data.datasets.zensus.ZensusPopulation.__init__() - Code Metrics - Inspection of "Add zipfile check" - openego/eGon-data - Measure and Improve Code Quality continuously with Scrutinizer

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Pull Request — dev (#970)

unknown

created 2022-10-06 10:46 UTC

data.datasets.zensus.ZensusPopulation.init() A

↳ Parent: data.datasets.zensus

Complexity

Conditions

Size

Total Lines	9
Code Lines	9

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
cc	1
eloc	9
nop	2
dl	0
loc	9
rs	9.95
c	0
b	0
f	0

"""The central module containing all code dealing with importing Zensus data.
"""

from pathlib import Path
from urllib.request import urlretrieve
import csv
import json
import os
import zipfile

from shapely.geometry import Point, shape
from shapely.prepared import prep
import pandas as pd

from egon.data import db, subprocess
from egon.data.config import settings
from egon.data.datasets import Dataset
import egon.data.config


class ZensusPopulation(Dataset):
    def __init__(self, dependencies):
        super().__init__(
            name="ZensusPopulation",
            version="0.0.0",
            dependencies=dependencies,
            tasks=(
                download_zensus_pop,
                create_zensus_pop_table,
                population_to_postgres,
            ),
        )


class ZensusMiscellaneous(Dataset):
    def __init__(self, dependencies):
        super().__init__(
            name="ZensusMiscellaneous",
            version="0.0.0",
            dependencies=dependencies,
            tasks=(
                download_zensus_misc,
                create_zensus_misc_tables,
                zensus_misc_to_postgres,
            ),
        )


def download_zensus_pop():

    """Download Zensus csv file on population per hectar grid cell."""
    data_config = egon.data.config.datasets()
    zensus_population_config = data_config["zensus_population"][
        "original_data"
    ]
    download_directory = Path(".") / "zensus_population"
    # Create the folder, if it does not exists already
    if not os.path.exists(download_directory):
        os.mkdir(download_directory)

    target_file = (
        download_directory / zensus_population_config["target"]["file"]
    )

    if not os.path.isfile(target_file):
        urlretrieve(zensus_population_config["source"]["url"], target_file)


def download_zensus_misc():
    """Download Zensus csv files on data per hectar grid cell."""

    def download_and_check(target_file_misc, max_iteration=5):
        """Download file if doesnt exist and check afterwards. If badzip
        remove file and re-download. Repeat until file is fine or reached
        maximum iterations."""
        bad_file = True
        count = 0
        while bad_file:

            if not os.path.isfile(target_file_misc):
                urlretrieve(url, target_file_misc)

            # check zipfile
            try:
                _ = zipfile.ZipFile(target_file_misc)
                print(f"Zip file {target_file_misc} is good.")
                bad_file = False
            except zipfile.BadZipFile:
                os.remove(target_file_misc)
                count += 1
                if count > max_iteration:
                    raise zipfile.BadZipFile(
                        f"{target_file_misc} is" f" not a zip file"
                    )
                pass

    # Get data config
    data_config = egon.data.config.datasets()
    download_directory = Path(".") / "zensus_population"
    # Create the folder, if it does not exists already
    if not os.path.exists(download_directory):
        os.mkdir(download_directory)
    # Download remaining zensus data set on households, buildings, apartments

    zensus_config = data_config["zensus_misc"]["original_data"]
    zensus_misc_processed = data_config["zensus_misc"]["processed"]
    zensus_url = zensus_config["source"]["url"]
    zensus_files = zensus_misc_processed["file_table_map"].keys()
    url_path_map = list(zip(zensus_url, zensus_files))

    for url, path in url_path_map:
        target_file_misc = download_directory / path

        download_and_check(target_file_misc, max_iteration=5)


def create_zensus_pop_table():
    """Create tables for zensus data in postgres database"""

    # Get information from data configuration file
    data_config = egon.data.config.datasets()
    zensus_population_processed = data_config["zensus_population"]["processed"]

    # Create target schema
    db.execute_sql(
        f"CREATE SCHEMA IF NOT EXISTS {zensus_population_processed['schema']};"
    )

    # Create table for population data
    population_table = (
        f"{zensus_population_processed['schema']}"
        f".{zensus_population_processed['table']}"
    )

    db.execute_sql(f"DROP TABLE IF EXISTS {population_table} CASCADE;")

    db.execute_sql(
        f"CREATE TABLE {population_table}"
        f""" (id        SERIAL NOT NULL,
              grid_id    character varying(254) NOT NULL,
              x_mp       int,
              y_mp       int,
              population smallint,
              geom_point geometry(Point,3035),
              geom geometry (Polygon, 3035),
              CONSTRAINT {zensus_population_processed['table']}_pkey
              PRIMARY KEY (id)
        );
        """
    )


def create_zensus_misc_tables():
    """Create tables for zensus data in postgres database"""

