Codex Task Logs

Task ID: task_e_682e6d298d308323b9f63ce6e47754de

Environment setup
certifi ------------------------------ 16.00 KiB/155.88 KiB werkzeug ------------------------------ 75.17 KiB/219.24 KiB python-dateutil ------------------------------ 14.86 KiB/224.50 KiB pytest ------------------------------ 77.14 KiB/335.58 KiB greenlet ------------------------------ 16.00 KiB/589.71 KiB pyright ------------------------------ 0 B/5.31 MiB ruff ------------------------------ 32.00 KiB/11.02 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (5/33) iniconfig ------------------------------ 5.91 KiB/5.91 KiB python-slugify ------------------------------ 8.00 KiB/9.82 KiB pyee ------------------------------ 15.36 KiB/15.36 KiB itsdangerous ------------------------------ 14.88 KiB/15.85 KiB pytest-playwright ------------------------------ 16.23 KiB/16.23 KiB execnet ------------------------------ 14.88 KiB/39.66 KiB typing-extensions ------------------------------ 32.00 KiB/44.73 KiB pytest-xdist ------------------------------ 45.03 KiB/45.03 KiB requests ------------------------------ 14.88 KiB/63.41 KiB packaging ------------------------------ 16.00 KiB/64.91 KiB idna ------------------------------ 16.00 KiB/68.79 KiB urllib3 ------------------------------ 32.00 KiB/125.66 KiB jinja2 ------------------------------ 14.88 KiB/131.74 KiB charset-normalizer ------------------------------ 142.50 KiB/145.08 KiB certifi ------------------------------ 16.00 KiB/155.88 KiB werkzeug ------------------------------ 75.17 KiB/219.24 KiB python-dateutil ------------------------------ 14.86 KiB/224.50 KiB pytest ------------------------------ 77.14 KiB/335.58 KiB greenlet ------------------------------ 16.00 KiB/589.71 KiB pyright ------------------------------ 0 B/5.31 MiB ruff ------------------------------ 32.00 KiB/11.02 MiB duckdb ------------------------------ 717.61 KiB/19.27 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (5/33) python-slugify ------------------------------ 9.82 KiB/9.82 KiB pyee ------------------------------ 15.36 KiB/15.36 KiB itsdangerous ------------------------------ 14.88 KiB/15.85 KiB pytest-playwright ------------------------------ 16.23 KiB/16.23 KiB execnet ------------------------------ 30.88 KiB/39.66 KiB typing-extensions ------------------------------ 44.73 KiB/44.73 KiB pytest-xdist ------------------------------ 45.03 KiB/45.03 KiB requests ------------------------------ 30.88 KiB/63.41 KiB packaging ------------------------------ 16.00 KiB/64.91 KiB idna ------------------------------ 32.00 KiB/68.79 KiB urllib3 ------------------------------ 48.00 KiB/125.66 KiB jinja2 ------------------------------ 30.88 KiB/131.74 KiB charset-normalizer ------------------------------ 142.50 KiB/145.08 KiB certifi ------------------------------ 80.00 KiB/155.88 KiB werkzeug ------------------------------ 75.17 KiB/219.24 KiB python-dateutil ------------------------------ 30.86 KiB/224.50 KiB pytest ------------------------------ 93.14 KiB/335.58 KiB greenlet ------------------------------ 32.00 KiB/589.71 KiB pyright ------------------------------ 8.00 KiB/5.31 MiB ruff ------------------------------ 64.00 KiB/11.02 MiB duckdb ------------------------------ 781.61 KiB/19.27 MiB playwright ------------------------------ 30.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (5/33) python-slugify ------------------------------ 9.82 KiB/9.82 KiB pyee ------------------------------ 15.36 KiB/15.36 KiB itsdangerous ------------------------------ 14.88 KiB/15.85 KiB execnet ------------------------------ 30.88 KiB/39.66 KiB typing-extensions ------------------------------ 44.73 KiB/44.73 KiB pytest-xdist ------------------------------ 45.03 KiB/45.03 KiB requests ------------------------------ 30.88 KiB/63.41 KiB packaging ------------------------------ 16.00 KiB/64.91 KiB idna ------------------------------ 32.00 KiB/68.79 KiB urllib3 ------------------------------ 48.00 KiB/125.66 KiB jinja2 ------------------------------ 30.88 KiB/131.74 KiB charset-normalizer ------------------------------ 142.50 KiB/145.08 KiB certifi ------------------------------ 80.00 KiB/155.88 KiB werkzeug ------------------------------ 75.17 KiB/219.24 KiB python-dateutil ------------------------------ 30.86 KiB/224.50 KiB pytest ------------------------------ 109.14 KiB/335.58 KiB greenlet ------------------------------ 32.00 KiB/589.71 KiB pyright ------------------------------ 8.00 KiB/5.31 MiB ruff ------------------------------ 80.00 KiB/11.02 MiB duckdb ------------------------------ 781.61 KiB/19.27 MiB playwright ------------------------------ 30.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (5/33) pyee ------------------------------ 15.36 KiB/15.36 KiB itsdangerous ------------------------------ 14.88 KiB/15.85 KiB execnet ------------------------------ 30.88 KiB/39.66 KiB typing-extensions ------------------------------ 44.73 KiB/44.73 KiB pytest-xdist ------------------------------ 45.03 KiB/45.03 KiB requests ------------------------------ 30.88 KiB/63.41 KiB packaging ------------------------------ 32.00 KiB/64.91 KiB idna ------------------------------ 64.00 KiB/68.79 KiB urllib3 ------------------------------ 48.00 KiB/125.66 KiB jinja2 ------------------------------ 46.88 KiB/131.74 KiB charset-normalizer ------------------------------ 142.50 KiB/145.08 KiB certifi ------------------------------ 128.00 KiB/155.88 KiB werkzeug ------------------------------ 91.17 KiB/219.24 KiB python-dateutil ------------------------------ 46.86 KiB/224.50 KiB pytest ------------------------------ 109.14 KiB/335.58 KiB greenlet ------------------------------ 48.00 KiB/589.71 KiB pyright ------------------------------ 8.00 KiB/5.31 MiB ruff ------------------------------ 128.00 KiB/11.02 MiB duckdb ------------------------------ 829.61 KiB/19.27 MiB playwright ------------------------------ 30.91 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 typing-extensions ------------------------------ 44.73 KiB/44.73 KiB pytest-xdist ------------------------------ 45.03 KiB/45.03 KiB requests ------------------------------ 30.88 KiB/63.41 KiB packaging ------------------------------ 48.00 KiB/64.91 KiB idna ------------------------------ 64.00 KiB/68.79 KiB urllib3 ------------------------------ 48.00 KiB/125.66 KiB jinja2 ------------------------------ 46.88 KiB/131.74 KiB charset-normalizer ------------------------------ 142.50 KiB/145.08 KiB certifi ------------------------------ 155.88 KiB/155.88 KiB werkzeug ------------------------------ 91.17 KiB/219.24 KiB python-dateutil ------------------------------ 46.86 KiB/224.50 KiB pytest ------------------------------ 125.14 KiB/335.58 KiB greenlet ------------------------------ 48.00 KiB/589.71 KiB pyright ------------------------------ 8.00 KiB/5.31 MiB ruff ------------------------------ 176.00 KiB/11.02 MiB duckdb ------------------------------ 877.61 KiB/19.27 MiB playwright ------------------------------ 30.91 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 pytest-xdist ------------------------------ 45.03 KiB/45.03 KiB requests ------------------------------ 46.88 KiB/63.41 KiB packaging ------------------------------ 48.00 KiB/64.91 KiB idna ------------------------------ 64.00 KiB/68.79 KiB urllib3 ------------------------------ 64.00 KiB/125.66 KiB jinja2 ------------------------------ 62.88 KiB/131.74 KiB charset-normalizer ------------------------------ 142.50 KiB/145.08 KiB certifi ------------------------------ 155.88 KiB/155.88 KiB werkzeug ------------------------------ 91.17 KiB/219.24 KiB python-dateutil ------------------------------ 46.86 KiB/224.50 KiB pytest ------------------------------ 125.14 KiB/335.58 KiB greenlet ------------------------------ 48.00 KiB/589.71 KiB pyright ------------------------------ 8.00 KiB/5.31 MiB ruff ------------------------------ 192.00 KiB/11.02 MiB duckdb ------------------------------ 893.61 KiB/19.27 MiB playwright ------------------------------ 46.