Task ID: task_e_682d4e6e23e08323a16ce1b6e2e2b5ee
Building scubaduck @ file:///workspace/scubaduck
⠹ Preparing packages... (5/33)
python-slugify ------------------------------ 9.82 KiB/9.82 KiB
pyee ------------------------------ 15.36 KiB/15.36 KiB
markupsafe ------------------------------ 22.58 KiB/22.58 KiB
execnet ------------------------------ 30.88 KiB/39.66 KiB
requests ------------------------------ 32.00 KiB/63.41 KiB
packaging ------------------------------ 32.00 KiB/64.91 KiB
text-unidecode ------------------------------ 76.32 KiB/76.32 KiB
click ------------------------------ 64.00 KiB/99.76 KiB
flask ------------------------------ 78.88 KiB/100.88 KiB
urllib3 ------------------------------ 46.88 KiB/125.66 KiB
jinja2 ------------------------------ 93.56 KiB/131.74 KiB
charset-normalizer ------------------------------ 78.20 KiB/145.08 KiB
certifi ------------------------------ 155.88 KiB/155.88 KiB
werkzeug ------------------------------ 77.00 KiB/219.24 KiB
python-dateutil ------------------------------ 30.86 KiB/224.50 KiB
pytest ------------------------------ 30.88 KiB/335.58 KiB
greenlet ------------------------------ 16.00 KiB/589.71 KiB
pyright ------------------------------ 16.00 KiB/5.31 MiB
ruff ------------------------------ 32.00 KiB/11.02 MiB
duckdb ------------------------------ 158.06 KiB/19.27 MiB
playwright ------------------------------ 62.91 KiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠹ Preparing packages... (5/33)
pyee ------------------------------ 15.36 KiB/15.36 KiB
markupsafe ------------------------------ 22.58 KiB/22.58 KiB
execnet ------------------------------ 30.88 KiB/39.66 KiB
requests ------------------------------ 32.00 KiB/63.41 KiB
packaging ------------------------------ 32.00 KiB/64.91 KiB
text-unidecode ------------------------------ 76.32 KiB/76.32 KiB
click ------------------------------ 64.00 KiB/99.76 KiB
flask ------------------------------ 78.88 KiB/100.88 KiB
urllib3 ------------------------------ 46.88 KiB/125.66 KiB
jinja2 ------------------------------ 93.56 KiB/131.74 KiB
charset-normalizer ------------------------------ 94.20 KiB/145.08 KiB
certifi ------------------------------ 155.88 KiB/155.88 KiB
werkzeug ------------------------------ 77.00 KiB/219.24 KiB
python-dateutil ------------------------------ 30.86 KiB/224.50 KiB
pytest ------------------------------ 46.88 KiB/335.58 KiB
greenlet ------------------------------ 16.00 KiB/589.71 KiB
pyright ------------------------------ 16.00 KiB/5.31 MiB
ruff ------------------------------ 32.00 KiB/11.02 MiB
duckdb ------------------------------ 158.06 KiB/19.27 MiB
playwright ------------------------------ 62.91 KiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠹ Preparing packages... (5/33)
pyee ------------------------------ 15.36 KiB/15.36 KiB
markupsafe ------------------------------ 22.58 KiB/22.58 KiB
execnet ------------------------------ 30.88 KiB/39.66 KiB
requests ------------------------------ 48.00 KiB/63.41 KiB
packaging ------------------------------ 48.00 KiB/64.91 KiB
click ------------------------------ 80.00 KiB/99.76 KiB
flask ------------------------------ 78.88 KiB/100.88 KiB
urllib3 ------------------------------ 62.88 KiB/125.66 KiB
jinja2 ------------------------------ 109.56 KiB/131.74 KiB
charset-normalizer ------------------------------ 126.20 KiB/145.08 KiB
certifi ------------------------------ 155.88 KiB/155.88 KiB
werkzeug ------------------------------ 93.00 KiB/219.24 KiB
python-dateutil ------------------------------ 46.86 KiB/224.50 KiB
pytest ------------------------------ 62.88 KiB/335.58 KiB
greenlet ------------------------------ 32.00 KiB/589.71 KiB
pyright ------------------------------ 16.00 KiB/5.31 MiB
ruff ------------------------------ 78.17 KiB/11.02 MiB
duckdb ------------------------------ 254.06 KiB/19.27 MiB
playwright ------------------------------ 78.91 KiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠹ Preparing packages... (5/33)
pyee ------------------------------ 15.36 KiB/15.36 KiB
execnet ------------------------------ 30.88 KiB/39.66 KiB
requests ------------------------------ 48.00 KiB/63.41 KiB
packaging ------------------------------ 48.00 KiB/64.91 KiB
click ------------------------------ 80.00 KiB/99.76 KiB
flask ------------------------------ 78.88 KiB/100.88 KiB
urllib3 ------------------------------ 62.88 KiB/125.66 KiB
jinja2 ------------------------------ 109.56 KiB/131.74 KiB
charset-normalizer ------------------------------ 126.20 KiB/145.08 KiB
certifi ------------------------------ 155.88 KiB/155.88 KiB
werkzeug ------------------------------ 93.00 KiB/219.24 KiB
python-dateutil ------------------------------ 46.86 KiB/224.50 KiB
pytest ------------------------------ 62.88 KiB/335.58 KiB
greenlet ------------------------------ 32.00 KiB/589.71 KiB
pyright ------------------------------ 16.00 KiB/5.31 MiB
ruff ------------------------------ 110.17 KiB/11.02 MiB
duckdb ------------------------------ 270.06 KiB/19.27 MiB
playwright ------------------------------ 78.91 KiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠹ Preparing packages... (5/33)
execnet ------------------------------ 30.88 KiB/39.66 KiB
requests ------------------------------ 48.00 KiB/63.41 KiB
packaging ------------------------------ 48.00 KiB/64.91 KiB
click ------------------------------ 80.00 KiB/99.76 KiB
flask ------------------------------ 78.88 KiB/100.88 KiB
urllib3 ------------------------------ 77.80 KiB/125.66 KiB
jinja2 ------------------------------ 125.56 KiB/131.74 KiB
charset-normalizer ------------------------------ 126.20 KiB/145.08 KiB
certifi ------------------------------ 155.88 KiB/155.88 KiB
werkzeug ------------------------------ 93.00 KiB/219.24 KiB
python-dateutil ------------------------------ 46.86 KiB/224.50 KiB
pytest ------------------------------ 62.88 KiB/335.58 KiB
greenlet ------------------------------ 32.00 KiB/589.71 KiB
pyright ------------------------------ 16.00 KiB/5.31 MiB
ruff ------------------------------ 126.17 KiB/11.02 MiB
duckdb ------------------------------ 286.06 KiB/19.27 MiB
playwright ------------------------------ 78.91 KiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠹ Preparing packages... (5/33)
execnet ------------------------------ 39.66 KiB/39.66 KiB
requests ------------------------------ 48.00 KiB/63.41 KiB
packaging ------------------------------ 64.91 KiB/64.91 KiB
click ------------------------------ 96.00 KiB/99.76 KiB
flask ------------------------------ 94.88 KiB/100.88 KiB
urllib3 ------------------------------ 77.80 KiB/125.66 KiB
jinja2 ------------------------------ 125.56 KiB/131.74 KiB
charset-normalizer ------------------------------ 126.20 KiB/145.08 KiB
werkzeug ------------------------------ 93.00 KiB/219.24 KiB
python-dateutil ------------------------------ 62.86 KiB/224.50 KiB
pytest ------------------------------ 76.88 KiB/335.58 KiB
greenlet ------------------------------ 32.00 KiB/589.71 KiB
pyright ------------------------------ 16.00 KiB/5.31 MiB
ruff ------------------------------ 158.17 KiB/11.02 MiB
duckdb ------------------------------ 318.06 KiB/19.27 MiB
playwright ------------------------------ 78.91 KiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠹ Preparing packages... (5/33)
execnet ------------------------------ 39.66 KiB/39.66 KiB
requests ------------------------------ 63.41 KiB/63.41 KiB
packaging ------------------------------ 64.91 KiB/64.91 KiB
click ------------------------------ 99.76 KiB/99.76 KiB
flask ------------------------------ 100.88 KiB/100.88 KiB
urllib3 ------------------------------ 77.80 KiB/125.66 KiB
jinja2 ------------------------------ 131.74 KiB/131.74 KiB
charset-normalizer ------------------------------ 142.20 KiB/145.08 KiB
werkzeug ------------------------------ 109.00 KiB/219.24 KiB
python-dateutil ------------------------------ 93.38 KiB/224.50 KiB
pytest ------------------------------ 108.88 KiB/335.58 KiB
greenlet ------------------------------ 48.00 KiB/589.71 KiB
pyright ------------------------------ 128.00 KiB/5.31 MiB
ruff ------------------------------ 270.17 KiB/11.02 MiB
duckdb ------------------------------ 429.61 KiB/19.27 MiB
playwright ------------------------------ 94.91 KiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠹ Preparing packages... (5/33)
execnet ------------------------------ 39.66 KiB/39.66 KiB
requests ------------------------------ 63.41 KiB/63.41 KiB
packaging ------------------------------ 64.91 KiB/64.91 KiB
flask ------------------------------ 100.88 KiB/100.88 KiB
urllib3 ------------------------------ 93.80 KiB/125.66 KiB
jinja2 ------------------------------ 131.74 KiB/131.74 KiB
charset-normalizer ------------------------------ 142.20 KiB/145.08 KiB
werkzeug ------------------------------ 109.00 KiB/219.24 KiB
python-dateutil ------------------------------ 141.38 KiB/224.50 KiB
pytest ------------------------------ 124.88 KiB/335.58 KiB
greenlet ------------------------------ 62.48 KiB/589.71 KiB
pyright ------------------------------ 160.00 KiB/5.31 MiB
ruff ------------------------------ 318.17 KiB/11.02 MiB
duckdb ------------------------------ 477.61 KiB/19.27 MiB
playwright ------------------------------ 94.91 KiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠹ Preparing packages... (5/33)
execnet ------------------------------ 39.66 KiB/39.66 KiB
packaging ------------------------------ 64.91 KiB/64.91 KiB
flask ------------------------------ 100.88 KiB/100.88 KiB
urllib3 ------------------------------ 93.80 KiB/125.66 KiB
jinja2 ------------------------------ 131.74 KiB/131.74 KiB
charset-normalizer ------------------------------ 145.08 KiB/145.08 KiB
werkzeug ------------------------------ 109.00 KiB/219.24 KiB
python-dateutil ------------------------------ 205.38 KiB/224.50 KiB
pytest ------------------------------ 124.88 KiB/335.58 KiB
greenlet ------------------------------ 78.48 KiB/589.71 KiB
pyright ------------------------------ 224.00 KiB/5.31 MiB
ruff ------------------------------ 382.17 KiB/11.02 MiB
duckdb ------------------------------ 541.61 KiB/19.27 MiB
playwright ------------------------------ 94.91 KiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠹ Preparing packages... (5/33)
execnet ------------------------------ 39.66 KiB/39.66 KiB
flask ------------------------------ 100.88 KiB/100.88 KiB
urllib3 ------------------------------ 93.80 KiB/125.66 KiB
jinja2 ------------------------------ 131.74 KiB/131.74 KiB
charset-normalizer ------------------------------ 145.08 KiB/145.08 KiB
werkzeug ------------------------------ 125.00 KiB/219.24 KiB
python-dateutil ------------------------------ 221.38 KiB/224.50 KiB
pytest ------------------------------ 124.88 KiB/335.58 KiB
greenlet ------------------------------ 94.48 KiB/589.71 KiB
pyright ------------------------------ 240.00 KiB/5.31 MiB
ruff ------------------------------ 382.17 KiB/11.02 MiB
duckdb ------------------------------ 541.61 KiB/19.27 MiB
playwright ------------------------------ 94.91 KiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠹ Preparing packages... (5/33)
flask ------------------------------ 100.88 KiB/100.88 KiB
urllib3 ------------------------------ 93.80 KiB/125.66 KiB
jinja2 ------------------------------ 131.74 KiB/131.74 KiB
charset-normalizer ------------------------------ 145.08 KiB/145.08 KiB
werkzeug ------------------------------ 125.00 KiB/219.24 KiB
python-dateutil ------------------------------ 221.38 KiB/224.50 KiB
pytest ------------------------------ 124.88 KiB/335.58 KiB
greenlet ------------------------------ 110.48 KiB/589.71 KiB
pyright ------------------------------ 249.81 KiB/5.31 MiB
ruff ------------------------------ 398.17 KiB/11.02 MiB
duckdb ------------------------------ 557.61 KiB/19.27 MiB
playwright ------------------------------ 94.91 KiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠹ Preparing packages... (5/33)
urllib3 ------------------------------ 93.80 KiB/125.66 KiB
jinja2 ------------------------------ 131.74 KiB/131.74 KiB
charset-normalizer ------------------------------ 145.08 KiB/145.08 KiB
werkzeug ------------------------------ 125.00 KiB/219.24 KiB
python-dateutil ------------------------------ 221.38 KiB/224.50 KiB
pytest ------------------------------ 124.88 KiB/335.58 KiB
greenlet ------------------------------ 126.48 KiB/589.71 KiB
pyright ------------------------------ 249.81 KiB/5.31 MiB
ruff ------------------------------ 414.17 KiB/11.02 MiB
duckdb ------------------------------ 573.61 KiB/19.27 MiB
playwright ------------------------------ 94.91 KiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠹ Preparing packages... (5/33)
urllib3 ------------------------------ 93.80 KiB/125.66 KiB
charset-normalizer ------------------------------ 145.08 KiB/145.08 KiB
werkzeug ------------------------------ 125.00 KiB/219.24 KiB
python-dateutil ------------------------------ 221.38 KiB/224.50 KiB
pytest ------------------------------ 140.88 KiB/335.58 KiB
greenlet ------------------------------ 126.48 KiB/589.71 KiB
pyright ------------------------------ 249.81 KiB/5.31 MiB
ruff ------------------------------ 414.17 KiB/11.02 MiB
duckdb ------------------------------ 573.61 KiB/19.27 MiB
playwright ------------------------------ 94.91 KiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠹ Preparing packages... (5/33)
urllib3 ------------------------------ 93.80 KiB/125.66 KiB
werkzeug ------------------------------ 125.00 KiB/219.24 KiB
python-dateutil ------------------------------ 221.38 KiB/224.50 KiB
pytest ------------------------------ 140.88 KiB/335.58 KiB
greenlet ------------------------------ 142.48 KiB/589.71 KiB
pyright ------------------------------ 265.81 KiB/5.31 MiB
ruff ------------------------------ 430.17 KiB/11.02 MiB
duckdb ------------------------------ 589.61 KiB/19.27 MiB
playwright ------------------------------ 110.91 KiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠹ Preparing packages... (5/33)
urllib3 ------------------------------ 109.80 KiB/125.66 KiB
werkzeug ------------------------------ 141.00 KiB/219.24 KiB
pytest ------------------------------ 188.88 KiB/335.58 KiB
greenlet ------------------------------ 302.48 KiB/589.71 KiB
pyright ------------------------------ 425.81 KiB/5.31 MiB
ruff ------------------------------ 590.17 KiB/11.02 MiB
duckdb ------------------------------ 749.61 KiB/19.27 MiB
playwright ------------------------------ 110.91 KiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠹ Preparing packages... (5/33)
urllib3 ------------------------------ 109.80 KiB/125.66 KiB
werkzeug ------------------------------ 141.00 KiB/219.24 KiB
pytest ------------------------------ 188.88 KiB/335.58 KiB
greenlet ------------------------------ 350.48 KiB/589.71 KiB
pyright ------------------------------ 473.81 KiB/5.31 MiB
ruff ------------------------------ 638.17 KiB/11.02 MiB
duckdb ------------------------------ 781.61 KiB/19.27 MiB
playwright ------------------------------ 110.91 KiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠹ Preparing packages... (5/33)
werkzeug ------------------------------ 157.00 KiB/219.24 KiB
pytest ------------------------------ 220.88 KiB/335.58 KiB
greenlet ------------------------------ 462.48 KiB/589.71 KiB
pyright ------------------------------ 761.81 KiB/5.31 MiB
ruff ------------------------------ 926.17 KiB/11.02 MiB
duckdb ------------------------------ 1.06 MiB/19.27 MiB
playwright ------------------------------ 286.91 KiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠹ Preparing packages... (5/33)
werkzeug ------------------------------ 189.00 KiB/219.24 KiB
pytest ------------------------------ 236.88 KiB/335.58 KiB
greenlet ------------------------------ 478.48 KiB/589.71 KiB
pyright ------------------------------ 909.44 KiB/5.31 MiB
ruff ------------------------------ 1.07 MiB/11.02 MiB
duckdb ------------------------------ 1.22 MiB/19.27 MiB
playwright ------------------------------ 456.56 KiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠸ Preparing packages... (25/33)
pytest ------------------------------ 284.88 KiB/335.58 KiB
greenlet ------------------------------ 494.48 KiB/589.71 KiB
pyright ------------------------------ 1.23 MiB/5.31 MiB
ruff ------------------------------ 1.43 MiB/11.02 MiB
duckdb ------------------------------ 1.58 MiB/19.27 MiB
playwright ------------------------------ 808.56 KiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠸ Preparing packages... (25/33)
pytest ------------------------------ 316.88 KiB/335.58 KiB
greenlet ------------------------------ 494.48 KiB/589.71 KiB
pyright ------------------------------ 1.33 MiB/5.31 MiB
ruff ------------------------------ 1.64 MiB/11.02 MiB
duckdb ------------------------------ 1.78 MiB/19.27 MiB
playwright ------------------------------ 1.00 MiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠸ Preparing packages... (25/33)
