Codex Task Logs

Task ID: task_e_682fe77556a88323ae4617370c6b1f8d

Environment setup
Configuring language runtimes... + rm -- /tmp/5XyqqT-setup_script.sh + source ./codex_setup.sh ++ uv sync --frozen Using CPython 3.12.3 interpreter at: /usr/bin/python3.12 Creating virtual environment at: .venv Building scubaduck @ file:///workspace/scubaduck Downloading ruff (11.0MiB) Downloading pyright (5.3MiB) Downloading playwright (43.1MiB) Downloading duckdb (19.3MiB) Built scubaduck @ file:///workspace/scubaduck Downloading ruff Downloading duckdb Downloading playwright Downloading pyright Prepared 33 packages in 3.21s Installed 33 packages in 109ms + blinker==1.9.0 + certifi==2025.4.26 + charset-normalizer==3.4.2 + click==8.2.0 + duckdb==1.2.2 + execnet==2.1.1 + flask==3.1.1 + greenlet==3.2.2 + idna==3.10 + iniconfig==2.1.0 + itsdangerous==2.2.0 + jinja2==3.1.6 + markupsafe==3.0.2 + nodeenv==1.9.1 + packaging==25.0 + playwright==1.52.0 + pluggy==1.6.0 + pyee==13.0.0 + pyright==1.1.400 + pytest==8.3.5 + pytest-base-url==2.1.0 + pytest-playwright==0.7.0 + pytest-xdist==3.6.1 + python-dateutil==2.9.0.post0 + python-slugify==8.0.4 + requests==2.32.3 + ruff==0.11.10 + scubaduck==0.1.0 (from file:///workspace/scubaduck) + six==1.17.0 + text-unidecode==1.3 + typing-extensions==4.13.2 + urllib3==2.4.0 + werkzeug==3.1.3 ++ source .venv/bin/activate +++ '[' -z '' ']' +++ '[' -n x ']' +++ SCRIPT_PATH=.venv/bin/activate +++ '[' .venv/bin/activate = /tmp/5XyqqT-setup_script.sh ']' +++ deactivate nondestructive +++ unset -f pydoc +++ '[' -z '' ']' +++ '[' -z '' ']' +++ hash -r +++ '[' -z '' ']' +++ unset VIRTUAL_ENV +++ unset VIRTUAL_ENV_PROMPT +++ '[' '!' nondestructive = nondestructive ']' +++ VIRTUAL_ENV=/workspace/scubaduck/.venv +++ '[' linux-gnu = cygwin ']' +++ '[' linux-gnu = msys ']' +++ export VIRTUAL_ENV +++ '[' -z '' ']' +++ unset SCRIPT_PATH +++ _OLD_VIRTUAL_PATH=/root/.cargo/bin:/root/.rbenv/shims:/root/.rbenv/bin:/root/.rbenv/shims:/root/.local/share/swiftly/bin:/root/.bun/bin:/root/.nvm/versions/node/v22.16.0/bin:/root/.pyenv/shims:3441PYENV_ROOT/shims:/root/.pyenv/bin:/usr/local/go/bin:/root/go/bin:/root/.rbenv/bin:/root/.rbenv/shims:/root/.bun/bin:/root/.local/bin:/root/.pyenv/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin +++ PATH=/workspace/scubaduck/.venv/bin:/root/.cargo/bin:/root/.rbenv/shims:/root/.rbenv/bin:/root/.rbenv/shims:/root/.local/share/swiftly/bin:/root/.bun/bin:/root/.nvm/versions/node/v22.16.0/bin:/root/.pyenv/shims:3441PYENV_ROOT/shims:/root/.pyenv/bin:/usr/local/go/bin:/root/go/bin:/root/.rbenv/bin:/root/.rbenv/shims:/root/.bun/bin:/root/.local/bin:/root/.pyenv/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin +++ export PATH +++ '[' xscubaduck '!=' x ']' +++ VIRTUAL_ENV_PROMPT=scubaduck +++ export VIRTUAL_ENV_PROMPT +++ '[' -z '' ']' +++ '[' -z '' ']' +++ _OLD_VIRTUAL_PS1= +++ PS1='(scubaduck) ' +++ export PS1 +++ alias pydoc +++ true +++ hash -r ++ python -c 'import os; import duckdb; con = duckdb.connect(); con.execute(f"SET http_proxy = '\''{os.getenv("HTTP_PROXY")}'\''"); con.execute("INSTALL '\''sqlite'\'';")' ++ playwright install chromium Downloading Chromium 136.0.7103.25 (playwright build v1169) from https://cdn.playwright.dev/dbazure/download/playwright/builds/chromium/1169/chromium-linux.zip 167.7 MiB [] 0% 0.0s167.7 MiB [] 0% 42.3s167.7 MiB [] 0% 33.1s167.7 MiB [] 0% 38.1s167.7 MiB [] 0% 26.2s167.7 MiB [] 0% 19.6s167.7 MiB [] 0% 15.3s167.7 MiB [] 1% 11.8s167.7 MiB [] 1% 10.7s167.7 MiB [] 1% 9.9s167.7 MiB [] 1% 8.9s167.7 MiB [] 2% 7.3s167.7 MiB [] 3% 5.8s167.7 MiB [] 3% 5.9s167.7 MiB [] 4% 5.5s167.7 MiB [] 4% 5.0s167.7 MiB [] 5% 5.0s167.7 MiB [] 5% 4.9s167.7 MiB [] 6% 4.8s167.7 MiB [] 6% 4.5s167.7 MiB [] 7% 4.4s167.7 MiB [] 9% 3.9s167.7 MiB [] 10% 3.7s167.7 MiB [] 11% 3.4s167.7 MiB [] 12% 3.2s167.7 MiB [] 13% 3.0s167.7 MiB [] 14% 2.9s167.7 MiB [] 15% 2.8s167.7 MiB [] 16% 2.7s167.7 MiB [] 17% 2.6s167.7 MiB [] 18% 2.4s167.7 MiB [] 20% 2.3s167.7 MiB [] 21% 2.2s167.7 MiB [] 22% 2.1s167.7 MiB [] 24% 2.0s167.7 MiB [] 25% 1.9s167.7 MiB [] 26% 1.9s167.7 MiB [] 27% 1.8s167.7 MiB [] 28% 1.8s167.7 MiB [] 29% 1.8s167.7 MiB [] 30% 1.8s167.7 MiB [] 31% 1.7s167.7 MiB [] 32% 1.7s167.7 MiB [] 33% 1.6s167.7 MiB [] 35% 1.6s167.7 MiB [] 36% 1.6s167.7 MiB [] 36% 1.5s167.7 MiB [] 38% 1.5s167.7 MiB [] 39% 1.4s167.7 MiB [] 41% 1.4s167.7 MiB [] 42% 1.3s167.7 MiB [] 43% 1.3s167.7 MiB [] 44% 1.3s167.7 MiB [] 45% 1.2s167.7 MiB [] 46% 1.2s167.7 MiB [] 47% 1.2s167.7 MiB [] 48% 1.2s167.7 MiB [] 49% 1.2s167.7 MiB [] 50% 1.1s167.7 MiB [] 50% 1.2s167.7 MiB [] 51% 1.1s167.7 MiB [] 52% 1.1s167.7 MiB [] 53% 1.1s167.7 MiB [] 54% 1.0s167.7 MiB [] 55% 1.0s167.7 MiB [] 56% 1.0s167.7 MiB [] 57% 1.0s167.7 MiB [] 58% 0.9s167.7 MiB [] 60% 0.9s167.7 MiB [] 61% 0.8s167.7 MiB [] 62% 0.8s167.7 MiB [] 63% 0.8s167.7 MiB [] 64% 0.8s167.7 MiB [] 65% 0.8s167.7 MiB [] 66% 0.7s167.7 MiB [] 67% 0.7s167.7 MiB [] 68% 0.7s167.7 MiB [] 69% 0.7s167.7 MiB [] 70% 0.6s167.7 MiB [] 71% 0.6s167.7 MiB [] 72% 0.6s167.7 MiB [] 73% 0.6s167.7 MiB [] 74% 0.6s167.7 MiB [] 74% 0.5s167.7 MiB [] 75% 0.5s167.7 MiB [] 76% 0.5s167.7 MiB [] 77% 0.5s167.7 MiB [] 78% 0.5s167.7 MiB [] 79% 0.4s167.7 MiB [] 80% 0.4s167.7 MiB [] 81% 0.4s167.7 MiB [] 83% 0.4s167.7 MiB [] 83% 0.3s167.7 MiB [] 84% 0.3s167.7 MiB [] 86% 0.3s167.7 MiB [] 87% 0.3s167.7 MiB [] 88% 0.2s167.7 MiB [] 89% 0.2s167.7 MiB [] 90% 0.2s167.7 MiB [] 91% 0.2s167.7 MiB [] 92% 0.1s167.7 MiB [] 94% 0.1s167.7 MiB [] 95% 0.1s167.7 MiB [] 96% 0.1s167.7 MiB [] 97% 0.0s167.7 MiB [] 99% 0.0s167.7 MiB [] 100% 0.0s Chromium 136.0.7103.25 (playwright build v1169) downloaded to /root/.cache/ms-playwright/chromium-1169 Downloading FFMPEG playwright build v1011 from https://cdn.playwright.dev/dbazure/download/playwright/builds/ffmpeg/1011/ffmpeg-linux.zip 2.3 MiB [] 0% 0.0s2.3 MiB [] 4% 0.4s2.3 MiB [] 7% 0.4s2.3 MiB [] 11% 0.4s2.3 MiB [] 21% 0.3s2.3 MiB [] 36% 0.2s2.3 MiB [] 45% 0.1s2.3 MiB [] 70% 0.1s2.3 MiB [] 100% 0.0s FFMPEG playwright build v1011 downloaded to /root/.cache/ms-playwright/ffmpeg-1011 Downloading Chromium Headless Shell 136.0.7103.25 (playwright build v1169) from https://cdn.playwright.dev/dbazure/download/playwright/builds/chromium/1169/chromium-headless-shell-linux.zip 101.4 MiB [] 0% 0.0s101.4 MiB [] 0% 12.8s101.4 MiB [] 0% 16.3s101.4 MiB [] 0% 20.5s101.4 MiB [] 0% 12.4s101.4 MiB [] 0% 10.6s101.4 MiB [] 1% 8.1s101.4 MiB [] 1% 7.6s101.4 MiB [] 2% 5.6s101.4 MiB [] 3% 3.9s101.4 MiB [] 4% 3.9s101.4 MiB [] 5% 3.5s101.4 MiB [] 6% 3.0s101.4 MiB [] 7% 2.6s101.4 MiB [] 9% 2.4s101.4 MiB [] 10% 2.3s101.4 MiB [] 11% 2.1s101.4 MiB [] 13% 1.8s101.4 MiB [] 14% 1.8s101.4 MiB [] 16% 1.7s101.4 MiB [] 17% 1.7s101.4 MiB [] 19% 1.6s101.4 MiB [] 20% 1.7s101.4 MiB [] 22% 1.5s101.4 MiB [] 23% 1.5s101.4 MiB [] 25% 1.5s101.4 MiB [] 27% 1.3s101.4 MiB [] 29% 1.3s101.4 MiB [] 31% 1.2s101.4 MiB [] 34% 1.1s101.4 MiB [] 36% 1.0s101.4 MiB [] 39% 1.0s101.4 MiB [] 40% 0.9s101.4 MiB [] 42% 0.9s101.4 MiB [] 43% 0.9s101.4 MiB [] 45% 0.8s101.4 MiB [] 47% 0.8s101.4 MiB [] 50% 0.7s101.4 MiB [] 53% 0.6s101.4 MiB [] 55% 0.6s101.4 MiB [] 57% 0.6s101.4 MiB [] 59% 0.5s101.4 MiB [] 62% 0.5s101.4 MiB [] 64% 0.5s101.4 MiB [] 65% 0.4s101.4 MiB [] 66% 0.4s101.4 MiB [] 69% 0.4s101.4 MiB [] 70% 0.4s101.4 MiB [] 71% 0.4s101.4 MiB [] 72% 0.3s101.4 MiB [] 73% 0.3s101.4 MiB [] 76% 0.3s101.4 MiB [] 78% 0.3s101.4 MiB [] 81% 0.2s101.4 MiB [] 85% 0.2s101.4 MiB [] 87% 0.1s101.4 MiB [] 89% 0.1s101.4 MiB [] 91% 0.1s101.4 MiB [] 92% 0.1s101.4 MiB [] 93% 0.1s101.4 MiB [] 96% 0.0s101.4 MiB [] 97% 0.0s101.4 MiB [] 98% 0.0s101.4 MiB [] 99% 0.0s101.4 MiB [] 100% 0.0s Chromium Headless Shell 136.0.7103.25 (playwright build v1169) downloaded to /root/.cache/ms-playwright/chromium_headless_shell-1169 ++ echo 'source .venv/bin/activate'
Internet turned off
Add a test showing that SCUBADUCK_DB can be used with a parquet file. Add any missing functionality if needed.