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (5/33) execnet ------------------------------ 30.88 KiB/39.66 KiB pytest-xdist ------------------------------ 45.03 KiB/45.03 KiB requests ------------------------------ 46.88 KiB/63.41 KiB packaging ------------------------------ 48.00 KiB/64.91 KiB idna ------------------------------ 64.00 KiB/68.79 KiB urllib3 ------------------------------ 64.00 KiB/125.66 KiB jinja2 ------------------------------ 62.88 KiB/131.74 KiB charset-normalizer ------------------------------ 142.50 KiB/145.08 KiB certifi ------------------------------ 155.88 KiB/155.88 KiB werkzeug ------------------------------ 91.17 KiB/219.24 KiB python-dateutil ------------------------------ 46.86 KiB/224.50 KiB pytest ------------------------------ 125.14 KiB/335.58 KiB greenlet ------------------------------ 48.00 KiB/589.71 KiB pyright ------------------------------ 8.00 KiB/5.31 MiB ruff ------------------------------ 192.00 KiB/11.02 MiB duckdb ------------------------------ 893.61 KiB/19.27 MiB playwright ------------------------------ 46.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (5/33) execnet ------------------------------ 30.88 KiB/39.66 KiB requests ------------------------------ 46.88 KiB/63.41 KiB packaging ------------------------------ 48.00 KiB/64.91 KiB idna ------------------------------ 64.00 KiB/68.79 KiB urllib3 ------------------------------ 64.00 KiB/125.66 KiB jinja2 ------------------------------ 78.88 KiB/131.74 KiB charset-normalizer ------------------------------ 145.08 KiB/145.08 KiB certifi ------------------------------ 155.88 KiB/155.88 KiB werkzeug ------------------------------ 91.17 KiB/219.24 KiB python-dateutil ------------------------------ 46.86 KiB/224.50 KiB pytest ------------------------------ 125.14 KiB/335.58 KiB greenlet ------------------------------ 48.00 KiB/589.71 KiB pyright ------------------------------ 8.00 KiB/5.31 MiB ruff ------------------------------ 208.00 KiB/11.02 MiB duckdb ------------------------------ 909.61 KiB/19.27 MiB playwright ------------------------------ 46.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (5/33) execnet ------------------------------ 30.88 KiB/39.66 KiB requests ------------------------------ 46.88 KiB/63.41 KiB packaging ------------------------------ 64.91 KiB/64.91 KiB urllib3 ------------------------------ 77.20 KiB/125.66 KiB jinja2 ------------------------------ 78.88 KiB/131.74 KiB charset-normalizer ------------------------------ 145.08 KiB/145.08 KiB certifi ------------------------------ 155.88 KiB/155.88 KiB werkzeug ------------------------------ 107.17 KiB/219.24 KiB python-dateutil ------------------------------ 62.86 KiB/224.50 KiB pytest ------------------------------ 141.14 KiB/335.58 KiB greenlet ------------------------------ 64.00 KiB/589.71 KiB pyright ------------------------------ 16.00 KiB/5.31 MiB ruff ------------------------------ 240.00 KiB/11.02 MiB duckdb ------------------------------ 957.61 KiB/19.27 MiB playwright ------------------------------ 46.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (5/33) execnet ------------------------------ 30.88 KiB/39.66 KiB requests ------------------------------ 46.88 KiB/63.41 KiB packaging ------------------------------ 64.91 KiB/64.91 KiB urllib3 ------------------------------ 77.20 KiB/125.66 KiB jinja2 ------------------------------ 78.88 KiB/131.74 KiB certifi ------------------------------ 155.88 KiB/155.88 KiB werkzeug ------------------------------ 107.17 KiB/219.24 KiB python-dateutil ------------------------------ 62.86 KiB/224.50 KiB pytest ------------------------------ 141.14 KiB/335.58 KiB greenlet ------------------------------ 64.00 KiB/589.71 KiB pyright ------------------------------ 16.00 KiB/5.31 MiB ruff ------------------------------ 256.00 KiB/11.02 MiB duckdb ------------------------------ 957.61 KiB/19.27 MiB playwright ------------------------------ 46.91 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 urllib3 ------------------------------ 77.20 KiB/125.66 KiB jinja2 ------------------------------ 94.88 KiB/131.74 KiB werkzeug ------------------------------ 107.17 KiB/219.24 KiB python-dateutil ------------------------------ 78.86 KiB/224.50 KiB pytest ------------------------------ 173.14 KiB/335.58 KiB greenlet ------------------------------ 128.00 KiB/589.71 KiB pyright ------------------------------ 16.00 KiB/5.31 MiB ruff ------------------------------ 320.00 KiB/11.02 MiB duckdb ------------------------------ 1021.61 KiB/19.27 MiB playwright ------------------------------ 46.91 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 urllib3 ------------------------------ 77.20 KiB/125.66 KiB jinja2 ------------------------------ 94.88 KiB/131.74 KiB werkzeug ------------------------------ 107.17 KiB/219.24 KiB python-dateutil ------------------------------ 94.86 KiB/224.50 KiB pytest ------------------------------ 173.14 KiB/335.58 KiB greenlet ------------------------------ 144.00 KiB/589.71 KiB pyright ------------------------------ 16.00 KiB/5.31 MiB ruff ------------------------------ 320.00 KiB/11.02 MiB duckdb ------------------------------ 1.01 MiB/19.27 MiB playwright ------------------------------ 46.91 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 urllib3 ------------------------------ 93.20 KiB/125.66 KiB jinja2 ------------------------------ 126.88 KiB/131.74 KiB werkzeug ------------------------------ 123.17 KiB/219.24 KiB python-dateutil ------------------------------ 190.86 KiB/224.50 KiB pytest ------------------------------ 189.14 KiB/335.58 KiB greenlet ------------------------------ 240.00 KiB/589.71 KiB pyright ------------------------------ 16.00 KiB/5.31 MiB ruff ------------------------------ 432.00 KiB/11.02 MiB duckdb ------------------------------ 1.11 MiB/19.27 MiB playwright ------------------------------ 62.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (5/33) execnet ------------------------------ 39.66 KiB/39.66 KiB urllib3 ------------------------------ 93.20 KiB/125.66 KiB jinja2 ------------------------------ 126.88 KiB/131.74 KiB werkzeug ------------------------------ 123.17 KiB/219.24 KiB python-dateutil ------------------------------ 224.50 KiB/224.50 KiB pytest ------------------------------ 189.14 KiB/335.58 KiB greenlet ------------------------------ 272.00 KiB/589.71 KiB pyright ------------------------------ 16.00 KiB/5.31 MiB ruff ------------------------------ 460.16 KiB/11.02 MiB duckdb ------------------------------ 1.14 MiB/19.27 MiB playwright ------------------------------ 62.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (5/33) urllib3 ------------------------------ 93.20 KiB/125.66 KiB jinja2 ------------------------------ 126.88 KiB/131.74 KiB werkzeug ------------------------------ 123.17 KiB/219.24 KiB python-dateutil ------------------------------ 224.50 KiB/224.50 KiB pytest ------------------------------ 189.14 KiB/335.58 KiB greenlet ------------------------------ 304.00 KiB/589.71 KiB pyright ------------------------------ 32.00 KiB/5.31 MiB ruff ------------------------------ 492.16 KiB/11.02 MiB duckdb ------------------------------ 1.17 MiB/19.27 MiB playwright ------------------------------ 62.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (5/33) urllib3 ------------------------------ 109.20 KiB/125.66 KiB jinja2 ------------------------------ 131.74 KiB/131.74 KiB werkzeug ------------------------------ 139.17 KiB/219.24 KiB pytest ------------------------------ 221.14 KiB/335.58 KiB greenlet ------------------------------ 463.49 KiB/589.71 KiB pyright ------------------------------ 191.70 KiB/5.31 MiB ruff ------------------------------ 652.16 KiB/11.02 MiB duckdb ------------------------------ 1.33 MiB/19.27 MiB playwright ------------------------------ 78.