    # Get information from data configuration file
    data_config = egon.data.config.datasets()
    zensus_misc_processed = data_config["zensus_misc"]["processed"]

    # Create target schema
    db.execute_sql(
        f"CREATE SCHEMA IF NOT EXISTS {zensus_misc_processed['schema']};"
    )

    # Create tables for household, apartment and building
    for table in zensus_misc_processed["file_table_map"].values():
        misc_table = f"{zensus_misc_processed['schema']}.{table}"

        db.execute_sql(f"DROP TABLE IF EXISTS {misc_table} CASCADE;")
        db.execute_sql(
            f"CREATE TABLE {misc_table}"
            f""" (id                 SERIAL,
                  grid_id            VARCHAR(50),
                  grid_id_new        VARCHAR (50),
                  attribute          VARCHAR(50),
                  characteristics_code smallint,
                  characteristics_text text,
                  quantity           smallint,
                  quantity_q         smallint,
                  zensus_population_id int,
                  CONSTRAINT {table}_pkey PRIMARY KEY (id)
            );
            """
        )


def target(source, dataset):
    """Generate the target path corresponding to a source path.

    Parameters
    ----------
    dataset: str
        Toggles between production (`dataset='Everything'`) and test mode e.g.
        (`dataset='Schleswig-Holstein'`).
        In production mode, data covering entire Germany
        is used. In the test mode a subset of this data is used for testing the
        workflow.
    Returns
    -------
    Path
        Path to target csv-file

    """
    return Path(
        os.path.join(Path("."), "zensus_population", source.stem)
        + "."
        + dataset
        + source.suffix
    )


def select_geom():
    """Select the union of the geometries of Schleswig-Holstein from the
    database, convert their projection to the one used in the CSV file,
    output the result to stdout as a GeoJSON string and read it into a
    prepared shape for filtering.

    """
    docker_db_config = db.credentials()

    geojson = subprocess.run(
        ["ogr2ogr"]
        + ["-s_srs", "epsg:4326"]
        + ["-t_srs", "epsg:3035"]
        + ["-f", "GeoJSON"]
        + ["/vsistdout/"]
        + [
            f"PG:host={docker_db_config['HOST']}"
            f" user='{docker_db_config['POSTGRES_USER']}'"
            f" password='{docker_db_config['POSTGRES_PASSWORD']}'"
            f" port={docker_db_config['PORT']}"
            f" dbname='{docker_db_config['POSTGRES_DB']}'"
        ]
        + ["-sql", "SELECT ST_Union(geometry) FROM boundaries.vg250_lan"],
        text=True,
    )
    features = json.loads(geojson.stdout)["features"]
    assert (
        len(features) == 1
    ), f"Found {len(features)} geometry features, expected exactly one."

    return prep(shape(features[0]["geometry"]))


def filter_zensus_population(filename, dataset):
    """This block filters lines in the source CSV file and copies
    the appropriate ones to the destination based on geometry.


    Parameters
    ----------
    filename : str
        Path to input csv-file
    dataset: str, optional
        Toggles between production (`dataset='Everything'`) and test mode e.g.
        (`dataset='Schleswig-Holstein'`).
        In production mode, data covering entire Germany
        is used. In the test mode a subset of this data is used for testing the
        workflow.
    Returns
    -------
    str
        Path to output csv-file

    """

    csv_file = Path(filename).resolve(strict=True)

    schleswig_holstein = select_geom()

    if not os.path.isfile(target(csv_file, dataset)):

        with open(csv_file, mode="r", newline="") as input_lines:
            rows = csv.DictReader(input_lines, delimiter=";")
            gitter_ids = set()
            with open(
                target(csv_file, dataset), mode="w", newline=""
            ) as destination:
                output = csv.DictWriter(
                    destination, delimiter=";", fieldnames=rows.fieldnames
                )
                output.writeheader()
                output.writerows(
                    gitter_ids.add(row["Gitter_ID_100m"]) or row
                    for row in rows
                    if schleswig_holstein.intersects(
                        Point(float(row["x_mp_100m"]), float(row["y_mp_100m"]))
                    )
                )
    return target(csv_file, dataset)


def filter_zensus_misc(filename, dataset):
    """This block filters lines in the source CSV file and copies
    the appropriate ones to the destination based on grid_id values.