I'll locate and open the AGENTS.md file in the root directory.

shell
ls
bash: .venv/bin/activate: No such file or directory root@f39a1dc6c281:/workspace# ls scubaduck

I mistakenly ran ls on the root directory; I need to move into the repo.

shell
root@f39a1dc6c281:/workspace# cd scubaduck root@f39a1dc6c281:/workspace/scubaduck# ls AGENTS.md codex_setup.sh scubaduck tests README.md pyproject.toml stubs uv.lock

Let's check out the AGENTS.md file to see relevant instructions.

shell
root@f39a1dc6c281:/workspace/scubaduck# cat AGENTS.md - Use "source .venv/bin/activate" to activate the virtual environment before running any commands - ONLY use non-interactive commands like cat, sed, apply_patch to do edits. Do NOT use interactive editors. - Do NOT attempt to install packages. Only the packages specified in pyproject.toml are available. You cannot add new packages. If you desperately want another package, make a note of it in the final PR description. - Use conventional commits to format PR title - There are no nested AGENTS.md files, this is the only agents file - When using Playwright, ONLY use chromium browser. This browser is already installed. - Use "ruff check" to check lint, "ruff format" to autoformat files and "pyright" to typecheck. - When writing the PR description, include the original prompt supplied by the user. - When you add functionality to the server, add server tests to tests/test_server.py. When you add features to the frontend, add frontend tests to tests/test_web.py

I'll start by checking the directories in the /workspace/scubaduck repo for our test.

shell
root@f39a1dc6c281:/workspace/scubaduck# ls scubaduck __init__.py sample.csv server.py static

I’ll take a look at the tests to check their structure and coverage.

shell
root@f39a1dc6c281:/workspace/scubaduck# ls tests conftest.py test_server_time.py test_web_graph.py test_multi_table_web.py test_server_timeseries.py test_web_table.py test_server.py test_web.py test_web_timeseries.py test_server_basic.py test_web_basics.py web_utils.py test_server_db_types.py test_web_chips.py test_server_errors.py test_web_columns.py

I'm going to peek at the README to see what info it holds.

shell
root@f39a1dc6c281:/workspace/scubaduck# cat README.md | head -n 20 I really like Scuba (Meta's internal real-time database system). The distributed , real-time database part of Scuba is quite difficult (and expensive) to replica te, but I also really like Scuba's UI for doing queries, and I have found myself wishing that I have access to it even for "small" databases, e.g., I have a sql ite dataset I want to explore. Pivotal ideas: * Time series by default. In the dedicated "time series" view, there are many fe atures specifically oriented towards working towards tables that represent event s that occurred over time: the start, end, compare, aggregate and granularity fi elds all specially privilege the timestamp field. In fact, you can't log events to Scuba's backing data store without a timestamp, they always come with one. (S cuba also supports other views that don't presuppose a time series, but the time series is the most beloved and well used view.) This is in contrast to typical software which tries to generalize to arbitrary data first, with time series bei ng added on later. * It's all about exploration. Scuba is predicated on the idea that you don't kno w what you're looking for, that you are going to spend time tweaking queries and changing filters/grouping as part of an investigation to figure out why a syste m behaves the way it is. So the filters/comparisons/groupings you want to edit a re always visible on the left sidebar, with the expectation that you're going to tweak the query to look at something else. Similarly, all the parameters of you r query get saved into your URL, so your browser history can double up as a quer y history / you can easily share a query with someone else. This is contrast to typical software which is often oriented to making pretty dashboards and reports . (This function is important too, but it's not what I want in exploration mode! ) * You can fix data problems in the query editor. It's pretty common to have mess ed up and ended up with a database that doesn't have exactly the columns you nee d, or some columns that are corrupted in some way. Scuba has pretty robust suppo rt for defining custom columns with arbitrary SQL functions, grouping over them as if they were native functions, and doing so with minimal runtime cost (Scuba aims to turn around your query in milliseconds!) Having to go and run a huge dat a pipeline to fix your data is a big impediment to exploration; quick and easy c ustom columns means you can patch over problems when you're investigating and fi x them for real later. We're going to build a exploratory data analysis tool like Scuba for time series database (i.e., a database with a mandatory timestamp representing the time an event occurred). We'll use DuckDB as the underlying SQL engine served from a Py thon server, and render the GUI/results as a webpage with vanilla HTML and JS. W e'll use choices.js to support token inputs. We define a token input to mean a text input element where as you type a dropdown displays with valid values, and if you select one or press enter, the selection turns into a token/chip that can only be deleted as one unit. To start, we are going to support one views: samples. The samples view only all ows you to view individual samples from the database, subject to a filter. Our m ain UI concept is that there is a left sidebar that is the query editor, and the right side that shows the view. The sidebar is always visible and defaults to the query parameters of the current view. After you make changes to the query, clicking the "Dive" button updates the view. The URL of the page encodes all of the values of the query (and gets updated when you Dive), so the browser's back button lets you view previous queries. The query editor's job is to generate a SQL query, which then is applied on the database, and then the result visualized according to the view. Here are the settings you can apply to the query. The help text should show up w hen you mouse over the field name: * Start/End - Help text: "Sets the start/end of the time range to query. Can be any kind of datetime string. For example: 'April 23, 2014' or 'yesterday'." The UI for this selector supports both relative selections (now, -1 hour, -3 hours, -12 hours, -1 day, -3 days, -1 week, -1 fortnight, -30 days, -90 days, -1 month, -1 year) as well as specifying an absolute date. The way this field is rendere d is there is a free form text box, a drop down arrow (for the relative selector s), and then a calendar button (for date selection). * Order By - Help text: "Choose a column to sort results by." There is an ASC/D ESC toggle next to it.

I'll scroll through the tests to understand their context better.

shell
root@f39a1dc6c281:/workspace/scubaduck# ls tests | head conftest.py test_multi_table_web.py test_server.py test_server_basic.py test_server_db_types.py test_server_errors.py test_server_time.py test_server_timeseries.py test_web.py test_web_basics.py

I'm reviewing the tests to see how well they cover the DB functionality.

shell
root@f39a1dc6c281:/workspace/scubaduck# sed -n '1,160p' tests/conftest.py from __future__ import annotations import threading from collections.abc import Iterator import pytest from werkzeug.serving import make_server from scubaduck.server import app @pytest.fixture() def server_url() -> Iterator[str]: httpd = make_server("127.0.0.1", 0, app) port = httpd.server_port thread = threading.Thread(target=httpd.serve_forever) thread.start() try: yield f"http://127.0.0.1:{port}" finally: httpd.shutdown() thread.join()

I'll look for references to SCUBADUCK_DB in the project.

shell
root@f39a1dc6c281:/workspace/scubaduck# grep -R "SCUBADUCK_DB" -n tests/test_server_db_types.py:219: monkeypatch.setenv("SCUBADUCK_DB", str(csv _file)) tests/test_server_db_types.py:232: monkeypatch.setenv("SCUBADUCK_DB", str(mis sing))
.venv/lib/python3.12/site-packages/scubaduck-0.1.0.dist-info/METADATA:59:By defa ult the server loads `sample.csv`. Set the `SCUBADUCK_DB` environment .venv/lib64/python3.12/site-packages/scubaduck-0.1.0.dist-info/METADATA:59:By de fault the server loads `sample.csv`. Set the `SCUBADUCK_DB` environment README.md:48:By default the server loads `sample.csv`. Set the `SCUBADUCK_DB` en vironment scubaduck/server.py:418: env_db = os.environ.get("SCUBADUCK_DB")

I’ll examine tests/test_server_db_types.py, focusing on the relevant lines.