greenlet ------------------------------ 510.48 KiB/589.71 KiB
pyright ------------------------------ 1.67 MiB/5.31 MiB
ruff ------------------------------ 2.05 MiB/11.02 MiB
duckdb ------------------------------ 2.20 MiB/19.27 MiB
playwright ------------------------------ 1.41 MiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠸ Preparing packages... (25/33)
greenlet ------------------------------ 542.48 KiB/589.71 KiB
pyright ------------------------------ 1.78 MiB/5.31 MiB
ruff ------------------------------ 2.22 MiB/11.02 MiB
duckdb ------------------------------ 2.35 MiB/19.27 MiB
playwright ------------------------------ 1.56 MiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠸ Preparing packages... (25/33)
greenlet ------------------------------ 589.71 KiB/589.71 KiB
pyright ------------------------------ 1.81 MiB/5.31 MiB
ruff ------------------------------ 2.97 MiB/11.02 MiB
duckdb ------------------------------ 3.12 MiB/19.27 MiB
playwright ------------------------------ 2.31 MiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠸ Preparing packages... (25/33)
pyright ------------------------------ 1.81 MiB/5.31 MiB
ruff ------------------------------ 3.14 MiB/11.02 MiB
duckdb ------------------------------ 3.29 MiB/19.27 MiB
playwright ------------------------------ 2.48 MiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠸ Preparing packages... (25/33)
pyright ------------------------------ 1.83 MiB/5.31 MiB
ruff ------------------------------ 3.65 MiB/11.02 MiB
duckdb ------------------------------ 3.81 MiB/19.27 MiB
playwright ------------------------------ 3.02 MiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠼ Preparing packages... (28/33)
pyright ------------------------------ 1.87 MiB/5.31 MiB
ruff ------------------------------ 4.42 MiB/11.02 MiB
duckdb ------------------------------ 4.59 MiB/19.27 MiB
playwright ------------------------------ 3.78 MiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
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pyright ------------------------------ 1.92 MiB/5.31 MiB
ruff ------------------------------ 5.24 MiB/11.02 MiB
duckdb ------------------------------ 5.42 MiB/19.27 MiB
playwright ------------------------------ 4.59 MiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
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pyright ------------------------------ 1.95 MiB/5.31 MiB
ruff ------------------------------ 6.08 MiB/11.02 MiB
duckdb ------------------------------ 6.26 MiB/19.27 MiB
playwright ------------------------------ 5.44 MiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
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pyright ------------------------------ 1.98 MiB/5.31 MiB
ruff ------------------------------ 6.90 MiB/11.02 MiB
duckdb ------------------------------ 7.09 MiB/19.27 MiB
playwright ------------------------------ 6.27 MiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
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pyright ------------------------------ 2.03 MiB/5.31 MiB
ruff ------------------------------ 7.67 MiB/11.02 MiB
duckdb ------------------------------ 7.86 MiB/19.27 MiB
playwright ------------------------------ 7.03 MiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠴ Preparing packages... (28/33)
pyright ------------------------------ 2.08 MiB/5.31 MiB
ruff ------------------------------ 8.47 MiB/11.02 MiB
duckdb ------------------------------ 8.65 MiB/19.27 MiB
playwright ------------------------------ 7.83 MiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠴ Preparing packages... (28/33)
pyright ------------------------------ 2.09 MiB/5.31 MiB
ruff ------------------------------ 9.29 MiB/11.02 MiB
duckdb ------------------------------ 9.50 MiB/19.27 MiB
playwright ------------------------------ 8.64 MiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
⠴ Preparing packages... (28/33)
pyright ------------------------------ 2.12 MiB/5.31 MiB
ruff ------------------------------ 10.12 MiB/11.02 MiB
duckdb ------------------------------ 10.30 MiB/19.27 MiB
playwright ------------------------------ 9.52 MiB/43.05 MiB
Building scubaduck @ file:///workspace/scubaduck
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pyright ------------------------------ 2.14 MiB/5.31 MiB
ruff ------------------------------ 10.91 MiB/11.02 MiB
duckdb ------------------------------ 11.11 MiB/19.27 MiB
playwright ------------------------------ 10.31 MiB/43.05 MiB
Built scubaduck @ file:///workspace/scubaduck
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pyright ------------------------------ 2.14 MiB/5.31 MiB
ruff ------------------------------ 11.02 MiB/11.02 MiB
duckdb ------------------------------ 11.27 MiB/19.27 MiB
playwright ------------------------------ 10.45 MiB/43.05 MiB
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pyright ------------------------------ 2.14 MiB/5.31 MiB
duckdb ------------------------------ 11.30 MiB/19.27 MiB
playwright ------------------------------ 10.48 MiB/43.05 MiB
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pyright ------------------------------ 2.17 MiB/5.31 MiB
duckdb ------------------------------ 12.17 MiB/19.27 MiB
playwright ------------------------------ 11.33 MiB/43.05 MiB
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pyright ------------------------------ 2.19 MiB/5.31 MiB
duckdb ------------------------------ 13.44 MiB/19.27 MiB
playwright ------------------------------ 12.64 MiB/43.05 MiB
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pyright ------------------------------ 2.20 MiB/5.31 MiB
duckdb ------------------------------ 14.70 MiB/19.27 MiB
playwright ------------------------------ 13.88 MiB/43.05 MiB
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pyright ------------------------------ 2.22 MiB/5.31 MiB
duckdb ------------------------------ 15.94 MiB/19.27 MiB
playwright ------------------------------ 15.13 MiB/43.05 MiB
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pyright ------------------------------ 2.23 MiB/5.31 MiB
duckdb ------------------------------ 17.23 MiB/19.27 MiB
playwright ------------------------------ 16.39 MiB/43.05 MiB
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pyright ------------------------------ 2.25 MiB/5.31 MiB
duckdb ------------------------------ 18.45 MiB/19.27 MiB
playwright ------------------------------ 17.62 MiB/43.05 MiB
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pyright ------------------------------ 2.26 MiB/5.31 MiB
duckdb ------------------------------ 19.20 MiB/19.27 MiB
playwright ------------------------------ 18.97 MiB/43.05 MiB
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pyright ------------------------------ 2.30 MiB/5.31 MiB
playwright ------------------------------ 20.06 MiB/43.05 MiB
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pyright ------------------------------ 2.34 MiB/5.31 MiB
playwright ------------------------------ 20.74 MiB/43.05 MiB
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pyright ------------------------------ 2.39 MiB/5.31 MiB
playwright ------------------------------ 23.12 MiB/43.05 MiB
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pyright ------------------------------ 2.42 MiB/5.31 MiB
playwright ------------------------------ 25.66 MiB/43.05 MiB
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pyright ------------------------------ 2.44 MiB/5.31 MiB
playwright ------------------------------ 28.16 MiB/43.05 MiB
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pyright ------------------------------ 2.47 MiB/5.31 MiB
playwright ------------------------------ 30.91 MiB/43.05 MiB
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pyright ------------------------------ 2.50 MiB/5.31 MiB
playwright ------------------------------ 33.45 MiB/43.05 MiB
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playwright ------------------------------ 35.73 MiB/43.05 MiB
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pyright ------------------------------ 2.58 MiB/5.31 MiB
playwright ------------------------------ 38.11 MiB/43.05 MiB
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pyright ------------------------------ 2.61 MiB/5.31 MiB
playwright ------------------------------ 39.72 MiB/43.05 MiB
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pyright ------------------------------ 2.64 MiB/5.31 MiB
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playwright ------------------------------ 41.41 MiB/43.05 MiB
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pyright ------------------------------ 2.79 MiB/5.31 MiB
playwright ------------------------------ 42.50 MiB/43.05 MiB
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pyright ------------------------------ 4.39 MiB/5.31 MiB
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pyright ------------------------------ 4.53 MiB/5.31 MiB
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Prepared 33 packages in 2.54s
░░░░░░░░░░░░░░░░░░░░ [0/0] Installing wheels...
░░░░░░░░░░░░░░░░░░░░ [0/33] Installing wheels...
░░░░░░░░░░░░░░░░░░░░ [0/33] iniconfig==2.1.0
░░░░░░░░░░░░░░░░░░░░ [1/33] iniconfig==2.1.0
░░░░░░░░░░░░░░░░░░░░ [1/33] click==8.2.0
█░░░░░░░░░░░░░░░░░░░ [2/33] click==8.2.0
█░░░░░░░░░░░░░░░░░░░ [2/33] nodeenv==1.9.1
█░░░░░░░░░░░░░░░░░░░ [3/33] nodeenv==1.9.1
█░░░░░░░░░░░░░░░░░░░ [3/33] requests==2.32.3
██░░░░░░░░░░░░░░░░░░ [4/33] requests==2.32.3
██░░░░░░░░░░░░░░░░░░ [4/33] itsdangerous==2.2.0
███░░░░░░░░░░░░░░░░░ [5/33] itsdangerous==2.2.0
███░░░░░░░░░░░░░░░░░ [5/33] pytest-base-url==2.1.0
███░░░░░░░░░░░░░░░░░ [6/33] pytest-base-url==2.1.0
███░░░░░░░░░░░░░░░░░ [6/33] pluggy==1.6.0
████░░░░░░░░░░░░░░░░ [7/33] pluggy==1.6.0
████░░░░░░░░░░░░░░░░ [7/33] packaging==25.0
████░░░░░░░░░░░░░░░░ [8/33] packaging==25.0
████░░░░░░░░░░░░░░░░ [8/33] idna==3.10
█████░░░░░░░░░░░░░░░ [9/33] idna==3.10
███████████████████░ [32/33] pyright==1.1.400
████████████████████ [33/33] pyright==1.1.400
Installed 33 packages in 113ms
+ 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/MwaiaH-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/v22.15.1/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/v22.15.1/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
++ 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% 30.7s167.7 MiB [] 0% 32.3s167.7 MiB [] 0% 24.4s167.7 MiB [] 0% 13.1s167.7 MiB [] 1% 7.2s167.7 MiB [] 1% 5.6s167.7 MiB [] 2% 4.8s167.7 MiB [] 3% 3.9s167.7 MiB [] 4% 3.1s167.7 MiB [] 5% 2.7s167.7 MiB [] 6% 2.6s167.7 MiB [] 7% 2.3s167.7 MiB [] 8% 2.2s167.7 MiB [] 10% 2.1s167.7 MiB [] 10% 2.0s167.7 MiB [] 12% 1.8s167.7 MiB [] 13% 1.7s167.7 MiB [] 15% 1.7s167.7 MiB [] 16% 1.6s167.7 MiB [] 18% 1.6s167.7 MiB [] 19% 1.5s167.7 MiB [] 20% 1.4s167.7 MiB [] 22% 1.4s167.7 MiB [] 23% 1.3s167.7 MiB [] 24% 1.3s167.7 MiB [] 26% 1.2s167.7 MiB [] 27% 1.2s167.7 MiB [] 29% 1.1s167.7 MiB [] 31% 1.1s167.7 MiB [] 33% 1.0s167.7 MiB [] 34% 1.0s167.7 MiB [] 35% 1.0s167.7 MiB [] 37% 0.9s167.7 MiB [] 38% 0.9s167.7 MiB [] 39% 0.9s167.7 MiB [] 41% 0.9s167.7 MiB [] 43% 0.8s167.7 MiB [] 44% 0.8s167.7 MiB [] 46% 0.8s167.7 MiB [] 47% 0.7s167.7 MiB [] 49% 0.7s167.7 MiB [] 51% 0.7s167.7 MiB [] 52% 0.6s167.7 MiB [] 54% 0.6s167.7 MiB [] 55% 0.6s167.7 MiB [] 57% 0.6s167.7 MiB [] 58% 0.6s167.7 MiB [] 59% 0.5s167.7 MiB [] 61% 0.5s167.7 MiB [] 62% 0.5s167.7 MiB [] 64% 0.5s167.7 MiB [] 65% 0.4s167.7 MiB [] 66% 0.4s167.7 MiB [] 68% 0.4s167.7 MiB [] 69% 0.4s167.7 MiB [] 70% 0.4s167.7 MiB [] 71% 0.4s167.7 MiB [] 73% 0.4s167.7 MiB [] 74% 0.3s167.7 MiB [] 76% 0.3s167.7 MiB [] 77% 0.3s167.7 MiB [] 79% 0.3s167.7 MiB [] 80% 0.3s167.7 MiB [] 82% 0.2s167.7 MiB [] 83% 0.2s167.7 MiB [] 84% 0.2s167.7 MiB [] 86% 0.2s167.7 MiB [] 87% 0.2s167.7 MiB [] 88% 0.1s167.7 MiB [] 90% 0.1s167.7 MiB [] 91% 0.1s167.7 MiB [] 93% 0.1s167.7 MiB [] 94% 0.1s167.7 MiB [] 96% 0.0s167.7 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 [] 3% 0.5s2.3 MiB [] 6% 0.5s2.3 MiB [] 15% 0.3s2.3 MiB [] 31% 0.1s2.3 MiB [] 55% 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% 21.1s101.4 MiB [] 0% 19.0s101.4 MiB [] 0% 13.0s101.4 MiB [] 0% 10.7s101.4 MiB [] 1% 4.8s101.4 MiB [] 3% 2.6s101.4 MiB [] 4% 2.5s101.4 MiB [] 4% 2.8s101.4 MiB [] 5% 2.5s101.4 MiB [] 7% 2.3s101.4 MiB [] 7% 2.5s101.4 MiB [] 7% 2.6s101.4 MiB [] 8% 2.6s101.4 MiB [] 9% 2.4s101.4 MiB [] 10% 2.4s101.4 MiB [] 11% 2.4s101.4 MiB [] 12% 2.3s101.4 MiB [] 15% 1.9s101.4 MiB [] 17% 1.6s101.4 MiB [] 20% 1.4s101.4 MiB [] 23% 1.2s101.4 MiB [] 25% 1.1s101.4 MiB [] 28% 1.0s101.4 MiB [] 31% 0.9s101.4 MiB [] 35% 0.8s101.4 MiB [] 36% 0.8s101.4 MiB [] 38% 0.7s101.4 MiB [] 41% 0.7s101.4 MiB [] 44% 0.6s101.4 MiB [] 46% 0.6s101.4 MiB [] 47% 0.6s101.4 MiB [] 51% 0.5s101.4 MiB [] 54% 0.5s101.4 MiB [] 58% 0.4s101.4 MiB [] 60% 0.4s101.4 MiB [] 62% 0.4s101.4 MiB [] 66% 0.3s101.4 MiB [] 68% 0.3s101.4 MiB [] 71% 0.3s101.4 MiB [] 74% 0.2s101.4 MiB [] 76% 0.2s101.4 MiB [] 79% 0.2s101.4 MiB [] 82% 0.2s101.4 MiB [] 85% 0.1s101.4 MiB [] 87% 0.1s101.4 MiB [] 91% 0.1s101.4 MiB [] 93% 0.1s101.4 MiB [] 96% 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'I’ve just checked AGENTS.md to see the instructions for guidance.
bash: .venv/bin/activate: No such file or directory
root@8b10638fd893:/workspace# ls
scubaduckroot@8b10638fd893:/workspace# cd scubaduck
root@8b10638fd893:/workspace/scubaduck# ls
AGENTS.md codex_setup.sh scubaduck tests
README.md pyproject.toml stubs uv.lockI'll check AGENTS.md now to see what instructions there are for me.
root@8b10638fd893:/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.pyI'll check the root README for any helpful hints or instructions.
root@8b10638fd893:/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) as well a
s specifying an absolute date. The way this field is rendered is there is a fre
e form text box, a drop down arrow (for the relative selectors), and then a cale
ndar 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.The README is a bit lengthy, but it’s fine. I’ll check for more instructions.
root@8b10638fd893:/workspace/scubaduck# sed -n '1,80p' 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.pyI'll activate the virtual environment and check which files are present with 'ls'.
root@8b10638fd893:/workspace/scubaduck# ls -a
. .git .gitignore AGENTS.md codex_setup.sh scubaduck tests
.. .github .venv README.md pyproject.toml stubs uv.lockroot@8b10638fd893:/workspace/scubaduck# source .venv/bin/activate
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'll run ruff check, ruff format, and pyright to ensure everything's in order.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# ruff check >/tmp/ruff_check.
txt && tail -n 20 /tmp/ruff_check.txt
All checks passed!(scubaduck) root@8b10638fd893:/workspace/scubaduck# ruff format >/tmp/ruff_forma
t.txt && tail -n 20 /tmp/ruff_format.txt
6 files left unchanged(scubaduck) root@8b10638fd893:/workspace/scubaduck# pyright >/tmp/pyright.txt &&
tail -n 20 /tmp/pyright.txt0 errors, 0 warnings, 0 informations
(scubaduck) root@8b10638fd893:/workspace/scubaduck#Time to run the tests and see how everything holds up!
(scubaduck) root@8b10638fd893:/workspace/scubaduck# pytest -q >/tmp/pytest.txt &
& tail -n 20 /tmp/pytest.txtbringing up nodes...
bringing up nodes...
........................................................ [100%]
56 passed in 9.43s(scubaduck) root@8b10638fd893:/workspace/scubaduck# tail -n 20 /tmp/pytest.txt
bringing up nodes...
bringing up nodes...
........................................................ [100%]
56 passed in 9.43s
(scubaduck) root@8b10638fd893:/workspace/scubaduck#Time Series view fails due to a query issue with string columns. I'll inspect the server code.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# ls scubaduck
__init__.py __pycache__ sample.csv server.py static(scubaduck) root@8b10638fd893:/workspace/scubaduck# sed -n '350,460p' scubaduck/
server.py
elif agg == "avg" or agg in {"min", "max"}:
need_numeric = False
allow_time = True
else:
need_numeric = False
allow_time = False
if need_numeric or allow_time:
for c in params.columns:
if c in params.group_by or c == params.x_axis:
continue
ctype = column_types.get(c, "").upper()
is_numeric = any(
t in ctype
for t in [
"INT",
"DECIMAL",
"REAL",
"DOUBLE",
"FLOAT",
"NUMERIC",
"HUGEINT",
]
)
is_time = "TIMESTAMP" in ctype or "DATE" in ctype or "TIME"
in ctype
if need_numeric and not is_numeric:
return (
jsonify(
{
"error": f"Aggregate {agg} cannot be applied
to column {c}",
}
),
400,
)
if allow_time and not (is_numeric or is_time):
return (
jsonify(
{
"error": f"Aggregate {agg} cannot be applied
to column {c}",
}
),
400,
)
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,
)
return jsonify({"sql": sql, "rows": rows})
return app
app = create_app()
if __name__ == "__main__":
app.run(debug=True)
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'll look for the build_query function now!
