type hinting

Author: drkane

ukgrantmaking/management/commands/export.py

@@ -3,10 +3,10 @@
 from ukgrantmaking.models.funder import Funder, FunderNote, FunderTag
 from ukgrantmaking.models.funder_year import FunderYear
 from ukgrantmaking.models.grant import Grant
-from ukgrantmaking.views import export_all_data
+from ukgrantmaking.views import export_all_data_excel
 
 
-@click.group(invoke_without_command=False)
+@click.group()
 def main():
     pass
 
@@ -15,11 +15,11 @@ def main():
 @click.argument("filename", type=click.Path())
 def grants(filename):
     models = [Grant]
-    export_all_data(models, filename)
+    export_all_data_excel(models, filename)
 
 
 @main.command()
 @click.argument("filename", type=click.Path())
 def funders(filename):
     models = [Funder, FunderYear, FunderTag, FunderNote]
-    export_all_data(models, filename)
+    export_all_data_excel(models, filename)

ukgrantmaking/utils/__init__.py

@@ -19,7 +19,7 @@ def batched(iterable, n: int = DEFAULT_BATCH_SIZE):
 
 
 def do_batched_update(
-    model: models.Model,
+    model: type[models.Model],
     iterable: Generator[Dict, None, None],
     unique_fields: list[str],
     update_fields: list[str],

ukgrantmaking/utils/funder_individuals_summary.py

@@ -9,7 +9,9 @@
 from ukgrantmaking.models.funder_utils import FUNDER_CATEGORIES
 
 
-def funder_individuals_summary(current_fy: FinancialYear, effective_date: datetime):
+def funder_individuals_summary(
+    current_fy: FinancialYear, effective_date: datetime
+) -> pd.DataFrame:
     summary_individuals = (
         pd.DataFrame.from_records(
             Funder.objects.filter(

ukgrantmaking/utils/funder_over_time.py

@@ -11,13 +11,13 @@
 
 def funder_over_time(
     current_fy: FinancialYear,
-    columns: list[tuple[str, str, models.Aggregate]],
+    columns: list[tuple[str, str, type[models.Aggregate]]],
     effective_date: datetime,
     n: int = 100,
     n_years: int = 5,
     sortby: str = "-cy_scale",
     **filters,
-):
+) -> pd.DataFrame:
     orgs = funder_table(
         current_fy,
         [

ukgrantmaking/utils/funder_summary.py

@@ -9,7 +9,7 @@
 from ukgrantmaking.models.funder_utils import FUNDER_CATEGORIES
 
 
-def funder_summary(current_fy: FinancialYear, effective_date: datetime):
+def funder_summary(current_fy: FinancialYear, effective_date: datetime) -> pd.DataFrame:
     result = (
         pd.DataFrame.from_records(
             Funder.objects.filter(

ukgrantmaking/utils/funder_summary_by_size.py

@@ -9,7 +9,9 @@
 from ukgrantmaking.models.funder_utils import FUNDER_CATEGORIES
 
 
-def funder_summary_by_size(current_fy: FinancialYear, effective_date: datetime):
+def funder_summary_by_size(
+    current_fy: FinancialYear, effective_date: datetime
+) -> pd.DataFrame:
     result = (
         pd.DataFrame.from_records(
             Funder.objects.filter(

ukgrantmaking/utils/funder_table.py

@@ -17,9 +17,9 @@ def funder_table(
     n: int = 100,
     sortby: str = "-cy_scale",
     tag_children: Optional[list[str]] = None,
-    spending_threshold: int = 25_000,
+    spending_threshold: int | None = 25_000,
     **filters,
-):
+) -> pd.DataFrame:
     ascending = True
     if sortby.startswith("-"):
         sortby = sortby[1:]
@@ -227,11 +227,11 @@ def funder_table(
         ]
         if not tag_children_df.empty:
             tag_categories = pd.crosstab(
-                tag_children_df["funder_id"],
-                tag_children_df["fundertag__parent"],
+                index=tag_children_df["funder_id"],
+                columns=tag_children_df["fundertag__parent"],
                 values=tag_children_df["fundertag"],
-                aggfunc=lambda x: "; ".join(x),
-            )
+                aggfunc=lambda x: "; ".join(x),  # type: ignore
+            )  # type: ignore
             df = df.join(tag_categories, on="org_id", how="left")
             columns += tag_children
 

