[Issue #1541] Fail CI when there are outstanding linter changes (#1583)

## Summary
Fixes #1541

### Time to review: __2 mins__

## Changes proposed

Splits `lint` into:

- format
- format-check
- lint

Their purposes are explained inline

## Context for reviewers

See #1541

.github/workflows/ci-analytics.yml

@@ -33,6 +33,9 @@ jobs:
       - name: Install analytics package using poetry
         run: make install
 
+      - name: Check formatters
+        run: make format-check
+
       - name: Run linting
         run: make lint
 

analytics/Makefile

@@ -75,15 +75,18 @@ login:
 build:
 	docker-compose build
 
-lint:
-	@echo "=> Running code quality checks"
-	@echo "============================="
-	$(POETRY) black src tests
-	$(POETRY) ruff src tests --fix
-	$(POETRY) pylint src tests
-	$(POETRY) mypy src
-	@echo "============================="
-	@echo "=> All checks succeeded"
+release-build:
+	docker buildx build \
+		--target release \
+		--platform=linux/amd64 \
+		--build-arg RUN_USER=$(RUN_USER) \
+		--build-arg RUN_UID=$(RUN_UID) \
+		$(OPTS) \
+		.
+
+#########
+# Tests #
+#########
 
 unit-test:
 	@echo "=> Running unit tests"
@@ -100,14 +103,33 @@ test-audit: unit-test e2e-test
 	@echo "============================="
 	$(POETRY) coverage report --show-missing --fail-under=$(MIN_TEST_COVERAGE)
 
-release-build:
-	docker buildx build \
-		--target release \
-		--platform=linux/amd64 \
-		--build-arg RUN_USER=$(RUN_USER) \
-		--build-arg RUN_UID=$(RUN_UID) \
-		$(OPTS) \
-		.
+##########################
+# Formatting and Linting #
+##########################
+
+format: ## runs code formatting
+	@echo "=> Running code formatting"
+	@echo "============================="
+	$(POETRY) black src tests
+	$(POETRY) ruff --fix src tests
+	@echo "============================="
+	@echo "=> Code formatting complete"
+
+format-check: ## runs code formatting checks
+	@echo "=> Running code formatting checks"
+	@echo "============================="
+	$(POETRY) black --check src tests
+	$(POETRY) ruff  --fix --exit-non-zero-on-fix src tests
+	@echo "============================="
+	@echo "=> All checks succeeded"
+
+lint: ## runs code quality checks
+	@echo "=> Running code quality checks"
+	@echo "============================="
+	$(POETRY) pylint src tests
+	$(POETRY) mypy src
+	@echo "============================="
+	@echo "=> All checks succeeded"
 
 #################
 # Data Commands #

analytics/src/analytics/metrics/burnup.py

@@ -184,15 +184,9 @@ def _isolate_data_for_this_sprint(self) -> pd.DataFrame:
 
     #     """
     #     # create local copies of the key column names
-    #     agg_col = self.opened_col if status == "opened" else self.closed_col
-    #     unit_col = self.unit.value
-    #     key_cols = [agg_col, unit_col]
     #     # create a dummy column to sum per row if the unit is tasks
     #     if self.unit == Unit.issues:
-    #         df[unit_col] = 1
     #     # isolate the key columns, group by open or closed date, then sum the units
-    #     df_agg = df[key_cols].groupby(agg_col, as_index=False).agg({unit_col: "sum"})
-    #     return df_agg.rename(columns={agg_col: self.date_col, unit_col: status})
 
     # def _get_tix_date_range(self, df: pd.DataFrame) -> pd.DataFrame:
     #     """
@@ -210,12 +204,5 @@ def _isolate_data_for_this_sprint(self) -> pd.DataFrame:
 
     #     """
     #     # get earliest date an issue was opened and latest date one was closed
-    #     sprint_end = self.dataset.sprint_end(self.sprint)
-    #     opened_min = df[self.opened_col].min()
-    #     closed_max = df[self.closed_col].max()
-    #     closed_max = sprint_end if closed_max is nan else max(sprint_end, closed_max)
     #     # creates a dataframe with one row for each day between min and max date
     #     return pd.DataFrame(
-    #         pd.date_range(opened_min, closed_max),
-    #         columns=[self.date_col],
-    #     )

analytics/src/analytics/metrics/utils.py

@@ -10,7 +10,9 @@
 
 
 def get_daily_tix_counts_by_status(
-    df: pd.DataFrame, status: Literal["opened", "closed"], unit: Unit,
+    df: pd.DataFrame,
+    status: Literal["opened", "closed"],
+    unit: Unit,
 ) -> pd.DataFrame:
     """
     Count the number of issues or points opened or closed by date.