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (5/33) urllib3 ------------------------------ 109.20 KiB/125.66 KiB werkzeug ------------------------------ 139.17 KiB/219.24 KiB pytest ------------------------------ 221.14 KiB/335.58 KiB greenlet ------------------------------ 463.49 KiB/589.71 KiB pyright ------------------------------ 239.70 KiB/5.31 MiB ruff ------------------------------ 700.16 KiB/11.02 MiB duckdb ------------------------------ 1.36 MiB/19.27 MiB playwright ------------------------------ 78.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (5/33) werkzeug ------------------------------ 171.17 KiB/219.24 KiB pytest ------------------------------ 253.14 KiB/335.58 KiB greenlet ------------------------------ 479.49 KiB/589.71 KiB pyright ------------------------------ 527.70 KiB/5.31 MiB ruff ------------------------------ 988.16 KiB/11.02 MiB duckdb ------------------------------ 1.65 MiB/19.27 MiB playwright ------------------------------ 110.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (5/33) werkzeug ------------------------------ 203.17 KiB/219.24 KiB pytest ------------------------------ 301.14 KiB/335.58 KiB greenlet ------------------------------ 479.49 KiB/589.71 KiB pyright ------------------------------ 735.70 KiB/5.31 MiB ruff ------------------------------ 1.17 MiB/11.02 MiB duckdb ------------------------------ 1.86 MiB/19.27 MiB playwright ------------------------------ 110.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (5/33) pytest ------------------------------ 333.14 KiB/335.58 KiB greenlet ------------------------------ 495.49 KiB/589.71 KiB pyright ------------------------------ 959.70 KiB/5.31 MiB ruff ------------------------------ 1.38 MiB/11.02 MiB duckdb ------------------------------ 2.08 MiB/19.27 MiB playwright ------------------------------ 254.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (5/33) greenlet ------------------------------ 511.49 KiB/589.71 KiB pyright ------------------------------ 1.20 MiB/5.31 MiB ruff ------------------------------ 1.65 MiB/11.02 MiB duckdb ------------------------------ 2.35 MiB/19.27 MiB playwright ------------------------------ 536.56 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (5/33) greenlet ------------------------------ 575.49 KiB/589.71 KiB pyright ------------------------------ 1.72 MiB/5.31 MiB ruff ------------------------------ 2.28 MiB/11.02 MiB duckdb ------------------------------ 2.99 MiB/19.27 MiB playwright ------------------------------ 1.16 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (5/33) pyright ------------------------------ 1.79 MiB/5.31 MiB ruff ------------------------------ 2.62 MiB/11.02 MiB duckdb ------------------------------ 3.31 MiB/19.27 MiB playwright ------------------------------ 1.49 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠸ Preparing packages... (28/33) pyright ------------------------------ 1.81 MiB/5.31 MiB ruff ------------------------------ 3.32 MiB/11.02 MiB duckdb ------------------------------ 4.02 MiB/19.27 MiB playwright ------------------------------ 2.17 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠸ Preparing packages... (28/33) pyright ------------------------------ 1.86 MiB/5.31 MiB ruff ------------------------------ 4.59 MiB/11.02 MiB duckdb ------------------------------ 5.30 MiB/19.27 MiB playwright ------------------------------ 3.44 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠸ Preparing packages... (28/33) pyright ------------------------------ 1.93 MiB/5.31 MiB ruff ------------------------------ 5.98 MiB/11.02 MiB duckdb ------------------------------ 6.69 MiB/19.27 MiB playwright ------------------------------ 4.83 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠸ Preparing packages... (28/33) pyright ------------------------------ 2.00 