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# Copyright (c) 2023 Cisco and/or its affiliates.
# Licensed 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.
"""Initialize Flask app.
"""
import logging
import pandas as pd
from flask import Flask
from flask_assets import Environment, Bundle
from .utils.constants import Constants as C
from .data.data import Data
def init_app():
"""Construct core Flask application with embedded Dash app.
"""
logging.basicConfig(
format=C.LOG_FORMAT,
datefmt=C.LOG_DATE_FORMAT,
level=C.LOG_LEVEL
)
app = Flask(__name__, instance_relative_config=False)
app.logger.info("Application started.")
app.config.from_object("config.Config")
with app.app_context():
# Import parts of our core Flask app.
from . import routes
assets = Environment()
assets.init_app(app)
# Compile static assets.
sass_bundle = Bundle(
"sass/lux.scss",
filters="libsass",
output="dist/css/bootstrap.css",
depends="**/*.scss",
extra={
"rel": "stylesheet"
}
)
assets.register("sass_all", sass_bundle)
sass_bundle.build()
if C.TIME_PERIOD is None or C.TIME_PERIOD > C.MAX_TIME_PERIOD:
time_period = C.MAX_TIME_PERIOD
else:
time_period = C.TIME_PERIOD
data = Data(
data_spec_file=C.DATA_SPEC_FILE,
).read_all_data(days=time_period)
# Import Dash applications.
from .news.news import init_news
app = init_news(
app,
data_stats=data["statistics"],
data_trending=data["trending"]
)
from .stats.stats import init_stats
app = init_stats(
app,
data_stats=data["statistics"],
data_trending=data["trending"]
)
from .trending.trending import init_trending
app = init_trending(
app,
data_trending=data["trending"]
)
from .report.report import init_report
app = init_report(
app,
data_iterative=data["iterative"]
)
return app
app = init_app()
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