    Parameters
    ----------
    filename : str
        Path to input csv-file
    dataset: str, optional
        Toggles between production (`dataset='Everything'`) and test mode e.g.
        (`dataset='Schleswig-Holstein'`).
        In production mode, data covering entire Germany
        is used. In the test mode a subset of this data is used for testing the
        workflow.
    Returns
    -------
    str
        Path to output csv-file

    """
    csv_file = Path(filename).resolve(strict=True)

    gitter_ids = set(
        pd.read_sql(
            "SELECT grid_id from society.destatis_zensus_population_per_ha",
            con=db.engine(),
        ).grid_id.values
    )

    if not os.path.isfile(target(csv_file, dataset)):
        with open(
            csv_file, mode="r", newline="", encoding="iso-8859-1"
        ) as inputs:
            rows = csv.DictReader(inputs, delimiter=",")
            with open(
                target(csv_file, dataset),
                mode="w",
                newline="",
                encoding="iso-8859-1",
            ) as destination:
                output = csv.DictWriter(
                    destination, delimiter=",", fieldnames=rows.fieldnames
                )
                output.writeheader()
                output.writerows(
                    row for row in rows if row["Gitter_ID_100m"] in gitter_ids
                )
    return target(csv_file, dataset)


def population_to_postgres():
    """Import Zensus population data to postgres database"""
    # Get information from data configuration file
    data_config = egon.data.config.datasets()
    zensus_population_orig = data_config["zensus_population"]["original_data"]
    zensus_population_processed = data_config["zensus_population"]["processed"]
    input_file = (
        Path(".")
        / "zensus_population"
        / zensus_population_orig["target"]["file"]
    )
    dataset = settings()["egon-data"]["--dataset-boundary"]

    # Read database configuration from docker-compose.yml
    docker_db_config = db.credentials()

    population_table = (
        f"{zensus_population_processed['schema']}"
        f".{zensus_population_processed['table']}"
    )

    with zipfile.ZipFile(input_file) as zf:
        for filename in zf.namelist():

            zf.extract(filename)

            if dataset == "Everything":
                filename_insert = filename
            else:
                filename_insert = filter_zensus_population(filename, dataset)

            host = ["-h", f"{docker_db_config['HOST']}"]
            port = ["-p", f"{docker_db_config['PORT']}"]
            pgdb = ["-d", f"{docker_db_config['POSTGRES_DB']}"]
            user = ["-U", f"{docker_db_config['POSTGRES_USER']}"]
            command = [
                "-c",
                rf"\copy {population_table} (grid_id, x_mp, y_mp, population)"
                rf" FROM '{filename_insert}' DELIMITER ';' CSV HEADER;",
            ]
            subprocess.run(
                ["psql"] + host + port + pgdb + user + command,
                env={"PGPASSWORD": docker_db_config["POSTGRES_PASSWORD"]},
            )

        os.remove(filename)


    db.execute_sql(
        f"UPDATE {population_table} zs"
        " SET geom_point=ST_SetSRID(ST_MakePoint(zs.x_mp, zs.y_mp), 3035);"
    )

    db.execute_sql(
        f"UPDATE {population_table} zs"
        """ SET geom=ST_SetSRID(
                (ST_MakeEnvelope(zs.x_mp-50,zs.y_mp-50,zs.x_mp+50,zs.y_mp+50)),
                3035
            );
        """
    )

    db.execute_sql(
        f"CREATE INDEX {zensus_population_processed['table']}_geom_idx ON"
        f" {population_table} USING gist (geom);"
    )

    db.execute_sql(
        f"CREATE INDEX"
        f" {zensus_population_processed['table']}_geom_point_idx"
        f" ON  {population_table} USING gist (geom_point);"
    )


def zensus_misc_to_postgres():
    """Import data on buildings, households and apartments to postgres db"""

    # Get information from data configuration file
    data_config = egon.data.config.datasets()
    zensus_misc_processed = data_config["zensus_misc"]["processed"]
    zensus_population_processed = data_config["zensus_population"]["processed"]
    file_path = Path(".") / "zensus_population"
    dataset = settings()["egon-data"]["--dataset-boundary"]

    population_table = (
        f"{zensus_population_processed['schema']}"
        f".{zensus_population_processed['table']}"
    )

