docs: remove coverage, fix typos, and update solutions

Bilbottom · Jun 7, 2024 · bd1d8a4 · bd1d8a4
1 parent 5d1a152
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diff --git a/.github/workflows/generate-docs.yaml b/.github/workflows/generate-docs.yaml
@@ -20,9 +20,9 @@ jobs:
   build-docs:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
       - run: pipx install poetry
-      - uses: actions/setup-python@v4
+      - uses: actions/setup-python@v5
         with: { python-version: 3.11, cache: poetry }
       - run: poetry install --with docs
       - run: poetry run mkdocs gh-deploy --force
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -1,7 +1,7 @@
 ---
 ci:
   autoupdate_schedule: quarterly
-  skip: ["poetry-lock", "sourcery", "pylint", "pytest", "coverage-badge"]
+  skip: ["poetry-lock", "sourcery", "pylint"]
 
 repos:
   - repo: meta
@@ -93,21 +93,3 @@ repos:
         types: ["python"]
         args: ["-rn", "--rcfile=pyproject.toml"]
         exclude: "^.*$" # Exclude everything for now
-
-  # Testing and coverage
-  - repo: local
-    hooks:
-      - id: pytest
-        name: Run unit tests
-        entry: pytest tests
-        language: system
-        pass_filenames: false
-        always_run: true
-        exclude: "^.*$" # Exclude everything for now
-      - id: coverage-badge
-        name: Generate coverage badge
-        entry: coverage-badge -o coverage.svg -f
-        language: system
-        pass_filenames: false
-        always_run: true
-        exclude: "^.*$" # Exclude everything for now
diff --git a/coverage.svg b/coverage.svg
diff --git a/docs/challenging-sql-problems/problems/silver/suspicious-login-activity.md b/docs/challenging-sql-problems/problems/silver/suspicious-login-activity.md
@@ -44,4 +44,4 @@ The solution can be found at:
 <!-- prettier-ignore -->
 >? TIP: **Hint 2**
 >
-> Use the difference between two `ROW_NUMBER()` functions to create a group for each user and event type. Partition on `user_id` for one and partitioning on both `user_id` and `event_id` for the other, ordering both by `event_id`.
+> Use the difference between two `ROW_NUMBER()` functions to create a group for each user and event type. Partition on `user_id` for one and partition on both `user_id` and `event_type` for the other, ordering both by `event_id`.
diff --git a/docs/challenging-sql-problems/solutions/bronze/temperature-anomaly-detection--snowflake.sql b/docs/challenging-sql-problems/solutions/bronze/temperature-anomaly-detection--snowflake.sql
@@ -0,0 +1,27 @@
+```sql
+with temperatures as (
+    select
+        site_id,
+        reading_datetime,
+        temperature,
+        sum(temperature) over (
+            partition by site_id
+            order by reading_datetime rows between 2 preceding and 2 following
+        ) as sum_temps
+    from readings
+    qualify 5 = count(*) over (
+        partition by site_id
+        order by reading_datetime rows between 2 preceding and 2 following
+    )
+)
+
+select
+    * exclude (sum_temps),
+    round((sum_temps - temperature) / 4, 4) as average_temperature,
+    round(100 * (temperature - average_temperature) / temperature, 4) as percentage_increase
+from temperatures
+where percentage_increase > 10
+order by
+    site_id,
+    reading_datetime
+```
diff --git a/docs/challenging-sql-problems/solutions/bronze/temperature-anomaly-detection--sql-server.sql b/docs/challenging-sql-problems/solutions/bronze/temperature-anomaly-detection--sql-server.sql
@@ -1,41 +1,28 @@
 ```sql
-with temps as (
+with temperatures as (
     select
         site_id,
         reading_datetime,
         temperature,
-        (
-            avg(temperature) over rows_before_site_reading
-            + avg(temperature) over rows_after_site_reading
-        ) / 2 as average_temperature,
-        (
-            count(temperature) over rows_before_site_reading
-            + count(temperature) over rows_after_site_reading
-        ) as count_of_rows
+        (sum(temperature) over rows_around_site_reading - temperature) / 4 as average_temperature,
+        count(*) over rows_around_site_reading as count_of_rows
     from readings
-    window
-        rows_before_site_reading as (
-            partition by site_id
-            order by reading_datetime
-            rows between 2 preceding and 1 preceding
-        ),
-        rows_after_site_reading as (
-            partition by site_id
-            order by reading_datetime
-            rows between 1 following and 2 following
-        )
+    window rows_around_site_reading as (
+        partition by site_id
+        order by reading_datetime rows between 2 preceding and 2 following
+    )
 )
 
 select
     site_id,
     reading_datetime,
     temperature,
     round(average_temperature, 4) as average_temperature,
-    round(100.0 * (temperature - average_temperature) / average_temperature, 4) as percentage_increase
-from temps
+    round(100.0 * (temperature - average_temperature) / temperature, 4) as percentage_increase
+from temperatures
 where 1=1
-    and count_of_rows = 4
-    and (temperature - average_temperature) / average_temperature > 0.1
+    and count_of_rows = 5
+    and (temperature - average_temperature) / temperature > 0.1
 order by
     site_id,
     reading_datetime

diff --git a/docs/challenging-sql-problems/solutions/bronze/temperature-anomaly-detection.md b/docs/challenging-sql-problems/solutions/bronze/temperature-anomaly-detection.md
@@ -30,6 +30,11 @@ Some SQL solutions per database are provided below.
 >
 --8<-- "docs/challenging-sql-problems/solutions/bronze/temperature-anomaly-detection--duckdb.sql"
 
+<!-- prettier-ignore -->
+> SUCCESS: **Snowflake**
+>
+--8<-- "docs/challenging-sql-problems/solutions/bronze/temperature-anomaly-detection--snowflake.sql"
+
 <!-- prettier-ignore -->
 > SUCCESS: **SQL Server**
 >