(scubaduck) root@8b10638fd893:/workspace/scubaduck# grep -n "build_query" -n scu
baduck/server.py
138:def build_query(params: QueryParams, column_types: Dict[str, str] | None = N
one) -> str:
392: sql = build_query(params, column_types)(scubaduck) root@8b10638fd893:/workspace/scubaduck# sed -n '138,270p' scubaduck/
server.py
def build_query(params: QueryParams, column_types: Dict[str, str] | None = None)
-> str:
select_parts: list[str] = []
group_cols = params.group_by[:]
if params.graph_type == "timeseries":
sec = _granularity_seconds(params.granularity, params.start, params.end)
x_axis = params.x_axis or "timestamp"
bucket_expr = (
f"TIMESTAMP 'epoch' + INTERVAL '{sec} second' * "
f"CAST(floor(epoch({x_axis})/{sec}) AS BIGINT)"
)
select_parts.append(f"{bucket_expr} AS bucket")
group_cols = ["bucket"] + group_cols
has_agg = bool(group_cols) or params.aggregate is not None
if has_agg:
select_parts.extend(group_cols)
agg = (params.aggregate or "avg").lower()
def agg_expr(col: str) -> str:
if agg.startswith("p"):
quant = float(agg[1:]) / 100
return f"quantile({col}, {quant})"
if agg == "count distinct":
return f"count(DISTINCT {col})"
if agg == "avg" and column_types is not None:
ctype = column_types.get(col, "").upper()
if "TIMESTAMP" in ctype or "DATE" in ctype or "TIME" in ctype:
return (
"TIMESTAMP 'epoch' + INTERVAL '1 second' * "
f"CAST(avg(epoch({col})) AS BIGINT)"
)
return f"{agg}({col})"
for col in params.columns:
if col in group_cols:
continue
select_parts.append(f"{agg_expr(col)} AS {col}")
if params.show_hits:
select_parts.insert(len(group_cols), "count(*) AS Hits")
else:
select_parts.extend(params.columns)
for name, expr in params.derived_columns.items():
select_parts.append(f"{expr} AS {name}")
select_clause = ", ".join(select_parts) if select_parts else "*"
query = f"SELECT {select_clause} FROM events"
where_parts: list[str] = []
if params.start:
where_parts.append(f"timestamp >= '{params.start}'")
if params.end:
where_parts.append(f"timestamp <= '{params.end}'")
for f in params.filters:
op = f.op
if op in {"empty", "!empty"}:
val = "''"
else:
if f.value is None:
continue
if isinstance(f.value, list):
if not f.value:
continue
if op == "=":
vals = " OR ".join(f"{f.column} = '{v}'" for v in f.value)
where_parts.append(f"({vals})")
continue
val = f"'{f.value}'" if isinstance(f.value, str) else str(f.value)
if op == "contains":
where_parts.append(f"{f.column} ILIKE '%' || {val} || '%'")
elif op == "!contains":
where_parts.append(f"{f.column} NOT ILIKE '%' || {val} || '%'")
elif op == "empty":
where_parts.append(f"{f.column} = {val}")
elif op == "!empty":
where_parts.append(f"{f.column} != {val}")
else:
where_parts.append(f"{f.column} {op} {val}")
if where_parts:
query += " WHERE " + " AND ".join(where_parts)
if group_cols:
query += " GROUP BY " + ", ".join(group_cols)
if params.order_by:
query += f" ORDER BY {params.order_by} {params.order_dir}"
if params.limit is not None:
query += f" LIMIT {params.limit}"
return query
def create_app(db_file: str | Path | None = None) -> Flask:
app = Flask(__name__, static_folder="static")
db_path = Path(db_file or Path(__file__).with_name("sample.csv")).resolve()
con = _load_database(db_path)
column_types: Dict[str, str] = {
r[1]: r[2] for r in con.execute("PRAGMA table_info(events)").fetchall()
}
sample_cache: Dict[Tuple[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("/api/columns")
def columns() -> Any: # pyright: ignore[reportUnusedFunction]
rows = con.execute("PRAGMA table_info(events)").fetchall()
return jsonify([{"name": r[1], "type": r[2]} for r in rows])
def _cache_get(key: Tuple[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], 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]
column = request.args.get("column")
substr = request.args.get("q", "")
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:
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I’ll keep scrolling to the end to check for any remaining functions.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# sed -n '270,360p' scubaduck/
server.py
if "CHAR" not in ctype and "STRING" not in ctype and "VARCHAR" not in ct
ype:
return jsonify([])
key = (column, substr)
cached = _cache_get(key)
if cached is not None:
return jsonify(cached)
rows = con.execute(
f"SELECT DISTINCT {column} FROM events WHERE CAST({column} AS VARCHA
R) 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"),
columns=payload.get("columns", []),
derived_columns=payload.get("derived_columns", {}),
graph_type=payload.get("graph_type", "samples"),
group_by=payload.get("group_by", []),
aggregate=payload.get("aggregate"),
show_hits=payload.get("show_hits", False),
x_axis=payload.get("x_axis"),
granularity=payload.get("granularity", "Auto"),
fill=payload.get("fill", "0"),
)
for f in payload.get("filters", []):
params.filters.append(Filter(f["column"], f["op"], f.get("value")))
if params.graph_type not in {"table", "timeseries"} and (
params.group_by or params.aggregate or params.show_hits
):
return (
jsonify(
{
"error": "group_by, aggregate and show_hits are only val
id for table or timeseries view"
}
),
400,
)
valid_cols = set(column_types.keys())
if params.graph_type == "timeseries":
if params.x_axis is None:
for cand in ["time", "timestamp"]:
if cand in valid_cols:
params.x_axis = cand
break
if params.x_axis is None or params.x_axis not in valid_cols:
return jsonify({"error": "Invalid x_axis"}), 400
ctype = column_types.get(params.x_axis, "").upper()
if not any(t in ctype for t in ["TIMESTAMP", "DATE", "TIME"]):
return jsonify({"error": "x_axis must be a time column"}), 400
for col in params.columns:
if col not in valid_cols:
return jsonify({"error": f"Unknown column: {col}"}), 400
for col in params.group_by:
if col not in valid_cols:
return jsonify({"error": f"Unknown column: {col}"}), 400
if params.order_by and params.order_by not in valid_cols:
return jsonify({"error": f"Unknown column: {params.order_by}"}), 400
if params.group_by:
agg = (params.aggregate or "avg").lower()
if agg.startswith("p") or agg == "sum":
need_numeric = True
allow_time = False
elif agg == "avg" or agg in {"min", "max"}:
need_numeric = False
allow_time = True
else:
need_numeric = False
allow_time = False
if need_numeric or allow_time:
for c in params.columns:
if c in params.group_by or c == params.x_axis:
continue
ctype = column_types.get(c, "").upper()(scubaduck) root@8b10638fd893:/workspace/scubaduck# sed -n '360,460p' scubaduck/
server.py
ctype = column_types.get(c, "").upper()
is_numeric = any(
t in ctype
for t in [
"INT",
"DECIMAL",
"REAL",
"DOUBLE",
"FLOAT",
"NUMERIC",
"HUGEINT",
]
)
is_time = "TIMESTAMP" in ctype or "DATE" in ctype or "TIME"
in ctype
if need_numeric and not is_numeric:
return (
jsonify(
{
"error": f"Aggregate {agg} cannot be applied
to column {c}",
}
),
400,
)
if allow_time and not (is_numeric or is_time):
return (
jsonify(
{
"error": f"Aggregate {agg} cannot be applied
to column {c}",
}
),
400,
)
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,
)
return jsonify({"sql": sql, "rows": rows})
return app
app = create_app()
if __name__ == "__main__":
app.run(debug=True)
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I’m reviewing the timeseries query logic and checking if there’s a missing group_by.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# grep -n "QueryParams" -n scu
baduck/server.py
27:class QueryParams:
138:def build_query(params: QueryParams, column_types: Dict[str, str] | None = N
one) -> str:
293: params = QueryParams((scubaduck) root@8b10638fd893:/workspace/scubaduck# sed -n '20,60p' scubaduck/se
rver.py
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"
def _load_database(path: Path) -> duckdb.DuckDBPyConnection:
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()
sconn = sqlite3.connect(path)
info = sconn.execute("PRAGMA table_info(events)").fetchall()
col_defs = ", ".join(f"{r[1]} {r[2]}" for r in info)
con.execute(f"CREATE TABLE events ({col_defs})")
placeholders = ",".join("?" for _ in info)
for row in sconn.execute("SELECT * FROM events"):
con.execute(f"INSERT INTO events VALUES ({placeholders})", row)
(scubaduck) root@8b10638fd893:/workspace/scubaduck#The issue arises when 'avg' is applied to string columns, causing a binder error.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# ls scubaduck/static
index.html(scubaduck) root@8b10638fd893:/workspace/scubaduck# grep -n "Time Series" -n scu
baduck/static/index.html
114: <div id="header">sample.csv - events <select id="graph_type"><option value
="samples">Samples</option><option value="table">Table</option><option value="ti
meseries">Time Series</option></select></div>(scubaduck) root@8b10638fd893:/workspace/scubaduck# sed -n '100,260p' scubaduck/
static/index.html
}
.col-group-header {
overflow: hidden;
}
.col-group-header .links {
float: right;
}
.col-group-header .links a {
margin-left: 5px;
}
/* Column resizer removed */
</style>
</head>
<body>
<div id="header">sample.csv - events <select id="graph_type"><option value="sa
mples">Samples</option><option value="table">Table</option><option value="timese
ries">Time Series</option></select></div>
<div id="content">
<div id="sidebar">
<div id="tabs">
<button class="tab active" data-tab="settings">View Settings</button>
<button class="tab" data-tab="columns">Columns</button>
<button id="dive" onclick="dive()">Dive</button>
</div>
<div id="settings" class="tab-content active">
<div class="field">
<label>Start<span class="help" title="Sets the start/end of the time r
ange to query. Can be any kind of datetime string. For example: 'April 23, 2014'
or 'yesterday'.">[?]</span></label>
<div class="rel-box">
<input id="start" type="text" />
<button type="button" class="rel-btn" data-target="start-select">	
660;</button>
<div id="start-select" class="rel-dropdown" data-input="start">
<div data-value="-1 hour">-1 hour</div>
<div data-value="-3 hours">-3 hours</div>
<div data-value="-12 hours">-12 hours</div>
<div data-value="-1 day">-1 day</div>
<div data-value="-3 days">-3 days</div>
<div data-value="-1 week">-1 week</div>
<div data-value="-1 fortnight">-1 fortnight</div>
<div data-value="-30 days">-30 days</div>
<div data-value="-90 days">-90 days</div>
</div>
</div>
</div>
<div class="field">
<label>End<span class="help" title="Sets the start/end of the time ran
ge to query. Can be any kind of datetime string. For example: 'April 23, 2014' o
r 'yesterday'.">[?]</span></label>
<div class="rel-box">
<input id="end" type="text" />
<button type="button" class="rel-btn" data-target="end-select">φ
0;</button>
<div id="end-select" class="rel-dropdown" data-input="end">
<div data-value="now">now</div>
<div data-value="-1 hour">-1 hour</div>
<div data-value="-3 hours">-3 hours</div>
<div data-value="-12 hours">-12 hours</div>
<div data-value="-1 day">-1 day</div>
<div data-value="-3 days">-3 days</div>
<div data-value="-1 week">-1 week</div>
<div data-value="-1 fortnight">-1 fortnight</div>
<div data-value="-30 days">-30 days</div>
<div data-value="-90 days">-90 days</div>
</div>
</div>
</div>
<div class="field">
<label>Order By<span class="help" title="Choose a column to sort resul
ts by.">[?]</span></label>
<select id="order_by"></select>
<button id="order_dir" type="button">ASC \u25B2</button>
</div>
<div class="field">
<label>Limit<span class="help" title="Choose the maximum number of res
ults to show in the chart after any aggregations have been applied. For example,
a limit of 10 will show no more than 10 rows for a table, etc.">[?]</span></lab
el>
<input id="limit" type="number" value="100" />
</div>
<div id="x_axis_field" class="field" style="display:none;">
<label>X-axis</label>
<select id="x_axis"></select>
</div>
<div id="granularity_field" class="field" style="display:none;">
<label>Granularity</label>
<select id="granularity">
<option>Auto</option>
<option>Fine</option>
<option>1 second</option>
<option>5 seconds</option>
<option>10 seconds</option>
<option>30 seconds</option>
<option>1 minute</option>
<option>4 minutes</option>
<option>5 minutes</option>
<option>10 minutes</option>
<option>15 minutes</option>
<option>30 minutes</option>
<option>1 hour</option>
<option>3 hours</option>
<option>6 hours</option>
<option>1 day</option>
<option>1 week</option>
<option>30 days</option>
</select>
</div>
<div id="fill_field" class="field" style="display:none;">
<label>Fill Missing Buckets</label>
<select id="fill">
<option value="0">Fill with 0 (Per Series)</option>
<option value="connect">Connect (Per Series)</option>
<option value="blank">Leave blank</option>
</select>
</div>
<div id="group_by_field" class="field" style="display:none;">
<label>Group By</label>
<div class="chip-box">
<div class="chip-input">
<input id="group_by" class="f-val" type="text">
<button type="button" class="chip-copy">⎘</button>
</div>
<div class="chip-dropdown"></div>
</div>
</div>
<div id="aggregate_field" class="field" style="display:none;">
<label>Aggregate</label>
<select id="aggregate">
<option>Avg</option>
<option>Count</option>
<option>Sum</option>
<option>Min</option>
<option>Max</option>
<option>Count Distinct</option>
<option>p5</option>
<option>p25</option>
<option>p50</option>
<option>p70</option>
<option>p75</option>
<option>p90</option>
<option>p95</option>
<option>p99</option>
<option>p99.9</option>
<option>p99.99</option>
</select>
</div>
<div id="show_hits_field" class="field" style="display:none;">
<label>Show Hits</label>
<input id="show_hits" type="checkbox" checked>
</div>
<div id="filters">
<h4>Filters<span class="help" title="You can create as many filters as
you want. You can either write a filter using a UI or manual SQL. In the UI, fi
lter consists of a column name, a relation (e.g., =, !=, <, >) and then a text f
ield. The text field is a token input. It accepts multiple tokens for = relation
, in which case we match using an OR for all options.">[?]</span></h4>
<div id="filter_list"></div>
<button id="add_filter" type="button" onclick="addFilter()">Add Filter
</button>
</div>
<div id="query_info" style="margin-top:10px;"></div>
</div>
<div id="columns" class="tab-content">
<div id="column_actions">
<a id="columns_all" href="#">All</a>
<a id="columns_none" href="#">None</a>
</div>
<div id="column_groups"></div>
</div>
</div>
<div id="sidebar-resizer"></div>
<div id="view">
<table id="results"></table>
</div>
</div>
<script>
const allColumns = [];
(scubaduck) root@8b10638fd893:/workspace/scubaduck#Scrolling to reveal the JavaScript code just after the HTML section.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# sed -n '260,520p' scubaduck/
static/index.html
const allColumns = [];
const columnTypes = {};
const stringColumns = [];
const integerColumns = [];
const timeColumns = [];
let selectedColumns = [];
let displayType = 'samples';
let groupBy = {chips: [], addChip: () => {}, renderChips: () => {}};
function initDropdown(select) {
const wrapper = document.createElement('div');
wrapper.className = 'dropdown';
if (select.classList.contains('f-col')) {
wrapper.classList.add('f-col');
}
select.parentNode.insertBefore(wrapper, select);
wrapper.appendChild(select);
select.style.display = 'none';
const disp = document.createElement('div');
disp.className = 'dropdown-display';
function updateDisplay() {
const opt = select.options[select.selectedIndex];
disp.textContent = opt ? opt.textContent : '';
}
updateDisplay();
wrapper.appendChild(disp);
const menu = document.createElement('div');
menu.className = 'dropdown-menu';
const search = document.createElement('input');
search.placeholder = 'Search';
menu.appendChild(search);
const list = document.createElement('div');
menu.appendChild(list);
wrapper.appendChild(menu);
function close() {
menu.style.display = 'none';
}
function open() {
renderOptions();
menu.style.display = 'block';
search.focus();
}
disp.addEventListener('click', () => {
if (menu.style.display === 'block') {
close();
} else {
open();
}
});
document.addEventListener('click', e => {
if (!wrapper.contains(e.target)) {
close();
}
});
function renderOptions() {
const q = search.value.toLowerCase();
list.innerHTML = '';
Array.from(select.options).forEach(o => {
if (!o.textContent.toLowerCase().includes(q)) return;
const div = document.createElement('div');
div.className = 'option';
if (q) {
const text = o.textContent;
const idx = text.toLowerCase().indexOf(q);
if (idx !== -1) {
div.innerHTML =
text.slice(0, idx) +
'<u>' +
text.slice(idx, idx + q.length) +
'</u>' +
text.slice(idx + q.length);
} else {
div.textContent = text;
}
} else {
div.textContent = o.textContent;
}
if (o.value === select.value) div.classList.add('selected');
div.addEventListener('mousedown', evt => {
evt.preventDefault();
select.value = o.value;
select.dispatchEvent(new Event('change'));
updateDisplay();
close();
});
list.appendChild(div);
});
}
search.addEventListener('input', renderOptions);
select.addEventListener('change', updateDisplay);
}
// Sidebar resizing
const sidebar = document.getElementById('sidebar');
const sidebarResizer = document.getElementById('sidebar-resizer');
let sidebarWidth = parseInt(localStorage.getItem('sidebarWidth') || 450, 10);
sidebar.style.width = sidebarWidth + 'px';
let sidebarResize = false;
function startSidebarDrag(e) {
e.preventDefault();
sidebarResize = true;
document.addEventListener('mousemove', onSidebarDrag);
document.addEventListener('mouseup', stopSidebarDrag);
}
function onSidebarDrag(e) {
if (!sidebarResize) return;
sidebarWidth = Math.max(200, e.clientX - sidebar.getBoundingClientRect().left)
;
sidebar.style.width = sidebarWidth + 'px';
}
function stopSidebarDrag() {
document.removeEventListener('mousemove', onSidebarDrag);
document.removeEventListener('mouseup', stopSidebarDrag);
sidebarResize = false;
localStorage.setItem('sidebarWidth', sidebarWidth);
}
sidebarResizer.addEventListener('mousedown', startSidebarDrag);
...
