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Create geonames.py

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  1. geonames.py +114 -0
geonames.py ADDED
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+ #!/usr/bin/env python3
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+ # -*- coding: utf-8 -*-
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+ import os
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+ from functools import partial
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+ from pathlib import Path
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+
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+ import datasets
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+ import pandas as pd
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+ from datasets import DatasetDict, load_dataset
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+
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+ from data.data_loader_base import DataLoaderBase
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+
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+ VERSION = datasets.Version("0.0.1")
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+
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+ AVAILABLE_DATASETS = {
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+ 'geonames': 'https://download.geonames.org/export/dump/allCountries.zip',
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+ 'alternateNames': 'https://download.geonames.org/export/dump/alternateNames.zip',
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+ }
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+ FIELDS = [
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+ "geonameid", # integer id of record in geonames database
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+ "name", # name of geographical point (utf8) varchar(200)
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+ "asciiname", # name of geographical point in plain ascii characters, varchar(200)
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+ "alternatenames",
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+ # alternatenames, comma separated, ascii names automatically transliterated, convenience attribute from alternatename table, varchar(10000)
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+ "latitude", # latitude in decimal degrees (wgs84)
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+ "longitude", # longitude in decimal degrees (wgs84)
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+ "feature_class", # see http://www.geonames.org/export/codes.html, char(1)
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+ "feature_code", # see http://www.geonames.org/export/codes.html, varchar(10)
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+ "country_code", # ISO-3166 2-letter country code, 2 characters
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+ "cc2",
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+ # alternate country codes, comma separated, ISO-3166 2-letter country code, 200 characters
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+ "admin1_code",
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+ # fipscode (subject to change to iso code), see exceptions below, see file admin1Codes.txt for display names of this code; varchar(20)
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+ "admin2_code",
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+ # code for the second administrative division, a county in the US, see file admin2Codes.txt; varchar(80)
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+ "admin3_code", # code for third level administrative division, varchar(20)
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+ "admin4_code", # code for fourth level administrative division, varchar(20)
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+ "population", # bigint (8 byte int)
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+ "elevation", # in meters, integer
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+ "dem",
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+ # digital elevation model, srtm3 or gtopo30, average elevation of 3''x3'' (ca 90mx90m) or 30''x30'' (ca 900mx900m) area in meters, integer. srtm processed by cgiar/ciat.
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+ "timezone", # the iana timezone id (see file timeZone.txt) varchar(40)
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+ "modification_date", # date of last modification in yyyy-MM-dd format"
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+ ]
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+
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+
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+ class GeonamesDataset(datasets.GeneratorBasedBuilder, DataLoaderBase):
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+ """GeonamesDataset dataset."""
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+
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+ @staticmethod
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+ def load(data_name_config: str = "geonames") -> DatasetDict:
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+ ds = load_dataset(__file__, data_name_config)
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+ return ds
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+
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+ def _info(self):
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+ return datasets.DatasetInfo(
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+ description="",
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+ features=datasets.Features(
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+ {
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+ "geonameid": datasets.Value("string"),
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+ "name": datasets.Value("string"),
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+ "asciiname": datasets.Value("string"),
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+ "alternatenames": datasets.Value("string"),
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+ "latitude": datasets.Value("string"),
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+ "longitude": datasets.Value("string"),
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+ "feature_class": datasets.Value("string"),
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+ "feature_code": datasets.Value("string"),
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+ "country_code": datasets.Value("string"),
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+ "cc2": datasets.Value("string"),
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+ "admin1_code": datasets.Value("string"),
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+ "admin2_code": datasets.Value("string"),
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+ "admin3_code": datasets.Value("string"),
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+ "admin4_code": datasets.Value("string"),
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+ "population": datasets.Value("string"),
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+ "elevation": datasets.Value("string"),
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+ "dem": datasets.Value("string"),
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+ "timezone": datasets.Value("string"),
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+ "modification_date": datasets.Value("string"),
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+ }
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+ ),
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+ supervised_keys=None,
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+ homepage="https://download.geonames.org/export/zip/",
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+ citation="",
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+ )
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+
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+ def _split_generators(self, dl_manager):
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+ root_paths = {
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+ "geonames": Path(dl_manager.download_and_extract(AVAILABLE_DATASETS["geonames"]))/'allCountries.txt',
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+ "alternateNames": Path(dl_manager.download_and_extract(AVAILABLE_DATASETS["alternateNames"]))/'alternateNames.txt',
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+ }
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+ return [
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+ datasets.SplitGenerator(
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+ name=datasets.Split.TRAIN,
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+ gen_kwargs={
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+ "root_path": root_paths, "split": "train"
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+ },
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+ ),
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+ ]
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+
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+ def _generate_examples(self, root_path, split):
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+ data_file = str(root_path["geonames"])
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+ data = pd.read_csv(
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+ data_file, sep="\t", header=None,
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+ encoding='utf-8', usecols=list(range(len(FIELDS))), names=FIELDS
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+ )
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+ # data_file = str(root_path["alternateNames"])
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+ # alt_data = pd.read_csv(
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+ # data_file, sep="\t", header=None,
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+ # encoding='utf-8', names=["id", "geonameid", "altname"], nrows=100
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+ # )
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+ # data = data.merge(alt_data, on="geonameid", how="left")
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+ for idx, sample in data.iterrows():
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+ yield idx, dict(sample)
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+