shell
root@f39a1dc6c281:/workspace/scubaduck# sed -n '1,260p' tests/test_server_db_typ es.py from __future__ import annotations import json from pathlib import Path import duckdb import pytest from scubaduck import server def _make_payload() -> dict[str, object]: return { "table": "events", "start": "2024-01-01 00:00:00", "end": "2024-01-02 00:00:00", "order_by": "timestamp", "order_dir": "ASC", "limit": 10, "columns": ["timestamp", "event", "value", "user"], "filters": [], } def test_database_types(tmp_path: Path) -> None: csv_file = tmp_path / "events.csv" csv_file.write_text(Path("scubaduck/sample.csv").read_text()) sqlite_file = tmp_path / "events.sqlite" import sqlite3 conn = sqlite3.connect(sqlite_file) conn.execute( "CREATE TABLE events (timestamp TEXT, event TEXT, value INTEGER, user TE XT)" ) with open(csv_file) as f: next(f) for line in f: ts, ev, val, user = line.strip().split(",") conn.execute( "INSERT INTO events VALUES (?, ?, ?, ?)", (ts, ev, int(val), use r) ) conn.commit() conn.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcce ssIssue] duckdb_file = tmp_path / "events.duckdb" con = duckdb.connect(duckdb_file) con.execute( f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{csv_file.as_posix ()}')" ) con.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcces sIssue] for db in (csv_file, sqlite_file, duckdb_file): app = server.create_app(db) client = app.test_client() payload = _make_payload() rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/js on" ) rows = rv.get_json()["rows"] assert len(rows) == 3 def test_sqlite_longvarchar(tmp_path: Path) -> None: sqlite_file = tmp_path / "events.sqlite" import sqlite3 conn = sqlite3.connect(sqlite_file) conn.execute( "CREATE TABLE events (timestamp TEXT, url LONGVARCHAR, title VARCHAR(10) )" ) conn.execute( "INSERT INTO events VALUES ('2024-01-01 00:00:00', 'https://a.com', 'Hom e')" ) conn.commit() conn.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcce ssIssue] app = server.create_app(sqlite_file) client = app.test_client() payload = { "table": "events", "start": "2024-01-01 00:00:00", "end": "2024-01-01 01:00:00", "order_by": "timestamp", "columns": ["timestamp", "url", "title"], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert rv.status_code == 200 assert data["rows"][0][1] == "https://a.com" def test_sqlite_bigint(tmp_path: Path) -> None: sqlite_file = tmp_path / "big.sqlite" import sqlite3 conn = sqlite3.connect(sqlite_file) conn.execute("CREATE TABLE events (timestamp TEXT, value INTEGER)") big_value = 13385262862605259 conn.execute( "INSERT INTO events VALUES ('2024-01-01 00:00:00', ?)", (big_value,), ) conn.commit() conn.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcce ssIssue] app = server.create_app(sqlite_file) client = app.test_client() payload = { "table": "events", ... rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert rv.status_code == 200 assert data["rows"][0][1] == big_value def test_sqlite_bytes(tmp_path: Path) -> None: sqlite_file = tmp_path / "bin.sqlite" import sqlite3 conn = sqlite3.connect(sqlite_file) conn.execute("CREATE TABLE events (timestamp TEXT, data BLOB)") conn.execute( "INSERT INTO events VALUES ('2024-01-01 00:00:00', ?)", (b"\x00\xff",), ) conn.commit() conn.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcce ssIssue] app = server.create_app(sqlite_file) client = app.test_client() payload = { "table": "events", "order_by": "timestamp", "columns": ["timestamp", "data"], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert rv.status_code == 200 assert data["rows"] == [["2024-01-01 00:00:00", "b'\\x00\\xff'"]] def test_sqlite_boolean_aggregation(tmp_path: Path) -> None: sqlite_file = tmp_path / "bool.sqlite" import sqlite3 conn = sqlite3.connect(sqlite_file) conn.execute("CREATE TABLE events (timestamp TEXT, flag BOOLEAN)") conn.execute("INSERT INTO events VALUES ('2024-01-01 00:00:00', 1)") conn.execute("INSERT INTO events VALUES ('2024-01-01 00:30:00', 0)") conn.commit() conn.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcce ssIssue] app = server.create_app(sqlite_file) client = app.test_client() payload = { "table": "events", "start": "2024-01-01 00:00:00", "end": "2024-01-02 00:00:00", "graph_type": "table", "aggregate": "Avg", "columns": ["flag"], "show_hits": True, } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert rv.status_code == 200 assert data["rows"][0][0] == 2 assert data["rows"][0][1] == 0.5 def test_sqlite_boolean_group_by(tmp_path: Path) -> None: sqlite_file = tmp_path / "bool.sqlite" import sqlite3 conn = sqlite3.connect(sqlite_file) conn.execute("CREATE TABLE events (id INTEGER, ts TEXT, flag BOOLEAN)") conn.execute("INSERT INTO events VALUES (1, '2024-01-01 00:00:00', 1)") conn.execute("INSERT INTO events VALUES (1, '2024-01-01 00:30:00', 0)") conn.execute("INSERT INTO events VALUES (2, '2024-01-01 01:00:00', 1)") conn.commit() conn.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcce ssIssue] app = server.create_app(sqlite_file) client = app.test_client() payload = { "table": "events", "start": "2024-01-01 00:00:00", "end": "2024-01-02 00:00:00", "graph_type": "table", "time_column": "ts", "aggregate": "Avg", "group_by": ["id"], "columns": ["flag"], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert rv.status_code == 200 rows = sorted(data["rows"]) # order can vary assert rows == [[1, 2, 0.5], [2, 1, 1.0]] def test_envvar_db(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: csv_file = tmp_path / "custom.csv" csv_file.write_text("timestamp,event,value,user\n2024-01-01 00:00:00,login,5 ,bob\n") monkeypatch.setenv("SCUBADUCK_DB", str(csv_file)) app = server.create_app() client = app.test_client() payload = _make_payload() rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) rows = rv.get_json()["rows"] assert len(rows) == 1 def test_envvar_db_missing(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> N one: missing = tmp_path / "missing.sqlite" monkeypatch.setenv("SCUBADUCK_DB", str(missing)) with pytest.raises(FileNotFoundError): server.create_app()
root@f39a1dc6c281:/workspace/scubaduck# sed -n '260,520p' tests/test_server_db_t ypes.py

I'll look at test_server_db_types.py and add a test for SCUBADUCK_DB loading Parquet.

shell
root@f39a1dc6c281:/workspace/scubaduck# sed -n '1,200p' scubaduck/server.py from __future__ import annotations from dataclasses import dataclass, field, replace from typing import Any, Dict, List, Tuple, cast import re from datetime import datetime, timedelta, timezone import time from pathlib import Path import os import traceback import math import duckdb from dateutil import parser as dtparser from dateutil.relativedelta import relativedelta from flask import Flask, jsonify, request, send_from_directory def _quote(ident: str) -> str: """Return identifier quoted for SQL.""" return f'"{ident.replace('"', '""')}"' @dataclass class Filter: column: str op: str value: str | int | float | list[str] | None @dataclass class QueryParams: start: str | None = None end: str | None = None order_by: str | None = None order_dir: str = "ASC" limit: int | None = None columns: list[str] = field(default_factory=lambda: []) filters: list[Filter] = field(default_factory=lambda: []) derived_columns: dict[str, str] = field(default_factory=lambda: {}) graph_type: str = "samples" group_by: list[str] = field(default_factory=lambda: []) aggregate: str | None = None show_hits: bool = False x_axis: str | None = None granularity: str = "Auto" fill: str = "0" table: str = "events" time_column: str | None = "timestamp" time_unit: str = "s" def _load_database(path: Path) -> duckdb.DuckDBPyConnection: if not path.exists(): raise FileNotFoundError(path) ext = path.suffix.lower() if ext == ".csv": con = duckdb.connect() con.execute( f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{path.as_posix ()}')" ) elif ext in {".db", ".sqlite"}: con = duckdb.connect() con.execute("LOAD sqlite") con.execute(f"ATTACH '{path.as_posix()}' AS db (TYPE SQLITE)") tables = [ r[0] for r in con.execute( "SELECT name FROM sqlite_master WHERE type='table'" ).fetchall() ] for t in tables: con.execute(f'CREATE VIEW "{t}" AS SELECT * FROM db."{t}"') else: con = duckdb.connect(path) return con def _create_test_database() -> duckdb.DuckDBPyConnection: """Return a DuckDB connection with a small multi-table dataset.""" con = duckdb.connect() con.execute( "CREATE TABLE events (id INTEGER PRIMARY KEY, ts INTEGER, val REAL, name TEXT, flag BOOLEAN)" ) con.execute("INSERT INTO events VALUES (1, 1704067200, 1.5, 'alice', 1)") con.execute("INSERT INTO events VALUES (2, 1704070800, 2.0, 'bob', 0)") con.execute('CREATE TABLE extra (ts INTEGER, "desc" TEXT, num INTEGER)') con.execute("INSERT INTO extra VALUES (1704067200, 'x', 1)") con.execute("INSERT INTO extra VALUES (1704070800, 'y', 2)") return con _REL_RE = re.compile( r"([+-]?\d+(?:\.\d*)?)\s*(hour|hours|day|days|week|weeks|fortnight|fortnight s|month|months|year|years)", re.IGNORECASE, ) def parse_time(val: str | None) -> str | None: """Parse an absolute or relative time string into ``YYYY-MM-DD HH:MM:SS``."" " if val is None or val == "": return None s = val.strip() if s.lower() == "now": dt = datetime.now(timezone.utc) return dt.replace(microsecond=0).strftime("%Y-%m-%d %H:%M:%S") m = _REL_RE.fullmatch(s) if m: qty = float(m.group(1)) unit = m.group(2).lower() now = datetime.now(timezone.utc) dt: datetime if unit.startswith("hour"): dt = now + timedelta(hours=qty) elif unit.startswith("day"): dt = now + timedelta(days=qty) elif unit.startswith("week"): dt = now + timedelta(weeks=qty) elif unit.startswith("fortnight"): dt = now + timedelta(weeks=2 * qty) elif unit.startswith("month"): if qty.is_integer(): dt = now + relativedelta(months=int(qty)) else: dt = now + timedelta(days=30 * qty) elif unit.startswith("year"): if qty.is_integer(): dt = now + relativedelta(years=int(qty)) else: dt = now + timedelta(days=365 * qty) else: # pragma: no cover - defensive raise ValueError(f"Unsupported unit: {unit}") return dt.replace(microsecond=0).strftime("%Y-%m-%d %H:%M:%S") dt = dtparser.parse(s) return dt.replace(microsecond=0, tzinfo=None).strftime("%Y-%m-%d %H:%M:%S") def _numeric_to_datetime(value: int | float, unit: str) -> datetime: """Convert a numeric timestamp ``value`` with unit ``unit`` to ``datetime``. Heuristically fall back to seconds when the converted value is before 1990 but the seconds interpretation is in a reasonable range. This handles integer columns stored in seconds even when ``unit`` is mistakenly set to a finer granularity. """ divisor = { "s": 1, "ms": 1000, "us": 1_000_000, "ns": 1_000_000_000, }.get(unit, 1) dt = datetime.fromtimestamp(int(value) / divisor, tz=timezone.utc) if unit != "s" and dt.year < 1990: alt = datetime.fromtimestamp(int(value), tz=timezone.utc) if alt.year >= 1990: dt = alt return dt def _suggest_time_unit(value: int | float, given: str) -> str | None: """Return a plausible time unit for ``value`` not equal to ``given``.""" for unit in ("s", "ms", "us", "ns"): if unit == given: continue try: dt = _numeric_to_datetime(value, unit) except Exception: continue if 1990 <= dt.year <= 2500: return unit return None def _granularity_seconds(granularity: str, start: str | None, end: str | None) - > int: gran = granularity.lower() mapping = { "1 second": 1, "5 seconds": 5, "10 seconds": 10, "30 seconds": 30, "1 minute": 60, "4 minutes": 240, "5 minutes": 300, "10 minutes": 600, "15 minutes": 900, "30 minutes": 1800, "1 hour": 3600, "3 hours": 10800, "6 hours": 21600, "1 day": 86400, "1 week": 604800, "30 days": 2592000,

