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flaskr/controllers/main_controller.py 27.7 KB
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import traceback
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from copy import deepcopy

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import re
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import geopy
import sqlalchemy
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from os.path import join
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from os import unlink, getenv

from flask import (
    Blueprint,
    Response,
    render_template,
    flash,
    request,
    redirect,
    url_for,
    abort,
    send_from_directory,
)
from flaskr.extensions import cache, basic_auth, mail, send_email
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from flaskr.forms import LoginForm, EstimateForm
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from flaskr.models import db, User, Estimation, StatusEnum, ScenarioEnum
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from flaskr.geocoder import CachedGeocoder
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from flaskr.core import (
    generate_unique_id,
    get_emission_models,
    increment_hit_counter,
)
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from flaskr.content import content, base_url
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from wtforms import validators

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from yaml import safe_dump as yaml_dump

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import csv
# from io import StringIO
from cStringIO import StringIO
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import pandas
from pandas.compat import StringIO as PandasStringIO

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main = Blueprint('main', __name__)


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OUT_ENCODING = 'utf-8'


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# -----------------------------------------------------------------------------
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pi_email = "didier.barret@gmail.com"  # todo: move to content YAML or .env
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# pi_email = "goutte@protonmail.com"
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# -----------------------------------------------------------------------------
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@main.route('/favicon.ico')
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@cache.cached(timeout=10000)
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def favicon():  # we want it served from the root, not from static/
    return send_from_directory(
        join(main.root_path, '..', 'static', 'img'),
        'favicon.ico', mimetype='image/vnd.microsoft.icon'
    )


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@main.route('/')
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@main.route('/home')
@main.route('/home.html')
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# @cache.cached(timeout=1000)
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def home():
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    models = get_emission_models()
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    models_dict = {}
    for model in models:
        models_dict[model.slug] = model.__dict__
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    increment_hit_counter()
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    return render_template(
        'home.html',
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        models=models_dict,
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        colors=[model.color for model in models],
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        labels=[model.name for model in models],
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    )
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def gather_addresses(from_list, from_file):
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    """
    Gather a list of addresses from the provided list and file.
    If the file is provided the list is ignored.
    """
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    addresses = []
    if from_file:
        file_mimetype = from_file.mimetype
        file_contents = from_file.read()

        rows_dicts = None

        if 'text/csv' == file_mimetype:

            rows_dicts = pandas \
                .read_csv(PandasStringIO(file_contents)) \
                .rename(str.lower, axis='columns') \
                .to_dict(orient="row")

        # Here are just *some* of the mimetypes that Microsoft's
        # garbage spreadsheet files may have.
        # application/vnd.ms-excel (official)
        # application/msexcel
        # application/x-msexcel
        # application/x-ms-excel
        # application/x-excel
        # application/x-dos_ms_excel
        # application/xls
        # application/x-xls
        # application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
        # ... Let's check extension instead.

        elif from_file.filename.endswith('xls') \
                or from_file.filename.endswith('xlsx'):

            rows_dicts = pandas \
                .read_excel(PandasStringIO(file_contents)) \
                .rename(str.lower, axis='columns') \
                .to_dict(orient="row")

        # Python 3.7 only
        # elif from_file.filename.endswith('ods'):
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        #     rows_dicts = read_ods(PandasStringIO(file_contents), 1) \
        #         .rename(str.lower, axis='columns') \
        #         .to_dict(orient="row")

        if rows_dicts is not None:
            for row_dict in rows_dicts:
                if 'address' in row_dict:
                    addresses.append(row_dict['address'])
                    continue
                address = None
                if 'city' in row_dict:
                    address = row_dict['city']
                if 'country' in row_dict:
                    if address is None:
                        address = row_dict['country']
                    else:
                        address += "," + row_dict['country']
                if address is not None:
                    addresses.append(address)
                else:
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                    raise validators.ValidationError(
                        "We could not find Address data in the spreadsheet."
                    )
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        else:
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            raise validators.ValidationError(
                "We could not find any data in the spreadsheet."
            )
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    else:
        addresses = from_list.replace("\r", '').split("\n")

