Merge pull request #3 from HYLODE/reversion

Creating a minimum viable version of the sitrep dashboard

.env.example

@@ -26,9 +26,6 @@ API_BASEROW_USERNAME=hyui
 # Current hycastle and hymind on GAE08 5207/5208 respectively
 API_HYCASTLE_URL=http://hycastle:1234
 API_HYMIND_URL=http://hymind:1234
-API_TOWERMAIL_URL=http://towermail:1234
-API_ELECTIVES_TAP_URL=http://somehost:1234
-API_EMERGENCY_TAP_URL=http://somehost:1234
 # Hylode-Bot : slack API hook
 API_SLACK_LOG_WEBHOOK=https://hooks.slack.com/services/foo/bar/baz
 

.gitignore

@@ -926,9 +926,6 @@ docs/_linkcheck/
 # Docker cruft
 .bash_history
 
-# ignore generated data
-src/api/perrt/admission_probability/generated_data
-
 # local jupyter lab for exploratory work
 jupyter/
 

.pre-commit-config.yaml

@@ -69,3 +69,7 @@ repos:
         name: detect-secrets - Detect secrets in staged code
         args: [ "--baseline", ".secrets.baseline" ]
         exclude: .*/tests/.*|^\.cruft\.json|.env.example$
+  - repo: https://github.com/pappasam/toml-sort
+    rev: v0.23.1
+    hooks:
+      - id: toml-sort-fix

api/pyproject.toml

@@ -6,36 +6,36 @@ build-backend = "setuptools.build_meta"
 name = "hyui-api"
 version = "0.0.1"
 dependencies = [
-    "loguru == 0.6.0",
-    "notifiers == 1.3.3",
-    "hyui-models",
-    "arrow == 1.2.3",
-    "fastapi[all] == 0.85.0",
-    "fastapi-utils==0.2.1",
-    "pandas == 1.5.1",
-    "pyodbc == 4.0.35",
-    "psycopg2-binary == 2.9.5",
-    "pydantic == 1.10.2",
-    "SQLAlchemy == 1.4.41",
-    "sqlmodel == 0.0.8",
-    "uvicorn[standard] == 0.18.3",
-    "scikit-learn == 1.1.3",
-    "imbalanced-learn == 0.10.1",
-    "category-encoders == 2.6.0",
-    "xgboost == 1.5.0",
+  "loguru == 0.6.0",
+  "notifiers == 1.3.3",
+  "hyui-models",
+  "arrow == 1.2.3",
+  "fastapi[all] == 0.99.1",
+  "fastapi-utils==0.2.1",
+  "pandas == 1.5.1",
+  "pyodbc == 4.0.35",
+  "psycopg2-binary == 2.9.5",
+  "pydantic >=1.10.2,<2.0",
+  "SQLAlchemy == 1.4.41",
+  "sqlmodel == 0.0.8",
+  "uvicorn[standard] == 0.18.3",
+  "scikit-learn == 1.1.3",
+  "imbalanced-learn == 0.10.1",
+  "category-encoders == 2.6.0",
+  "xgboost == 1.5.0"
 ]
 
 [project.optional-dependencies]
 test = [
-    "pre-commit == 2.20.0",
-    "pytest == 7.1.3"
+  "pre-commit == 2.20.0",
+  "pytest == 7.1.3"
 ]
 
-[tool.setuptools.package-data]
-"*" = ["*.sql", "*.json", "*.db"]
-
 [tool.pytest.ini_options]
 minversion = "7.1.3"
 testpaths = [
-    "src/api/tests"
+  "src/api/tests"
 ]
+
+[tool.setuptools.package-data]
+"*" = ["*.sql", "*.json", "*.db"]

api/src/api/census/wrangle.py

@@ -1,3 +1,4 @@
+import numpy as np
 import pandas as pd
 import warnings
 
@@ -49,10 +50,15 @@ def _aggregate_by_department(df: pd.DataFrame) -> pd.DataFrame:
     # source
     # placeholder: need to subtract closed from empties
     # res["opens"] = res["empties"]
+
+    # Calculate days since last discharge, but handle NaT values in wards by allowing
+    # the quantity to be a float rather than integer
+    res["days_since_last_dc"] = (
+        (res["modified_at"] - res["days_since_last_dc"]).dt.floor("d").dt.days
+    )
+    # Convert remaining NaT values to -999, then convert the Series dtype to int
     res["days_since_last_dc"] = (
-        (res["modified_at"] - res["days_since_last_dc"])
-        .apply(lambda x: pd.Timedelta.floor(x, "d"))
-        .dt.days
+        res["days_since_last_dc"].replace(np.nan, -999.0).astype(int)
     )
 
     # use days since last dc and there being no patients to define if a ward
@@ -65,12 +71,27 @@ def _aggregate_by_department(df: pd.DataFrame) -> pd.DataFrame:
         ]
     ).T.all(axis="columns")
 
-    res["closed_perm"] = pd.DataFrame(
-        [
-            res["days_since_last_dc"] > 30,
-            res["patients"] == 0,
-        ]
-    ).T.all(axis="columns")
+    def _closed_perm_conditions(row: pd.Series) -> bool:
+        """Calculate permanent closure conditions.
+
+        Handles NaT values of days_since_last_dc, which are
+        converted to -999.
+
+        Args:
+            row (pd.Series): Pandas DataFrame row
+
+        Returns:
+            bool: Is the ward permanently closed?
+        """
+        if row["days_since_last_dc"] > 30 and row["patients"] == 0:
+            closed = True
+        elif row["days_since_last_dc"] < 0:
+            closed = True
+        else:
+            closed = False
+        return closed
+
+    res["closed_perm"] = res.apply(_closed_perm_conditions, axis=1)
 
     # drop closed perm
     # mask = ~res["closed_perm"]

api/src/api/config.py

@@ -15,11 +15,6 @@ class Settings(BaseSettings):
     baserow_username: str
 
     hycastle_url: AnyHttpUrl
-    hymind_url: AnyHttpUrl
-    towermail_url: AnyHttpUrl
-
-    electives_tap_url: AnyHttpUrl
-    emergency_tap_url: AnyHttpUrl
 
     echo_sql: bool = False