I need to keep scrolling to capture more details. Let's go a bit further.

shell
root@f39a1dc6c281:/workspace/scubaduck# grep -n "create_app" -n scubaduck/server .py 415:def create_app(db_file: str | Path | None = None) -> Flask: 754:app = create_app()
root@f39a1dc6c281:/workspace/scubaduck# sed -n '402,464p' scubaduck/server.py if where_parts: lines.append("WHERE " + " AND ".join(where_parts)) if group_cols: lines.append("GROUP BY " + ", ".join(_quote(c) for c in group_cols)) if order_by: lines.append(f"ORDER BY {_quote(order_by)} {params.order_dir}") elif params.graph_type == "timeseries": lines.append("ORDER BY bucket") if params.limit is not None: lines.append(f"LIMIT {params.limit}") return "\n".join(lines) def create_app(db_file: str | Path | None = None) -> Flask: app = Flask(__name__, static_folder="static") if db_file is None: env_db = os.environ.get("SCUBADUCK_DB") if env_db: db_file = env_db if isinstance(db_file, str) and db_file.upper() == "TEST": con = _create_test_database() else: db_path = Path(db_file or Path(__file__).with_name("sample.csv")).resolv e() con = _load_database(db_path) tables = [r[0] for r in con.execute("SHOW TABLES").fetchall()] if not tables: raise ValueError("No tables found in database") default_table = tables[0] columns_cache: Dict[str, Dict[str, str]] = {} def get_columns(table: str) -> Dict[str, str]: if table not in columns_cache: rows = con.execute(f'PRAGMA table_info("{table}")').fetchall() if not rows: raise ValueError(f"Unknown table: {table}") columns_cache[table] = {r[1]: r[2] for r in rows} return columns_cache[table] sample_cache: Dict[Tuple[str, str, str], Tuple[List[str], float]] = {} CACHE_TTL = 60.0 CACHE_LIMIT = 200 @app.route("/") def index() -> Any: # pyright: ignore[reportUnusedFunction] assert app.static_folder is not None return send_from_directory(app.static_folder, "index.html") @app.route("/js/<path:filename>") def js(filename: str) -> Any: # pyright: ignore[reportUnusedFunction] assert app.static_folder is not None folder = Path(app.static_folder) / "js" return send_from_directory(folder, filename) @app.route("/api/tables") def tables_endpoint() -> Any: # pyright: ignore[reportUnusedFunction] return jsonify(tables) @app.route("/api/columns") def columns() -> Any: # pyright: ignore[reportUnusedFunction] table = request.args.get("table", default_table) rows = con.execute(f'PRAGMA table_info("{table}")').fetchall() return jsonify([{"name": r[1], "type": r[2]} for r in rows])
root@f39a1dc6c281:/workspace/scubaduck# sed -n '464,520p' scubaduck/server.py def _cache_get(key: Tuple[str, str, str]) -> List[str] | None: item = sample_cache.get(key) if item is None: return None vals, ts = item if time.time() - ts > CACHE_TTL: del sample_cache[key] return None sample_cache[key] = (vals, time.time()) return vals def _cache_set(key: Tuple[str, str, str], vals: List[str]) -> None: sample_cache[key] = (vals, time.time()) if len(sample_cache) > CACHE_LIMIT: oldest = min(sample_cache.items(), key=lambda kv: kv[1][1])[0] del sample_cache[oldest] @app.route("/api/samples") def sample_values() -> Any: # pyright: ignore[reportUnusedFunction] table = request.args.get("table", default_table) column = request.args.get("column") substr = request.args.get("q", "") column_types = get_columns(table) if not column or column not in column_types: return jsonify([]) ctype = column_types[column].upper() if "CHAR" not in ctype and "STRING" not in ctype and "VARCHAR" not in ct ype: return jsonify([]) key = (table, column, substr) cached = _cache_get(key) if cached is not None: return jsonify(cached) qcol = _quote(column) rows = con.execute( f"SELECT DISTINCT {qcol} FROM \"{table}\" WHERE CAST({qcol} AS VARCH AR) ILIKE '%' || ? || '%' LIMIT 20", [substr], ).fetchall() values = [r[0] for r in rows] _cache_set(key, values) return jsonify(values) @app.route("/api/query", methods=["POST"]) def query() -> Any: # pyright: ignore[reportUnusedFunction] payload = request.get_json(force=True) try: start = parse_time(payload.get("start")) end = parse_time(payload.get("end")) except Exception as exc: return jsonify({"error": str(exc)}), 400 params = QueryParams( start=start, end=end, order_by=payload.get("order_by"), order_dir=payload.get("order_dir", "ASC"), limit=payload.get("limit"),

I'm continuing to scroll to the bottom now. Almost there!

shell
root@f39a1dc6c281:/workspace/scubaduck# grep -n "parquet" -n scubaduck/server.py

It seems there's no built-in support for Parquet in the server. I should check README.