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    clean_addresses = []
    for address in addresses:
        if not address:
            continue
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        if type(address).__name__ == 'str':
            address = unicode(address, 'utf-8')
        if re.match(r"City\s*,\s*Country", address, re.I & re.U) is not None:
            continue  # ignore inevitable copy/paste bloopers
        clean_addresses.append(address)
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    addresses = clean_addresses

    # Remove empty lines (if any) and white characters
    addresses = [a.strip() for a in addresses if a]
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    return "\n".join(addresses)


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@main.route("/estimate", methods=["GET", "POST"])
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@main.route("/estimate.html", methods=["GET", "POST"])
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def estimate():  # register new estimation request, more accurately
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    maximum_travels_to_compute = 1000000
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    models = get_emission_models()
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    form = EstimateForm()

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    def show_form():
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        return render_template("request-estimation.html", form=form, models=models)
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    if form.validate_on_submit():

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        estimation = Estimation()
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        # estimation.email = form.email.data
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        estimation.run_name = form.run_name.data
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        estimation.first_name = form.first_name.data
        estimation.last_name = form.last_name.data
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        estimation.institution = form.institution.data
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        estimation.status = StatusEnum.pending
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        try:
            estimation.origin_addresses = gather_addresses(
                form.origin_addresses.data,
                form.origin_addresses_file.data
            )
        except validators.ValidationError as e:
            form.origin_addresses_file.errors.append(e.message)
            return show_form()

        try:
            estimation.destination_addresses = gather_addresses(
                form.destination_addresses.data,
                form.destination_addresses_file.data
            )
        except validators.ValidationError as e:
            form.destination_addresses_file.errors.append(e.message)
            return show_form()

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        estimation.use_train_below_km = form.use_train_below_km.data
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        models_slugs = []
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        models_count = 0
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        for model in models:
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            if getattr(form, 'use_model_%s' % model.slug).data:
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                models_slugs.append(model.slug)
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                models_count += 1
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        estimation.models_slugs = u"\n".join(models_slugs)
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        travels_to_compute = \
            models_count * \
            (estimation.origin_addresses.count("\n") + 1) * \
            (estimation.destination_addresses.count("\n") + 1)
        if travels_to_compute > maximum_travels_to_compute:
            message = """
            Too many travels to compute. (%d > %d)
            We're working on increasing this limitation.
            Please contact us directly if you wish to boost this issue
            or get a dedicated estimation.
            """ % (travels_to_compute, maximum_travels_to_compute)
            form.origin_addresses.errors.append(message)
            form.destination_addresses.errors.append(message)
            # form.origin_addresses_file.errors.append(message)
            # form.destination_addresses_file.errors.append(message)
            return show_form()

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        db.session.add(estimation)
        db.session.commit()

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        send_email(
            to_recipient=pi_email,
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            subject="[TCFM] New Estimation Request: %s" % estimation.public_id,
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            message=render_template(
                'email/run_requested.html',
                base_url=base_url,
                estimation=estimation,
            )
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        )

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        flash("Estimation request submitted successfully.", "success")
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        return redirect(url_for(
            endpoint=".consult_estimation",
            public_id=estimation.public_id,
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            extension='html'
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        ))
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        # return render_template("estimate-debrief.html", form=form)

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    return show_form()
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@main.route("/invalidate")
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@main.route("/invalidate.html")
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def invalidate():
    stuck_estimations = Estimation.query \
        .filter_by(status=StatusEnum.working) \
        .all()

    for estimation in stuck_estimations:
        estimation.status = StatusEnum.failure
        estimation.errors = "Invalidated. Try again."
        db.session.commit()

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    return "Estimations invalidated: %d" % len(stuck_estimations)


@main.route("/invalidate-geocache")
@main.route("/invalidate-geocache.html")
def invalidate_geocache():
    geocache = 'geocache.db'

    unlink(geocache)

    return "Geocache invalidated."
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@main.route("/compute")
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def compute():  # process the queue of estimation requests
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    # maximum_addresses_to_compute = 30000
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    def _respond(_msg):
        return "<pre>%s</pre>" % _msg

    def _handle_failure(_estimation, _failure_message):
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        _estimation.status = StatusEnum.failure
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        _estimation.errors = _failure_message
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        db.session.commit()
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        send_email(
            to_recipient=pi_email,
            subject="[TCFM] Run failed: %s" % _estimation.public_id,
            message=render_template(
                'email/run_failed.html',
                base_url=base_url,
                estimation=_estimation,
            )
        )
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    def _handle_warning(_estimation, _warning_message):
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        if not _estimation.warnings:
            _estimation.warnings = _warning_message
        else:
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            _estimation.warnings += _warning_message
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            # _estimation.warnings = u"%s\n%s" % \
            #                        (_estimation.warnings, _warning_message)
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        db.session.commit()