if (g.querySelector('.col-group-header').textContent.startsWith('Strings'))
{
g.style.display = showTable || showTS ? 'none' : '';
}
});
if (showTS) {
const lim = document.getElementById('limit');
if (!lim.dataset.setByUser) {
lim.value = '7';
}
}
displayType = graphTypeSel.value;
}
orderDirBtn.addEventListener('click', () => {
orderDir = orderDir === 'ASC' ? 'DESC' : 'ASC';
updateOrderDirButton();
});
updateOrderDirButton();
graphTypeSel.addEventListener('change', updateDisplayTypeUI);
fetch('/api/columns').then(r => r.json()).then(cols => {
const orderSelect = document.getElementById('order_by');
const xAxisSelect = document.getElementById('x_axis');
const groupsEl = document.getElementById('column_groups');
const groups = {
time: {name: 'Time', cols: [], ul: null},
integer: {name: 'Integers', cols: [], ul: null},
string: {name: 'Strings', cols: [], ul: null}
};
cols.forEach(c => {
const t = c.type.toUpperCase();
columnTypes[c.name] = c.type;
allColumns.push(c.name);
let g = 'string';
if (t.includes('INT')) g = 'integer';
if (t.includes('TIMESTAMP')) {
g = 'time';
timeColumns.push(c.name);
}
groups[g].cols.push(c.name);
if (g !== 'string') {
const o = document.createElement('option');
o.value = c.name;
o.textContent = c.name;
orderSelect.appendChild(o);
}
});
timeColumns.forEach(name => {
const o = document.createElement('option');
o.value = name;
o.textContent = name;
xAxisSelect.appendChild(o);
});
Object.keys(groups).forEach(key => {
const g = groups[key];
const div = document.createElement('div');
div.className = 'col-group';
const header = document.createElement('div');
header.className = 'col-group-header';
header.appendChild(document.createTextNode(g.name + ': '));
const links = document.createElement('span');
links.className = 'links';
const allBtn = document.createElement('a');
allBtn.href = '#';
allBtn.textContent = 'All';
const noneBtn = document.createElement('a');
noneBtn.href = '#';
noneBtn.textContent = 'None';
links.appendChild(allBtn);
links.appendChild(noneBtn);
header.appendChild(links);
div.appendChild(header);
const ul = document.createElement('ul');
g.ul = ul;
g.cols.forEach(name => {
const li = document.createElement('li');
const label = document.createElement('label');
const cb = document.createElement('input');
cb.type = 'checkbox';
cb.value = name;
cb.checked = true;
cb.addEventListener('change', updateSelectedColumns);
label.appendChild(cb);
label.appendChild(document.createTextNode(' ' + name));
li.appendChild(label);
ul.appendChild(li);
});
allBtn.addEventListener('click', e => {
e.preventDefault();
ul.querySelectorAll('input').forEach(cb => (cb.checked = true));
updateSelectedColumns();
});
noneBtn.addEventListener('click', e => {
e.preventDefault();
ul.querySelectorAll('input').forEach(cb => (cb.checked = false));
updateSelectedColumns();
});
div.appendChild(ul);
groupsEl.appendChild(div);
});
document.getElementById('columns_all').addEventListener('click', e => {
e.preventDefault();
groupsEl.querySelectorAll('input').forEach(cb => (cb.checked = true));
updateSelectedColumns();
});
document.getElementById('columns_none').addEventListener('click', e => {
e.preventDefault();
groupsEl.querySelectorAll('input').forEach(cb => (cb.checked = false));
updateSelectedColumns();
});
updateSelectedColumns();
groupBy = document.getElementById('group_by').closest('.field');
initChipInput(groupBy, typed =>
allColumns.filter(c => c.toLowerCase().includes(typed.toLowerCase()))
);
initDropdown(orderSelect);
initDropdown(document.getElementById('aggregate'));
document.getElementById('limit').addEventListener('input', e => {
e.target.dataset.setByUser = '1';
});
updateDisplayTypeUI();
addFilter();
initFromUrl();
});
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'll keep going and open the remaining lines after line 520.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# sed -n '520,780p' scubaduck/
static/index.html
document.querySelectorAll('#tabs .tab').forEach(btn => {
btn.addEventListener('click', () => {
document.querySelectorAll('#tabs .tab').forEach(t => t.classList.remove('act
ive'));
document.querySelectorAll('.tab-content').forEach(c => c.classList.remove('a
ctive'));
btn.classList.add('active');
document.getElementById(btn.dataset.tab).classList.add('active');
});
});
document.querySelectorAll('.rel-btn').forEach(btn => {
btn.addEventListener('click', () => {
const dd = document.getElementById(btn.dataset.target);
const show = dd.style.display === 'none' || dd.style.display === '';
document.querySelectorAll('.rel-dropdown').forEach(d => (d.style.display = '
none'));
dd.style.display = show ? 'block' : 'none';
});
});
document.querySelectorAll('.rel-dropdown div').forEach(opt => {
opt.addEventListener('click', () => {
const box = opt.closest('.rel-box');
const input = box.querySelector('input');
input.value = opt.dataset.value || opt.textContent;
opt.parentElement.style.display = 'none';
});
});
document.addEventListener('click', e => {
document.querySelectorAll('.rel-dropdown').forEach(dd => {
if (!dd.parentElement.contains(e.target)) dd.style.display = 'none';
});
});
function updateSelectedColumns() {
const base = allColumns.filter(name => {
const cb = document.querySelector(`#column_groups input[value="${name}"]`);
if (!cb || !cb.checked) return false;
if (graphTypeSel.value === 'table' && isStringColumn(name)) return false;
return true;
});
if (graphTypeSel.value === 'table' || graphTypeSel.value === 'timeseries') {
selectedColumns = groupBy.chips.slice();
if (document.getElementById('show_hits').checked) selectedColumns.push('Hits
');
base.forEach(c => {
if (!selectedColumns.includes(c)) selectedColumns.push(c);
});
} else {
selectedColumns = base;
}
}
function isStringColumn(name) {
const t = (columnTypes[name] || '').toUpperCase();
return t.includes('CHAR') || t.includes('STRING') || t.includes('VARCHAR');
}
function isIntegerColumn(name) {
const t = (columnTypes[name] || '').toUpperCase();
return t.includes('INT');
}
function isTimeColumn(name) {
const t = (columnTypes[name] || '').toUpperCase();
return t.includes('TIMESTAMP');
}
function formatNumber(val) {
if (typeof val !== 'number') val = Number(val);
if (Number.isNaN(val)) return '';
if (val === 0) return '0';
const abs = Math.abs(val);
if (abs > 999.999) {
const units = [
{n: 1e12, s: 'T'},
{n: 1e9, s: 'B'},
{n: 1e6, s: 'M'},
{n: 1e3, s: 'K'},
];
for (const u of units) {
if (abs >= u.n) {
return (val / u.n).toFixed(2) + ' ' + u.s;
}
}
}
if (abs < 0.0005) return '0.000';
return val.toFixed(3);
}
function initChipInput(filter, fetchOptions) {
const input = filter.querySelector('.f-val');
const chipsEl = filter.querySelector('.chip-input');
const dropdown = filter.querySelector('.chip-dropdown');
const copyBtn = filter.querySelector('.chip-copy');
filter.chips = [];
filter.renderChips = renderChips;
filter.addChip = addChip;
let highlight = 0;
let dropdownLocked = false;
chipsEl.addEventListener('click', () => {
input.focus();
});
function renderChips() {
chipsEl.querySelectorAll('.chip').forEach(c => c.remove());
filter.chips.forEach((v, i) => {
const span = document.createElement('span');
span.className = 'chip';
span.textContent = v;
const x = document.createElement('span');
x.className = 'x';
x.textContent = '✖';
x.addEventListener('click', e => {
e.stopPropagation();
filter.chips.splice(i, 1);
renderChips();
input.focus();
});
span.appendChild(x);
...
function addChip(val) {
if (!val) return;
const i = filter.chips.indexOf(val);
if (i !== -1) {
filter.chips.splice(i, 1);
} else {
filter.chips.push(val);
}
input.value = '';
renderChips();
}
copyBtn.addEventListener('click', () => {
navigator.clipboard && navigator.clipboard.writeText(filter.chips.join(','))
;
});
input.addEventListener('paste', e => {
e.preventDefault();
const text = e.clipboardData.getData('text');
if (e.shiftKey) {
addChip(text.trim());
} else {
text.split(',').forEach(t => addChip(t.trim()));
}
hideDropdown();
});
input.addEventListener('keydown', e => {
if (e.key === 'ArrowDown') {
if (dropdown.style.display !== 'none') {
highlight = Math.min(highlight + 1, dropdown.children.length - 1);
updateHighlight();
}
e.preventDefault();
} else if (e.key === 'ArrowUp') {
if (dropdown.style.display !== 'none') {
highlight = Math.max(highlight - 1, 0);
updateHighlight();
}
e.preventDefault();
} else if (e.key === 'Backspace' && input.value === '') {
if (filter.chips.length > 0) {
filter.chips.pop();
renderChips();
}
} else if (e.key === 'Enter') {
if (dropdown.style.display !== 'none' && dropdown.children.length > 0) {
const val = dropdown.children[highlight].dataset.value;
if (val !== input.value.trim()) {
addChip(val);
} else {
addChip(input.value.trim());
}
} else {
addChip(input.value.trim());
}
hideDropdown();
e.preventDefault();
}
});
function renderDropdown(vals) {
dropdown.innerHTML = '';
const typed = input.value.trim();
if (typed) {
vals.splice(1, 0, typed);
}
vals.forEach((v, i) => {
const d = document.createElement('div');
d.textContent = v;
d.dataset.value = v;
d.addEventListener('mouseover', () => {
highlight = i;
updateHighlight();
});
d.addEventListener('mousedown', evt => {
evt.preventDefault();
addChip(v);
hideDropdown();
input.blur();
});
dropdown.appendChild(d);
});
if (vals.length) {
highlight = 0;
updateHighlight();
showDropdown();
} else {
hideDropdown();
}
}
function loadOptions() {
dropdownLocked = false;
if (!fetchOptions) {
dropdown.innerHTML = '';
return;
}
Promise.resolve(fetchOptions(input.value, filter)).then(values => {
renderDropdown(Array.isArray(values) ? values : []);
});
}
input.addEventListener('focus', loadOptions);
input.addEventListener('input', loadOptions);
document.addEventListener('click', evt => {
if (evt.target !== input) {
hideDropdown();
}
});
}
function addFilter() {
const container = document.createElement('div');
container.className = 'filter';
container.innerHTML = `
<div class="filter-row">
<select class="f-col"></select>
<select class="f-op"></select>
<button type="button" class="remove" onclick="this.closest('.filter').remo
ve()">✖</button>
</div>
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'll check the timeseries logic, focusing on groupby and time aggregation in the code.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# grep -n "timeseries" -n scub
aduck/static/index.html | head
114: <div id="header">sample.csv - events <select id="graph_type"><option value
="samples">Samples</option><option value="table">Table</option><option value="ti
meseries">Time Series</option></select></div>
390: const showTS = graphTypeSel.value === 'timeseries';
559: if (graphTypeSel.value === 'table' || graphTypeSel.value === 'timeseries')
{
886: if (graphTypeSel.value === 'table' || graphTypeSel.value === 'timeseries')
{
891: if (graphTypeSel.value === 'timeseries') {
909: if (params.graph_type === 'table' || params.graph_type === 'timeseries') {
914: if (params.graph_type === 'timeseries') {
1158: if (graphTypeSel.value === 'timeseries') {(scubaduck) root@8b10638fd893:/workspace/scubaduck# sed -n '870,930p' scubaduck/
static/index.html
order_by: document.getElementById('order_by').value,
order_dir: orderDir,
limit: parseInt(document.getElementById('limit').value, 10),
columns: selectedColumns.filter(c => c !== 'Hits'),
graph_type: graphTypeSel.value,
filters: Array.from(document.querySelectorAll('#filters .filter')).map(f =>
{
const chips = f.chips || [];
const op = f.querySelector('.f-op').value;
let value = null;
if (op !== 'empty' && op !== '!empty') {
value = chips.length === 0 ? null : (chips.length === 1 ? chips[0] : chi
ps);
}
const colSel = f.querySelector('.f-col select') || f.querySelector('.f-col
');
return {column: colSel.value, op, value};
})
};
if (graphTypeSel.value === 'table' || graphTypeSel.value === 'timeseries') {
payload.group_by = groupBy.chips || [];
payload.aggregate = document.getElementById('aggregate').value;
payload.show_hits = document.getElementById('show_hits').checked;
}
if (graphTypeSel.value === 'timeseries') {
payload.x_axis = document.getElementById('x_axis').value;
payload.granularity = document.getElementById('granularity').value;
payload.fill = document.getElementById('fill').value;
}
return payload;
}
function paramsToSearch(params) {
const sp = new URLSearchParams();
if (params.start) sp.set('start', params.start);
if (params.end) sp.set('end', params.end);
if (params.order_by) sp.set('order_by', params.order_by);
if (params.order_dir) sp.set('order_dir', params.order_dir);
if (params.limit !== null && params.limit !== undefined) sp.set('limit', param
s.limit);
if (params.columns && params.columns.length) sp.set('columns', params.columns.
join(','));
if (params.filters && params.filters.length) sp.set('filters', JSON.stringify(
params.filters));
if (params.graph_type) sp.set('graph_type', params.graph_type);
if (params.graph_type === 'table' || params.graph_type === 'timeseries') {
if (params.group_by && params.group_by.length) sp.set('group_by', params.gro
up_by.join(','));
if (params.aggregate) sp.set('aggregate', params.aggregate);
if (params.show_hits) sp.set('show_hits', '1');
}
if (params.graph_type === 'timeseries') {
if (params.x_axis) sp.set('x_axis', params.x_axis);
if (params.granularity) sp.set('granularity', params.granularity);
if (params.fill) sp.set('fill', params.fill);
}
const qs = sp.toString();
return qs ? '?' + qs : '';
}
function applyParams(params) {
document.getElementById('start').value = params.start || '';
document.getElementById('end').value = params.end || '';
if (params.order_by) {
document.getElementById('order_by').value = params.order_by;
}
orderDir = params.order_dir || 'ASC';
updateOrderDirButton();(scubaduck) root@8b10638fd893:/workspace/scubaduck# sed -n '930,1160p' scubaduck
/static/index.html
updateOrderDirButton();
if (params.limit !== undefined && params.limit !== null) {
document.getElementById('limit').value = params.limit;
}
graphTypeSel.value = params.graph_type || 'samples';
updateDisplayTypeUI();
if (params.x_axis) document.getElementById('x_axis').value = params.x_axis;
if (params.granularity) document.getElementById('granularity').value = params.
granularity;
if (params.fill) document.getElementById('fill').value = params.fill;
if (params.group_by) {
groupBy.chips.splice(0, groupBy.chips.length, ...params.group_by);
groupBy.renderChips();
}
if (params.aggregate) document.getElementById('aggregate').value = params.aggr
egate;
document.getElementById('show_hits').checked = params.show_hits ?? true;
document.querySelectorAll('#column_groups input').forEach(cb => {
cb.checked = !params.columns || params.columns.includes(cb.value);
});
updateSelectedColumns();
const list = document.getElementById('filter_list');
list.innerHTML = '';
if (params.filters && params.filters.length) {
params.filters.forEach(f => {
addFilter();
const el = list.lastElementChild;
const colSel = el.querySelector('.f-col select') || el.querySelector('.f-c
ol');
colSel.value = f.column;
colSel.dispatchEvent(new Event('change'));
el.querySelector('.f-op').value = f.op;
el.querySelector('.f-op').dispatchEvent(new Event('change'));
if (f.value !== null && f.op !== 'empty' && f.op !== '!empty') {
const values = Array.isArray(f.value) ? f.value : [f.value];
values.forEach(v => el.addChip(v));
el.renderChips();
}
});
} else {
addFilter();
}
}
function parseSearch() {
const sp = new URLSearchParams(window.location.search);
const params = {};
if (sp.has('start')) params.start = sp.get('start');
if (sp.has('end')) params.end = sp.get('end');
if (sp.has('order_by')) params.order_by = sp.get('order_by');
if (sp.has('order_dir')) params.order_dir = sp.get('order_dir');
if (sp.has('limit')) params.limit = parseInt(sp.get('limit'), 10);
if (sp.has('columns')) params.columns = sp.get('columns').split(',').filter(c
=> c);
if (sp.has('filters')) {
try { params.filters = JSON.parse(sp.get('filters')); } catch(e) { params.fi
lters = []; }
}
if (sp.has('graph_type')) params.graph_type = sp.get('graph_type');
if (sp.has('group_by')) params.group_by = sp.get('group_by').split(',').filter
(c => c);
if (sp.has('aggregate')) params.aggregate = sp.get('aggregate');
if (sp.has('show_hits')) params.show_hits = sp.get('show_hits') === '1';
if (sp.has('x_axis')) params.x_axis = sp.get('x_axis');
if (sp.has('granularity')) params.granularity = sp.get('granularity');
if (sp.has('fill')) params.fill = sp.get('fill');
return params;
}
function initFromUrl() {
const params = parseSearch();
history.replaceState(params, '', paramsToSearch(params));
applyParams(params);
dive(false);
}
window.addEventListener('popstate', e => {
const params = e.state || parseSearch();
applyParams(params);
dive(false);
});
let originalRows = [];
let sortState = {index: null, dir: null};
function renderTable(rows) {
const table = document.getElementById('results');
table.innerHTML = '';
if (rows.length === 0) return;
let hitsIndex = selectedColumns.indexOf('Hits');
let totalHits = 0;
if (hitsIndex !== -1) {
totalHits = rows.reduce((s, r) => s + Number(r[hitsIndex]), 0);
}
const header = document.createElement('tr');
selectedColumns.forEach((col, i) => {
const th = document.createElement('th');
let label = col;
if (
displayType === 'table' &&
col !== 'Hits' &&
!(groupBy.chips || []).includes(col)
) {
const agg = document.getElementById('aggregate').value.toLowerCase();
label += ` (${agg})`;
}
th.textContent = label;
th.dataset.index = i;
th.addEventListener('click', handleSort);
if (sortState.index === i) {
th.classList.add('sorted');
th.textContent =
label + (sortState.dir === 'desc' ? ' \u25BC' : ' \u25B2');
}
if (!isStringColumn(col)) th.style.textAlign = 'right';
header.appendChild(th);
});
table.appendChild(header);
rows.forEach(row => {
const tr = document.createElement('tr');
tr.addEventListener('click', () => {
tr.classList.toggle('selected');
});
row.forEach((v, i) => {
const col = selectedColumns[i];
const td = document.createElement('td');
if (isTimeColumn(col)) {
const d = new Date(v);
td.textContent = d.toLocaleString('en-US', {
weekday: 'short',
month: 'short',
day: 'numeric',
year: 'numeric',
hour: 'numeric',
minute: 'numeric',
second: 'numeric',
hour12: true,
timeZoneName: 'short'
});
} else {
if (col === 'Hits') {
const pct = totalHits ? ((v / totalHits) * 100).toFixed(1) : '0';
td.textContent = `${formatNumber(v)} (${pct}%)`;
} else {
td.textContent = isStringColumn(col) ? v : formatNumber(v);
}
}
td.style.textAlign = isStringColumn(col) ? 'left' : 'right';
tr.appendChild(td);
});
table.appendChild(tr);
});
// ensure table does not overflow unless necessary
const view = document.getElementById('view');
if (table.scrollWidth <= view.clientWidth) {
table.style.width = '100%';
}
}
function handleSort(e) {
const idx = parseInt(e.target.dataset.index, 10);
if (sortState.index !== idx) {
sortState.index = idx;
sortState.dir = 'asc';
} else if (sortState.dir === 'asc') {
sortState.dir = 'desc';
} else if (sortState.dir === 'desc') {
sortState.index = null;
sortState.dir = null;
} else {
sortState.dir = 'asc';
}
let rows = originalRows.slice();
if (sortState.index !== null) {
rows.sort((a, b) => {
const va = a[sortState.index];
const vb = b[sortState.index];
if (va === vb) return 0;
if (sortState.dir === 'desc') return va < vb ? 1 : -1;
return va > vb ? 1 : -1;
});
}
renderTable(rows);
}
function showTimeSeries(data) {
const view = document.getElementById('view');
if (data.rows.length === 0) {
view.innerHTML = '<p id="empty-message">Empty data provided to table</p>';
return;
}
const width = 600;
const height = 400;
view.innerHTML = '<div id="legend"></div><svg id="chart" width="' + width + '"
height="' + height + '"></svg>';
const svg = document.getElementById('chart');
const legend = document.getElementById('legend');
const groups = groupBy.chips || [];
const hasHits = document.getElementById('show_hits').checked ? 1 : 0;
const series = {};
let minX = Infinity, maxX = -Infinity, minY = Infinity, maxY = -Infinity;
data.rows.forEach(r => {
const ts = new Date(r[0]).getTime();
const key = groups.map((_, i) => r[1 + i]).join(':') || 'all';
const val = Number(r[1 + groups.length + hasHits]);
if (!series[key]) series[key] = [];
series[key].push({x: ts, y: val});
if (ts < minX) minX = ts;
if (ts > maxX) maxX = ts;
if (val < minY) minY = val;
if (val > maxY) maxY = val;
});
const colors = ['#1f77b4','#ff7f0e','#2ca02c','#d62728','#9467bd','#8c564b','#
e377c2'];
let colorIndex = 0;
const xScale = x => ((x - minX) / (maxX - minX)) * (width - 60) + 50;
const yScale = y => height - 30 - ((y - minY) / (maxY - minY)) * (height - 60)
;
Object.keys(series).forEach(key => {
const pts = series[key];
const color = colors[colorIndex++ % colors.length];
const path = pts.map((p,i)=> (i===0? 'M':'L') + xScale(p.x) + ' ' + yScale(p
.y)).join(' ');
const el = document.createElementNS('http://www.w3.org/2000/svg','path');
el.setAttribute('d', path);
el.setAttribute('fill','none');
el.setAttribute('stroke', color);
svg.appendChild(el);
const item = document.createElement('div');
item.textContent = key;
item.style.color = color;
legend.appendChild(item);
});
}
function showResults(data) {
window.lastResults = data;
const view = document.getElementById('view');
if (graphTypeSel.value === 'timeseries') {
showTimeSeries(data);
} else {
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'll review lines 1160 to 1420 in the JS file next.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# sed -n '1160,1420p' scubaduc
k/static/index.html
} else {
if (data.rows.length === 0) {
view.innerHTML =
'<p id="empty-message">Empty data provided to table</p><table id="result
s"></table>';
} else {
view.innerHTML = '<table id="results"></table>';
}
originalRows = data.rows.slice();
sortState = {index: null, dir: null};
renderTable(originalRows);
}
document.getElementById('query_info').textContent =
`Your query took about ${lastQueryTime} ms`;
}
function showError(err) {
window.lastResults = err;
const view = document.getElementById('view');
let msg = '';
if (typeof err === 'string') {
msg = err;
} else if (err) {
msg = err.error || 'Error';
if (err.sql) {
msg += '\nSQL: ' + err.sql;
}
if (err.traceback) {
msg += '\n' + err.traceback;
}
}
view.innerHTML = `<pre id="error-message">${msg}</pre>`;
document.getElementById('query_info').textContent = '';
}
function setSelectValue(selector, value) {
const el = typeof selector === 'string' ? document.querySelector(selector) : s
elector;
if (el) {
const select = el.tagName === 'SELECT' ? el : el.querySelector('select');
if (select) {
select.value = value;
select.dispatchEvent(new Event('change'));
}
}
}
</script>
</body>
</html>
(scubaduck) root@8b10638fd893:/workspace/scubaduck#The timeseries uses showTimeSeries; selected columns include groupBy, hits, and base columns. The bug happens when string columns are included in aggregators. I'll implement a fix for this by unchecked time columns.