shell
root@f39a1dc6c281:/workspace/scubaduck# grep -n "parquet" -R
.venv/lib/python3.12/site-packages/pyright/dist/dist/typeshed-fallback/stubs/geo pandas/geopandas/_exports.pyi:6:from geopandas.io.arrow import _read_feather as read_feather, _read_parquet as read_parquet .venv/lib/python3.12/site-packages/pyright/dist/dist/typeshed-fallback/stubs/geo pandas/geopandas/_exports.pyi:14: "read_parquet", .venv/lib/python3.12/site-packages/pyright/dist/dist/typeshed-fallback/stubs/geo pandas/geopandas/io/arrow.pyi:13:def _read_parquet( .venv/lib/python3.12/site-packages/pyright/dist/dist/typeshed-fallback/stubs/geo pandas/geopandas/io/arrow.pyi:18: **kwargs, # kwargs passed to pyarrow.parqu et.read_table .venv/lib/python3.12/site-packages/pyright/dist/dist/typeshed-fallback/stubs/geo pandas/geopandas/geodataframe.pyi:218: def to_parquet( # type: ignore[overri de] .venv/lib/python3.12/site-packages/pyright/dist/dist/typeshed-fallback/stubs/geo pandas/geopandas/__init__.pyi:11: read_parquet as read_parquet, grep: .venv/lib/python3.12/site-packages/duckdb/duckdb.cpython-312-x86_64-linux- gnu.so: binary file matches grep: .venv/lib/python3.12/site-packages/duckdb/__pycache__/__init__.cpython-312 .pyc: binary file matches .venv/lib/python3.12/site-packages/duckdb/experimental/spark/sql/readwriter.py:2 5: def parquet( .venv/lib/python3.12/site-packages/duckdb/experimental/spark/sql/readwriter.py:3 8: relation.write_parquet(path, compression=compression) .venv/lib/python3.12/site-packages/duckdb/experimental/spark/sql/readwriter.py:1 16: elif format == "parquet": .venv/lib/python3.12/site-packages/duckdb/experimental/spark/sql/readwriter.py:1 17: rel = self.session.conn.read_parquet(path) .venv/lib/python3.12/site-packages/duckdb/experimental/spark/sql/readwriter.py:2 50: def parquet(self, *paths: str, **options: "OptionalPrimitiveType") -> "Da taFrame": .venv/lib/python3.12/site-packages/duckdb/experimental/spark/sql/readwriter.py:2 58: rel = self.session.conn.read_parquet(path) .venv/lib/python3.12/site-packages/duckdb/__init__.py:124: from_parquet, .venv/lib/python3.12/site-packages/duckdb/__init__.py:125: read_parquet, .venv/lib/python3.12/site-packages/duckdb/__init__.py:126: from_parquet, .venv/lib/python3.12/site-packages/duckdb/__init__.py:127: read_parquet, .venv/lib/python3.12/site-packages/duckdb/__init__.py:203: 'from_parquet', .venv/lib/python3.12/site-packages/duckdb/__init__.py:204: 'read_parquet', .venv/lib/python3.12/site-packages/duckdb/__init__.py:205: 'from_parquet', .venv/lib/python3.12/site-packages/duckdb/__init__.py:206: 'read_parquet', .venv/lib/python3.12/site-packages/duckdb-stubs/__init__.pyi:345: def from_pa rquet(self, file_glob: str, binary_as_string: bool = False, *, file_row_number: bool = False, filename: bool = False, hive_partitioning: bool = False, union_by_ name: bool = False, compression: Optional[str] = None) -> DuckDBPyRelation: ... .venv/lib/python3.12/site-packages/duckdb-stubs/__init__.pyi:346: def read_pa rquet(self, file_glob: str, binary_as_string: bool = False, *, file_row_number: bool = False, filename: bool = False, hive_partitioning: bool = False, union_by_ name: bool = False, compression: Optional[str] = None) -> DuckDBPyRelation: ... .venv/lib/python3.12/site-packages/duckdb-stubs/__init__.pyi:474: def to_parq uet( .venv/lib/python3.12/site-packages/duckdb-stubs/__init__.pyi:514: def write_p arquet( .venv/lib/python3.12/site-packages/duckdb-stubs/__init__.pyi:692:def from_parque t(file_glob: str, binary_as_string: bool = False, *, file_row_number: bool = Fal se, filename: bool = False, hive_partitioning: bool = False, union_by_name: bool = False, compression: Optional[str] = None, connection: DuckDBPyConnection = .. .) -> DuckDBPyRelation: ... .venv/lib/python3.12/site-packages/duckdb-stubs/__init__.pyi:693:def read_parque t(file_glob: str, binary_as_string: bool = False, *, file_row_number: bool = Fal se, filename: bool = False, hive_partitioning: bool = False, union_by_name: bool = False, compression: Optional[str] = None, connection: DuckDBPyConnection = .. .) -> DuckDBPyRelation: ... .venv/lib64/python3.12/site-packages/pyright/dist/dist/typeshed-fallback/stubs/g eopandas/geopandas/_exports.pyi:6:from geopandas.io.arrow import _read_feather a s read_feather, _read_parquet as read_parquet .venv/lib64/python3.12/site-packages/pyright/dist/dist/typeshed-fallback/stubs/g eopandas/geopandas/_exports.pyi:14: "read_parquet", .venv/lib64/python3.12/site-packages/pyright/dist/dist/typeshed-fallback/stubs/g eopandas/geopandas/io/arrow.pyi:13:def _read_parquet( .venv/lib64/python3.12/site-packages/pyright/dist/dist/typeshed-fallback/stubs/g eopandas/geopandas/io/arrow.pyi:18: **kwargs, # kwargs passed to pyarrow.par quet.read_table .venv/lib64/python3.12/site-packages/pyright/dist/dist/typeshed-fallback/stubs/g eopandas/geopandas/geodataframe.pyi:218: def to_parquet( # type: ignore[over ride] .venv/lib64/python3.12/site-packages/pyright/dist/dist/typeshed-fallback/stubs/g eopandas/geopandas/__init__.pyi:11: read_parquet as read_parquet, grep: .venv/lib64/python3.12/site-packages/duckdb/duckdb.cpython-312-x86_64-linu x-gnu.so: binary file matches grep: .venv/lib64/python3.12/site-packages/duckdb/__pycache__/__init__.cpython-3 12.pyc: binary file matches .venv/lib64/python3.12/site-packages/duckdb/experimental/spark/sql/readwriter.py :25: def parquet( .venv/lib64/python3.12/site-packages/duckdb/experimental/spark/sql/readwriter.py :38: relation.write_parquet(path, compression=compression) .venv/lib64/python3.12/site-packages/duckdb/experimental/spark/sql/readwriter.py :116: elif format == "parquet": .venv/lib64/python3.12/site-packages/duckdb/experimental/spark/sql/readwriter.py :117: rel = self.session.conn.read_parquet(path) .venv/lib64/python3.12/site-packages/duckdb/experimental/spark/sql/readwriter.py :250: def parquet(self, *paths: str, **options: "OptionalPrimitiveType") -> " DataFrame": .venv/lib64/python3.12/site-packages/duckdb/experimental/spark/sql/readwriter.py :258: rel = self.session.conn.read_parquet(path) .venv/lib64/python3.12/site-packages/duckdb/__init__.py:124: from_parquet, .venv/lib64/python3.12/site-packages/duckdb/__init__.py:125: read_parquet, .venv/lib64/python3.12/site-packages/duckdb/__init__.py:126: from_parquet, .venv/lib64/python3.12/site-packages/duckdb/__init__.py:127: read_parquet, .venv/lib64/python3.12/site-packages/duckdb/__init__.py:203: 'from_parquet', .venv/lib64/python3.12/site-packages/duckdb/__init__.py:204: 'read_parquet', .venv/lib64/python3.12/site-packages/duckdb/__init__.py:205: 'from_parquet', .venv/lib64/python3.12/site-packages/duckdb/__init__.py:206: 'read_parquet', .venv/lib64/python3.12/site-packages/duckdb-stubs/__init__.pyi:345: def from_ parquet(self, file_glob: str, binary_as_string: bool = False, *, file_row_number : bool = False, filename: bool = False, hive_partitioning: bool = False, union_b y_name: bool = False, compression: Optional[str] = None) -> DuckDBPyRelation: .. . .venv/lib64/python3.12/site-packages/duckdb-stubs/__init__.pyi:346: def read_ parquet(self, file_glob: str, binary_as_string: bool = False, *, file_row_number : bool = False, filename: bool = False, hive_partitioning: bool = False, union_b y_name: bool = False, compression: Optional[str] = None) -> DuckDBPyRelation: .. . .venv/lib64/python3.12/site-packages/duckdb-stubs/__init__.pyi:474: def to_pa rquet( .venv/lib64/python3.12/site-packages/duckdb-stubs/__init__.pyi:514: def write _parquet( .venv/lib64/python3.12/site-packages/duckdb-stubs/__init__.pyi:692:def from_parq uet(file_glob: str, binary_as_string: bool = False, *, file_row_number: bool = F alse, filename: bool = False, hive_partitioning: bool = False, union_by_name: bo ol = False, compression: Optional[str] = None, connection: DuckDBPyConnection = ...) -> DuckDBPyRelation: ... .venv/lib64/python3.12/site-packages/duckdb-stubs/__init__.pyi:693:def read_parq uet(file_glob: str, binary_as_string: bool = False, *, file_row_number: bool = F alse, filename: bool = False, hive_partitioning: bool = False, union_by_name: bo ol = False, compression: Optional[str] = None, connection: DuckDBPyConnection = ...) -> DuckDBPyRelation: ...

It looks like _load_database needs to handle Parquet files properly. I'll modify it and add a test. I'll check the README for more insight.

shell
root@f39a1dc6c281:/workspace/scubaduck# grep -n "SCUBADUCK_DB" -n README.md 48:By default the server loads `sample.csv`. Set the `SCUBADUCK_DB` environment
root@f39a1dc6c281:/workspace/scubaduck# sed -n '40,60p' README.md ## Running the server Activate the virtual environment and run the Flask development server: ```bash flask --app scubaduck.server run --debug ``` By default the server loads `sample.csv`. Set the `SCUBADUCK_DB` environment variable to point at a different database file (CSV, SQLite or DuckDB) if you want to use another dataset. The special value `TEST` starts the server with a small in-memory SQLite dataset used by the automated tests. If the file does not exist, the server will raise a `FileNotFoundError` during startup.

I need to add Parquet support to _load_database and explore tests for server types.

shell
root@f39a1dc6c281:/workspace/scubaduck# grep -n "_load_database" -R
scubaduck/server.py:55:def _load_database(path: Path) -> duckdb.DuckDBPyConnecti on: scubaduck/server.py:425: con = _load_database(db_path)

I'll check for .venv to start the setup and run 'source .venv/bin/activate'.

shell
root@f39a1dc6c281:/workspace/scubaduck# ls -a . .git .gitignore AGENTS.md codex_setup.sh scubaduck tests .. .github .venv README.md pyproject.toml stubs uv.lock

Time to activate the .venv environment and get started!

shell
root@f39a1dc6c281:/workspace/scubaduck# source .venv/bin/activate (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll start by adding a test for SCUBADUCK_DB with Parquet in test_server_db_types.py.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# sed -n '200,260p' tests/test _server_db_types.py "end": "2024-01-02 00:00:00", "graph_type": "table", "time_column": "ts", "aggregate": "Avg", "group_by": ["id"], "columns": ["flag"], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert rv.status_code == 200 rows = sorted(data["rows"]) # order can vary assert rows == [[1, 2, 0.5], [2, 1, 1.0]] def test_envvar_db(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: csv_file = tmp_path / "custom.csv" csv_file.write_text("timestamp,event,value,user\n2024-01-01 00:00:00,login,5 ,bob\n") monkeypatch.setenv("SCUBADUCK_DB", str(csv_file)) app = server.create_app() client = app.test_client() payload = _make_payload() rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) rows = rv.get_json()["rows"] assert len(rows) == 1 def test_envvar_db_missing(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> N one: missing = tmp_path / "missing.sqlite" monkeypatch.setenv("SCUBADUCK_DB", str(missing)) with pytest.raises(FileNotFoundError): server.create_app() (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll look at test_server_basic or another test to see how it’s structured.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# sed -n '1,40p' tests/test_se rver_basic.py from __future__ import annotations import json from scubaduck import server def test_basic_query() -> None: app = server.app client = app.test_client() payload = { "table": "events", "start": "2024-01-01 00:00:00", "end": "2024-01-02 00:00:00", "order_by": "timestamp", "order_dir": "ASC", "limit": 10, "columns": ["timestamp", "event", "value", "user"], "filters": [], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert data rows = data["rows"] # We expect first three rows (until 2024-01-02 00:00:00) assert len(rows) == 3 assert rows[0][1] == "login" assert rows[1][1] == "logout" def test_js_served() -> None: app = server.app client = app.test_client() rv = client.get("/js/chip_input.js") assert rv.status_code == 200 assert b"initChipInput" in rv.data (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

The instructions clearly ask to add server tests to tests/test_server.py. Let's open it.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# sed -n '1,200p' tests/test_s erver.py """Legacy test module. Tests have been split into multiple files: - test_server_basic.py - test_server_db_types.py - test_server_time.py - test_server_errors.py - test_server_timeseries.py """ (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

The instructions require adding server tests to tests/test_server.py, despite recent test splits.