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    estimation = None
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    try:
        response = ""
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        count_working = Estimation.query \
            .filter_by(status=StatusEnum.working) \
            .count()
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        if 0 < count_working:
            return _respond("Already working on estimation.")
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        try:
            estimation = Estimation.query \
                .filter_by(status=StatusEnum.pending) \
                .order_by(Estimation.id.asc()) \
                .first()
        except sqlalchemy.orm.exc.NoResultFound:
            return _respond("No estimation in the queue.")
        except Exception as e:
            return _respond("Database error: %s" % (e,))

        if not estimation:
            return _respond("No estimation in the queue.")

        estimation.status = StatusEnum.working
        db.session.commit()
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        response += u"Processing estimation `%s`...\n" % (
            estimation.public_id
        )
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        # GEOCODE ADDRESSES ###################################################

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        failed_addresses = []
        geocoder = CachedGeocoder()
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        # GEOCODE ORIGINS #####################################################
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        origins_addresses = estimation.origin_addresses.strip().split("\n")
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        origins_addresses_count = len(origins_addresses)
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        origins = []
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        # if origins_addresses_count > maximum_addresses_to_compute:
        #     errmsg = u"Too many origins. (%d > %d) \n" \
        #              u"Please contact us " \
        #              u"for support of more origins." % \
        #              (origins_addresses_count, maximum_addresses_to_compute)
        #     _handle_failure(estimation, errmsg)
        #     return _respond(errmsg)
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        for i in range(origins_addresses_count):
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            origin_address = origins_addresses[i].strip()
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            if not origin_address:
                continue

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            if origin_address in failed_addresses:
                continue
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            try:
                origin = geocoder.geocode(origin_address.encode('utf-8'))
            except geopy.exc.GeopyError as e:
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                warning = u"Ignoring origin `%s` " \
                          u"since we failed to geocode it.\n%s\n" % (
                            origin_address, e,
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                )
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                response += warning
                _handle_warning(estimation, warning)
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                failed_addresses.append(origin_address)
                continue
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            if origin is None:
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                warning = u"Ignoring origin `%s` " \
                          u"since we failed to geocode it.\n" % (
                            origin_address,
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                )
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                response += warning
                _handle_warning(estimation, warning)
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                failed_addresses.append(origin_address)
                continue
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            origins.append(origin)
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            response += u"Origin `%s` geocoded to `%s` (%f, %f).\n" % (
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                origin_address, origin.address,
                origin.latitude, origin.longitude,
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            )
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        # GEOCODE DESTINATIONS ################################################
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        destinations_addresses = estimation.destination_addresses.strip().split("\n")
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        destinations_addresses_count = len(destinations_addresses)
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        destinations = []
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        # if destinations_addresses_count > maximum_addresses_to_compute:
        #     errmsg = u"Too many destinations. (%d > %d) \n" \
        #              u"Please contact us " \
        #              u"for support of that many destinations." \
        #              % (
        #                  destinations_addresses_count,
        #                  maximum_addresses_to_compute,
        #              )
        #     _handle_failure(estimation, errmsg)
        #     return _respond(errmsg)
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        for i in range(destinations_addresses_count):
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            destination_address = destinations_addresses[i].strip()
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            if not destination_address:
                continue

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            if destination_address in failed_addresses:
                continue
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            try:
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                destination = geocoder.geocode(
                    destination_address.encode('utf-8')
                )
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            except geopy.exc.GeopyError as e:
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                warning = u"Ignoring destination `%s` " \
                          u"since we failed to geocode it.\n%s\n" % (
                            destination_address, e,
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                )
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                response += warning
                _handle_warning(estimation, warning)
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                failed_addresses.append(destination_address)
                continue
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            if destination is None:
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                warning = u"Ignoring destination `%s` " \
                          u"since we failed to geocode it.\n" % (
                            destination_address,
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                )
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                response += warning
                _handle_warning(estimation, warning)
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                failed_addresses.append(destination_address)
                continue
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            # print(repr(destination.raw))
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            destinations.append(destination)