    # Read database configuration from docker-compose.yml
    docker_db_config = db.credentials()

    for input_file, table in zensus_misc_processed["file_table_map"].items():
        with zipfile.ZipFile(file_path / input_file) as zf:
            csvfiles = [n for n in zf.namelist() if n.lower()[-3:] == "csv"]
            for filename in csvfiles:
                zf.extract(filename)

                if dataset == "Everything":
                    filename_insert = filename
                else:
                    filename_insert = filter_zensus_misc(filename, dataset)

                host = ["-h", f"{docker_db_config['HOST']}"]
                port = ["-p", f"{docker_db_config['PORT']}"]
                pgdb = ["-d", f"{docker_db_config['POSTGRES_DB']}"]
                user = ["-U", f"{docker_db_config['POSTGRES_USER']}"]
                command = [
                    "-c",
                    rf"\copy {zensus_population_processed['schema']}.{table}"
                    f"""(grid_id,
                        grid_id_new,
                        attribute,
                        characteristics_code,
                        characteristics_text,
                        quantity,
                        quantity_q)
                        FROM '{filename_insert}' DELIMITER ','
                        CSV HEADER
                        ENCODING 'iso-8859-1';""",
                ]
                subprocess.run(
                    ["psql"] + host + port + pgdb + user + command,
                    env={"PGPASSWORD": docker_db_config["POSTGRES_PASSWORD"]},
                )

            os.remove(filename)


        db.execute_sql(
            f"""UPDATE {zensus_population_processed['schema']}.{table} as b
                    SET zensus_population_id = zs.id
                    FROM {population_table} zs
                    WHERE b.grid_id = zs.grid_id;"""
        )

        db.execute_sql(
            f"""ALTER TABLE {zensus_population_processed['schema']}.{table}
                    ADD CONSTRAINT {table}_fkey
                    FOREIGN KEY (zensus_population_id)
                    REFERENCES {population_table}(id);"""
        )

    # Create combined table
    create_combined_zensus_table()

    # Delete entries for unpopulated cells
    adjust_zensus_misc()


def create_combined_zensus_table():
    """Create combined table with buildings, apartments and population per cell

    Only apartment and building data with acceptable data quality
    (quantity_q<2) is used, all other data is dropped. For more details on data
    quality see Zensus docs:
    https://www.zensus2011.de/DE/Home/Aktuelles/DemografischeGrunddaten.html

    If there's no data on buildings or apartments for a certain cell, the value
    for building_count resp. apartment_count contains NULL.
    """
    sql_script = os.path.join(
        os.path.dirname(__file__), "create_combined_zensus_table.sql"
    )
    db.execute_sql_script(sql_script)


def adjust_zensus_misc():
    """Delete unpopulated cells in zensus-households, -buildings and -apartments

    Some unpopulated zensus cells are listed in:
    - egon_destatis_zensus_household_per_ha
    - egon_destatis_zensus_building_per_ha
    - egon_destatis_zensus_apartment_per_ha

    This can be caused by missing population
    information due to privacy or other special cases (e.g. holiday homes
    are listed as buildings but are not permanently populated.)
    In the follwong tasks of egon-data, only data of populated cells is used.

    Returns
    -------
    None.

    """
    # Get information from data configuration file
    data_config = egon.data.config.datasets()
    zensus_population_processed = data_config["zensus_population"]["processed"]
    zensus_misc_processed = data_config["zensus_misc"]["processed"]

    population_table = (
        f"{zensus_population_processed['schema']}"
        f".{zensus_population_processed['table']}"
    )

    for input_file, table in zensus_misc_processed["file_table_map"].items():
        db.execute_sql(
            f"""
             DELETE FROM {zensus_population_processed['schema']}.{table} as b
             WHERE b.zensus_population_id IN (
                 SELECT id FROM {population_table}
                 WHERE population < 0);"""
        )