MiB/5.31 MiB ruff ------------------------------ 7.29 MiB/11.02 MiB duckdb ------------------------------ 8.05 MiB/19.27 MiB playwright ------------------------------ 6.14 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠸ Preparing packages... (28/33) pyright ------------------------------ 2.06 MiB/5.31 MiB ruff ------------------------------ 8.29 MiB/11.02 MiB duckdb ------------------------------ 9.11 MiB/19.27 MiB playwright ------------------------------ 7.19 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠼ Preparing packages... (28/33) pyright ------------------------------ 2.11 MiB/5.31 MiB ruff ------------------------------ 9.61 MiB/11.02 MiB duckdb ------------------------------ 10.40 MiB/19.27 MiB playwright ------------------------------ 8.47 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠼ Preparing packages... (28/33) pyright ------------------------------ 2.14 MiB/5.31 MiB ruff ------------------------------ 11.01 MiB/11.02 MiB duckdb ------------------------------ 11.87 MiB/19.27 MiB playwright ------------------------------ 9.92 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠼ Preparing packages... (28/33) pyright ------------------------------ 2.14 MiB/5.31 MiB duckdb ------------------------------ 11.93 MiB/19.27 MiB playwright ------------------------------ 10.00 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠼ Preparing packages... (28/33) pyright ------------------------------ 2.17 MiB/5.31 MiB duckdb ------------------------------ 13.44 MiB/19.27 MiB playwright ------------------------------ 11.55 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠼ Preparing packages... (28/33) pyright ------------------------------ 2.20 MiB/5.31 MiB duckdb ------------------------------ 15.31 MiB/19.27 MiB playwright ------------------------------ 13.39 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠴ Preparing packages... (29/33) pyright ------------------------------ 2.25 MiB/5.31 MiB duckdb ------------------------------ 17.41 MiB/19.27 MiB playwright ------------------------------ 15.42 MiB/43.05 MiB Built scubaduck @ file:///workspace/scubaduck ⠴ Preparing packages... (29/33) pyright ------------------------------ 2.25 MiB/5.31 MiB duckdb ------------------------------ 17.86 MiB/19.27 MiB playwright ------------------------------ 15.87 MiB/43.05 MiB ⠴ Preparing packages... (29/33) pyright ------------------------------ 2.28 MiB/5.31 MiB duckdb ------------------------------ 19.19 MiB/19.27 MiB playwright ------------------------------ 17.34 MiB/43.05 MiB ⠴ Preparing packages... (29/33) pyright ------------------------------ 2.36 MiB/5.31 MiB playwright ------------------------------ 18.87 MiB/43.05 MiB ⠴ Preparing packages... (29/33) pyright ------------------------------ 2.39 MiB/5.31 MiB playwright ------------------------------ 20.81 MiB/43.05 MiB ⠴ Preparing packages... (29/33) pyright ------------------------------ 2.43 MiB/5.31 MiB playwright ------------------------------ 25.33 MiB/43.05 MiB ⠦ Preparing packages... (31/33) pyright ------------------------------ 2.51 MiB/5.31 MiB playwright ------------------------------ 26.85 MiB/43.05 MiB ⠦ Preparing packages... (31/33) pyright ------------------------------ 2.66 MiB/5.31 MiB playwright ------------------------------ 29.28 MiB/43.05 MiB ⠦ Preparing packages... (31/33) pyright ------------------------------ 2.74 MiB/5.31 MiB playwright ------------------------------ 31.26 MiB/43.05 MiB ⠦ Preparing packages... (31/33) pyright ------------------------------ 2.84 MiB/5.31 MiB playwright ------------------------------ 32.90 MiB/43.05 MiB ⠧ Preparing packages... (31/33) pyright ------------------------------ 2.95 MiB/5.31 MiB playwright ------------------------------ 34.90 MiB/43.05 MiB ⠧ Preparing packages... (31/33) pyright ------------------------------ 3.07 MiB/5.31 MiB playwright ------------------------------ 36.45 MiB/43.05 MiB ⠧ Preparing