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            response += u"Destination `%s` geocoded to `%s` (%f, %f).\n" % (
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                destination_address, destination.address,
                destination.latitude, destination.longitude,
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            )
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        geocoder.close()

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        # GTFO IF NO ORIGINS OR NO DESTINATIONS ###############################
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        if 0 == len(origins):
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475
            response += u"Failed to geocode ALL the origin(s).\n"
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            _handle_failure(estimation, response)
            return _respond(response)
        if 0 == len(destinations):
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            response += u"Failed to geocode ALL the destination(s).\n"
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            _handle_failure(estimation, response)
            return _respond(response)
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        # GRAB AND CONFIGURE THE EMISSION MODELS ##############################
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        emission_models = estimation.get_models()
        # print(emission_models)
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        extra_config = {
            'use_train_below_distance': estimation.use_train_below_km,
            # 'use_train_below_distance': 300,
        }
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        # PREPARE RESULT DICTIONARY THAT WILL BE STORED #######################
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        results = {}

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        # UTILITY PRIVATE FUNCTION(S) #########################################
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        def _get_city_key(_location):
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            return _location.address.split(',')[0]

            # _city_key = _location.address
            # # if 'address100' in _location.raw['address']:
            # #     _city_key = _location.raw['address']['address100']
            # if 'city' in _location.raw['address']:
            #     _city_key = _location.raw['address']['city']
            # elif 'state' in _location.raw['address']:
            #     _city_key = _location.raw['address']['state']
            # return _city_key

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        def _get_country_key(_location):
            return _location.address.split(',')[-1]

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        def compute_one_to_many(
                _origin,
                _destinations,
                _extra_config=None
        ):
            _results = {}
            footprints = {}

            destinations_by_city_key = {}

            cities_sum_foot = {}
            cities_sum_dist = {}
            cities_dict_first_model = None
            for model in emission_models:
                cities_dict = {}
                for _destination in _destinations:
                    footprint = model.compute_travel_footprint(
                        origin_latitude=_origin.latitude,
                        origin_longitude=_origin.longitude,
                        destination_latitude=_destination.latitude,
                        destination_longitude=_destination.longitude,
                        extra_config=_extra_config,
                    )
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                    _key = _get_city_key(_destination)
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                    destinations_by_city_key[_key] = _destination

                    if _key not in cities_dict:
                        cities_dict[_key] = {
                            'city': _key,
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                            'country': _get_country_key(_destination),
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                            'address': _destination.address,
                            'footprint': 0.0,
                            'distance': 0.0,
                            'train_trips': 0,
                            'plane_trips': 0,
                        }
                    cities_dict[_key]['footprint'] += footprint['co2eq_kg']
                    cities_dict[_key]['distance'] += footprint['distance_km']
                    cities_dict[_key]['train_trips'] += footprint['train_trips']
                    cities_dict[_key]['plane_trips'] += footprint['plane_trips']
                    if _key not in cities_sum_foot:
                        cities_sum_foot[_key] = 0.0
                    cities_sum_foot[_key] += footprint['co2eq_kg']
                    if _key not in cities_sum_dist:
                        cities_sum_dist[_key] = 0.0
                    cities_sum_dist[_key] += footprint['distance_km']

                cities = sorted(cities_dict.values(), key=lambda c: c['footprint'])

                footprints[model.slug] = {
                    'cities': cities,
                }

                if cities_dict_first_model is None:
                    cities_dict_first_model = deepcopy(cities_dict)

            _results['footprints'] = footprints

            total_foot = 0.0
            total_dist = 0.0
            total_train_trips = 0
            total_plane_trips = 0

            cities_mean_dict = {}
            for city in cities_sum_foot.keys():
                city_mean_foot = 1.0 * cities_sum_foot[city] / len(emission_models)
                city_mean_dist = 1.0 * cities_sum_dist[city] / len(emission_models)
                city_train_trips = cities_dict_first_model[city]['train_trips']
                city_plane_trips = cities_dict_first_model[city]['plane_trips']
                cities_mean_dict[city] = {
                    'address': destinations_by_city_key[city].address,
                    'city': city,
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                    'country': _get_country_key(destinations_by_city_key[city]),
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                    'footprint': city_mean_foot,
                    'distance': city_mean_dist,
                    'train_trips': city_train_trips,
                    'plane_trips': city_plane_trips,
                }
                total_foot += city_mean_foot
                total_dist += city_mean_dist
                total_train_trips += city_train_trips
                total_plane_trips += city_plane_trips

            cities_mean = [cities_mean_dict[k] for k in cities_mean_dict.keys()]
            cities_mean = sorted(cities_mean, key=lambda c: c['footprint'])