1		"""The central module containing all code dealing with importing Zensus data.
2		"""
3
4		from pathlib import Path
5		from urllib.request import urlretrieve
6		import csv
7		import json
8		import os
9		import zipfile
10
11		from shapely.geometry import Point, shape
12		from shapely.prepared import prep
13		import pandas as pd
14
15		from egon.data import db, subprocess
16		from egon.data.config import settings
17		from egon.data.datasets import Dataset
18		import egon.data.config
19
20
21		class ZensusPopulation(Dataset):
22		def __init__(self, dependencies):
23		super().__init__(
24		name="ZensusPopulation",
25		version="0.0.0",
26		dependencies=dependencies,
27		tasks=(
28		download_zensus_pop,
29		create_zensus_pop_table,
30		population_to_postgres,
31		),
32		)
33
34
35		class ZensusMiscellaneous(Dataset):
36		def __init__(self, dependencies):
37		super().__init__(
38		name="ZensusMiscellaneous",
39		version="0.0.0",
40		dependencies=dependencies,
41		tasks=(
42		download_zensus_misc,
43		create_zensus_misc_tables,
44		zensus_misc_to_postgres,
45		),
46		)
47
48
49	View Code Duplication	def download_zensus_pop():
		0 ignored issues – show Duplication introduced 2021-09-01 11:18 UTC by Report Bug Copy Issue Report This code seems to be duplicated in your project. Loading history...
50		"""Download Zensus csv file on population per hectar grid cell."""
51		data_config = egon.data.config.datasets()
52		zensus_population_config = data_config["zensus_population"][
53		"original_data"
54		]
55		download_directory = Path(".") / "zensus_population"
56		# Create the folder, if it does not exists already
57		if not os.path.exists(download_directory):
58		os.mkdir(download_directory)
59
60		target_file = (
61		download_directory / zensus_population_config["target"]["file"]
62		)
63
64		if not os.path.isfile(target_file):
65		urlretrieve(zensus_population_config["source"]["url"], target_file)
66
67
68		def download_zensus_misc():
69		"""Download Zensus csv files on data per hectar grid cell."""
70
71		def download_and_check(target_file_misc, max_iteration=5):
72		"""Download file if doesnt exist and check afterwards. If badzip
73		remove file and re-download. Repeat until file is fine or reached
74		maximum iterations."""
75		bad_file = True
76		count = 0
77		while bad_file:
78
79		if not os.path.isfile(target_file_misc):
80		urlretrieve(url, target_file_misc)
81
82		# check zipfile
83		try:
84		_ = zipfile.ZipFile(target_file_misc)
85		print(f"Zip file {target_file_misc} is good.")
86		bad_file = False
87		except zipfile.BadZipFile:
88		os.remove(target_file_misc)
89		count += 1
90		if count > max_iteration:
91		raise zipfile.BadZipFile(
92		f"{target_file_misc} is" f" not a zip file"
93		)
94		pass
95
96		# Get data config
97		data_config = egon.data.config.datasets()
98		download_directory = Path(".") / "zensus_population"
99		# Create the folder, if it does not exists already
100		if not os.path.exists(download_directory):
101		os.mkdir(download_directory)
102		# Download remaining zensus data set on households, buildings, apartments
103
104		zensus_config = data_config["zensus_misc"]["original_data"]
105		zensus_misc_processed = data_config["zensus_misc"]["processed"]
106		zensus_url = zensus_config["source"]["url"]
107		zensus_files = zensus_misc_processed["file_table_map"].keys()
108		url_path_map = list(zip(zensus_url, zensus_files))
109
110		for url, path in url_path_map:
111		target_file_misc = download_directory / path
112
113		download_and_check(target_file_misc, max_iteration=5)
114
115
116		def create_zensus_pop_table():
117		"""Create tables for zensus data in postgres database"""
118
119		# Get information from data configuration file
120		data_config = egon.data.config.datasets()
121		zensus_population_processed = data_config["zensus_population"]["processed"]
122
123		# Create target schema
124		db.execute_sql(
125		f"CREATE SCHEMA IF NOT EXISTS {zensus_population_processed['schema']};"
126		)
127
128		# Create table for population data
129		population_table = (
130		f"{zensus_population_processed['schema']}"
131		f".{zensus_population_processed['table']}"
132		)
133
134		db.execute_sql(f"DROP TABLE IF EXISTS {population_table} CASCADE;")
135
136		db.execute_sql(
137		f"CREATE TABLE {population_table}"
138		f""" (id SERIAL NOT NULL,
139		grid_id character varying(254) NOT NULL,
140		x_mp int,
