Beispiel #1
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def _save_raw_data_chunk(chunk, file_pk, prog_key, increment, *args, **kwargs):
    """Save the raw data to the database."""
    import_file = ImportFile.objects.get(pk=file_pk)
    # Save our "column headers" and sample rows for F/E.
    source_type = get_source_type(import_file)
    for c in chunk:
        raw_bs = BuildingSnapshot()
        raw_bs.import_file = import_file
        raw_bs.extra_data = c
        raw_bs.source_type = source_type

        # We require a save to get our PK
        # We save here to set our initial source PKs.
        raw_bs.save()
        super_org = import_file.import_record.super_organization
        raw_bs.super_organization = super_org

        set_initial_sources(raw_bs)
        raw_bs.save()

    # Indicate progress
    increment_cache(prog_key, increment)
Beispiel #2
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def _save_raw_data_chunk(chunk, file_pk, prog_key, increment, *args, **kwargs):
    """Save the raw data to the database."""
    import_file = ImportFile.objects.get(pk=file_pk)
    # Save our "column headers" and sample rows for F/E.
    source_type = get_source_type(import_file)
    for c in chunk:
        raw_bs = BuildingSnapshot()
        raw_bs.import_file = import_file
        raw_bs.extra_data = c
        raw_bs.source_type = source_type

        # We require a save to get our PK
        # We save here to set our initial source PKs.
        raw_bs.save()
        super_org = import_file.import_record.super_organization
        raw_bs.super_organization = super_org

        set_initial_sources(raw_bs)
        raw_bs.save()

    # Indicate progress
    increment_cache(prog_key, increment)
Beispiel #3
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def create_models(data, import_file):
    """
    Create a BuildingSnapshot, a CanonicalBuilding, and a Meter. Then, create
    TimeSeries models for each meter reading in data.

    :param data: dictionary of building data from a Green Button XML file
        in the form returned by xml_importer.building_data
    :param import_file: ImportFile referencing the original xml file; needed
        for linking to BuildingSnapshot and for determining super_organization
    :returns: the created CanonicalBuilding
    """
    # cache data on import_file; this is a proof of concept and we
    # only have two example files available so we hardcode the only
    # heading present.
    import_file.cached_first_row = ROW_DELIMITER.join(["address"])
    import_file.cached_second_to_fifth_row = ROW_DELIMITER.join(
        [data['address']]
    )
    import_file.save()

    raw_bs = BuildingSnapshot()
    raw_bs.import_file = import_file

    # We require a save to get our PK
    # We save here to set our initial source PKs.
    raw_bs.save()
    super_org = import_file.import_record.super_organization
    raw_bs.super_organization = super_org

    set_initial_sources(raw_bs)
    raw_bs.address_line_1 = data['address']
    raw_bs.source_type = GREEN_BUTTON_BS

    raw_bs.save()

    # create canonical building
    cb = CanonicalBuilding.objects.create(canonical_snapshot=raw_bs)

    raw_bs.canonical_building = cb
    raw_bs.save()

    # log building creation
    AuditLog.objects.create(
        organization=import_file.import_record.super_organization,
        user=import_file.import_record.owner,
        content_object=cb,
        action="create_building",
        action_note="Created building",
    )

    # create meter for this dataset (each dataset is a single energy type)
    e_type = energy_type(data['service_category'])
    e_type_string = next(
        pair[1] for pair in seed.models.ENERGY_TYPES if pair[0] == e_type
    )

    m_name = "gb_{0}[{1}]".format(str(raw_bs.id), e_type_string)
    m_energy_units = energy_units(data['meter']['uom'])
    meter = Meter.objects.create(
        name=m_name, energy_type=e_type, energy_units=m_energy_units
    )

    meter.building_snapshot.add(raw_bs)
    meter.save()

    # now time series data for the meter
    for reading in data['interval']['readings']:
        start_time = int(reading['start_time'])
        duration = int(reading['duration'])

        begin_time = datetime.fromtimestamp(start_time)
        end_time = datetime.fromtimestamp(start_time + duration)
        value = reading['value']
        cost = reading['cost']

        new_ts = TimeSeries.objects.create(
            begin_time=begin_time,
            end_time=end_time,
            reading=value,
            cost=cost
        )

        new_ts.meter = meter
        new_ts.save()

    return cb
Beispiel #4
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def create_models(data, import_file):
    """
    Create a BuildingSnapshot, a CanonicalBuilding, and a Meter. Then, create
    TimeSeries models for each meter reading in data.

    :param data: dictionary of building data from a Green Button XML file
        in the form returned by xml_importer.building_data
    :param import_file: ImportFile referencing the original xml file; needed
        for linking to BuildingSnapshot and for determining super_organization
    :returns: the created CanonicalBuilding
    """
    # cache data on import_file; this is a proof of concept and we
    # only have two example files available so we hardcode the only
    # heading present.
    import_file.cached_first_row = ROW_DELIMITER.join(["address"])
    import_file.cached_second_to_fifth_row = ROW_DELIMITER.join(
        [data['address']])
    import_file.save()

    raw_bs = BuildingSnapshot()
    raw_bs.import_file = import_file

    # We require a save to get our PK
    # We save here to set our initial source PKs.
    raw_bs.save()
    super_org = import_file.import_record.super_organization
    raw_bs.super_organization = super_org

    raw_bs.address_line_1 = data['address']
    raw_bs.source_type = GREEN_BUTTON_BS

    raw_bs.save()

    # create canonical building
    cb = CanonicalBuilding.objects.create(canonical_snapshot=raw_bs)

    raw_bs.canonical_building = cb
    raw_bs.save()

    # log building creation
    AuditLog.objects.create(
        organization=import_file.import_record.super_organization,
        user=import_file.import_record.owner,
        content_object=cb,
        action="create_building",
        action_note="Created building",
    )

    # create meter for this dataset (each dataset is a single energy type)
    e_type = energy_type(data['service_category'])
    e_type_string = next(pair[1] for pair in seed.models.ENERGY_TYPES
                         if pair[0] == e_type)

    m_name = "gb_{0}[{1}]".format(str(raw_bs.id), e_type_string)
    m_energy_units = energy_units(data['meter']['uom'])
    meter = Meter.objects.create(name=m_name,
                                 energy_type=e_type,
                                 energy_units=m_energy_units)

    meter.building_snapshot.add(raw_bs)
    meter.save()

    # now time series data for the meter
    for reading in data['interval']['readings']:
        start_time = int(reading['start_time'])
        duration = int(reading['duration'])

        begin_time = datetime.fromtimestamp(start_time,
                                            tz=timezone.get_current_timezone())
        end_time = datetime.fromtimestamp(start_time + duration,
                                          tz=timezone.get_current_timezone())
        value = reading['value']
        cost = reading['cost']

        new_ts = TimeSeries.objects.create(begin_time=begin_time,
                                           end_time=end_time,
                                           reading=value,
                                           cost=cost)

        new_ts.meter = meter
        new_ts.save()

    return cb