            _results['mean_footprint'] = {  # DEPRECATED?
                'cities': cities_mean
584b13cc   Antoine Goutenoir   Order the results...
604
            }
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            _results['cities'] = cities_mean
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606

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            _results['total'] = total_foot  # DEPRECATED
            _results['footprint'] = total_foot
584b13cc   Antoine Goutenoir   Order the results...
609

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            _results['distance'] = total_dist
            _results['train_trips'] = total_train_trips
            _results['plane_trips'] = total_plane_trips
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            return _results
24f55cde   Antoine Goutenoir   Geocode destinati...
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        # SCENARIO A : One Origin, At Least One Destination ###################
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        #
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        # We compute the sum of each of the travels' footprint,
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        # for each of the Emission Models, and present a mean of all Models.
        #
        if 1 == len(origins):
            estimation.scenario = ScenarioEnum.one_to_many
            results = compute_one_to_many(
                _origin=origins[0],
                _destinations=destinations,
                _extra_config=extra_config,
            )
94ae2730   Antoine Goutenoir   Ignore duplicates...
628

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        # SCENARIO B : At Least One Origin, One Destination ###################
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        #
        # Same as A for now.
        #
        elif 1 == len(destinations):
            estimation.scenario = ScenarioEnum.many_to_one
            results = compute_one_to_many(
                _origin=destinations[0],
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637
                _destinations=origins,
8a693e06   Antoine Goutenoir   Glue the extra co...
638
                _extra_config=extra_config,
314c65e2   Antoine Goutenoir   Implement Scenari...
639
            )
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640

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641
        # SCENARIO C : At Least One Origin, At Least One Destination ##########
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        #
        # Run Scenario A for each Destination, and expose optimum Destination.
        #
        else:
            estimation.scenario = ScenarioEnum.many_to_many
            unique_city_keys = []
            result_cities = []
            for destination in destinations:
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651
                city_key = _get_city_key(destination)
                country_key = _get_country_key(destination)
59125398   Antoine Goutenoir   Improve resilience.
652
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655
656

                if city_key in unique_city_keys:
                    continue
                else:
                    unique_city_keys.append(city_key)
1d48272e   Antoine Goutenoir   Compute the mean ...
657

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                city_results = compute_one_to_many(
                    _origin=destination,
                    _destinations=origins,
                    _extra_config=extra_config,
                )
                city_results['city'] = city_key
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664
                city_results['country'] = country_key
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                city_results['address'] = destination.address
                result_cities.append(city_results)

            result_cities = sorted(result_cities, key=lambda c: int(c['footprint']))
            results = {
                'cities': result_cities,
            }

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673
        # WRITE RESULTS INTO THE DATABASE #####################################
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674

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675
        estimation.status = StatusEnum.success
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676
        # Don't use YAML, it is too slow for big data.
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677
        # estimation.output_yaml = u"%s" % yaml_dump(results)
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678
        estimation.informations = response
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679
        estimation.set_output_dict(results)
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680
681
        db.session.commit()

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686
        # SEND AN EMAIL #######################################################

        send_email(
            to_recipient=pi_email,
            subject="[TCFM] Run completed: %s" % estimation.public_id,
3e6505e2   Antoine Goutenoir   Add content to th...
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            message=render_template(
                'email/run_completed.html',
                base_url=base_url,
                estimation=estimation,
            )
e2637443   Antoine Goutenoir   Send emails to ad...
692
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694
        )

        # FINALLY, RESPOND ####################################################
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695

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696
        # YAML is too expensive, let's not
f48f4a8f   Antoine Goutenoir   Optimize a bottle...
697
        # response += yaml_dump(results) + "\n"
a4c03d8e   Antoine Goutenoir   Add the controlle...
698