I'll follow instructions and add the test to tests/test_server.py, referencing existing tests.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# git log -1 --stat commit e08b86baa34cfb3a5182ad3681596db58c2b1642 (HEAD -> work, main) Author: Edward Z. Yang <ezyang@mit.edu> Date: Thu May 22 23:01:28 2025 -0400 fix(dropdown): ensure selected item is scrolled into view (#154) scubaduck/static/js/view_settings.js | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

The HEAD commit is from 2025, not 2023. I'll check earlier commits for tests.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# git log --stat -5 | head -n 40 commit e08b86baa34cfb3a5182ad3681596db58c2b1642 Author: Edward Z. Yang <ezyang@mit.edu> Date: Thu May 22 23:01:28 2025 -0400 fix(dropdown): ensure selected item is scrolled into view (#154) scubaduck/static/js/view_settings.js | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) commit 2451f864f3fec8ad4422f119f55359deeef24f66 Author: Edward Z. Yang <ezyang@mit.edu> Date: Thu May 22 23:01:18 2025 -0400 fix(server): enforce series limit in sparse timeseries (#153) scubaduck/server.py | 19 +++++++++++++++++++ tests/test_server_timeseries.py | 24 ++++++++++++++++++++++++ 2 files changed, 43 insertions(+) commit b2bd0b9c4ad50e37b08bc506d29b98c1edb7d3a6 Author: Edward Z. Yang <ezyang@mit.edu> Date: Thu May 22 22:50:48 2025 -0400 feat(server): suggest time unit in errors (#152) scubaduck/server.py | 47 ++++++++++++++++++++++++--------------------- tests/test_server_errors.py | 21 ++++++++++++++++++++ 2 files changed, 46 insertions(+), 22 deletions(-) commit 6afebd641798d002d60f4bc883c166b1e0e9ac39 Author: Edward Z. Yang <ezyang@mit.edu> Date: Thu May 22 22:45:04 2025 -0400 fix(frontend): prevent clipped rotated time labels (#150) scubaduck/static/js/timeseries_chart.js | 5 +++-- tests/test_web_timeseries.py | 24 ++++++++++++++++++++++++ 2 files changed, 27 insertions(+), 2 deletions(-) commit 079223c1ff5209fba979fad03f8178f7e3c03886 (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll check earlier commits to find relevant tests.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# git log --stat -5 --skip=5 | head -n 40 commit 80a8cedc3fc2d49185d00e1c7ed03f2cbb8cc8ab Author: Edward Z. Yang <ezyang@mit.edu> Date: Thu May 22 22:37:26 2025 -0400 fix(ui): show count series for numeric timestamps (#148) scubaduck/static/js/timeseries_chart.js | 8 ++++++- tests/test_server_errors.py | 2 +- tests/test_web_timeseries.py | 39 +++++++++++++++++++++++++++++++++ 3 files changed, 47 insertions(+), 2 deletions(-) commit e90ea2e7d9288691773ea777ed5f4dffe4b5f6f3 Author: Edward Z. Yang <ezyang@mit.edu> Date: Thu May 22 22:37:08 2025 -0400 fix(server): json encode bytes (#149) scubaduck/server.py | 6 ++++++ tests/test_server_db_types.py | 28 ++++++++++++++++++++++++++++ 2 files changed, 34 insertions(+) commit a8074f6ccca3f3c7a48bdc2aa762ea90177b1b87 Author: Edward Z. Yang <ezyang@mit.edu> Date: Thu May 22 22:28:01 2025 -0400 fix(server): drop duplicate count column in table view (#147) scubaduck/server.py | 5 +++-- tests/test_server_errors.py | 2 +- tests/test_server_timeseries.py | 21 +++++++++++++++++++++ 3 files changed, 25 insertions(+), 3 deletions(-) commit 2ac2fc5088f297ae0f0b00b319b420d450c710a7 Author: Edward Z. Yang <ezyang@mit.edu> Date: Thu May 22 22:17:15 2025 -0400 fix(ui): reset view settings on table change (#144) scubaduck/static/js/view_settings.js | 44 +++++++++++++++++++++++++++++++----- tests/test_multi_table_web.py | 26 +++++++++++++++++++++ (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll examine the commit message for format and apply the same style when committing.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# git show e90ea2e7d9288691773 ea777ed5f4dffe4b5f6f3 --stat commit e90ea2e7d9288691773ea777ed5f4dffe4b5f6f3 Author: Edward Z. Yang <ezyang@mit.edu> Date: Thu May 22 22:37:08 2025 -0400 fix(server): json encode bytes (#149) scubaduck/server.py | 6 ++++++ tests/test_server_db_types.py | 28 ++++++++++++++++++++++++++++ 2 files changed, 34 insertions(+) (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

It's another commit with a "fix" message. I'll check the diff for test style.

shell
ea777ed5f4dffe4b5f6f3 | head -n 80 commit e90ea2e7d9288691773ea777ed5f4dffe4b5f6f3 Author: Edward Z. Yang <ezyang@mit.edu> Date: Thu May 22 22:37:08 2025 -0400 fix(server): json encode bytes (#149) diff --git a/scubaduck/server.py b/scubaduck/server.py index 5f48427..af7c77f 100644 --- a/scubaduck/server.py +++ b/scubaduck/server.py @@ -711,6 +711,12 @@ def create_app(db_file: str | Path | None = None) -> Flask: 400, ) + def _serialize(value: Any) -> Any: + if isinstance(value, bytes): + return repr(value) + return value + + rows = [[_serialize(v) for v in r] for r in rows] result: Dict[str, Any] = {"sql": sql, "rows": rows} if params.start is not None: result["start"] = str(params.start) diff --git a/tests/test_server_db_types.py b/tests/test_server_db_types.py index e4841a1..20ba1f6 100644 --- a/tests/test_server_db_types.py +++ b/tests/test_server_db_types.py @@ -121,6 +121,34 @@ def test_sqlite_bigint(tmp_path: Path) -> None: assert data["rows"][0][1] == big_value +def test_sqlite_bytes(tmp_path: Path) -> None: + sqlite_file = tmp_path / "bin.sqlite" + import sqlite3 + + conn = sqlite3.connect(sqlite_file) + conn.execute("CREATE TABLE events (timestamp TEXT, data BLOB)") + conn.execute( + "INSERT INTO events VALUES ('2024-01-01 00:00:00', ?)", + (b"\x00\xff",), + ) + conn.commit() + conn.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcc essIssue] + + app = server.create_app(sqlite_file) + client = app.test_client() + payload = { + "table": "events", + "order_by": "timestamp", + "columns": ["timestamp", "data"], + } + rv = client.post( + "/api/query", data=json.dumps(payload), content_type="application/json" + ) + data = rv.get_json() + assert rv.status_code == 200 + assert data["rows"] == [["2024-01-01 00:00:00", "b'\\x00\\xff'"]] + + def test_sqlite_boolean_aggregation(tmp_path: Path) -> None: sqlite_file = tmp_path / "bool.sqlite" import sqlite3 (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll check the test file for DB types and related server code around _load_database.

shell
server.py mx.strftime("%Y-%m-%d %H:%M:%S") if not isinstance(mx, str) else mx ) bucket_size: int | None = None series_limit = params.limit if params.graph_type == "timeseries": bucket_size = _granularity_seconds( params.granularity, params.start if isinstance(params.start, str) else None, params.end if isinstance(params.end, str) else None, ) if ( params.limit is not None and params.start is not None and params.end is not None ): try: start_dt = dtparser.parse(params.start) end_dt = dtparser.parse(params.end) buckets = math.ceil( (end_dt - start_dt).total_seconds() / bucket_size ) if buckets > 1: params.limit *= buckets except Exception: pass sql = build_query(params, column_types) try: rows = con.execute(sql).fetchall() except Exception as exc: tb = traceback.format_exc() print(f"Query failed:\n{sql}\n{tb}") return ( jsonify({"sql": sql, "error": str(exc), "traceback": tb}), 400, ) def _serialize(value: Any) -> Any: if isinstance(value, bytes): return repr(value) return value rows = [[_serialize(v) for v in r] for r in rows] if ( params.graph_type == "timeseries" and params.group_by and series_limit is not None ): key_slice = slice(1, 1 + len(params.group_by)) kept: set[tuple[Any, ...]] = set() filtered: list[list[Any]] = [] for row in rows: key = tuple(row[key_slice]) if key not in kept: if len(kept) >= series_limit: (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll scroll down to the bottom to check all relevant content.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# sed -n '736,792p' scubaduck/ server.py if len(kept) >= series_limit: continue kept.add(key) filtered.append(row) rows = filtered result: Dict[str, Any] = {"sql": sql, "rows": rows} if params.start is not None: result["start"] = str(params.start) if params.end is not None: result["end"] = str(params.end) if bucket_size is not None: result["bucket_size"] = bucket_size return jsonify(result) return app app = create_app() if __name__ == "__main__": app.run(debug=True) (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I’ll update _load_database to handle both Parquet and CSV formats when creating tables.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# head -n 5 scubaduck/sample.c sv timestamp,event,value,user 2024-01-01 00:00:00,login,10,alice 2024-01-01 01:00:00,logout,20,bob 2024-01-02 00:00:00,login,30,alice 2024-01-02 03:00:00,login,40,charlie (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I’ll check if a sample parquet file is available to verify the tests.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# ls scubaduck | grep parquet (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll generate a sample CSV for testing instead of using Parquet due to restrictions.

shell
name = "scubaduck" version = "0.1.0" description = "Scuba on DuckDB" readme = "README.md" requires-python = ">=3.12" license = {text = "MIT"} dependencies = [ "duckdb", "flask", "python-dateutil>=2.9.0.post0", ] [build-system] requires = ["hatchling"] build-backend = "hatchling.build" [tool.pytest.ini_options] addopts = "-n auto --tb=native" [tool.pyright] # Pyright configuration with strict settings include = ["scubaduck", "tests"] exclude = ["**/__pycache__", "dist"] stubPath = "stubs" venvPath = "." venv = ".venv" reportMissingImports = true reportMissingTypeStubs = true pythonVersion = "3.12" pythonPlatform = "All" typeCheckingMode = "strict" reportUnknownMemberType = true reportUnknownParameterType = true reportUnknownVariableType = true reportUnknownArgumentType = true reportPrivateImportUsage = true reportUntypedFunctionDecorator = true reportFunctionMemberAccess = true reportIncompatibleMethodOverride = true [tool.ruff] target-version = "py312" [tool.uv] dev-dependencies = [ "pytest>=8.3.5", "ruff>=0.11.2", "pytest-xdist>=3.6.1", "playwright>=1.52.0", "pyright>=1.1.350", "pytest-playwright>=0.7.0", ] (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I see that DuckDB supports Parquet file creation, so I'll check tests for usage.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# grep -n "write_parquet" -R t ests | head (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll look at test_server_db_types.py to replicate the test style and structure.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# grep -n "_make_payload" -n t ests/test_server_db_types.py 12:def _make_payload() -> dict[str, object]: 56: payload = _make_payload() 222: payload = _make_payload() (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll go up and check the earlier lines to examine how _make_payload is defined.

