Release covidcast-indicators 0.3.59

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.3.58
+current_version = 0.3.59
 commit = True
 message = chore: bump covidcast-indicators to {new_version}
 tag = False

ansible/templates/sir_complainsalot-params-prod.json.j2

@@ -44,7 +44,13 @@
     },
     "nssp": {
       "max_age":19,
-      "maintainers": []
+      "maintainers": [],
+      "retired-signals": [
+        "pct_ed_visits_combined_2023rvr",
+        "pct_ed_visits_covid_2023rvr",
+        "pct_ed_visits_influenza_2023rvr",
+        "pct_ed_visits_rsv_2023rvr"
+      ]
     },
     "nhsn": {
       "max_age":19,

changehc/version.cfg

@@ -1 +1 @@
-current_version = 0.3.58
+current_version = 0.3.59

claims_hosp/version.cfg

@@ -1 +1 @@
-current_version = 0.3.58
+current_version = 0.3.59

doctor_visits/version.cfg

@@ -1 +1 @@
-current_version = 0.3.58
+current_version = 0.3.59

google_symptoms/version.cfg

@@ -1 +1 @@
-current_version = 0.3.58
+current_version = 0.3.59

hhs_hosp/version.cfg

@@ -1 +1 @@
-current_version = 0.3.58
+current_version = 0.3.59

nchs_mortality/version.cfg

@@ -1 +1 @@
-current_version = 0.3.58
+current_version = 0.3.59

nhsn/delphi_nhsn/constants.py

@@ -2,6 +2,9 @@
 
 GEOS = ["state", "nation", "hhs"]
 
+MAIN_DATASET_ID = "ua7e-t2fy"
+PRELIM_DATASET_ID = "mpgq-jmmr"
+
 # column name from socrata
 TOTAL_ADMISSION_COVID_API = "totalconfc19newadm"
 TOTAL_ADMISSION_FLU_API = "totalconfflunewadm"

nhsn/delphi_nhsn/patch.py

@@ -0,0 +1,94 @@
+"""
+This module is used for patching data in the delphi_nhsn package.
+
+To use this module, you need to specify the range of issue dates in params.json, like so:
+
+{
+  "common": {
+    ...
+  },
+  "validation": {
+    ...
+  },
+  "patch": {
+    "patch_dir": "/Users/minhkhuele/Desktop/delphi/covidcast-indicators/nhsn/patch"
+  }
+}
+
+It will generate data for the range of issue dates corresponding to source data files available in "backup_dir"
+specified under "common", and store them in batch issue format under "patch_dir":
+[name-of-patch]/issue_[issue-date]/nhsn/actual_data_file.csv
+"""
+
+from datetime import datetime
+from os import makedirs
+from pathlib import Path
+from typing import List
+
+from delphi_utils import get_structured_logger, read_params
+from epiweeks import Week
+
+from .run import run_module
+
+
+def filter_source_files(source_files: List[Path]):
+    """
+    Filter patch files such that each element in the list is an unique epiweek with the latest issue date.
+
+    Parameters
+    ----------
+    source_files
+
+    Returns
+    -------
+    list of issue dates
+
+    """
+    epiweek_dict = dict()
+
+    for file in source_files:
+        if "prelim" not in file.stem:
+            current_issue_date = datetime.strptime(file.name.split(".")[0], "%Y%m%d")
+            epiweek = Week.fromdate(current_issue_date)
+            epiweek_dict[epiweek] = file
+
+    filtered_patch_list = list(epiweek_dict.values())
+    return filtered_patch_list
+
+
+def patch(params):
+    """
+    Run the doctor visits indicator for a range of issue dates.
+
+    The range of issue dates is specified in params.json using the following keys:
+    - "patch": Only used for patching data
+        - "patch_dir": str, directory to write all issues output
+    """
+    logger = get_structured_logger("delphi_nhsn.patch", filename=params["common"]["log_filename"])
+
+    source_files = sorted(Path(params["common"]["backup_dir"]).glob("*.csv.gz"))
+    makedirs(params["patch"]["patch_dir"], exist_ok=True)
+
+    logger.info(
+        "Starting patching",
+        patch_directory=params["patch"]["patch_dir"],
+        start_issue=source_files[0].name.split(".")[0],
+        end_issue=source_files[-1].name.split(".")[0],
+    )
+
+    patch_list = filter_source_files(source_files)
+    for file in patch_list:
+        issue_date_str = file.name.split(".")[0]
+        logger.info("Running issue", issue_date=datetime.strptime(issue_date_str, "%Y%m%d").strftime("%Y-%m-%d"))
+        params["patch"]["issue_date"] = issue_date_str
+        # regardless of week date type or not the directory name must be issue_date_YYYYMMDD
+        # conversion in done in acquisition
+        current_issue_dir = f"{params['patch']['patch_dir']}/issue_{issue_date_str}/nhsn"
+        makedirs(current_issue_dir, exist_ok=True)
+        params["common"]["export_dir"] = current_issue_dir
+        params["common"]["custom_run"] = True
+        run_module(params, logger)
+
+
+if __name__ == "__main__":
+    patch(read_params())