59125398   Antoine Goutenoir   Improve resilience.
699
        return _respond(response)
4392f295   Goutte   Update the Estima...
700

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701
    except Exception as e:
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702
        errmsg = u"Computation failed : %s" % (e,)
ce850e3a   Antoine Goutenoir   Revert traceback.
703
        # errmsg = u"%s\n\n%s" % (errmsg, traceback.format_exc())
59125398   Antoine Goutenoir   Improve resilience.
704
705
706
        if estimation:
            _handle_failure(estimation, errmsg)
        return _respond(errmsg)
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707
708


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710
@main.route("/estimation/<public_id>.<extension>")
def consult_estimation(public_id, extension):
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712
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717
    try:
        estimation = Estimation.query \
            .filter_by(public_id=public_id) \
            .one()
    except sqlalchemy.orm.exc.NoResultFound:
        return abort(404)
    except Exception as e:
59125398   Antoine Goutenoir   Improve resilience.
718
        # TODO: log?
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        return abort(500)

    # allowed_formats = ['html']
    # if format not in allowed_formats:
    #     abort(404)

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725
    unavailable_statuses = [StatusEnum.pending, StatusEnum.working]
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726

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727
    if extension in ['xhtml', 'html', 'htm']:
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        if estimation.status in unavailable_statuses:
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734
            return render_template(
                "estimation-queue-wait.html",
                estimation=estimation
            )
        else:
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            estimation_output = estimation.get_output_dict()
            estimation_sum = 0
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737
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            if estimation_output:
                for city in estimation_output['cities']:
                    estimation_sum += city['footprint']
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740

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742
            return render_template(
                "estimation.html",
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743
                estimation=estimation,
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745
                estimation_output=estimation_output,
                estimation_sum=estimation_sum,
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746
747
            )

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748
    elif extension in ['yaml', 'yml']:
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        if estimation.status in unavailable_statuses:
            abort(404)

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        return u"%s" % yaml_dump(estimation.get_output_dict())
        # return estimation.output_yaml
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755

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756
    elif 'csv' == extension:
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757

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760
        if estimation.status in unavailable_statuses:
            abort(404)

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762
        si = StringIO()
        cw = csv.writer(si, quoting=csv.QUOTE_ALL)
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763
        cw.writerow([
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764
            u"city", u"country", u"address",
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768
            u"co2_kg",
            u"distance_km",
            u"plane trips_amount",
            u'train trips_amount',
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769
        ])
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770
771

        results = estimation.get_output_dict()
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774
        for city in results['cities']:
            cw.writerow([
                city['city'].encode(OUT_ENCODING),
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775
                city['country'].encode(OUT_ENCODING),
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777
778
                city['address'].encode(OUT_ENCODING),
                round(city['footprint'], 3),
                round(city['distance'], 3),
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780
                city['plane_trips'],
                city['train_trips'],
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781
782
            ])

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790
        # return si.getvalue().strip('\r\n')
        return Response(
            response=si.getvalue().strip('\r\n'),
            headers={
                'Content-type': 'text/csv',
                'Content-disposition': "attachment; filename=%s.csv"%public_id,
            },
        )
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793

    else:
        abort(404)
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794
795


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@main.route("/scaling_laws.csv")
def get_scaling_laws_csv():
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    distances = content.laws_plot.distances
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    models = get_emission_models()

    si = StringIO()
    cw = csv.writer(si, quoting=csv.QUOTE_ALL)

    header = ['distance'] + [model.slug for model in models]
    cw.writerow(header)

    for distance in distances:
        row = [distance]
        for model in models:
            row.append(model.compute_airplane_distance_footprint(distance))
        cw.writerow(row)

    return Response(
        response=si.getvalue().strip('\r\n'),
        headers={
            'Content-type': 'text/csv',
            'Content-disposition': 'attachment; filename=scaling_laws.csv',
        },
    )


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@main.route("/test")
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# @basic_auth.required
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def dev_test():
    import os

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    # email_content = render_template(
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    #     'email/run_completed.html',
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    #     # run=run,
    # )
    # send_email(
    #     'goutte@protonmail.com',
    #     subject=u"[TCFC] New run request",
    #     message=email_content
    # )

    return "ok"