I'll add both server and frontend tests: server for query, frontend for UI behavior.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# ls tests
__pycache__ conftest.py test_server.py test_web.pyfrom pathlib import Path
import duckdb
from scubaduck import server
import pytest
def test_basic_query() -> None:
app = server.app
client = app.test_client()
payload = {
"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_filter_multi_token() -> None:
app = server.app
client = app.test_client()
payload = {
"start": "2024-01-01 00:00:00",
"end": "2024-01-02 03:00:00",
"order_by": "timestamp",
"limit": 10,
"columns": ["timestamp", "event", "value", "user"],
"filters": [{"column": "user", "op": "=", "value": ["alice", "charlie"]}
],
}
rv = client.post(
"/api/query", data=json.dumps(payload), content_type="application/json"
)
data = rv.get_json()
assert data
rows = data["rows"]
# Should only return rows for alice and charlie
assert len(rows) == 3
assert rows[0][3] == "alice"
assert rows[-1][3] == "charlie"
def test_empty_filter_is_noop() -> None:
app = server.app
client = app.test_client()
base_payload = {
"start": "2024-01-01 00:00:00",
"end": "2024-01-03 00:00:00",
"limit": 100,
"columns": ["timestamp", "event", "value", "user"],
}
no_filter = {**base_payload, "filters": []}
empty_filter = {
**base_payload,
"filters": [{"column": "user", "op": "=", "value": None}],
}
rv1 = client.post(
"/api/query", data=json.dumps(no_filter), content_type="application/json
"
)
rv2 = client.post(
"/api/query", data=json.dumps(empty_filter), content_type="application/j
son"
)
rows1 = rv1.get_json()["rows"]
rows2 = rv2.get_json()["rows"]
assert rows1 == rows2
def test_select_columns() -> None:
app = server.app
client = app.test_client()
payload = {
"start": "2024-01-01 00:00:00",
"end": "2024-01-03 00:00:00",
"order_by": "timestamp",
"limit": 10,
"columns": ["timestamp", "user"],
"filters": [],
}
rv = client.post(
"/api/query", data=json.dumps(payload), content_type="application/json"
)
data = rv.get_json()
assert data
rows = data["rows"]
assert len(rows[0]) == 2
assert rows[0][1] == "alice"
def test_string_filter_ops() -> None:
app = server.app
client = app.test_client()
base = {
"start": "2024-01-01 00:00:00",
"end": "2024-01-03 00:00:00",
"order_by": "timestamp",
"limit": 100,
"columns": ["timestamp", "event", "value", "user"],
}
contains = {
**base,
"filters": [{"column": "user", "op": "contains", "value": "ali"}],
}
rv = client.post(
"/api/query", data=json.dumps(contains), content_type="application/json"
)
rows = rv.get_json()["rows"]
assert all("ali" in r[3] for r in rows)
regex = {
**base,
"filters": [{"column": "user", "op": "~", "value": "^a.*"}],
}
rv = client.post(
"/api/query", data=json.dumps(regex), content_type="application/json"
)
rows = rv.get_json()["rows"]
assert all(r[3].startswith("a") for r in rows)
assert len(rows) == 2
not_empty = {**base, "filters": [{"column": "user", "op": "!empty"}]}
rv = client.post(
"/api/query", data=json.dumps(not_empty), content_type="application/json
"
)
assert len(rv.get_json()["rows"]) == 4
def _make_payload() -> dict[str, object]:
return {
"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""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_group_by_table() -> None:
app = server.app
client = app.test_client()
payload = {
"start": "2024-01-01 00:00:00",
"end": "2024-01-03 00:00:00",
"graph_type": "table",
"order_by": "user",
"limit": 10,
"columns": ["value"],
"group_by": ["user"],
"aggregate": "Sum",
"show_hits": True,
}
rv = client.post(
"/api/query", data=json.dumps(payload), content_type="application/json"
)
rows = rv.get_json()["rows"]
assert rows[0][0] == "alice"
assert rows[0][1] == 2
assert rows[0][2] == 40
def test_relative_time_query(monkeypatch: pytest.MonkeyPatch) -> None:
app = server.app
client = app.test_client()
from datetime import datetime
fixed_now = datetime(2024, 1, 2, 4, 0, 0)
class FixedDateTime(datetime):
@classmethod
def now(cls, tz=None): # type: ignore[override]
return fixed_now if tz is None else fixed_now.astimezone(tz)
monkeypatch.setattr(server, "datetime", FixedDateTime)
payload = {
"start": "-1 hour",
"end": "now",
"order_by": "timestamp",
"limit": 100,
"columns": ["timestamp", "event", "value", "user"],
"filters": [],
}
rv = client.post(
"/api/query", data=json.dumps(payload), content_type="application/json"
)
data = rv.get_json()
assert rv.status_code == 200
assert len(data["rows"]) == 1
assert data["rows"][0][3] == "charlie"
def test_invalid_time_error() -> None:
app = server.app
client = app.test_client()
payload = {
"start": "nonsense",
"end": "now",
"order_by": "timestamp",
"limit": 10,
"columns": ["timestamp"],
"filters": [],
}
rv = client.post(
"/api/query", data=json.dumps(payload), content_type="application/json"
)
data = rv.get_json()
assert rv.status_code == 400
assert "error" in data
def test_query_error_returns_sql_and_traceback() -> None:
app = server.app
client = app.test_client()
payload = {
"start": "2024-01-01 00:00:00",
"end": "2024-01-03 00:00:00",
"columns": ["event"],
"group_by": ["user"],
"aggregate": "avg",
}
rv = client.post(
"/api/query", data=json.dumps(payload), content_type="application/json"
)
data = rv.get_json()
assert rv.status_code == 400
assert "error" in data
def test_table_unknown_column_error() -> None:
app = server.app
client = app.test_client()
payload = {
"start": "2024-01-01 00:00:00",
"end": "2024-01-03 00:00:00",
"graph_type": "table",
"order_by": "timestamp",
"limit": 100,
"columns": ["user", "Hits", "value"],
"group_by": ["user"],
"aggregate": "Count",
"show_hits": True,
}
rv = client.post(
"/api/query", data=json.dumps(payload), content_type="application/json"
)
data = rv.get_json()
assert rv.status_code == 400
assert "Unknown column" in data["error"]
def test_samples_view_rejects_group_by() -> None:
app = server.app
client = app.test_client()
payload = {
"graph_type": "samples",
"group_by": ["user"],
"columns": ["timestamp"],
}
rv = client.post(
"/api/query", data=json.dumps(payload), content_type="application/json"
)
data = rv.get_json()data = rv.get_json()
assert rv.status_code == 400
assert "only valid" in data["error"]
def test_table_avg_with_timestamp() -> None:
app = server.app
client = app.test_client()
payload = {
"start": "2024-01-01 00:00:00",
"end": "2024-01-03 00:00:00",
"graph_type": "table",
"order_by": "user",
"limit": 100,
"columns": ["user", "timestamp", "value"],
"group_by": ["user"],
}
rv = client.post(
"/api/query", data=json.dumps(payload), content_type="application/json"
)
data = rv.get_json()
assert rv.status_code == 200
assert "error" not in data
rows = data["rows"]
assert rows[0][0] == "alice"
from dateutil import parser
ts = parser.parse(rows[0][1]).replace(tzinfo=None)
assert ts == parser.parse("2024-01-01 12:00:00")
def test_timeseries_basic() -> None:
app = server.app
client = app.test_client()
payload = {
"start": "2024-01-01 00:00:00",
"end": "2024-01-03 00:00:00",
"graph_type": "timeseries",
"limit": 100,
"group_by": ["user"],
"aggregate": "Count",
"columns": ["value"],
"x_axis": "timestamp",
"granularity": "1 day",
}
rv = client.post(
"/api/query", data=json.dumps(payload), content_type="application/json"
)
data = rv.get_json()
assert rv.status_code == 200
assert len(data["rows"]) == 4
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'll go through the remaining tests to see how everything looks.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# sed -n '640,960p' tests/test
_server.py
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I found that when group_by is empty, the aggregator still applies, causing errors on non-numeric columns. I'll fix this by validating the aggregator before applying it, even when there’s no group_by.
To avoid binder errors, I'll uncheck string columns by default in the timeseries view.
To avoid errors, I'll modify the server to validate aggregator usage and uncheck time columns by default.
)
def run_query(
page: Any,
url: str,
*,
start: str | None = None,
end: str | None = None,
order_by: str | None = None,
order_dir: str | None = "ASC",
limit: int | None = None,
group_by: list[str] | None = None,
aggregate: str | None = None,
) -> dict[str, Any]:
page.goto(url)
page.wait_for_selector("#order_by option", state="attached")
page.wait_for_selector("#order_dir", state="attached")
page.wait_for_function("window.lastResults !== undefined")
if start is not None:
page.fill("#start", start)
if end is not None:
page.fill("#end", end)
if order_by is not None:
select_value(page, "#order_by", order_by)
if order_dir is not None and order_dir == "DESC":
page.click("#order_dir")
if limit is not None:
page.fill("#limit", str(limit))
if group_by is not None:
select_value(page, "#graph_type", "table")
page.evaluate(
"g => { groupBy.chips = g; groupBy.renderChips(); }",
group_by,
)
if aggregate is not None:
select_value(page, "#graph_type", "table")
select_value(page, "#aggregate", aggregate)
page.evaluate("window.lastResults = undefined")
page.click("text=Dive")
page.wait_for_function("window.lastResults !== undefined")
return page.evaluate("window.lastResults")
def test_range_filters(page: Any, server_url: str) -> None:
data = run_query(
page,
server_url,
start="2024-01-02 00:00:00",
end="2024-01-02 04:00:00",
order_by="timestamp",
limit=100,
)
assert len(data["rows"]) == 2
from dateutil import parser
timestamps = [parser.parse(row[0]).replace(tzinfo=None) for row in data["row
s"]]
assert timestamps == [
parser.parse("2024-01-02 00:00:00"),
parser.parse("2024-01-02 03:00:00"),
]
def test_order_by(page: Any, server_url: str) -> None:
data = run_query(
page,
server_url,
start="2024-01-01 00:00:00",
end="2024-01-03 00:00:00",
order_by="value",
order_dir="DESC",
limit=100,
)
values = [row[2] for row in data["rows"]]
assert values == sorted(values, reverse=True)
def test_limit(page: Any, server_url: str) -> None:
data = run_query(
page,
server_url,
start="2024-01-01 00:00:00",
end="2024-01-03 00:00:00",
order_by="timestamp",
limit=2,
)
assert len(data["rows"]) == 2
def test_simple_filter(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#order_by option", state="attached")
page.click("text=Add Filter")
filter_el = page.query_selector("#filters .filter:last-child")
assert filter_el
page.evaluate(
"arg => setSelectValue(arg.el.querySelector('.f-col'), arg.val)",
{"el": filter_el, "val": "user"},
)
val_input = filter_el.query_selector(".f-val")
val_input.click()
page.keyboard.type("alice")
page.keyboard.press("Enter")
page.click("text=Dive")
page.wait_for_function("window.lastResults !== undefined")
data = page.evaluate("window.lastResults")
assert len(data["rows"]) == 2
assert all(row[3] == "alice" for row in data["rows"])
def test_default_filter_and_layout(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#order_by option", state="attached")
count = page.evaluate("document.querySelectorAll('#filters .filter').length"
)
assert count == 1
last_is_button = page.evaluate(
"document.querySelector('#filters').lastElementChild.id === 'add_filter'
"
)
assert last_is_button
position = page.evaluate(
"getComputedStyle(document.querySelector('#filters .filter button.remove
')).position"
)
assert position == "static"
def test_filter_remove_alignment(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#order_by option", state="attached")
diff = page.evaluate(
"() => { const r=document.querySelector('#filters .filter-row').getBound
ingClientRect(); const x=document.querySelector('#filters .filter-row button.rem
ove').getBoundingClientRect(); return Math.abs(r.right - x.right); }"
)
assert diff <= 1
def test_header_and_tabs(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#order_by option", state="attached")
header = page.text_content("#header")
assert "sample.csv" in header
assert "events" in header
assert page.is_visible("#settings")
assert page.is_hidden("#columns")
page.click("text=Columns")
assert page.is_visible("#columns")
cols = [c.strip() for c in page.locator("#column_groups li").all_inner_texts
()]
assert "timestamp" in cols
assert "event" in cols
page.click("text=View Settings")
assert page.is_visible("#settings")
btn_color = page.evaluate(
"getComputedStyle(document.querySelector('#dive')).backgroundColor"
)
assert "rgb(0, 128, 0)" == btn_color
sidebar_overflow = page.evaluate(
"getComputedStyle(document.querySelector('#sidebar')).overflowY"
)
view_overflow = page.evaluate(
"getComputedStyle(document.querySelector('#view')).overflowY"
)
assert sidebar_overflow == "auto"
assert view_overflow == "auto"
def test_graph_type_table_fields(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#graph_type", state="attached")
select_value(page, "#graph_type", "table")
assert page.is_visible("#group_by_field")
assert page.is_visible("#aggregate_field")
assert page.is_visible("#show_hits_field")
page.click("text=Columns")
assert not page.is_visible("text=Strings:")
def test_graph_type_timeseries_fields(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#graph_type", state="attached")
select_value(page, "#graph_type", "timeseries")
assert page.is_visible("#group_by_field")
assert page.is_visible("#aggregate_field")
assert page.is_visible("#x_axis_field")
assert page.is_visible("#granularity_field")
assert page.is_visible("#fill_field")
def test_help_and_alignment(page: Any, server_url: str) -> None:
page.goto(server_url))
assert text_align == "right"
def test_table_sorting(page: Any, server_url: str) -> None:
run_query(
page,
server_url,
start="2024-01-01 00:00:00",
end="2024-01-03 00:00:00",
order_by="timestamp",
order_dir="ASC",
limit=100,
)
# header alignment
align = page.evaluate(
"getComputedStyle(document.querySelector('#results th')).textAlign"
)
assert align == "right"
header = page.locator("#results th").nth(3)
def values() -> list[str]:
return page.locator("#results td:nth-child(4)").all_inner_texts()
orig_rows = values()
assert orig_rows == ["alice", "bob", "alice", "charlie"]
first_sql = page.evaluate("window.lastResults.sql")
header.click()
assert values() == sorted(orig_rows)
assert header.inner_text().endswith("▲")
color = page.evaluate(
"getComputedStyle(document.querySelector('#results th:nth-child(4)')).co
lor"
)
assert "0, 0, 255" in color
assert page.evaluate("window.lastResults.sql") == first_sql
header.click()
assert values() == sorted(orig_rows, reverse=True)
assert header.inner_text().endswith("▼")
header.click()
assert values() == orig_rows
assert header.inner_text() == "user"
color = page.evaluate(
"getComputedStyle(document.querySelector('#results th:nth-child(4)')).co
lor"
)
assert "0, 0, 255" not in color
def test_relative_dropdown(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#order_by option", state="attached")
btn = page.query_selector('[data-target="start-select"]')
assert btn
btn.click()
page.click("#start-select div:text('-3 hours')")
assert page.input_value("#start") == "-3 hours"
def test_end_dropdown_now(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#order_by option", state="attached")
page.click('[data-target="end-select"]')
page.click("#end-select div:text('now')")
assert page.input_value("#end") == "now"
def test_invalid_time_error_shown(page: Any, server_url: str) -> None:
data = run_query(
page,
server_url,
start="nonsense",
end="now",
order_by="timestamp",
)
assert "error" in data
msg = page.text_content("#view")
assert "nonsense" in msg
def test_table_avg_group_by(page: Any, server_url: str) -> None:
data = run_query(
page,
server_url,
start="2024-01-01 00:00:00",
end="2024-01-03 00:00:00",
order_by="timestamp",
group_by=["user"],
aggregate="Avg",
)
assert "error" not in data
assert len(data["rows"]) == 3
def test_column_toggle_and_selection(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#order_by option", state="attached")
page.click("text=Columns")
page.wait_for_selector("#column_groups input", state="attached")
count = page.evaluate(
"document.querySelectorAll('#column_groups input:checked').length"
)
assert count == 4
page.click("#columns_none")
count = page.evaluate(
"document.querySelectorAll('#column_groups input:checked').length"
)
assert count == 0
page.click("#columns_all")
count = page.evaluate(
"document.querySelectorAll('#column_groups input:checked').length"
)
assert count == 4
page.uncheck("#column_groups input[value='value']")
page.click("text=View Settings")
page.fill("#start", "2024-01-01 00:00:00")
page.fill("#end", "2024-01-02 00:00:00")
select_value(page, "#order_by", "timestamp")
page.fill("#limit", "10")
page.evaluate("window.lastResults = undefined")
page.click("text=Dive")
page.wait_for_function("window.lastResults !== undefined")
data = page.evaluate("window.lastResults")
assert len(data["rows"][0]) == 3
headers = page.locator("#results th").all_inner_texts()
assert "value" not in headers
def test_columns_links_alignment(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#order_by option", state="attached")
page.click("text=Columns")
page.wait_for_selector("#column_groups input", state="attached")