shell
from __future__ import annotations import json from pathlib import Path import duckdb import pytest from scubaduck import server def _make_payload() -> dict[str, object]: return { "table": "events", "start": "2024-01-01 00:00:00", "end": "2024-01-02 00:00:00", "order_by": "timestamp", "order_dir": "ASC", "limit": 10, "columns": ["timestamp", "event", "value", "user"], "filters": [], } def test_database_types(tmp_path: Path) -> None: csv_file = tmp_path / "events.csv" csv_file.write_text(Path("scubaduck/sample.csv").read_text()) sqlite_file = tmp_path / "events.sqlite" import sqlite3 conn = sqlite3.connect(sqlite_file) conn.execute( "CREATE TABLE events (timestamp TEXT, event TEXT, value INTEGER, user TE XT)" ) with open(csv_file) as f: next(f) for line in f: ts, ev, val, user = line.strip().split(",") conn.execute( "INSERT INTO events VALUES (?, ?, ?, ?)", (ts, ev, int(val), use r) ) conn.commit() conn.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcce ssIssue] duckdb_file = tmp_path / "events.duckdb" con = duckdb.connect(duckdb_file) con.execute( f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{csv_file.as_posix ()}')" )
) con.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcces sIssue] for db in (csv_file, sqlite_file, duckdb_file): app = server.create_app(db) client = app.test_client() payload = _make_payload() rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/js on" ) rows = rv.get_json()["rows"] assert len(rows) == 3 def test_sqlite_longvarchar(tmp_path: Path) -> None: sqlite_file = tmp_path / "events.sqlite" import sqlite3 conn = sqlite3.connect(sqlite_file) conn.execute( "CREATE TABLE events (timestamp TEXT, url LONGVARCHAR, title VARCHAR(10) )" ) conn.execute( "INSERT INTO events VALUES ('2024-01-01 00:00:00', 'https://a.com', 'Hom e')" ) conn.commit() conn.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcce ssIssue] app = server.create_app(sqlite_file) client = app.test_client() payload = { "table": "events", "start": "2024-01-01 00:00:00", "end": "2024-01-01 01:00:00", "order_by": "timestamp", "columns": ["timestamp", "url", "title"], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert rv.status_code == 200 assert data["rows"][0][1] == "https://a.com" def test_sqlite_bigint(tmp_path: Path) -> None: sqlite_file = tmp_path / "big.sqlite" import sqlite3 conn = sqlite3.connect(sqlite_file) conn.execute("CREATE TABLE events (timestamp TEXT, value INTEGER)") big_value = 13385262862605259 conn.execute( "INSERT INTO events VALUES ('2024-01-01 00:00:00', ?)", (big_value,), ) conn.commit() conn.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcce ssIssue] app = server.create_app(sqlite_file) client = app.test_client() payload = { "table": "events", "order_by": "timestamp", "columns": ["timestamp", "value"], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert rv.status_code == 200 (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll keep scrolling past 190 to review the environment tests we checked before.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# sed -n '190,260p' tests/test _server_db_types.py conn.execute("INSERT INTO events VALUES (1, '2024-01-01 00:30:00', 0)") conn.execute("INSERT INTO events VALUES (2, '2024-01-01 01:00:00', 1)") conn.commit() conn.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcce ssIssue] app = server.create_app(sqlite_file) client = app.test_client() payload = { "table": "events", "start": "2024-01-01 00:00:00", "end": "2024-01-02 00:00:00", "graph_type": "table", "time_column": "ts", "aggregate": "Avg", "group_by": ["id"], "columns": ["flag"], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert rv.status_code == 200 rows = sorted(data["rows"]) # order can vary assert rows == [[1, 2, 0.5], [2, 1, 1.0]] def test_envvar_db(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: csv_file = tmp_path / "custom.csv" csv_file.write_text("timestamp,event,value,user\n2024-01-01 00:00:00,login,5 ,bob\n") monkeypatch.setenv("SCUBADUCK_DB", str(csv_file)) app = server.create_app() client = app.test_client() payload = _make_payload() rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) rows = rv.get_json()["rows"] assert len(rows) == 1 def test_envvar_db_missing(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> N one: missing = tmp_path / "missing.sqlite" monkeypatch.setenv("SCUBADUCK_DB", str(missing)) with pytest.raises(FileNotFoundError): server.create_app() (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll check how to use DuckDB to convert sample.csv to a Parquet file.

shell
> import duckdb > print('duckdb version', duckdb.__version__) > PY duckdb version 1.2.2 (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I’ll implement _load_database support for .parquet. Also, I’ll update the README.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# sed -n '46,60p' README.md ``` By default the server loads `sample.csv`. Set the `SCUBADUCK_DB` environment variable to point at a different database file (CSV, SQLite or DuckDB) if you want to use another dataset. The special value `TEST` starts the server with a small in-memory SQLite dataset used by the automated tests. If the file does not exist, the server will raise a `FileNotFoundError` during startup. (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll mention Parquet as an allowed type and update the instructions for _load_database.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# cat scubaduck/__init__.py def hello() -> str: return "Hello from scubaduck!" (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I’ll take a look at the _load_database function by opening scubaduck/server.py.

shell
time_unit: str = "s" def _load_database(path: Path) -> duckdb.DuckDBPyConnection: if not path.exists(): raise FileNotFoundError(path) ext = path.suffix.lower() if ext == ".csv": con = duckdb.connect() con.execute( f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{path.as_posix ()}')" ) elif ext in {".db", ".sqlite"}: con = duckdb.connect() con.execute("LOAD sqlite") con.execute(f"ATTACH '{path.as_posix()}' AS db (TYPE SQLITE)") tables = [ r[0] for r in con.execute( "SELECT name FROM sqlite_master WHERE type='table'" ).fetchall() ] for t in tables: con.execute(f'CREATE VIEW "{t}" AS SELECT * FROM db."{t}"') else: con = duckdb.connect(path) return con (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll add a condition for Parquet formats in _load_database and check for .tsv. Then, I'll update the README, and create a test to verify the Parquet file loading using SCUBADUCK_DB. Finally, I'll tweak environment variable handling in tests.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# grep -n "monkeypatch" -n tes ts/test_server_db_types.py 216:def test_envvar_db(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: 219: monkeypatch.setenv("SCUBADUCK_DB", str(csv_file)) 230:def test_envvar_db_missing(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: 232: monkeypatch.setenv("SCUBADUCK_DB", str(missing)) (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

The environment variable tests start around line 216, so I'm checking from there.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# sed -n '214,240p' tests/test _server_db_types.py def test_envvar_db(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: csv_file = tmp_path / "custom.csv" csv_file.write_text("timestamp,event,value,user\n2024-01-01 00:00:00,login,5 ,bob\n") monkeypatch.setenv("SCUBADUCK_DB", str(csv_file)) app = server.create_app() client = app.test_client() payload = _make_payload() rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) rows = rv.get_json()["rows"] assert len(rows) == 1 def test_envvar_db_missing(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> N one: missing = tmp_path / "missing.sqlite" monkeypatch.setenv("SCUBADUCK_DB", str(missing)) with pytest.raises(FileNotFoundError): server.create_app() (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll add the test for parquet creation. But I need to verify the row count; sample.csv may have 4 rows.

shell
timestamp,event,value,user 2024-01-01 00:00:00,login,10,alice 2024-01-01 01:00:00,logout,20,bob 2024-01-02 00:00:00,login,30,alice 2024-01-02 03:00:00,login,40,charlie (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

The test expects 3 results based on the time range. I'll detect parquet format and implement necessary connection protocol for the new test.

shell
rver.py ext = path.suffix.lower() if ext == ".csv": con = duckdb.connect() con.execute( f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{path.as_posix ()}')" ) elif ext in {".db", ".sqlite"}: con = duckdb.connect() con.execute("LOAD sqlite") con.execute(f"ATTACH '{path.as_posix()}' AS db (TYPE SQLITE)") tables = [ r[0] for r in con.execute( "SELECT name FROM sqlite_master WHERE type='table'" ).fetchall() ] for t in tables: con.execute(f'CREATE VIEW "{t}" AS SELECT * FROM db."{t}"') (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I’ll apply this patch right after the csv branch. Let’s go ahead and do it.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# apply_patch<<'PATCH' > *** Begin Patch > *** Update File: scubaduck/server.py > @@ > - elif ext in {".db", ".sqlite"}: > + elif ext in {".parquet", ".parq"}: > + con = duckdb.connect() > + con.execute( > + f"CREATE TABLE events AS SELECT * FROM read_parquet('{path.as_pos ix()}')" > + ) > + elif ext in {".db", ".sqlite"}: > con = duckdb.connect() > con.execute("LOAD sqlite") > con.execute(f"ATTACH '{path.as_posix()}' AS db (TYPE SQLITE)") > *** End Patch > PATCH Success. Updated the following files: M scubaduck/server.py (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll take a look at the patch to ensure everything looks good.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# sed -n '54,84p' scubaduck/se rver.py def _load_database(path: Path) -> duckdb.DuckDBPyConnection: if not path.exists(): raise FileNotFoundError(path) ext = path.suffix.lower() if ext == ".csv": con = duckdb.connect() con.execute( f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{path.as_posix ()}')" ) elif ext in {".parquet", ".parq"}: con = duckdb.connect() con.execute( f"CREATE TABLE events AS SELECT * FROM read_parquet('{path.as_posix( )}')" ) elif ext in {".db", ".sqlite"}: con = duckdb.connect() con.execute("LOAD sqlite") con.execute(f"ATTACH '{path.as_posix()}' AS db (TYPE SQLITE)") tables = [ r[0] for r in con.execute( "SELECT name FROM sqlite_master WHERE type='table'" ).fetchall() ] for t in tables: con.execute(f'CREATE VIEW "{t}" AS SELECT * FROM db."{t}"') else: con = duckdb.connect(path) return con (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I’ll go ahead and update the README to reflect the changes.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# sed -n '46,60p' README.md ``` By default the server loads `sample.csv`. Set the `SCUBADUCK_DB` environment variable to point at a different database file (CSV, SQLite or DuckDB) if you want to use another dataset. The special value `TEST` starts the server with a small in-memory SQLite dataset used by the automated tests. If the file does not exist, the server will raise a `FileNotFoundError` during startup. (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll modify the setup to incorporate Parquet support in the process.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# apply_patch<<'PATCH' > *** Begin Patch > *** Update File: README.md > @@ > -By default the server loads `sample.csv`. Set the `SCUBADUCK_DB` environment > -variable to point at a different database file (CSV, SQLite or DuckDB) if you > +By default the server loads `sample.csv`. Set the `SCUBADUCK_DB` environment > +variable to point at a different database file (CSV, Parquet, SQLite or DuckD B) if you > *** End Patch > PATCH Success. Updated the following files: M README.md (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

