
"select_country": "france",
}
print("Creating a slice")
slc = Slice(
slice_name="Birth in France by department in 2016",
viz_type="country_map",
datasource_type=DatasourceType.TABLE,
datasource_id=tbl.id,
params=get_slice_json(slice_data),
)
misc_dash_slices.add(slc.slice_name)
merge_slice(slc)
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