tag = page.evaluate("document.getElementById('columns_all').tagName")
assert tag == "A"
align = page.evaluate(
"getComputedStyle(document.querySelector('#column_actions')).textAlign"
)
assert align == "right"
def test_column_group_links(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#order_by option", state="attached")
page.click("text=Columns")
page.wait_for_selector("#column_groups a", state="attached")
tag = page.evaluate("document.querySelector('#column_groups .col-group a').t
agName")
assert tag == "A"
def test_column_group_links_float_right(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#order_by option", state="attached")
page.click("text=Columns")
page.wait_for_selector("#column_groups .col-group .links", state="attached")
float_val = page.evaluate(
"getComputedStyle(document.querySelector('#column_groups .col-group .lin
ks')).float"
)
assert float_val == "right"
def test_chip_dropdown_navigation(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#order_by option", state="attached")
page.click("text=Add Filter")
f = page.query_selector("#filters .filter:last-child")
assert f
page.evaluate(
"arg => setSelectValue(arg.el.querySelector('.f-col'), arg.val)",
{"el": f, "val": "user"},
)
inp = f.query_selector(".f-val")
inp.click()
page.wait_for_selector("#filters .filter:last-child .chip-dropdown div")
page.keyboard.type("ali")
page.wait_for_selector("text=alice")
page.keyboard.press("ArrowDown")
page.keyboard.press("Enter")
chips = page.evaluate(
"Array.from(document.querySelectorAll('#filters .filter:last-child .chip
')).map(c => c.firstChild.textContent)"
)
assert chips == ["ali"]
page.click("#filters .filter:last-child .chip .x")
page.wait_for_selector(".chip", state="detached")inp = f.query_selector(".f-val")
inp.click()
page.keyboard.type("alice")
page.keyboard.press("Enter")
inp.click()
page.keyboard.type("bob")
page.keyboard.press("Enter")
f.query_selector(".chip-copy").click()
assert page.evaluate("navigator.clipboard._data") == "alice,bob"
page.evaluate(
"var f=document.querySelector('#filters .filter:last-child'); f.chips=[]
; f.querySelectorAll('.chip').forEach(c=>c.remove())"
)
page.wait_for_selector("#filters .chip", state="detached")
inp.click()
page.evaluate(
"var dt=new DataTransfer(); dt.setData('text/plain','alice,bob'); var e=
new ClipboardEvent('paste',{clipboardData:dt}); document.querySelector('#filters
.filter:last-child .f-val').dispatchEvent(e);"
)
chips = page.evaluate(
"Array.from(document.querySelectorAll('#filters .filter:last-child .chip
')).map(c => c.firstChild.textContent)"
)
assert chips[:2] == ["alice", "bob"]
page.evaluate(
"var f=document.querySelector('#filters .filter:last-child'); f.chips=[]
; f.querySelectorAll('.chip').forEach(c=>c.remove())"
)
page.wait_for_selector("#filters .chip", state="detached")
inp.click()
page.evaluate(
"var dt=new DataTransfer(); dt.setData('text/plain','alice,bob'); var e=
new ClipboardEvent('paste',{clipboardData:dt}); Object.defineProperty(e,'shiftKe
y',{value:true}); document.querySelector('#filters .filter:last-child .f-val').d
ispatchEvent(e);"
)
chips = page.evaluate(
"Array.from(document.querySelectorAll('#filters .filter:last-child .chip
')).map(c => c.firstChild.textContent)"
)
assert chips[-1] == "alice,bob"
def test_chip_dropdown_hides_on_outside_click(page: Any, server_url: str) -> Non
e:
page.goto(server_url)
page.wait_for_selector("#order_by option", state="attached")
page.click("text=Add Filter")
f = page.query_selector("#filters .filter:last-child")
assert f
page.evaluate(
"arg => setSelectValue(arg.el.querySelector('.f-col'), arg.val)",
{"el": f, "val": "user"},
)
inp = f.query_selector(".f-val")
inp.click()
page.wait_for_selector("#filters .filter:last-child .chip-dropdown div")
page.click("#header")
page.wait_for_selector("#filters .filter:last-child .chip-dropdown", state="
hidden")
def test_chip_input_no_outline(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#order_by option", state="attached")
page.click("text=Add Filter")
inp = page.query_selector("#filters .filter:last-child .f-val")
assert inp
inp.click()
outline = page.evaluate(
"getComputedStyle(document.querySelector('#filters .filter:last-child .f
-val')).outlineStyle"
)
assert outline == "none"
def test_chip_enter_keeps_focus(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#order_by option", state="attached")
page.click("text=Add Filter")
f = page.query_selector("#filters .filter:last-child")
assert f
page.evaluate(
"arg => setSelectValue(arg.el.querySelector('.f-col'), arg.val)",
{"el": f, "val": "user"},
)
inp = f.query_selector(".f-val")
inp.click()
page.wait_for_selector("#filters .filter:last-child .chip-dropdown")
page.keyboard.type("alice")
page.keyboard.press("Enter")
focused = page.evaluate(
"document.activeElement === document.querySelector('#filters .filter:las
t-child .f-val')"
)
assert focused
visible = page.evaluate(
"getComputedStyle(document.querySelector('#filters .filter:last-child .c
hip-dropdown')).display"
)
assert visible == "none"
def test_chip_delete_keeps_focus(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#order_by option", state="attached")
page.click("text=Add Filter")
f = page.query_selector("#filters .filter:last-child")
assert f
page.evaluate(
"arg => setSelectValue(arg.el.querySelector('.f-col'), arg.val)",
{"el": f, "val": "user"},
)
inp = f.query_selector(".f-val")
inp.click()
page.wait_for_selector("#filters .filter:last-child .chip-dropdown")
page.keyboard.type("alice")
page.keyboard.press("Enter")
page.keyboard.type("b")
page.wait_for_selector("#filters .filter:last-child .chip-dropdown")
f.query_selector(".chip .x").click()
page.wait_for_selector("#filters .filter:last-child .chip", state="detached"
)
...
end="2024-01-02 00:00:00",
order_by="timestamp",
limit=1,
)
cell = page.text_content("#results td")
assert cell != "Invalid Date"
valid = page.evaluate("v => !isNaN(Date.parse(v))", cell)
assert valid
def test_url_query_persistence(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#order_by option", state="attached")
page.wait_for_function("window.lastResults !== undefined")
page.fill("#start", "2024-01-01 00:00:00")
page.fill("#end", "2024-01-02 00:00:00")
page.fill("#limit", "1")
page.evaluate("window.lastResults = undefined")
page.click("text=Dive")
page.wait_for_function("window.lastResults !== undefined")
first_url = page.url
first_rows = page.evaluate("window.lastResults.rows.length")
page.fill("#limit", "2")
page.evaluate("window.lastResults = undefined")
page.click("text=Dive")
page.wait_for_function("window.lastResults !== undefined")
second_url = page.url
second_rows = page.evaluate("window.lastResults.rows.length")
assert second_rows != first_rows
assert first_url != second_url
page.go_back()
page.wait_for_function("window.lastResults !== undefined")
assert page.url == first_url
assert page.evaluate("window.lastResults.rows.length") == first_rows
def test_load_from_url(page: Any, server_url: str) -> None:
url = (
f"{server_url}?start=2024-01-01%2000:00:00&end=2024-01-02%2000:00:00"
"&order_by=timestamp&limit=2"
)
page.goto(url)
page.wait_for_selector("#order_by option", state="attached")
page.wait_for_function("window.lastResults !== undefined")
assert page.input_value("#start") == "2024-01-01 00:00:00"
assert page.input_value("#end") == "2024-01-02 00:00:00"
assert page.input_value("#limit") == "2"
assert page.evaluate("window.lastResults.rows.length") == 2
def test_empty_data_message(page: Any, server_url: str) -> None:
data = run_query(
page,
server_url,
start="2025-01-01 00:00:00",
end="2025-01-02 00:00:00",
order_by="timestamp",
limit=100,
)
assert data["rows"] == []
msg = page.text_content("#view")
assert "Empty data provided to table" in msg
def test_group_by_chip_from_url(page: Any, server_url: str) -> None:
url = f"{server_url}?graph_type=table&group_by=user&order_by=user&limit=10"
page.goto(url)
page.wait_for_selector("#group_by_field .chip", state="attached")
chips = page.evaluate(
"Array.from(document.querySelectorAll('#group_by_field .chip')).map(c =>
c.firstChild.textContent)"
)
assert chips == ["user"]
def test_group_by_autocomplete(page: Any, server_url: str) -> None:
page.goto(f"{server_url}?graph_type=table")
page.wait_for_selector("#group_by_field", state="visible")
inp = page.query_selector("#group_by_field .f-val")
assert inp
inp.click()
page.keyboard.type("us")
page.wait_for_selector("#group_by_field .chip-dropdown div")
options = page.locator("#group_by_field .chip-dropdown div").all_inner_texts
()
assert "user" in options
def test_group_by_copy_icon(page: Any, server_url: str) -> None:
page.goto(f"{server_url}?graph_type=table")
page.wait_for_selector("#group_by_field", state="visible")
icon = page.text_content("#group_by_field .chip-copy")
assert icon == "⎘"
def test_group_by_input_no_border(page: Any, server_url: str) -> None:
page.goto(f"{server_url}?graph_type=table")
page.wait_for_selector("#group_by_field", state="visible")
border = page.evaluate(
"getComputedStyle(document.querySelector('#group_by_field .f-val')).bord
erStyle"
)
assert border == "none"
def test_table_group_by_query(page: Any, server_url: str) -> None:
data = run_query(
page,
server_url,
start="2024-01-01 00:00:00",
end="2024-01-03 00:00:00",
order_by="timestamp",
limit=100,
group_by=["user"],
aggregate="Count",
)
assert "error" not in data
assert len(data["rows"]) == 3
def test_table_avg_no_group_by(page: Any, server_url: str) -> None:
data = run_query(
(scubaduck) root@8b10638fd893:/workspace/scubaduck#data = run_query(
page,
server_url,
aggregate="Avg",
)
assert len(data["rows"]) == 1
row = data["rows"][0]
assert row[0] == 4
from dateutil import parser
ts = parser.parse(row[1]).replace(tzinfo=None)
assert ts == parser.parse("2024-01-01 13:00:00")
assert row[2] == 25
def test_table_headers_show_aggregate(page: Any, server_url: str) -> None:
run_query(
page,
server_url,
aggregate="Avg",
)
headers = page.locator("#results th").all_inner_texts()
assert "Hits" in headers
assert "timestamp (avg)" in headers
assert "value (avg)" in headers
def test_format_number_function(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#order_by option", state="attached")
vals = page.evaluate(
"() => [formatNumber(815210), formatNumber(999.999), formatNumber(0.0004
), formatNumber(0)]"
)
assert vals == ["815.21 K", "999.999", "0.000", "0"]
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'll check the rest of test_web from line 1120 to the end.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# sed -n '1120,1600p' tests/te
st_web.py
(scubaduck) root@8b10638fd893:/workspace/scubaduck#Tests seem to end earlier, but I should confirm the file length is around 1200 lines.
833 tests/test_web.py
(scubaduck) root@8b10638fd893:/workspace/scubaduck#Looks like the file has 833 lines, not thousands. Let's search for timeseries tests.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# grep -n "timeseries" -n test
s/test_web.py | head
188:def test_graph_type_timeseries_fields(page: Any, server_url: str) -> None:
191: select_value(page, "#graph_type", "timeseries")(scubaduck) root@8b10638fd893:/workspace/scubaduck# grep -n "showTimeSeries" -n
tests/test_web.py
(scubaduck) root@8b10638fd893:/workspace/scubaduck#The bug happens when switching to Time Series with an incorrect 'avg' aggregator on a string column. I'll fix that by checking when an aggregator is 'avg' with numeric or time columns. I'll implement a server-side test for this and fix the frontend to defaults to numeric columns only when switching to timeseries.
I'll test the server's response for timeseries requests with ‘avg’ aggregator on a string column, expecting a 400 error. The default UI will also be updated to prevent errors from triggering by default.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# grep -n "test_table_avg_no_g
roup_by" -n tests/test_web.py
799:def test_table_avg_no_group_by(page: Any, server_url: str) -> None:page.keyboard.type("us")
page.wait_for_selector("#group_by_field .chip-dropdown div")
options = page.locator("#group_by_field .chip-dropdown div").all_inner_texts
()
assert "user" in options
def test_group_by_copy_icon(page: Any, server_url: str) -> None:
page.goto(f"{server_url}?graph_type=table")
page.wait_for_selector("#group_by_field", state="visible")
icon = page.text_content("#group_by_field .chip-copy")
assert icon == "⎘"
def test_group_by_input_no_border(page: Any, server_url: str) -> None:
page.goto(f"{server_url}?graph_type=table")
page.wait_for_selector("#group_by_field", state="visible")
border = page.evaluate(
"getComputedStyle(document.querySelector('#group_by_field .f-val')).bord
erStyle"
)
assert border == "none"
def test_table_group_by_query(page: Any, server_url: str) -> None:
data = run_query(
page,
server_url,
start="2024-01-01 00:00:00",
end="2024-01-03 00:00:00",
order_by="timestamp",
limit=100,
group_by=["user"],
aggregate="Count",
)
assert "error" not in data
assert len(data["rows"]) == 3
def test_table_avg_no_group_by(page: Any, server_url: str) -> None:
data = run_query(
page,
server_url,
aggregate="Avg",
)
assert len(data["rows"]) == 1
row = data["rows"][0]
assert row[0] == 4
from dateutil import parser
ts = parser.parse(row[1]).replace(tzinfo=None)
assert ts == parser.parse("2024-01-01 13:00:00")
assert row[2] == 25
def test_table_headers_show_aggregate(page: Any, server_url: str) -> None:
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I see 'test_table_avg_no_group_by' uses aggregate="Avg" but group_by=None. I'll add a test to check the default columns when switching to timeseries; specifically to ensure time columns aren't checked by default.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# grep -n "time series" -n tes
ts/test_web.py
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'll add a test for the timeseries scenario by checking default settings and initialization.
baduck/static/index.html
518: initFromUrl();
993:function initFromUrl() {/static/index.html
if (sp.has('filters')) {
try { params.filters = JSON.parse(sp.get('filters')); } catch(e) { params.fi
lters = []; }
}
if (sp.has('graph_type')) params.graph_type = sp.get('graph_type');
if (sp.has('group_by')) params.group_by = sp.get('group_by').split(',').filter
(c => c);
if (sp.has('aggregate')) params.aggregate = sp.get('aggregate');
if (sp.has('show_hits')) params.show_hits = sp.get('show_hits') === '1';
if (sp.has('x_axis')) params.x_axis = sp.get('x_axis');
if (sp.has('granularity')) params.granularity = sp.get('granularity');
if (sp.has('fill')) params.fill = sp.get('fill');
return params;
}
function initFromUrl() {
const params = parseSearch();
history.replaceState(params, '', paramsToSearch(params));
applyParams(params);
dive(false);
}
window.addEventListener('popstate', e => {
const params = e.state || parseSearch();
applyParams(params);
dive(false);
});
let originalRows = [];
let sortState = {index: null, dir: null};
function renderTable(rows) {
const table = document.getElementById('results');
table.innerHTML = '';
if (rows.length === 0) return;
let hitsIndex = selectedColumns.indexOf('Hits');
let totalHits = 0;
if (hitsIndex !== -1) {
totalHits = rows.reduce((s, r) => s + Number(r[hitsIndex]), 0);
}
const header = document.createElement('tr');
selectedColumns.forEach((col, i) => {
const th = document.createElement('th');
let label = col;
if (
displayType === 'table' &&
col !== 'Hits' &&
!(groupBy.chips || []).includes(col)
) {
const agg = document.getElementById('aggregate').value.toLowerCase();
label += ` (${agg})`;
}
th.textContent = label;
th.dataset.index = i;
th.addEventListener('click', handleSort);
if (sortState.index === i) {
th.classList.add('sorted');
th.textContent =
label + (sortState.dir === 'desc' ? ' \u25BC' : ' \u25B2');
}
if (!isStringColumn(col)) th.style.textAlign = 'right';
header.appendChild(th);
});
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I see I can replicate the timeseries_basic test from test_server.py to trigger the issue.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# grep -n "timeseries" -n test
s/test_server.py
351:def test_timeseries_basic() -> None:
357: "graph_type": "timeseries",(scubaduck) root@8b10638fd893:/workspace/scubaduck# sed -n '348,376p' tests/test
_server.py
assert ts == parser.parse("2024-01-01 12:00:00")
def test_timeseries_basic() -> None:
app = server.app
client = app.test_client()
payload = {
"start": "2024-01-01 00:00:00",
"end": "2024-01-03 00:00:00",
"graph_type": "timeseries",
"limit": 100,
"group_by": ["user"],
"aggregate": "Count",
"columns": ["value"],
"x_axis": "timestamp",
"granularity": "1 day",
}
rv = client.post(
"/api/query", data=json.dumps(payload), content_type="application/json"
)
data = rv.get_json()
assert rv.status_code == 200
assert len(data["rows"]) == 4
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I’ll add a server test for a timeseries query with string columns and "avg" aggregator.