packages... (31/33) pyright ------------------------------ 3.17 MiB/5.31 MiB playwright ------------------------------ 38.40 MiB/43.05 MiB ⠧ Preparing packages... (31/33) pyright ------------------------------ 3.25 MiB/5.31 MiB playwright ------------------------------ 39.94 MiB/43.05 MiB ⠇ Preparing packages... (31/33) pyright ------------------------------ 3.31 MiB/5.31 MiB playwright ------------------------------ 41.09 MiB/43.05 MiB ⠇ Preparing packages... (31/33) pyright ------------------------------ 3.48 MiB/5.31 MiB playwright ------------------------------ 41.92 MiB/43.05 MiB ⠇ Preparing packages... (31/33) pyright ------------------------------ 3.51 MiB/5.31 MiB ⠇ Preparing packages... (31/33) pyright ------------------------------ 3.64 MiB/5.31 MiB ⠇ Preparing packages... (31/33) pyright ------------------------------ 3.90 MiB/5.31 MiB ⠋ Preparing packages... (32/33) pyright ------------------------------ 4.25 MiB/5.31 MiB ⠋ Preparing packages... (32/33) pyright ------------------------------ 4.42 MiB/5.31 MiB ⠋ Preparing packages... (32/33) pyright ------------------------------ 4.57 MiB/5.31 MiB ⠋ Preparing packages... (32/33) Prepared 33 packages in 1.76s ░░░░░░░░░░░░░░░░░░░░ [0/0] Installing wheels... ░░░░░░░░░░░░░░░░░░░░ [0/33] Installing wheels... ░░░░░░░░░░░░░░░░░░░░ [0/33] six==1.17.0 ░░░░░░░░░░░░░░░░░░░░ [1/33] six==1.17.0 ░░░░░░░░░░░░░░░░░░░░ [1/33] pytest-base-url==2.1.0 █░░░░░░░░░░░░░░░░░░░ [2/33] pytest-base-url==2.1.0 █░░░░░░░░░░░░░░░░░░░ [2/33] pluggy==1.6.0 █░░░░░░░░░░░░░░░░░░░ [3/33] pluggy==1.6.0 █░░░░░░░░░░░░░░░░░░░ [3/33] idna==3.10 ██░░░░░░░░░░░░░░░░░░ [4/33] idna==3.10 ██░░░░░░░░░░░░░░░░░░ [4/33] markupsafe==3.0.2 ███░░░░░░░░░░░░░░░░░ [5/33] markupsafe==3.0.2 ███░░░░░░░░░░░░░░░░░ [5/33] nodeenv==1.9.1 ███░░░░░░░░░░░░░░░░░ [6/33] nodeenv==1.9.1 ███░░░░░░░░░░░░░░░░░ [6/33] iniconfig==2.1.0 ████░░░░░░░░░░░░░░░░ [7/33] iniconfig==2.1.0 ████░░░░░░░░░░░░░░░░ [7/33] text-unidecode==1.3 ████░░░░░░░░░░░░░░░░ [8/33] text-unidecode==1.3 ████░░░░░░░░░░░░░░░░ [8/33] flask==3.1.1 █████░░░░░░░░░░░░░░░ [9/33] flask==3.1.1 ███████████████████░ [32/33] pyright==1.1.400 Installed 33 packages in 83ms + 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/xSRPMj-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% 29.7s167.7 MiB [] 0% 31.8s167.7 MiB [] 0% 20.7s167.7 MiB [] 0% 13.2s167.7 MiB [] 0% 8.2s167.7 MiB [] 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[] 5% 2.2s101.4 MiB [] 6% 1.9s101.4 MiB [] 9% 1.4s101.4 MiB [] 11% 1.3s101.4 MiB [] 13% 1.2s101.4 MiB [] 16% 1.0s101.4 MiB [] 19% 0.9s101.4 MiB [] 22% 0.8s101.4 MiB [] 25% 0.7s101.4 MiB [] 25% 0.8s101.4 MiB [] 27% 0.8s101.4 MiB [] 28% 0.8s101.4 MiB [] 30% 0.7s101.4 MiB [] 34% 0.6s101.4 MiB [] 36% 0.6s101.4 MiB [] 39% 0.6s101.4 MiB [] 42% 0.5s101.4 MiB [] 45% 0.5s101.4 MiB [] 48% 0.4s101.4 MiB [] 51% 0.4s101.4 MiB [] 55% 0.4s101.4 MiB [] 58% 0.3s101.4 MiB [] 59% 0.3s101.4 MiB [] 62% 0.3s101.4 MiB [] 66% 0.3s101.4 MiB [] 69% 0.2s101.4 MiB [] 73% 0.2s101.4 MiB [] 77% 0.2s101.4 MiB [] 81% 0.1s101.4 MiB [] 85% 0.1s101.4 MiB [] 88% 0.1s101.4 MiB [] 90% 0.1s101.4 MiB [] 94% 0.0s101.4 MiB [] 98% 0.0s101.4 MiB [] 100% 0.0s Chromium Headless Shell 136.0.7103.25 (playwright build v1169) downloaded to /root/.cache/ms-playwright/chromium_headless_shell-1169 ++ echo 'source .venv/bin/activate'
Internet turned off
I loaded a sqlite database with SCUBADUCK_DB and it failed with: File "/Users/ezyang/Dev/scubaduck/scubaduck/server.py", line 309, in create_app con = _load_database(db_path) ^^^^^^^^^^^^^^^^^^^^^^^ File "/Users/ezyang/Dev/scubaduck/scubaduck/server.py", line 106, in _load_database con.execute(f'INSERT INTO "{t}" VALUES ({placeholders})', row) duckdb.duckdb.ConversionException: Conversion Error: Type INT64 with value 13385262862605259 can't be cast because the value is out of range for the destination type INT32 fix this

I'll check the root AGENTS.md for coding guidelines to help solve the issue.