nhsn/delphi_nhsn/pull.py

@@ -1,13 +1,14 @@
 # -*- coding: utf-8 -*-
 """Functions for pulling NSSP ER data."""
 import logging
+from pathlib import Path
 from typing import Optional
 
 import pandas as pd
 from delphi_utils import create_backup_csv
 from sodapy import Socrata
 
-from .constants import PRELIM_SIGNALS_MAP, PRELIM_TYPE_DICT, SIGNALS_MAP, TYPE_DICT
+from .constants import MAIN_DATASET_ID, PRELIM_DATASET_ID, PRELIM_SIGNALS_MAP, PRELIM_TYPE_DICT, SIGNALS_MAP, TYPE_DICT
 
 
 def pull_data(socrata_token: str, dataset_id: str):
@@ -27,7 +28,42 @@ def pull_data(socrata_token: str, dataset_id: str):
     return df
 
 
-def pull_nhsn_data(socrata_token: str, backup_dir: str, custom_run: bool, logger: Optional[logging.Logger] = None):
+def pull_data_from_file(filepath: str, issue_date: str, logger, prelim_flag=False) -> pd.DataFrame:
+    """
+    Pull data from source file.
+
+    The source file is generated from delphi_utils.create_backup_csv
+    Parameters
+    ----------
+    filepath: full path where the source file is located
+    issue_date: date when the file was pulled / generated
+    logger
+    prelim_flag: boolean to indicate which dataset to grab
+
+    Returns
+    -------
+    pd.DataFrame
+        Dataframe as described above.
+    """
+    df = pd.DataFrame()
+    if issue_date:
+        issue_date = issue_date.replace("-", "")
+        filename = f"{issue_date}_prelim.csv.gz" if prelim_flag else f"{issue_date}.csv.gz"
+        backup_file = Path(filepath, filename)
+
+        if backup_file.exists():
+            df = pd.read_csv(backup_file, compression="gzip")
+            logger.info("Pulling data from file", file=filename, num_rows=len(df))
+    return df
+
+
+def pull_nhsn_data(
+    socrata_token: str,
+    backup_dir: str,
+    custom_run: bool,
+    issue_date: Optional[str],
+    logger: Optional[logging.Logger] = None,
+):
     """Pull the latest NHSN hospital admission data, and conforms it into a dataset.
 
     The output dataset has:
@@ -52,7 +88,11 @@ def pull_nhsn_data(socrata_token: str, backup_dir: str, custom_run: bool, logger
         Dataframe as described above.
     """
     # Pull data from Socrata API
-    df = pull_data(socrata_token, dataset_id="ua7e-t2fy")
+    df = (
+        pull_data(socrata_token, dataset_id=MAIN_DATASET_ID)
+        if not custom_run
+        else pull_data_from_file(backup_dir, issue_date, logger, prelim_flag=False)
+    )
 
     keep_columns = list(TYPE_DICT.keys())
 
@@ -75,7 +115,11 @@ def pull_nhsn_data(socrata_token: str, backup_dir: str, custom_run: bool, logger
 
 
 def pull_preliminary_nhsn_data(
-    socrata_token: str, backup_dir: str, custom_run: bool, logger: Optional[logging.Logger] = None
+    socrata_token: str,
+    backup_dir: str,
+    custom_run: bool,
+    issue_date: Optional[str],
+    logger: Optional[logging.Logger] = None,
 ):
     """Pull the latest preliminary NHSN hospital admission data, and conforms it into a dataset.
 
@@ -100,8 +144,11 @@ def pull_preliminary_nhsn_data(
     pd.DataFrame
         Dataframe as described above.
     """
-    # Pull data from Socrata API
-    df = pull_data(socrata_token, dataset_id="mpgq-jmmr")
+    df = (
+        pull_data(socrata_token, dataset_id=PRELIM_DATASET_ID)
+        if not custom_run
+        else pull_data_from_file(backup_dir, issue_date, logger, prelim_flag=True)
+    )
 
     keep_columns = list(PRELIM_TYPE_DICT.keys())
 

nhsn/delphi_nhsn/run.py

@@ -25,7 +25,7 @@
 from .pull import pull_nhsn_data, pull_preliminary_nhsn_data
 
 
-def run_module(params):
+def run_module(params, logger=None):
     """
     Run the indicator.
 