" -n scubaduck/static/index.html
388:function updateDisplayTypeUI() {
415:graphTypeSel.addEventListener('change', updateDisplayTypeUI);
516: updateDisplayTypeUI();
935: updateDisplayTypeUI();(scubaduck) root@8b10638fd893:/workspace/scubaduck# sed -n '380,420p' scubaduck/
static/index.html
sidebarResizer.addEventListener('mousedown', startSidebarDrag);
let orderDir = 'ASC';
const orderDirBtn = document.getElementById('order_dir');
const graphTypeSel = document.getElementById('graph_type');
function updateOrderDirButton() {
orderDirBtn.textContent = orderDir + (orderDir === 'ASC' ? ' \u25B2' : ' \u25B
C');
}
function updateDisplayTypeUI() {
const showTable = graphTypeSel.value === 'table';
const showTS = graphTypeSel.value === 'timeseries';
document.getElementById('group_by_field').style.display = showTable || showTS
? 'flex' : 'none';
document.getElementById('aggregate_field').style.display = showTable || showTS
? 'flex' : 'none';
document.getElementById('show_hits_field').style.display = showTable ? 'flex'
: 'none';
document.getElementById('x_axis_field').style.display = showTS ? 'flex' : 'non
e';
document.getElementById('granularity_field').style.display = showTS ? 'flex' :
'none';
document.getElementById('fill_field').style.display = showTS ? 'flex' : 'none'
;
document.querySelectorAll('#column_groups .col-group').forEach(g => {
if (g.querySelector('.col-group-header').textContent.startsWith('Strings'))
{
g.style.display = showTable || showTS ? 'none' : '';
}
});
if (showTS) {
const lim = document.getElementById('limit');
if (!lim.dataset.setByUser) {
lim.value = '7';
}
}
displayType = graphTypeSel.value;
}
orderDirBtn.addEventListener('click', () => {
orderDir = orderDir === 'ASC' ? 'DESC' : 'ASC';
updateOrderDirButton();
});
updateOrderDirButton();
graphTypeSel.addEventListener('change', updateDisplayTypeUI);
fetch('/api/columns').then(r => r.json()).then(cols => {
const orderSelect = document.getElementById('order_by');
const xAxisSelect = document.getElementById('x_axis');
const groupsEl = document.getElementById('column_groups');
const groups = {(scubaduck) root@8b10638fd893:/workspace/scubaduck# sed -n '420,520p' scubaduck/
static/index.html
const groups = {
time: {name: 'Time', cols: [], ul: null},
integer: {name: 'Integers', cols: [], ul: null},
string: {name: 'Strings', cols: [], ul: null}
};
cols.forEach(c => {
const t = c.type.toUpperCase();
columnTypes[c.name] = c.type;
allColumns.push(c.name);
let g = 'string';
if (t.includes('INT')) g = 'integer';
if (t.includes('TIMESTAMP')) {
g = 'time';
timeColumns.push(c.name);
}
groups[g].cols.push(c.name);
if (g !== 'string') {
const o = document.createElement('option');
o.value = c.name;
o.textContent = c.name;
orderSelect.appendChild(o);
}
});
timeColumns.forEach(name => {
const o = document.createElement('option');
o.value = name;
o.textContent = name;
xAxisSelect.appendChild(o);
});
Object.keys(groups).forEach(key => {
const g = groups[key];
const div = document.createElement('div');
div.className = 'col-group';
const header = document.createElement('div');
header.className = 'col-group-header';
header.appendChild(document.createTextNode(g.name + ': '));
const links = document.createElement('span');
links.className = 'links';
const allBtn = document.createElement('a');
allBtn.href = '#';
allBtn.textContent = 'All';
const noneBtn = document.createElement('a');
noneBtn.href = '#';
noneBtn.textContent = 'None';
links.appendChild(allBtn);
links.appendChild(noneBtn);
header.appendChild(links);
div.appendChild(header);
const ul = document.createElement('ul');
g.ul = ul;
g.cols.forEach(name => {
const li = document.createElement('li');
const label = document.createElement('label');
const cb = document.createElement('input');
cb.type = 'checkbox';
cb.value = name;
cb.checked = true;
cb.addEventListener('change', updateSelectedColumns);
label.appendChild(cb);
label.appendChild(document.createTextNode(' ' + name));
li.appendChild(label);
ul.appendChild(li);
});
allBtn.addEventListener('click', e => {
e.preventDefault();
ul.querySelectorAll('input').forEach(cb => (cb.checked = true));
updateSelectedColumns();
});
noneBtn.addEventListener('click', e => {
e.preventDefault();
ul.querySelectorAll('input').forEach(cb => (cb.checked = false));
updateSelectedColumns();
});
div.appendChild(ul);
groupsEl.appendChild(div);
});
document.getElementById('columns_all').addEventListener('click', e => {
e.preventDefault();
groupsEl.querySelectorAll('input').forEach(cb => (cb.checked = true));
updateSelectedColumns();
});
document.getElementById('columns_none').addEventListener('click', e => {
e.preventDefault();
groupsEl.querySelectorAll('input').forEach(cb => (cb.checked = false));
updateSelectedColumns();
});
updateSelectedColumns();
groupBy = document.getElementById('group_by').closest('.field');
initChipInput(groupBy, typed =>
allColumns.filter(c => c.toLowerCase().includes(typed.toLowerCase()))
);
initDropdown(orderSelect);
initDropdown(document.getElementById('aggregate'));
document.getElementById('limit').addEventListener('input', e => {
e.target.dataset.setByUser = '1';
});
updateDisplayTypeUI();
addFilter();
initFromUrl();
});
(scubaduck) root@8b10638fd893:/workspace/scubaduck#When switching to time series, I’ll uncheck time columns by default to align with the requirement.
To avoid errors, I’ll uncheck non-numeric columns when switching to the time series view.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# cat scubaduck/sample.csv | h
ead
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@8b10638fd893:/workspace/scubaduck#The user expects to see a graph, but string columns cause errors. I'll adjust defaults.
The fix is to uncheck event, user, and time columns for timeseries graphs.
To prevent errors, I'll uncheck string columns and add server-side validation when switching to timeseries.
I'll improve checks for timeseries and non-grouped queries while preserving aggregation behavior.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# sed -n '312,420p' scubaduck/
server.py
if params.graph_type not in {"table", "timeseries"} and (
params.group_by or params.aggregate or params.show_hits
):
return (
jsonify(
{
"error": "group_by, aggregate and show_hits are only val
id for table or timeseries view"
}
),
400,
)
valid_cols = set(column_types.keys())
if params.graph_type == "timeseries":
if params.x_axis is None:
for cand in ["time", "timestamp"]:
if cand in valid_cols:
params.x_axis = cand
break
if params.x_axis is None or params.x_axis not in valid_cols:
return jsonify({"error": "Invalid x_axis"}), 400
ctype = column_types.get(params.x_axis, "").upper()
if not any(t in ctype for t in ["TIMESTAMP", "DATE", "TIME"]):
return jsonify({"error": "x_axis must be a time column"}), 400
for col in params.columns:
if col not in valid_cols:
return jsonify({"error": f"Unknown column: {col}"}), 400
for col in params.group_by:
if col not in valid_cols:
return jsonify({"error": f"Unknown column: {col}"}), 400
if params.order_by and params.order_by not in valid_cols:
return jsonify({"error": f"Unknown column: {params.order_by}"}), 400
if params.group_by:
agg = (params.aggregate or "avg").lower()
if agg.startswith("p") or agg == "sum":
need_numeric = True
allow_time = False
elif agg == "avg" or agg in {"min", "max"}:
need_numeric = False
allow_time = True
else:
need_numeric = False
allow_time = False
if need_numeric or allow_time:
for c in params.columns:
if c in params.group_by or c == params.x_axis:
continue
ctype = column_types.get(c, "").upper()
is_numeric = any(
t in ctype
for t in [
"INT",
"DECIMAL",
"REAL",
"DOUBLE",
"FLOAT",
"NUMERIC",
"HUGEINT",
]
)
is_time = "TIMESTAMP" in ctype or "DATE" in ctype or "TIME"
in ctype
if need_numeric and not is_numeric:
return (
jsonify(
{
"error": f"Aggregate {agg} cannot be applied
to column {c}",
}
),
400,
)
if allow_time and not (is_numeric or is_time):
return (
jsonify(
{
"error": f"Aggregate {agg} cannot be applied
to column {c}",
}
),
400,
)
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,
)
return jsonify({"sql": sql, "rows": rows})
return app
app = create_app()
if __name__ == "__main__":
app.run(debug=True)
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I need to adjust the condition to check for both group_by and "timeseries". I'll ensure that when params.group_by is absent, the default aggregator is still set to "avg." I must also account for timeseries grouping behavior and skip timestamp as the 'x_axis' column. Additionally, I'll update UI behavior to uncheck time-related columns if graph_type is timeseries.
I need to make sure time and string columns are unchecked in timeseries mode. I'll call updateDisplayTypeUI() after the checkboxes and updateSelectedColumns are triggered.
To prevent errors, I'll uncheck string and time columns by default in timeseries mode.
I'll add a test for timeseries graphs, checking for default unchecked time columns and no errors.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# git status --short(scubaduck) root@8b10638fd893:/workspace/scubaduck# git branch
main
* work
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I’ll update the server code as needed.
if params.x_axis is None or params.x_axis not in valid_cols:
return jsonify({"error": "Invalid x_axis"}), 400
ctype = column_types.get(params.x_axis, "").upper()
if not any(t in ctype for t in ["TIMESTAMP", "DATE", "TIME"]):
return jsonify({"error": "x_axis must be a time column"}), 400
for col in params.columns:
if col not in valid_cols:
return jsonify({"error": f"Unknown column: {col}"}), 400
for col in params.group_by:
if col not in valid_cols:
return jsonify({"error": f"Unknown column: {col}"}), 400
if params.order_by and params.order_by not in valid_cols:
return jsonify({"error": f"Unknown column: {params.order_by}"}), 400
if params.group_by:
agg = (params.aggregate or "avg").lower()
if agg.startswith("p") or agg == "sum":
need_numeric = True
allow_time = False
elif agg == "avg" or agg in {"min", "max"}:
need_numeric = False
allow_time = True
else:
need_numeric = False
allow_time = False
if need_numeric or allow_time:
for c in params.columns:
if c in params.group_by or c == params.x_axis:
continue
ctype = column_types.get(c, "").upper()
is_numeric = any(
t in ctype
for t in [
"INT",
"DECIMAL",
"REAL",
"DOUBLE",
"FLOAT",
"NUMERIC",
"HUGEINT",
]
)
is_time = "TIMESTAMP" in ctype or "DATE" in ctype or "TIME"
in ctype
if need_numeric and not is_numeric:
return (
jsonify(
{
"error": f"Aggregate {agg} cannot be applied
to column {c}",
}
),
400,
)
if allow_time and not (is_numeric or is_time):
return (
jsonify(
{
"error": f"Aggregate {agg} cannot be applied
to column {c}",
}
),
400,
)
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,
)
return jsonify({"sql": sql, "rows": rows})
return app
app = create_app()
if __name__ == "__main__":
app.run(debug=True)
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'll tweak the logic around group_by and graph_type for better handling.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# apply_patch<<'PATCH'
> *** Begin Patch
> *** Update File: scubaduck/server.py
> @@
> - if params.group_by:
> + if params.group_by or params.graph_type == "timeseries":
> agg = (params.aggregate or "avg").lower()
> *** End Patch
> PATCH
Success. Updated the following files:
M scubaduck/server.py
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'll verify that the new line was inserted correctly in the context.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# grep -n "params.group_by or
params.graph_type" -n scubaduck/server.py
345: if params.group_by or params.graph_type == "timeseries":
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'll show a code snippet around where the change occurred.
if col not in valid_cols:
return jsonify({"error": f"Unknown column: {col}"}), 400
if params.order_by and params.order_by not in valid_cols:
return jsonify({"error": f"Unknown column: {params.order_by}"}), 400
if params.group_by or params.graph_type == "timeseries":
agg = (params.aggregate or "avg").lower()
if agg.startswith("p") or agg == "sum":
need_numeric = True
allow_time = False
elif agg == "avg" or agg in {"min", "max"}:
need_numeric = False
allow_time = True
else:
need_numeric = False
allow_time = False
if need_numeric or allow_time:
for c in params.columns:
if c in params.group_by or c == params.x_axis:
continue
ctype = column_types.get(c, "").upper()
is_numeric = any(
t in ctype
for t in [
"INT",
"DECIMAL",
"REAL",
"DOUBLE",
"FLOAT",
"NUMERIC",
"HUGEINT",
]
)
is_time = "TIMESTAMP" in ctype or "DATE" in ctype or "TIME"
in ctype
if need_numeric and not is_numeric:
return (
jsonify(
{
"error": f"Aggregate {agg} cannot be applied
to column {c}",
}
),
400,
)
if allow_time and not (is_numeric or is_time):
return (
jsonify(
{
"error": f"Aggregate {agg} cannot be applied
to column {c}",
}
),
400,
)
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,
)
return jsonify({"sql": sql, "rows": rows})
return app
app = create_app()
if __name__ == "__main__":
app.run(debug=True)
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'm considering how the change affects the aggregator when group_by is empty and the query is run. The test test_table_avg_no_group_by confirms that it previously succeeded even without group_by. However, the aggregator could cause a binder error for invalid columns. I'll ensure timestamp columns remain valid but leave string columns unchecked. Time to patch the issue in index.html.
I'm opening a patch to modify the updateDisplayTypeUI function. Let's dive in.
function updateDisplayTypeUI() {
const showTable = graphTypeSel.value === 'table';
const showTS = graphTypeSel.value === 'timeseries';
document.getElementById('group_by_field').style.display = showTable || showTS
? 'flex' : 'none';
document.getElementById('aggregate_field').style.display = showTable || showTS
? 'flex' : 'none';
document.getElementById('show_hits_field').style.display = showTable ? 'flex'
: 'none';
document.getElementById('x_axis_field').style.display = showTS ? 'flex' : 'non
e';
document.getElementById('granularity_field').style.display = showTS ? 'flex' :
'none';
document.getElementById('fill_field').style.display = showTS ? 'flex' : 'none'
;
document.querySelectorAll('#column_groups .col-group').forEach(g => {
if (g.querySelector('.col-group-header').textContent.startsWith('Strings'))
{
g.style.display = showTable || showTS ? 'none' : '';
}
});
if (showTS) {
const lim = document.getElementById('limit');
if (!lim.dataset.setByUser) {
lim.value = '7';
}
}
displayType = graphTypeSel.value;
}
orderDirBtn.addEventListener('click', () => {
orderDir = orderDir === 'ASC' ? 'DESC' : 'ASC';
updateOrderDirButton();
});
updateOrderDirButton();
(scubaduck) root@8b10638fd893:/workspace/scubaduck#Time to apply the necessary changes and fix things up!
(scubaduck) root@8b10638fd893:/workspace/scubaduck# apply_patch<<'PATCH'
> *** Begin Patch
> *** Update File: scubaduck/static/index.html
> @@
> if (showTS) {
> const lim = document.getElementById('limit');
> if (!lim.dataset.setByUser) {
> lim.value = '7';
> }
> + document.querySelectorAll('#column_groups input').forEach(cb => {
> + if (isTimeColumn(cb.value) || isStringColumn(cb.value)) {
> + cb.checked = false;
> + }
> + });
> + updateSelectedColumns();
> }
> displayType = graphTypeSel.value;
> }
> *** End Patch
> PATCH
Success. Updated the following files:
M scubaduck/static/index.html
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'll add the server test for timeseries column validation after the timeseries_basic test.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# grep -n "test_timeseries_bas
ic" -n tests/test_server.py
351:def test_timeseries_basic() -> None:
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I think I'll add the new test right after this.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# sed -n '340,365p' tests/test
_server.py
data = rv.get_json()
assert rv.status_code == 200
assert "error" not in data
rows = data["rows"]
assert rows[0][0] == "alice"
from dateutil import parser
ts = parser.parse(rows[0][1]).replace(tzinfo=None)
assert ts == parser.parse("2024-01-01 12:00:00")
def test_timeseries_basic() -> None:
app = server.app
client = app.test_client()
payload = {
"start": "2024-01-01 00:00:00",
"end": "2024-01-03 00:00:00",
"graph_type": "timeseries",
"limit": 100,
"group_by": ["user"],
"aggregate": "Count",
"columns": ["value"],
"x_axis": "timestamp",
"granularity": "1 day",
}
rv = client.post(_server.py
rv = client.post(
"/api/query", data=json.dumps(payload), content_type="application/json"
)
data = rv.get_json()
assert rv.status_code == 200
assert len(data["rows"]) == 4
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'm going to patch the code before adding the new test.
> *** Begin Patch
> *** Update File: tests/test_server.py
> @@
> def test_timeseries_basic() -> None:
> @@
> assert len(data["rows"]) == 4
> +
> +
> +def test_timeseries_string_column_error() -> None:
> + app = server.app
> + client = app.test_client()
> + payload = {
> + "start": "2024-01-01 00:00:00",
> + "end": "2024-01-03 00:00:00",
> + "graph_type": "timeseries",
> + "limit": 7,
> + "columns": ["timestamp", "event", "value", "user"],
> + "x_axis": "timestamp",
> + "granularity": "1 hour",
> + }
> + rv = client.post(
> + "/api/query", data=json.dumps(payload), content_type="application/jso
n"
> + )
> + data = rv.get_json()
> + assert rv.status_code == 400
> + assert "Aggregate" in data["error"]
> *** End Patch
> PATCH
Success. Updated the following files:
M tests/test_server.py
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'll use ruff with formatting first, then modify test cases in test_web.py.
_web.py
def test_graph_type_table_fields(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#graph_type", state="attached")
select_value(page, "#graph_type", "table")
assert page.is_visible("#group_by_field")
assert page.is_visible("#aggregate_field")
assert page.is_visible("#show_hits_field")
page.click("text=Columns")
assert not page.is_visible("text=Strings:")
def test_graph_type_timeseries_fields(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#graph_type", state="attached")
select_value(page, "#graph_type", "timeseries")
assert page.is_visible("#group_by_field")
assert page.is_visible("#aggregate_field")
assert page.is_visible("#x_axis_field")
assert page.is_visible("#granularity_field")
assert page.is_visible("#fill_field")
def test_help_and_alignment(page: Any, server_url: str) -> None:
page.goto(server_url)
page.wait_for_selector("#order_by option", state="attached")
titles = page.evaluate(
"Array.from(document.querySelectorAll('#settings .help')).map(e => e.tit
le)"
)
assert any("start/end of the time range" in t for t in titles)
text_align = page.evaluate(
"getComputedStyle(document.querySelector('#settings label')).textAlign"
)
assert text_align == "right"
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I’ll add the new test after the timeseries fields or another existing test.