Next, I'll open tests/test_server_db_types.py to insert a new test.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# sed -n '208,245p' tests/test _server_db_types.py "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert rv.status_code == 200 rows = sorted(data["rows"]) # order can vary assert rows == [[1, 2, 0.5], [2, 1, 1.0]] def test_envvar_db(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: csv_file = tmp_path / "custom.csv" csv_file.write_text("timestamp,event,value,user\n2024-01-01 00:00:00,login,5 ,bob\n") monkeypatch.setenv("SCUBADUCK_DB", str(csv_file)) app = server.create_app() client = app.test_client() payload = _make_payload() rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) rows = rv.get_json()["rows"] assert len(rows) == 1 def test_envvar_db_missing(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> N one: missing = tmp_path / "missing.sqlite" monkeypatch.setenv("SCUBADUCK_DB", str(missing)) with pytest.raises(FileNotFoundError): server.create_app() (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll add a function to use Parquet, ensuring the path to sample.csv isn't absolute.

shell
> @@ > def test_envvar_db(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: > @@ > assert len(rows) == 1 > + > + > +def test_envvar_parquet(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> N one: > + parquet_file = tmp_path / "events.parquet" > + con = duckdb.connect() > + csv_path = Path("scubaduck/sample.csv").resolve() > + con.execute( > + f"COPY (SELECT * FROM read_csv_auto('{csv_path.as_posix()}')) TO '{pa rquet_file.as_posix()}' (FORMAT PARQUET)" > + ) > + con.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAc cessIssue] > + > + monkeypatch.setenv("SCUBADUCK_DB", str(parquet_file)) > + app = server.create_app() > + client = app.test_client() > + payload = _make_payload() > + rv = client.post( > + "/api/query", data=json.dumps(payload), content_type="application/jso n" > + ) > + rows = rv.get_json()["rows"] > + assert len(rows) == 3 > *** End Patch > PATCH Success. Updated the following files: M tests/test_server_db_types.py (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'm going to open the patch so I can take a look at what needs to be changed.

shell
def test_envvar_db(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: csv_file = tmp_path / "custom.csv" csv_file.write_text("timestamp,event,value,user\n2024-01-01 00:00:00,login,5 ,bob\n") monkeypatch.setenv("SCUBADUCK_DB", str(csv_file)) app = server.create_app() client = app.test_client() payload = _make_payload() rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) rows = rv.get_json()["rows"] assert len(rows) == 1 def test_envvar_parquet(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None : parquet_file = tmp_path / "events.parquet" con = duckdb.connect() csv_path = Path("scubaduck/sample.csv").resolve() con.execute( f"COPY (SELECT * FROM read_csv_auto('{csv_path.as_posix()}')) TO '{parqu et_file.as_posix()}' (FORMAT PARQUET)" ) con.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcces sIssue] monkeypatch.setenv("SCUBADUCK_DB", str(parquet_file)) app = server.create_app() client = app.test_client() payload = _make_payload() rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) rows = rv.get_json()["rows"] assert len(rows) == 3 def test_envvar_db_missing(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> N one: missing = tmp_path / "missing.sqlite" monkeypatch.setenv("SCUBADUCK_DB", str(missing)) with pytest.raises(FileNotFoundError): server.create_app() (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

Time to run ruff format and check the code style.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# ruff format README.md scubad uck/server.py tests/test_server_db_types.py error: Failed to parse README.md:1:3: Simple statements must be separated by new lines or semicolons 2 files left unchanged (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

Ruff works for Python, not README. I'll run it only on the Python files.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# ruff format scubaduck/server .py tests/test_server_db_types.py 2 files left unchanged (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll run a ruff check to ensure everything is properly formatted.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# ruff check scubaduck/server. py tests/test_server_db_types.py All checks passed!
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# pyright

0 errors, 0 warnings, 0 informations
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# pytest -q
bringing up nodes...









........................................................................ [ 56%]


128 passed in 20.48s (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

All tests passed, so I'll go ahead and commit the changes now.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# git status --short M README.md M scubaduck/server.py M tests/test_server_db_types.py (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I’ll gather the line ranges for the changes before committing.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# git diff --stat README.md | 2 +- scubaduck/server.py | 5 +++++ tests/test_server_db_types.py | 20 ++++++++++++++++++++ 3 files changed, 26 insertions(+), 1 deletion(-) (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I’ll open up the diff to double-check the changes.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# git diff -U1 README.md diff --git a/README.md b/README.md index 2e53d8c..6a6381f 100644 --- a/README.md +++ b/README.md @@ -48,3 +48,3 @@ flask --app scubaduck.server run --debug By default the server loads `sample.csv`. Set the `SCUBADUCK_DB` environment -variable to point at a different database file (CSV, SQLite or DuckDB) if you +variable to point at a different database file (CSV, Parquet, SQLite or DuckDB) if you want to use another dataset. The special value `TEST` starts the server with a (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll review the server diff to understand any changes.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# git diff -U3 scubaduck/serve r.py | sed -n '50,80p' (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I wonder if the patch is too small. I'll display the whole diff.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# git diff scubaduck/server.py diff --git a/scubaduck/server.py b/scubaduck/server.py index d292c4a..65ae821 100644 --- a/scubaduck/server.py +++ b/scubaduck/server.py @@ -62,6 +62,11 @@ def _load_database(path: Path) -> duckdb.DuckDBPyConnection: con.execute( f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{path.as_posi x()}')" ) + elif ext in {".parquet", ".parq"}: + con = duckdb.connect() + con.execute( + f"CREATE TABLE events AS SELECT * FROM read_parquet('{path.as_posix ()}')" + ) elif ext in {".db", ".sqlite"}: con = duckdb.connect() con.execute("LOAD sqlite") (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll review the diff to see if any tests were modified.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# git diff tests/test_server_d b_types.py | sed -n '220,260p' (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I’m considering patching earlier lines instead of 220 since it's a relative path.

shell
b_types.py diff --git a/tests/test_server_db_types.py b/tests/test_server_db_types.py index 20ba1f6..61141b0 100644 --- a/tests/test_server_db_types.py +++ b/tests/test_server_db_types.py @@ -227,6 +227,26 @@ def test_envvar_db(monkeypatch: pytest.MonkeyPatch, tmp_pat h: Path) -> None: assert len(rows) == 1 +def test_envvar_parquet(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> Non e: + parquet_file = tmp_path / "events.parquet" + con = duckdb.connect() + csv_path = Path("scubaduck/sample.csv").resolve() + con.execute( + f"COPY (SELECT * FROM read_csv_auto('{csv_path.as_posix()}')) TO '{parq uet_file.as_posix()}' (FORMAT PARQUET)" + ) + con.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcce ssIssue] + + monkeypatch.setenv("SCUBADUCK_DB", str(parquet_file)) + app = server.create_app() + client = app.test_client() + payload = _make_payload() + rv = client.post( + "/api/query", data=json.dumps(payload), content_type="application/json" + ) + rows = rv.get_json()["rows"] + assert len(rows) == 3 + + def test_envvar_db_missing(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: missing = tmp_path / "missing.sqlite" monkeypatch.setenv("SCUBADUCK_DB", str(missing)) (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

The diff looks good, so I’m ready to commit these changes!

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# git add README.md scubaduck/ server.py tests/test_server_db_types.py
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# git commit -m "feat(server): support parquet databases" && git status --short [work 38a1ca9] feat(server): support parquet databases 3 files changed, 26 insertions(+), 1 deletion(-) (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll run git status to make sure everything is in order.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# git status --short (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I'll reference the new features, and grab the server file lines we modified.

shell
sed -n '58,76p' 58 59 ext = path.suffix.lower() 60 if ext == ".csv": 61 con = duckdb.connect() 62 con.execute( 63 f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{path. as_posix()}')" 64 ) 65 elif ext in {".parquet", ".parq"}: 66 con = duckdb.connect() 67 con.execute( 68 f"CREATE TABLE events AS SELECT * FROM read_parquet('{path.a s_posix()}')" 69 ) 70 elif ext in {".db", ".sqlite"}: 71 con = duckdb.connect() 72 con.execute("LOAD sqlite") 73 con.execute(f"ATTACH '{path.as_posix()}' AS db (TYPE SQLITE)") 74 tables = [ 75 r[0] 76 for r in con.execute(
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# nl -ba README.md | sed -n '4 7,52p' 47 48 By default the server loads `sample.csv`. Set the `SCUBADUCK_DB` environ ment 49 variable to point at a different database file (CSV, Parquet, SQLite or DuckDB) if you 50 want to use another dataset. The special value `TEST` starts the server with a 51 small in-memory SQLite dataset used by the automated tests. If the file does 52 not exist, the server will raise a `FileNotFoundError` during startup. (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I’ll grab the lines from the failed tests now.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# nl -ba tests/test_server_db_ types.py | sed -n '224,255p' 224 "/api/query", data=json.dumps(payload), content_type="applicatio n/json" 225 ) 226 rows = rv.get_json()["rows"] 227 assert len(rows) == 1 228 229 230 def test_envvar_parquet(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: 231 parquet_file = tmp_path / "events.parquet" 232 con = duckdb.connect() 233 csv_path = Path("scubaduck/sample.csv").resolve() 234 con.execute( 235 f"COPY (SELECT * FROM read_csv_auto('{csv_path.as_posix()}')) TO '{parquet_file.as_posix()}' (FORMAT PARQUET)" 236 ) 237 con.close() # pyright: ignore[reportUnknownMemberType, reportAttrib uteAccessIssue] 238 239 monkeypatch.setenv("SCUBADUCK_DB", str(parquet_file)) 240 app = server.create_app() 241 client = app.test_client() 242 payload = _make_payload() 243 rv = client.post( 244 "/api/query", data=json.dumps(payload), content_type="applicatio n/json" 245 ) 246 rows = rv.get_json()["rows"] 247 assert len(rows) == 3 248 249 250 def test_envvar_db_missing(monkeypatch: pytest.MonkeyPatch, tmp_path: Pa th) -> None: 251 missing = tmp_path / "missing.sqlite" 252 monkeypatch.setenv("SCUBADUCK_DB", str(missing)) 253 with pytest.raises(FileNotFoundError): 254 server.create_app() (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

Let's output the test results and check for any issues.

shell
(scubaduck) root@f39a1dc6c281:/workspace/scubaduck# tail -n 2 <<'EOF' > $(grep -n "128 passed" -n -R) > EOF $(grep -n "128 passed" -n -R) (scubaduck) root@f39a1dc6c281:/workspace/scubaduck#

I can't get past test run output easily. I'll craft the PR with the chunk instead.