ukgrantmaking/utils/funder_trend_over_time.py

@@ -11,9 +11,9 @@
 def funder_trend_over_time(
     years: list[str],
     field: str,
-    aggregation: models.Aggregate,
+    aggregation: type[models.Aggregate],
     effective_date: datetime,
-):
+) -> pd.DataFrame:
     year_annotations = {}
     for year in years:
         year_annotations[year] = aggregation(

ukgrantmaking/utils/grant.py

@@ -145,7 +145,7 @@
 }
 
 
-def get_all_grants(current_fy: FinancialYear):
+def get_all_grants(current_fy: FinancialYear) -> pd.DataFrame:
     columns = [
         "grant_id",
         "funding_organisation_id",
@@ -366,7 +366,7 @@ def grant_table(
     columns: list[str] = DEFAULT_COLUMNS,
     n: int = 100,
     sortby: str = "-amount_awarded_GBP",
-):
+) -> pd.DataFrame:
     sort_ascending = True
     if sortby.startswith("-"):
         sortby = sortby[1:]
@@ -382,7 +382,7 @@ def grant_table(
 def grant_summary(
     df: pd.DataFrame,
     groupby: list[str] = ["category", "segment"],
-):
+) -> pd.DataFrame:
     summary = (
         df.groupby(groupby)
         .agg(**AGG_COLUMNS)
@@ -448,7 +448,7 @@ def grant_summary(
     total_key = tuple("Total" for k in groupby)
     if len(total_key) == 1:
         total_key = total_key[0]
-    summary.loc[total_key, :] = total_row.loc[total_key]
+    summary.loc[total_key, :] = total_row.loc[total_key]  # type: ignore
 
     summary = summary.rename(
         columns={
@@ -472,7 +472,7 @@ def grant_crosstab(
     groupby: list[str] = ["category", "segment"],
     column_field="amount_awarded_GBP_band",
     values_field="grant_id",
-):
+) -> pd.DataFrame:
     aggfunc = "count" if values_field == "grant_id" else "sum"
     summary = (
         pd.crosstab(
@@ -484,7 +484,7 @@ def grant_crosstab(
         .assign(
             Total=lambda x: x.sum(axis=1),
         )
-        .mask(lambda x: x["Total"] == 0)
+        .mask(lambda x: x["Total"] == 0)  # type: ignore
         .dropna(how="all")
     )
 
@@ -515,7 +515,7 @@ def grant_crosstab(
     total_key = tuple("Total" for k in groupby)
     if len(total_key) == 1:
         total_key = total_key[0]
-    summary.loc[total_key, :] = total_row.loc[total_key]
+    summary.loc[total_key, :] = total_row.loc[total_key]  # type: ignore
 
     if values_field in ("amount_awarded_GBP", "annual_amount"):
         summary = summary.divide(1_000_000).astype(float).round(1)
@@ -533,15 +533,15 @@ def grant_by_size(
     df: pd.DataFrame,
     groupby: list[str] = ["category", "segment"],
     **kwargs,
-):
+) -> pd.DataFrame:
     return grant_crosstab(df, groupby, column_field="amount_awarded_GBP_band", **kwargs)
 
 
 def grant_by_duration(
     df: pd.DataFrame,
     groupby: list[str] = ["category", "segment"],
     **kwargs,
-):
+) -> pd.DataFrame:
     return grant_crosstab(
         df, groupby, column_field="planned_dates_duration_band", **kwargs
     )
@@ -551,43 +551,45 @@ def recipient_types(
     df: pd.DataFrame,
     groupby: list[str] = ["category", "segment"],
     **kwargs,
-):
+) -> pd.DataFrame:
     return grant_crosstab(df, groupby, column_field="recipient_type", **kwargs)
 
 
 def recipients_by_size(
     df: pd.DataFrame,
     groupby: list[str] = ["category", "segment"],
     **kwargs,
-):
+) -> pd.DataFrame:
     return grant_crosstab(df, groupby, column_field="recipient_income_band", **kwargs)
 
 
 def recipients_by_scale(
     df: pd.DataFrame,
     groupby: list[str] = ["category", "segment"],
     **kwargs,
-):
+) -> pd.DataFrame:
     return grant_crosstab(df, groupby, column_field="recipient__scale", **kwargs)
 
 
 def grants_by_region(
     df: pd.DataFrame,
     groupby: list[str] = ["category", "segment"],
     **kwargs,
-):
+) -> pd.DataFrame:
     return grant_crosstab(df, groupby, column_field="region", **kwargs)
 
 
 def grants_by_country(
     df: pd.DataFrame,
     groupby: list[str] = ["category", "segment"],
     **kwargs,
-):
+) -> pd.DataFrame:
     return grant_crosstab(df, groupby, column_field="country", **kwargs)
 