141		y_mp int,
142		population smallint,
143		geom_point geometry(Point,3035),
144		geom geometry (Polygon, 3035),
145		CONSTRAINT {zensus_population_processed['table']}_pkey
146		PRIMARY KEY (id)
147		);
148		"""
149		)
150
151
152		def create_zensus_misc_tables():
153		"""Create tables for zensus data in postgres database"""
154
155		# Get information from data configuration file
156		data_config = egon.data.config.datasets()
157		zensus_misc_processed = data_config["zensus_misc"]["processed"]
158
159		# Create target schema
160		db.execute_sql(
161		f"CREATE SCHEMA IF NOT EXISTS {zensus_misc_processed['schema']};"
162		)
163
164		# Create tables for household, apartment and building
165		for table in zensus_misc_processed["file_table_map"].values():
166		misc_table = f"{zensus_misc_processed['schema']}.{table}"
167
168		db.execute_sql(f"DROP TABLE IF EXISTS {misc_table} CASCADE;")
169		db.execute_sql(
170		f"CREATE TABLE {misc_table}"
171		f""" (id SERIAL,
172		grid_id VARCHAR(50),
173		grid_id_new VARCHAR (50),
174		attribute VARCHAR(50),
175		characteristics_code smallint,
176		characteristics_text text,
177		quantity smallint,
178		quantity_q smallint,
179		zensus_population_id int,
180		CONSTRAINT {table}_pkey PRIMARY KEY (id)
181		);
182		"""
183		)
184
185
186		def target(source, dataset):
187		"""Generate the target path corresponding to a source path.
188
189		Parameters
190		----------
191		dataset: str
192		Toggles between production (`dataset='Everything'`) and test mode e.g.
193		(`dataset='Schleswig-Holstein'`).
194		In production mode, data covering entire Germany
195		is used. In the test mode a subset of this data is used for testing the
196		workflow.
197		Returns
198		-------
199		Path
200		Path to target csv-file
201
202		"""
203		return Path(
204		os.path.join(Path("."), "zensus_population", source.stem)
205		+ "."
206		+ dataset
207		+ source.suffix
208		)
209
210
211		def select_geom():
212		"""Select the union of the geometries of Schleswig-Holstein from the
213		database, convert their projection to the one used in the CSV file,
214		output the result to stdout as a GeoJSON string and read it into a
215		prepared shape for filtering.
216
217		"""
218		docker_db_config = db.credentials()
219
220		geojson = subprocess.run(
221		["ogr2ogr"]
222		+ ["-s_srs", "epsg:4326"]
223		+ ["-t_srs", "epsg:3035"]
224		+ ["-f", "GeoJSON"]
225		+ ["/vsistdout/"]
226		+ [
227		f"PG:host={docker_db_config['HOST']}"
228		f" user='{docker_db_config['POSTGRES_USER']}'"
229		f" password='{docker_db_config['POSTGRES_PASSWORD']}'"
230		f" port={docker_db_config['PORT']}"
231		f" dbname='{docker_db_config['POSTGRES_DB']}'"
232		]
233		+ ["-sql", "SELECT ST_Union(geometry) FROM boundaries.vg250_lan"],
234		text=True,
235		)
236		features = json.loads(geojson.stdout)["features"]
237		assert (
238		len(features) == 1
239		), f"Found {len(features)} geometry features, expected exactly one."
240
241		return prep(shape(features[0]["geometry"]))
242
243
244		def filter_zensus_population(filename, dataset):
245		"""This block filters lines in the source CSV file and copies
246		the appropriate ones to the destination based on geometry.
247
248
249		Parameters
250		----------
251		filename : str
252		Path to input csv-file
253		dataset: str, optional
254		Toggles between production (`dataset='Everything'`) and test mode e.g.
255		(`dataset='Schleswig-Holstein'`).
256		In production mode, data covering entire Germany
257		is used. In the test mode a subset of this data is used for testing the
258		workflow.
259		Returns
260		-------
261		str
262		Path to output csv-file
263
264		"""
265
266		csv_file = Path(filename).resolve(strict=True)
267
268		schleswig_holstein = select_geom()
269
270		if not os.path.isfile(target(csv_file, dataset)):
271
272		with open(csv_file, mode="r", newline="") as input_lines:
273		rows = csv.DictReader(input_lines, delimiter=";")
274		gitter_ids = set()
275		with open(
276		target(csv_file, dataset), mode="w", newline=""
277		) as destination:
278		output = csv.DictWriter(
279		destination, delimiter=";", fieldnames=rows.fieldnames
280		)
281		output.writeheader()
282		output.writerows(
283		gitter_ids.add(row["Gitter_ID_100m"]) or row
284		for row in rows
285		if schleswig_holstein.intersects(
286		Point(float(row["x_mp_100m"]), float(row["y_mp_100m"]))
287		)
288		)
289		return target(csv_file, dataset)