@@ -35,14 +35,16 @@ def run_module(params):
         Nested dictionary of parameters.
     """
     start_time = time.time()
-    logger = get_structured_logger(
-        __name__,
-        filename=params["common"].get("log_filename"),
-        log_exceptions=params["common"].get("log_exceptions", True),
-    )
+    if not logger:
+        logger = get_structured_logger(
+            __name__,
+            filename=params["common"].get("log_filename"),
+            log_exceptions=params["common"].get("log_exceptions", True),
+        )
     export_dir = params["common"]["export_dir"]
     backup_dir = params["common"]["backup_dir"]
     custom_run = params["common"].get("custom_run", False)
+    issue_date = params.get("patch", dict()).get("issue_date", None)
     socrata_token = params["indicator"]["socrata_token"]
     export_start_date = params["indicator"]["export_start_date"]
     run_stats = []
@@ -51,12 +53,16 @@ def run_module(params):
         export_start_date = date.today() - timedelta(days=date.today().weekday() + 2)
         export_start_date = export_start_date.strftime("%Y-%m-%d")
 
-    nhsn_df = pull_nhsn_data(socrata_token, backup_dir, custom_run=custom_run, logger=logger)
-    preliminary_nhsn_df = pull_preliminary_nhsn_data(socrata_token, backup_dir, custom_run=custom_run, logger=logger)
+    nhsn_df = pull_nhsn_data(socrata_token, backup_dir, custom_run=custom_run, issue_date=issue_date, logger=logger)
+    preliminary_nhsn_df = pull_preliminary_nhsn_data(
+        socrata_token, backup_dir, custom_run=custom_run, issue_date=issue_date, logger=logger
+    )
 
     geo_mapper = GeoMapper()
     signal_df_dict = {signal: nhsn_df for signal in SIGNALS_MAP}
-    signal_df_dict.update({signal: preliminary_nhsn_df for signal in PRELIM_SIGNALS_MAP})
+    # some of the source backups do not include for preliminary data TODO remove after first patch
+    if not preliminary_nhsn_df.empty:
+        signal_df_dict.update({signal: preliminary_nhsn_df for signal in PRELIM_SIGNALS_MAP})
 
     for signal, df_pull in signal_df_dict.items():
         for geo in GEOS:
@@ -67,14 +73,17 @@ def run_module(params):
                 df = df[df["geo_id"] == "us"]
             elif geo == "hhs":
                 df = df[df["geo_id"] != "us"]
+                df = df[df["geo_id"].str.len() == 2]
                 df.rename(columns={"geo_id": "state_id"}, inplace=True)
                 df = geo_mapper.add_geocode(df, "state_id", "state_code", from_col="state_id")
                 df = geo_mapper.add_geocode(df, "state_code", "hhs", from_col="state_code", new_col="hhs")
                 df = geo_mapper.replace_geocode(
                     df, from_col="state_code", from_code="state_code", new_col="geo_id", new_code="hhs"
                 )
-            else:
+            elif geo == "state":
                 df = df[df_pull["geo_id"] != "us"]
+                df = df[df["geo_id"].str.len() == 2]  # hhs region is a value in geo_id column
+
             df["se"] = np.nan
             df["sample_size"] = np.nan
             dates = create_export_csv(

nhsn/tests/conftest.py

@@ -16,10 +16,10 @@
 # queries the nhsn data with timestamp (2021-08-19, 2021-10-19) with CO and USA data
 
 
-with open("test_data/page.json", "r") as f:
+with open(f"{TEST_DIR}/test_data/page.json", "r") as f:
     TEST_DATA = json.load(f)
 
-with open("test_data/prelim_page.json", "r") as f:
+with open(f"{TEST_DIR}/test_data/prelim_page.json", "r") as f:
     PRELIM_TEST_DATA = json.load(f)
 
 @pytest.fixture(scope="session")
@@ -50,11 +50,12 @@ def params():
 @pytest.fixture
 def params_w_patch(params):
     params_copy = copy.deepcopy(params)
+    params_copy["common"]["custom_run"] = True
     params_copy["patch"] = {
-            "start_issue": "2024-06-27",
-            "end_issue": "2024-06-29",
-            "patch_dir": "./patch_dir"
+            "patch_dir": f"{TEST_DIR}/patch_dir",
+            "issue_date": "2024-12-12",
         }
+
     return params_copy
 
 @pytest.fixture(scope="function")