 
-def explode_crosstab(df: pd.DataFrame, groupby: list[str], field: str, **kwargs):
+def explode_crosstab(
+    df: pd.DataFrame, groupby: list[str], field: str, **kwargs
+) -> pd.DataFrame:
     ct = grant_crosstab(
         df[df[field].notnull()].explode(field).reset_index(),
         groupby,
@@ -608,7 +610,7 @@ def grants_by_who(
     df: pd.DataFrame,
     groupby: list[str] = ["category", "segment"],
     **kwargs,
-):
+) -> pd.DataFrame:
     field = "recipient__who"
     return explode_crosstab(
         df,
@@ -622,7 +624,7 @@ def grants_by_how(
     df: pd.DataFrame,
     groupby: list[str] = ["category", "segment"],
     **kwargs,
-):
+) -> pd.DataFrame:
     field = "recipient__how"
     return explode_crosstab(
         df,
@@ -636,7 +638,7 @@ def grants_by_what(
     df: pd.DataFrame,
     groupby: list[str] = ["category", "segment"],
     **kwargs,
-):
+) -> pd.DataFrame:
     field = "recipient__what"
     return explode_crosstab(
         df,
@@ -646,7 +648,7 @@ def grants_by_what(
     )
 
 
-def recipient_size_by_amount_awarded(df: pd.DataFrame, **kwargs):
+def recipient_size_by_amount_awarded(df: pd.DataFrame, **kwargs) -> pd.DataFrame:
     return grant_crosstab(
         df,
         ["amount_awarded_GBP_band"],
@@ -655,7 +657,7 @@ def recipient_size_by_amount_awarded(df: pd.DataFrame, **kwargs):
     )
 
 
-def number_of_grants_by_recipient(df: pd.DataFrame):
+def number_of_grants_by_recipient(df: pd.DataFrame) -> pd.DataFrame:
     summary = (
         df.groupby("recipient_id")
         .agg(
@@ -698,7 +700,7 @@ def number_of_grants_by_recipient(df: pd.DataFrame):
     return summary
 
 
-def who_funds_with_who(df: pd.DataFrame, groupby: str = "segment"):
+def who_funds_with_who(df: pd.DataFrame, groupby: str = "segment") -> pd.DataFrame:
     wfww = pd.crosstab(
         df["recipient_id"],
         df[groupby],

ukgrantmaking/utils/text.py

@@ -1,4 +1,5 @@
 import re
+from typing import Any
 
 import titlecase
 
@@ -7,7 +8,7 @@
 SENTENCE_SPLIT = re.compile(r"(\. )")
 
 
-def title_exceptions(word, **kwargs):
+def title_exceptions(word: str, **kwargs) -> str | None:
     word_test = word.strip("(){}<>.")
 
     # lowercase words
@@ -95,7 +96,7 @@ def title_exceptions(word, **kwargs):
     return None
 
 
-def to_titlecase(s, sentence=False):
+def to_titlecase(s: Any, sentence: bool = False) -> Any:
     if not isinstance(s, str):
         return s
 
@@ -116,11 +117,11 @@ def to_titlecase(s, sentence=False):
     return s[0].upper() + s[1:]
 
 
-def regex_search(s, regex):
+def regex_search(s: str, regex: str) -> bool:
     return re.search(regex, s) is not None
 
 
-def list_to_string(items, sep=", ", final_sep=" and "):
+def list_to_string(items: Any, sep: str = ", ", final_sep: str = " and ") -> str:
     if isinstance(items, str):
         return items
     if isinstance(items, set):
@@ -134,7 +135,7 @@ def list_to_string(items, sep=", ", final_sep=" and "):
         return sep.join(items[0:-1]) + final_sep + items[-1]
 
 
-def clean_url(url):
+def clean_url(url: str | None) -> str | None:
     if not url:
         return None
     url = re.sub(r"(https?:)?//", "", url)
@@ -145,7 +146,7 @@ def clean_url(url):
     return url
 
 
-def working_url(url):
+def working_url(url: str | None) -> str | None:
     if not url:
         return None
     if url.startswith("http") and not url.startswith("//"):