290
291
292		def filter_zensus_misc(filename, dataset):
293		"""This block filters lines in the source CSV file and copies
294		the appropriate ones to the destination based on grid_id values.
295
296
297		Parameters
298		----------
299		filename : str
300		Path to input csv-file
301		dataset: str, optional
302		Toggles between production (`dataset='Everything'`) and test mode e.g.
303		(`dataset='Schleswig-Holstein'`).
304		In production mode, data covering entire Germany
305		is used. In the test mode a subset of this data is used for testing the
306		workflow.
307		Returns
308		-------
309		str
310		Path to output csv-file
311
312		"""
313		csv_file = Path(filename).resolve(strict=True)
314
315		gitter_ids = set(
316		pd.read_sql(
317		"SELECT grid_id from society.destatis_zensus_population_per_ha",
318		con=db.engine(),
319		).grid_id.values
320		)
321
322		if not os.path.isfile(target(csv_file, dataset)):
323		with open(
324		csv_file, mode="r", newline="", encoding="iso-8859-1"
325		) as inputs:
326		rows = csv.DictReader(inputs, delimiter=",")
327		with open(
328		target(csv_file, dataset),
329		mode="w",
330		newline="",
331		encoding="iso-8859-1",
332		) as destination:
333		output = csv.DictWriter(
334		destination, delimiter=",", fieldnames=rows.fieldnames
335		)
336		output.writeheader()
337		output.writerows(
338		row for row in rows if row["Gitter_ID_100m"] in gitter_ids
339		)
340		return target(csv_file, dataset)
341
342
343		def population_to_postgres():
344		"""Import Zensus population data to postgres database"""
345		# Get information from data configuration file
346		data_config = egon.data.config.datasets()
347		zensus_population_orig = data_config["zensus_population"]["original_data"]
348		zensus_population_processed = data_config["zensus_population"]["processed"]
349		input_file = (
350		Path(".")
351		/ "zensus_population"
352		/ zensus_population_orig["target"]["file"]
353		)
354		dataset = settings()["egon-data"]["--dataset-boundary"]
355
356		# Read database configuration from docker-compose.yml
357		docker_db_config = db.credentials()
358
359		population_table = (
360		f"{zensus_population_processed['schema']}"
361		f".{zensus_population_processed['table']}"
362		)
363
364		with zipfile.ZipFile(input_file) as zf:
365		for filename in zf.namelist():
366
367		zf.extract(filename)
368
369		if dataset == "Everything":
370		filename_insert = filename
371		else:
372		filename_insert = filter_zensus_population(filename, dataset)
373
374		host = ["-h", f"{docker_db_config['HOST']}"]
375		port = ["-p", f"{docker_db_config['PORT']}"]
376		pgdb = ["-d", f"{docker_db_config['POSTGRES_DB']}"]
377		user = ["-U", f"{docker_db_config['POSTGRES_USER']}"]
378		command = [
379		"-c",
380		rf"\copy {population_table} (grid_id, x_mp, y_mp, population)"
381		rf" FROM '{filename_insert}' DELIMITER ';' CSV HEADER;",
382		]
383		subprocess.run(
384		["psql"] + host + port + pgdb + user + command,
385		env={"PGPASSWORD": docker_db_config["POSTGRES_PASSWORD"]},
386		)
387
388		os.remove(filename)
		0 ignored issues – show introduced 2021-01-14 05:17 UTC by Report Bug Copy Issue Report The variable `filename` does not seem to be defined in case the `for` loop on line `365` is not entered. Are you sure this can never be the case? Loading history...
389
390		db.execute_sql(
391		f"UPDATE {population_table} zs"
392		" SET geom_point=ST_SetSRID(ST_MakePoint(zs.x_mp, zs.y_mp), 3035);"
393		)
394
395		db.execute_sql(
396		f"UPDATE {population_table} zs"
397		""" SET geom=ST_SetSRID(
398		(ST_MakeEnvelope(zs.x_mp-50,zs.y_mp-50,zs.x_mp+50,zs.y_mp+50)),
399		3035
400		);
401		"""
402		)
403
404		db.execute_sql(
405		f"CREATE INDEX {zensus_population_processed['table']}_geom_idx ON"
406		f" {population_table} USING gist (geom);"
407		)
408
409		db.execute_sql(
410		f"CREATE INDEX"
411		f" {zensus_population_processed['table']}_geom_point_idx"
412		f" ON {population_table} USING gist (geom_point);"
413		)
414
415
416		def zensus_misc_to_postgres():
417		"""Import data on buildings, households and apartments to postgres db"""
418
419		# Get information from data configuration file
420		data_config = egon.data.config.datasets()
421		zensus_misc_processed = data_config["zensus_misc"]["processed"]
422		zensus_population_processed = data_config["zensus_population"]["processed"]
423		file_path = Path(".") / "zensus_population"
