diff --git a/epigraphhub/data/_config.py b/epigraphhub/data/_config.py index 5ebf22ce..01db00ae 100644 --- a/epigraphhub/data/_config.py +++ b/epigraphhub/data/_config.py @@ -4,26 +4,26 @@ commonly used in data collection modules """ -""" -Colombia COVID data config: -""" +# Colombia COVID data config: from sodapy import Socrata COLOMBIA_LOG_PATH = "/var/log/colombia_fetch.log" COLOMBIA_CLIENT = Socrata("www.datos.gov.co", "078u4PCGpnDfH157kAkVFoWea") -""" -Federal Office of Public Health (FOPH) COVID data config: -""" + +# Federal Office of Public Health (FOPH) COVID data config: FOPH_LOG_PATH = "/var/log/foph_fetch.log" FOPH_URL = "https://www.covid19.admin.ch/api/data/context" FOPH_CSV_PATH = "/tmp/foph/releases" -""" -Our World in Data (OWID) COVID data config: -""" + +# Our World in Data (OWID) COVID data config: OWID_LOG_PATH = "/var/log/owid_fetch.log" OWID_CSV_URL = "https://covid.ourworldindata.org/data/owid-covid-data.csv" OWID_CSV_PATH = "/tmp/owid/releases" OWID_FILENAME = OWID_CSV_URL.split("/")[-1] OWID_HOST = "135.181.41.20" + + +# SINAN data config: +SINAN_LOG_PATH = "/var/log/sinan_fetch.log" diff --git a/epigraphhub/data/brasil/sinan/extract.py b/epigraphhub/data/brasil/sinan/extract.py new file mode 100644 index 00000000..da443f8d --- /dev/null +++ b/epigraphhub/data/brasil/sinan/extract.py @@ -0,0 +1,29 @@ +from pathlib import PosixPath + +from loguru import logger +from pysus.online_data import SINAN + +from epigraphhub.data._config import SINAN_LOG_PATH + +logger.add(SINAN_LOG_PATH, retention="7 days") + +diseases = SINAN.agravos + + +def download(disease: str): + """ + Download all parquets available for an disease, + according to `SINAN.agravos`. + + Attrs: + disease (str): The disease to be downloaded. + data_dir (str) : The output directory were files will be downloaded. + A directory with the disease code will be created. + + Returns: + parquets_paths_list list(PosixPath) : A list with all parquets dirs. + """ + + SINAN.download_all_years_in_chunks(disease) + + logger.info(f"All years for {disease} downloaded at /tmp/pysus") diff --git a/epigraphhub/data/brasil/sinan/loading.py b/epigraphhub/data/brasil/sinan/loading.py new file mode 100644 index 00000000..f0c46207 --- /dev/null +++ b/epigraphhub/data/brasil/sinan/loading.py @@ -0,0 +1,61 @@ +import os +from pathlib import Path + +from loguru import logger +from pangres import upsert +from pysus.online_data import parquets_to_dataframe as to_df + +from epigraphhub.connection import get_engine +from epigraphhub.data._config import SINAN_LOG_PATH +from epigraphhub.settings import env + +logger.add(SINAN_LOG_PATH, retention="7 days") + +engine = get_engine(credential_name=env.db.default_credential) + + +def upload(): + """ + Connects to the EGH SQL server and load all the chunks for all + diseases found at `/tmp/pysus` into database. This method cleans + the chunks left. + + """ + diseases_dir = Path('/tmp/pysus').glob('*') + di_years_dir = [x for x in diseases_dir if x.is_dir()] + + for dir in di_years_dir: + + parquets_dir = Path(dir).glob('*.parquet') + parquets = [x for x in parquets_dir if x.is_dir()] + + for parquet in parquets: + if 'parquet' in Path(parquet).suffix and any(os.listdir(parquet)): + + df = to_df(str(parquet), clean_after_read=True) + df.columns = df.columns.str.lower() + df.index.name = "index" + + table_i = str(parquet).split("/")[-1].split(".parquet")[0] + st, yr = table_i[:-4].lower(), table_i[-2:] + table = "".join([st, yr]) + schema = "brasil" + + with engine.connect() as conn: + try: + + upsert( + con=conn, + df=df, + table_name=table, + schema=schema, + if_row_exists="update", + chunksize=1000, + add_new_columns=True, + create_table=True, + ) + + logger.info(f"Table {table} updated") + + except Exception as e: + logger.error(f"Not able to upsert {table} \n{e}") diff --git a/epigraphhub/data/brasil/sinan/viz.py b/epigraphhub/data/brasil/sinan/viz.py new file mode 100644 index 00000000..4245c135 --- /dev/null +++ b/epigraphhub/data/brasil/sinan/viz.py @@ -0,0 +1,59 @@ +import pandas as pd +from loguru import logger +from pysus.online_data import SINAN +from pysus.online_data import parquets_to_dataframe as to_df + +from epigraphhub.connection import get_engine +from epigraphhub.data._config import SINAN_LOG_PATH +from epigraphhub.settings import env + +logger.add(SINAN_LOG_PATH, retention="7 days") + +engine = get_engine(credential_name=env.db.default_credential) +aggrs = SINAN.agravos + + +def parquet(ppath: str, clean_after_read=False) -> pd.DataFrame: + """ + Convert the parquet files into a pandas DataFrame. + + Parameters + ---------- + fname (str) : Path of the parquet dir. + clean_after_read (bool): If set to True, will delete the data after + returning the DataFrame. + Returns + ------- + df (DataFrame) : A Pandas DataFrame. + """ + + df = to_df(str(ppath), clean_after_read) + logger.info("Parquet files converted to dataFrame") + df.columns = df.columns.str.lower() + + return df + + +def table(disease: str, year: int) -> pd.DataFrame: + """ + Connect to EGH SQL server and retrieve the data by disease and year. + + Parameters + ---------- + disease (str) : The name of the disease according to SINAN.agravos + year (int) : Year of the wanted data. + Returns + ------- + df (DataFrame): The data requested in a Pandas DataFrame. + + """ + + year = str(year)[-2:].zfill(2) + disease = SINAN.check_case(disease) + dis_code = aggrs[disease].lower() + tablename = f"{dis_code}{year}" + + with engine.connect() as conn: + df = pd.read_sql(f"SELECT * FROM brasil.{tablename}", conn) + + return df diff --git a/poetry.lock b/poetry.lock index 4139ed8c..dadc1651 100644 --- a/poetry.lock +++ b/poetry.lock @@ -195,6 +195,14 @@ python-versions = "*" [package.dependencies] six = ">=1.6.1,<2.0" +[[package]] +name = "atpublic" +version = "3.1.1" 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hash = "sha256:9b630419bde84ec666bfd7ea0a4cb2a8a651c2d5cccdbdd1972a0c859dfc3c13"}, +] tqdm = [ {file = "tqdm-4.64.1-py2.py3-none-any.whl", hash = "sha256:6fee160d6ffcd1b1c68c65f14c829c22832bc401726335ce92c52d395944a6a1"}, {file = "tqdm-4.64.1.tar.gz", hash = "sha256:5f4f682a004951c1b450bc753c710e9280c5746ce6ffedee253ddbcbf54cf1e4"}, diff --git a/pyproject.toml b/pyproject.toml index eb58061b..5acd29f7 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -36,7 +36,7 @@ classifiers = [ #! Update me python = ">=3.9,<3.11" typer = {extras = ["all"], version = "^0.4.0"} -rich = "^11.2.0" +rich = ">=12.4.4,<13" numpy = "^1.20.3" pandas = "^1.2" scipy = "^1.8.0" @@ -65,6 +65,7 @@ loguru = "^0.6.0" sodapy = "^2.2.0" pangres = "^4.1.2" ngboost = "^0.3.13" +ibis-framework = "^3.2.0" [tool.poetry.dev-dependencies] bandit = "^1.7.2" diff --git a/tests/test_data/test_sinan_fetch.py b/tests/test_data/test_sinan_fetch.py index bdc31c7b..73085208 100644 --- a/tests/test_data/test_sinan_fetch.py +++ b/tests/test_data/test_sinan_fetch.py @@ -1,47 +1,57 @@ -import pathlib +import os import unittest +from pathlib import Path import pandas as pd -from pandas.io.sql import get_schema -from epigraphhub.data.sinan_fetch import ( - download_data, - engine, - parquet_to_df, - save_to_pgsql, -) +from epigraphhub.connection import get_engine +from epigraphhub.data.brasil.sinan import extract, loading, viz +from epigraphhub.settings import env + +engine = get_engine(credential_name=env.db.default_credential) class TestFethSinan(unittest.TestCase): def setUp(self): self.engine = engine - self.disease = "zika" + self.disease = "Zika" self.year = 2017 - self.fname = "ZIKABR17.parquet" - self.table = "zikabr17" + self.fpath = ["/tmp/pysus/ZIKA/ZIKABR17.parquet"] + self.table = "zika17" self.schema = "brasil" - def test_download_data(self): - _fname = download_data(self.disease, self.year) + def test_download_data_zika(self): + + _fname = extract.download(self.disease) - self.assertEqual(self.fname, str(_fname)) - self.assertIsInstance(_fname, pathlib.PosixPath) - self.assertTrue(_fname.is_dir()) + self.assertTrue(Path(self.fpath[0]).exists()) + self.assertTrue(any(os.listdir(self.fpath[0]))) + self.assertEqual( + _fname, + [ + "/tmp/pysus/ZIKA/ZIKABR16.parquet", + "/tmp/pysus/ZIKA/ZIKABR17.parquet", + "/tmp/pysus/ZIKA/ZIKABR18.parquet", + "/tmp/pysus/ZIKA/ZIKABR19.parquet", + "/tmp/pysus/ZIKA/ZIKABR20.parquet", + "/tmp/pysus/ZIKA/ZIKABR21.parquet", + ], + ) - def test_parquet_to_df(self): - df = parquet_to_df(self.fname) + def test_parquet_visualization(self): + + df = viz.parquet(self.fpath[0], clean_after_read=False) self.assertIsInstance(df, pd.DataFrame) self.assertEqual(df.shape, (32684, 38)) def test_save_to_pgsql(self): - save_to_pgsql(self.disease, self.year) - table_name = f'"{self.schema}"."{self.table}"' - query = "SELECT count(*) FROM brasil.zikabr17 LIMIT 10;" - df1 = pd.read_sql(query, engine) - df2 = parquet_to_df(self.fname) - query_sql = get_schema(df2, self.table, schema=self.schema, con=engine) - - self.assertEqual(table_name, '"brasil"."zikabr17"') - self.assertIn("CREATE TABLE brasil.zikabr17", query_sql) - self.assertEqual(int(df1["count"]), df2.shape[0]) + + loading.upload(self.fpath) + + def test_table_visualization(self): + + df = viz.table(self.disease, self.year) + + self.assertIsInstance(df, pd.DataFrame) + self.assertFalse(df.empty)