> *** Begin Patch
> *** Update File: tests/test_web.py
> @@
> def test_graph_type_timeseries_fields(page: Any, server_url: str) -> None:
> @@
> assert page.is_visible("#fill_field")
> +
> +
> +def test_timeseries_default_query(page: Any, server_url: str) -> None:
> + page.goto(server_url)
> + page.wait_for_selector("#graph_type", state="attached")
> + select_value(page, "#graph_type", "timeseries")
> + page.evaluate("window.lastResults = undefined")
> + page.click("text=Dive")
> + page.wait_for_function("window.lastResults !== undefined")
> + data = page.evaluate("window.lastResults")
> + assert "error" not in data
> + assert page.is_visible("#chart")
> + page.click("text=Columns")
> + assert not page.is_checked("#column_groups input[value='timestamp']")
> *** End Patch
> PATCH
Success. Updated the following files:
M tests/test_web.py
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'll run ruff format to make sure the code is properly styled.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# ruff format scubaduck/server
.py scubaduck/static/index.html tests/test_server.py tests/test_web.py >/tmp/ruf
f_format.txt && tail -n 20 /tmp/ruff_format.txt
error: Failed to parse scubaduck/static/index.html:1:1: Expected a statement
(scubaduck) root@8b10638fd893:/workspace/scubaduck#Ruff format only supports Python files, so I won't run it on HTML.
.py tests/test_server.py tests/test_web.py >/tmp/ruff_format.txt && tail -n 20 /
tmp/ruff_format.txt
3 files left unchanged(scubaduck) root@8b10638fd893:/workspace/scubaduck# ruff check >/tmp/ruff_check.
txt && tail -n 20 /tmp/ruff_check.txt
All checks passed!(scubaduck) root@8b10638fd893:/workspace/scubaduck# pyright >/tmp/pyright.txt &&
tail -n 20 /tmp/pyright.txt0 errors, 0 warnings, 0 informations(scubaduck) root@8b10638fd893:/workspace/scubaduck# pytest -q >/tmp/pytest.txt &
& tail -n 20 /tmp/pytest.txt(scubaduck) root@8b10638fd893:/workspace/scubaduck#It seems like tests might not have run; I'll open the output file for details.
bringing up nodes...
bringing up nodes...
...........................F.............................. [100%]
=================================== FAILURES ===================================
___________________ test_timeseries_default_query[chromium] ____________________
[gw3] linux -- Python 3.12.3 /workspace/scubaduck/.venv/bin/python
Traceback (most recent call last):
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/_pytest/runner.p
y", line 341, in from_call
result: TResult | None = func()
^^^^^^
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/_pytest/runner.p
y", line 242, in <lambda>
lambda: runtest_hook(item=item, **kwds), when=when, reraise=reraise
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/pluggy/_hooks.py
", line 512, in __call__
return self._hookexec(self.name, self._hookimpls.copy(), kwargs, firstresult
)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
^
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/pluggy/_manager.
py", line 120, in _hookexec
return self._inner_hookexec(hook_name, methods, kwargs, firstresult)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/pluggy/_callers.
py", line 167, in _multicall
raise exception
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/pluggy/_callers.
py", line 139, in _multicall
teardown.throw(exception)
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/_pytest/threadex
ception.py", line 92, in pytest_runtest_call
yield from thread_exception_runtest_hook()
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/_pytest/threadex
ception.py", line 68, in thread_exception_runtest_hook
yield
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/pluggy/_callers.
py", line 139, in _multicall
teardown.throw(exception)
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/_pytest/unraisab
leexception.py", line 95, in pytest_runtest_call
yield from unraisable_exception_runtest_hook()
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/_pytest/unraisab
leexception.py", line 70, in unraisable_exception_runtest_hook
yield
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/pluggy/_callers.
py", line 139, in _multicall
teardown.throw(exception)
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/_pytest/logging.
py", line 846, in pytest_runtest_call
yield from self._runtest_for(item, "call")
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/_pytest/logging.
py", line 829, in _runtest_for
yield
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/pluggy/_callers.
py", line 139, in _multicall
teardown.throw(exception)
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/_pytest/capture.
py", line 898, in pytest_runtest_call
return (yield)
^^^^^
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/pluggy/_callers.
py", line 139, in _multicall
teardown.throw(exception)
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/_pytest/skipping
.py", line 257, in pytest_runtest_call
return (yield)
^^^^^
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/pluggy/_callers.
py", line 121, in _multicall
res = hook_impl.function(*args)
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/_pytest/runner.p
y", line 174, in pytest_runtest_call
item.runtest()
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/_pytest/python.p
y", line 1627, in runtest
self.ihook.pytest_pyfunc_call(pyfuncitem=self)
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/pluggy/_hooks.py
", line 512, in __call__
return self._hookexec(self.name, self._hookimpls.copy(), kwargs, firstresult
)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
^
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/pluggy/_manager.
py", line 120, in _hookexec
return self._inner_hookexec(hook_name, methods, kwargs, firstresult)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/pluggy/_callers.
py", line 167, in _multicall
raise exception
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/pluggy/_callers.
py", line 121, in _multicall
res = hook_impl.function(*args)
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/workspace/scubaduck/.venv/lib/python3.12/site-packages/_pytest/python.p
y", line 159, in pytest_pyfunc_call
result = testfunction(**testargs)
^^^^^^^^^^^^^^^^^^^^^^^^
File "/workspace/scubaduck/tests/test_web.py", line 207, in test_timeseries_de
fault_query
assert "error" not in data
AssertionError: assert 'error' not in {'error': 'Binder Error: column "timestamp
" must appear in the GROUP BY clause or must be part of an aggregate functio...P
BY bucket ORDER BY timestamp ASC LIMIT 7\n
^\n'}
----------------------------- Captured stdout call -----------------------------
Query failed:
SELECT TIMESTAMP 'epoch' + INTERVAL '3600 second' * CAST(floor(epoch(timestamp)/
3600) AS BIGINT) AS bucket, count(*) AS Hits, bucket, avg(value) AS value FROM e
vents GROUP BY bucket ORDER BY timestamp ASC LIMIT 7
Traceback (most recent call last):
File "/workspace/scubaduck/scubaduck/server.py", line 394, in query
rows = con.execute(sql).fetchall()
^^^^^^^^^^^^^^^^
duckdb.duckdb.BinderException: Binder Error: column "timestamp" must appear in t
he GROUP BY clause or must be part of an aggregate function.
Either add it to the GROUP BY list, or use "ANY_VALUE(timestamp)" if the exact v
alue of "timestamp" is not important.
LINE 1: ..., avg(value) AS value FROM events GROUP BY bucket ORDER BY timestamp
ASC LIMIT 7
^
------------------------------ Captured log call -------------------------------
INFO werkzeug:_internal.py:97 127.0.0.1 - - [21/May/2025 03:58:23] "GET / HT
TP/1.1" 200 -
INFO werkzeug:_internal.py:97 127.0.0.1 - - [21/May/2025 03:58:23] "GET /api
/columns HTTP/1.1" 200 -
INFO werkzeug:_internal.py:97 127.0.0.1 - - [21/May/2025 03:58:23] "POST /ap
i/query HTTP/1.1" 200 -
INFO werkzeug:_internal.py:97 127.0.0.1 - - [21/May/2025 03:58:23] "POST /ap
i/query HTTP/1.1" 400 -
=========================== short test summary info ============================
FAILED tests/test_web.py::test_timeseries_default_query[chromium] - assert 'e...
1 failed, 57 passed in 8.90s
(scubaduck) root@8b10638fd893:/workspace/scubaduck#The error appears because ORDER BY timestamp uses an ungrouped or unaggregated column. I'll adjust the query defaults to handle this.
The query fails due to ordering by an ungrouped timestamp. I need to adjust the logic for this case.
To fix the binder error, I can keep the timestamp checked but aggregate it.
Instead of unchecking timestamp, I’ll adjust order_by and uncheck string columns to avoid errors.
To avoid binder errors, I'll set order_by to empty or omit it when using time series.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# grep -n "order_by" -n scubad
uck/static/index.html | head
162: <select id="order_by"></select>
423: const orderSelect = document.getElementById('order_by');
876: order_by: document.getElementById('order_by').value,
909: if (params.order_by) sp.set('order_by', params.order_by);
932: if (params.order_by) {
933: document.getElementById('order_by').value = params.order_by;
982: if (sp.has('order_by')) params.order_by = sp.get('order_by');
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'm thinking of keeping timestamp for ordering even if it's unchecked for display. I could adjust the logic so the UI hides time columns but still includes them in the query for ordering.
I should keep timestamp checked for order_by to work while unchecking other time columns.
I'll likely hide timestamp in UI while keeping it selected for sorting purposes.
I'll adjust to avoid sorting by timestamp, setting order_by to '' or 'x_axis' instead.
I'll patch the UI and set order_by to '' to avoid undefined behavior in query.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# sed -n '388,418p' scubaduck/
static/index.html
function updateDisplayTypeUI() {
const showTable = graphTypeSel.value === 'table';
const showTS = graphTypeSel.value === 'timeseries';
document.getElementById('group_by_field').style.display = showTable || showTS
? 'flex' : 'none';
document.getElementById('aggregate_field').style.display = showTable || showTS
? 'flex' : 'none';
document.getElementById('show_hits_field').style.display = showTable ? 'flex'
: 'none';
document.getElementById('x_axis_field').style.display = showTS ? 'flex' : 'non
e';
document.getElementById('granularity_field').style.display = showTS ? 'flex' :
'none';
document.getElementById('fill_field').style.display = showTS ? 'flex' : 'none'
;
document.querySelectorAll('#column_groups .col-group').forEach(g => {
if (g.querySelector('.col-group-header').textContent.startsWith('Strings'))
{
g.style.display = showTable || showTS ? 'none' : '';
}
});
if (showTS) {
const lim = document.getElementById('limit');
if (!lim.dataset.setByUser) {
lim.value = '7';
}
document.querySelectorAll('#column_groups input').forEach(cb => {
if (isTimeColumn(cb.value) || isStringColumn(cb.value)) {
cb.checked = false;
}
});
updateSelectedColumns();
}
displayType = graphTypeSel.value;
}
orderDirBtn.addEventListener('click', () => {
orderDir = orderDir === 'ASC' ? 'DESC' : 'ASC';
updateOrderDirButton();
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'm updating the code to set order_by to blank as well.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# apply_patch<<'PATCH'
> *** Begin Patch
> *** Update File: scubaduck/static/index.html
> @@
> - if (showTS) {
> + if (showTS) {
> const lim = document.getElementById('limit');
> if (!lim.dataset.setByUser) {
> lim.value = '7';
> }
> document.querySelectorAll('#column_groups input').forEach(cb => {
> if (isTimeColumn(cb.value) || isStringColumn(cb.value)) {
> cb.checked = false;
> }
> });
> + document.getElementById('order_by').value = '';
> updateSelectedColumns();
> }
> *** End Patch
> PATCH
Success. Updated the following files:
M scubaduck/static/index.html
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'll run ruff for Python, but skip it for HTML since that's not possible.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# ruff format scubaduck/server
.py tests/test_server.py tests/test_web.py >/tmp/ruff_format.txt && tail -n 20 /
tmp/ruff_format.txt
3 files left unchanged
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'll give ruff another shot to make sure things are in order.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# ruff check >/tmp/ruff_check.
txt && tail -n 20 /tmp/ruff_check.txt
All checks passed!(scubaduck) root@8b10638fd893:/workspace/scubaduck# pyright >/tmp/pyright.txt &&
tail -n 20 /tmp/pyright.txt0 errors, 0 warnings, 0 informations
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'll run pytest one more time to check if the issue persists.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# pytest -q >/tmp/pytest.txt &
& tail -n 20 /tmp/pytest.txtbringing up nodes...
bringing up nodes...
.......................................................... [100%]
58 passed in 8.78s(scubaduck) root@8b10638fd893:/workspace/scubaduck# tail -n 20 /tmp/pytest.txt
bringing up nodes...
bringing up nodes...
.......................................................... [100%]
58 passed in 8.78s
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'll review the git status now to see where I stand with my changes.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# git status --short
M scubaduck/server.py
M scubaduck/static/index.html
M tests/test_server.py
M tests/test_web.py
(scubaduck) root@8b10638fd893:/workspace/scubaduck#Time to make the commit!
(scubaduck) root@8b10638fd893:/workspace/scubaduck# git diff --staged
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I need to add changes to staging before proceeding.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# git add scubaduck/server.py
scubaduck/static/index.html tests/test_server.py tests/test_web.py(scubaduck) root@8b10638fd893:/workspace/scubaduck# git commit -m "fix: handle t
imeseries avg on strings" && git status --short
[work 2517fb4] fix: handle timeseries avg on strings
4 files changed, 42 insertions(+), 1 deletion(-)(scubaduck) root@8b10638fd893:/workspace/scubaduck# git status --short
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I’ll grab lines around the changes in server.py for proper citation.
336 for col in params.columns:
337 if col not in valid_cols:
338 return jsonify({"error": f"Unknown column: {col}"}), 400
339 for col in params.group_by:
340 if col not in valid_cols:
341 return jsonify({"error": f"Unknown column: {col}"}), 400
342 if params.order_by and params.order_by not in valid_cols:
343 return jsonify({"error": f"Unknown column: {params.order_by}
"}), 400
344
345 if params.group_by or params.graph_type == "timeseries":
346 agg = (params.aggregate or "avg").lower()
347 if agg.startswith("p") or agg == "sum":
348 need_numeric = True
349 allow_time = False
350 elif agg == "avg" or agg in {"min", "max"}:
351 need_numeric = False
352 allow_time = True
353 else:
354 need_numeric = False
355 allow_time = False
356 if need_numeric or allow_time:
357 for c in params.columns:
358 if c in params.group_by or c == params.x_axis:
359 continue
360 ctype = column_types.get(c, "").upper()
361 is_numeric = any(
362 t in ctype
363 for t in [
364 "INT",
365 "DECIMAL",
366 "REAL",
367 "DOUBLE",
368 "FLOAT",
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'll grab a few more lines, extending from 368 to capture the patch.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# nl -ba scubaduck/server.py |
sed -n '345,380p'
345 if params.group_by or params.graph_type == "timeseries":
346 agg = (params.aggregate or "avg").lower()
347 if agg.startswith("p") or agg == "sum":
348 need_numeric = True
349 allow_time = False
350 elif agg == "avg" or agg in {"min", "max"}:
351 need_numeric = False
352 allow_time = True
353 else:
354 need_numeric = False
355 allow_time = False
356 if need_numeric or allow_time:
357 for c in params.columns:
358 if c in params.group_by or c == params.x_axis:
359 continue
360 ctype = column_types.get(c, "").upper()
361 is_numeric = any(
362 t in ctype
363 for t in [
364 "INT",
365 "DECIMAL",
366 "REAL",
367 "DOUBLE",
368 "FLOAT",
369 "NUMERIC",
370 "HUGEINT",
371 ]
372 )
373 is_time = "TIMESTAMP" in ctype or "DATE" in ctype or
"TIME" in ctype
374 if need_numeric and not is_numeric:
375 return (
376 jsonify(
377 {
378 "error": f"Aggregate {agg} cannot be
applied to column {c}",
379 }
380 ),
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'll grab the modified lines near the patch in the static/index.html file.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# nl -ba scubaduck/static/inde
x.html | sed -n '396,418p'
396 document.getElementById('fill_field').style.display = showTS ? 'flex'
: 'none';
397 document.querySelectorAll('#column_groups .col-group').forEach(g => {
398 if (g.querySelector('.col-group-header').textContent.startsWith('Str
ings')) {
399 g.style.display = showTable || showTS ? 'none' : '';
400 }
401 });
402 if (showTS) {
403 const lim = document.getElementById('limit');
404 if (!lim.dataset.setByUser) {
405 lim.value = '7';
406 }
407 document.querySelectorAll('#column_groups input').forEach(cb => {
408 if (isTimeColumn(cb.value) || isStringColumn(cb.value)) {
409 cb.checked = false;
410 }
411 });
412 document.getElementById('order_by').value = '';
413 updateSelectedColumns();
414 }
415 displayType = graphTypeSel.value;
416 }
417 orderDirBtn.addEventListener('click', () => {
418 orderDir = orderDir === 'ASC' ? 'DESC' : 'ASC';
(scubaduck) root@8b10638fd893:/workspace/scubaduck#I'm adding the new server test snippet now.
(scubaduck) root@8b10638fd893:/workspace/scubaduck# nl -ba tests/test_server.py
| sed -n '348,390p'
348 assert ts == parser.parse("2024-01-01 12:00:00")
349
350
351 def test_timeseries_basic() -> None:
352 app = server.app
353 client = app.test_client()
354 payload = {
355 "start": "2024-01-01 00:00:00",
356 "end": "2024-01-03 00:00:00",
357 "graph_type": "timeseries",
358 "limit": 100,
359 "group_by": ["user"],
360 "aggregate": "Count",
361 "columns": ["value"],
362 "x_axis": "timestamp",
363 "granularity": "1 day",
364 }
365 rv = client.post(
366 "/api/query", data=json.dumps(payload), content_type="applicatio
n/json"
367 )
368 data = rv.get_json()
369 assert rv.status_code == 200
370 assert len(data["rows"]) == 4
371
372
373 def test_timeseries_string_column_error() -> None:
374 app = server.app
375 client = app.test_client()
376 payload = {
377 "start": "2024-01-01 00:00:00",
378 "end": "2024-01-03 00:00:00",
379 "graph_type": "timeseries",
380 "limit": 7,
381 "columns": ["timestamp", "event", "value", "user"],
382 "x_axis": "timestamp",
383 "granularity": "1 hour",
384 }
385 rv = client.post(
386 "/api/query", data=json.dumps(payload), content_type="applicatio
n/json"
387 )
388 data = rv.get_json()
389 assert rv.status_code == 400
390 assert "Aggregate" in data["error"](scubaduck) root@8b10638fd893:/workspace/scubaduck# nl -ba tests/test_web.py | s
ed -n '188,214p'
188 def test_graph_type_timeseries_fields(page: Any, server_url: str) -> Non
e:
189 page.goto(server_url)
190 page.wait_for_selector("#graph_type", state="attached")
191 select_value(page, "#graph_type", "timeseries")
192 assert page.is_visible("#group_by_field")
193 assert page.is_visible("#aggregate_field")
194 assert page.is_visible("#x_axis_field")
195 assert page.is_visible("#granularity_field")
196 assert page.is_visible("#fill_field")
197
198
199 def test_timeseries_default_query(page: Any, server_url: str) -> None:
200 page.goto(server_url)
201 page.wait_for_selector("#graph_type", state="attached")
202 select_value(page, "#graph_type", "timeseries")
203 page.evaluate("window.lastResults = undefined")
204 page.click("text=Dive")
205 page.wait_for_function("window.lastResults !== undefined")
206 data = page.evaluate("window.lastResults")
207 assert "error" not in data
208 assert page.is_visible("#chart")
209 page.click("text=Columns")
210 assert not page.is_checked("#column_groups input[value='timestamp']"
)
211
212
213 def test_help_and_alignment(page: Any, server_url: str) -> None:
214 page.goto(server_url)
(scubaduck) root@8b10638fd893:/workspace/scubaduck#Time to finalize the PR and write the message summary.