424		dataset = settings()["egon-data"]["--dataset-boundary"]
425
426		population_table = (
427		f"{zensus_population_processed['schema']}"
428		f".{zensus_population_processed['table']}"
429		)
430
431		# Read database configuration from docker-compose.yml
432		docker_db_config = db.credentials()
433
434		for input_file, table in zensus_misc_processed["file_table_map"].items():
435		with zipfile.ZipFile(file_path / input_file) as zf:
436		csvfiles = [n for n in zf.namelist() if n.lower()[-3:] == "csv"]
437		for filename in csvfiles:
438		zf.extract(filename)
439
440		if dataset == "Everything":
441		filename_insert = filename
442		else:
443		filename_insert = filter_zensus_misc(filename, dataset)
444
445		host = ["-h", f"{docker_db_config['HOST']}"]
446		port = ["-p", f"{docker_db_config['PORT']}"]
447		pgdb = ["-d", f"{docker_db_config['POSTGRES_DB']}"]
448		user = ["-U", f"{docker_db_config['POSTGRES_USER']}"]
449		command = [
450		"-c",
451		rf"\copy {zensus_population_processed['schema']}.{table}"
452		f"""(grid_id,
453		grid_id_new,
454		attribute,
455		characteristics_code,
456		characteristics_text,
457		quantity,
458		quantity_q)
459		FROM '{filename_insert}' DELIMITER ','
460		CSV HEADER
461		ENCODING 'iso-8859-1';""",
462		]
463		subprocess.run(
464		["psql"] + host + port + pgdb + user + command,
465		env={"PGPASSWORD": docker_db_config["POSTGRES_PASSWORD"]},
466		)
467
468		os.remove(filename)
		0 ignored issues – show introduced 2021-01-28 16:52 UTC by Report Bug Copy Issue Report The variable `filename` does not seem to be defined for all execution paths. Loading history...
469
470		db.execute_sql(
471		f"""UPDATE {zensus_population_processed['schema']}.{table} as b
472		SET zensus_population_id = zs.id
473		FROM {population_table} zs
474		WHERE b.grid_id = zs.grid_id;"""
475		)
476
477		db.execute_sql(
478		f"""ALTER TABLE {zensus_population_processed['schema']}.{table}
479		ADD CONSTRAINT {table}_fkey
480		FOREIGN KEY (zensus_population_id)
481		REFERENCES {population_table}(id);"""
482		)
483
484		# Create combined table
485		create_combined_zensus_table()
486
487		# Delete entries for unpopulated cells
488		adjust_zensus_misc()
489
490
491		def create_combined_zensus_table():
492		"""Create combined table with buildings, apartments and population per cell
493
494		Only apartment and building data with acceptable data quality
495		(quantity_q<2) is used, all other data is dropped. For more details on data
496		quality see Zensus docs:
497		https://www.zensus2011.de/DE/Home/Aktuelles/DemografischeGrunddaten.html
498
499		If there's no data on buildings or apartments for a certain cell, the value
500		for building_count resp. apartment_count contains NULL.
501		"""
502		sql_script = os.path.join(
503		os.path.dirname(__file__), "create_combined_zensus_table.sql"
504		)
505		db.execute_sql_script(sql_script)
506
507
508		def adjust_zensus_misc():
509		"""Delete unpopulated cells in zensus-households, -buildings and -apartments
510
511		Some unpopulated zensus cells are listed in:
512		- egon_destatis_zensus_household_per_ha
513		- egon_destatis_zensus_building_per_ha
514		- egon_destatis_zensus_apartment_per_ha
515
516		This can be caused by missing population
517		information due to privacy or other special cases (e.g. holiday homes
518		are listed as buildings but are not permanently populated.)
519		In the follwong tasks of egon-data, only data of populated cells is used.
520
521		Returns
522		-------
523		None.
524
525		"""
526		# Get information from data configuration file
527		data_config = egon.data.config.datasets()
528		zensus_population_processed = data_config["zensus_population"]["processed"]
529		zensus_misc_processed = data_config["zensus_misc"]["processed"]
530
531		population_table = (
532		f"{zensus_population_processed['schema']}"
533		f".{zensus_population_processed['table']}"
534		)
535
536		for input_file, table in zensus_misc_processed["file_table_map"].items():
537		db.execute_sql(
538		f"""
539		DELETE FROM {zensus_population_processed['schema']}.{table} as b
540		WHERE b.zensus_population_id IN (
541		SELECT id FROM {population_table}
542		WHERE population < 0);"""
543		)
544

openego / eGon-data

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data.datasets.zensus.ZensusPopulation.__init__() A

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