shell
bash: .venv/bin/activate: No such file or directory root@74ff72a61187:/workspace# ls scubaduck
root@74ff72a61187:/workspace# cd scubaduck root@74ff72a61187:/workspace/scubaduck# ls AGENTS.md codex_setup.sh scubaduck tests README.md pyproject.toml stubs uv.lock
root@74ff72a61187:/workspace/scubaduck# cat AGENTS.md - Use "source .venv/bin/activate" to activate the virtual environment before running any commands - ONLY use non-interactive commands like cat, sed, apply_patch to do edits. Do NOT use interactive editors. - Do NOT attempt to install packages. Only the packages specified in pyproject.toml are available. You cannot add new packages. If you desperately want another package, make a note of it in the final PR description. - Use conventional commits to format PR title - There are no nested AGENTS.md files, this is the only agents file - When using Playwright, ONLY use chromium browser. This browser is already installed. - Use "ruff check" to check lint, "ruff format" to autoformat files and "pyright" to typecheck. - When writing the PR description, include the original prompt supplied by the user. - When you add functionality to the server, add server tests to tests/test_server.py. When you add features to the frontend, add frontend tests to tests/test_web.py

I see the AGENTS file has commands to activate the environment and run checks. Now, onto fixing the bug!

shell
root@74ff72a61187:/workspace/scubaduck# ls scubaduck __init__.py sample.csv server.py static
root@74ff72a61187:/workspace/scubaduck# sed -n '1,160p' scubaduck/server.py from __future__ import annotations from dataclasses import dataclass, field, replace from typing import Any, Dict, List, Tuple, cast import re from datetime import datetime, timedelta, timezone import time from pathlib import Path import os import sqlite3 import traceback import math import duckdb from dateutil import parser as dtparser from flask import Flask, jsonify, request, send_from_directory @dataclass class Filter: column: str op: str value: str | int | float | list[str] | None @dataclass class QueryParams: start: str | None = None end: str | None = None order_by: str | None = None order_dir: str = "ASC" limit: int | None = None columns: list[str] = field(default_factory=lambda: []) filters: list[Filter] = field(default_factory=lambda: []) derived_columns: dict[str, str] = field(default_factory=lambda: {}) graph_type: str = "samples" group_by: list[str] = field(default_factory=lambda: []) aggregate: str | None = None show_hits: bool = False x_axis: str | None = None granularity: str = "Auto" fill: str = "0" table: str = "events" def _normalize_sqlite_type(sql: str) -> str: """Map arbitrary SQLite column types to DuckDB-compatible types.""" t = sql.strip().upper() if "(" in t: t = t.split("(", 1)[0] if "INT" in t: return "INTEGER" if any(key in t for key in ("CHAR", "CLOB", "TEXT")): return "VARCHAR" if "BLOB" in t: return "BLOB" if any(key in t for key in ("DOUBLE", "REAL", "FLOA", "NUMERIC", "DECIMAL")) : return "DOUBLE" if "BOOL" in t: return "BOOLEAN" if "DATE" in t or "TIME" in t: return "TIMESTAMP" if "TIME" in t else "DATE" return "VARCHAR" def _load_database(path: Path) -> duckdb.DuckDBPyConnection: if not path.exists(): raise FileNotFoundError(path) ext = path.suffix.lower() if ext == ".csv": con = duckdb.connect() con.execute( f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{path.as_posix ()}')" ) elif ext in {".db", ".sqlite"}: con = duckdb.connect() try: con.execute("LOAD sqlite") con.execute(f"ATTACH '{path.as_posix()}' AS db (TYPE SQLITE)") tables = [ r[0] for r in con.execute( "SELECT name FROM db.sqlite_master WHERE type='table'" ).fetchall() ] for t in tables: con.execute(f'CREATE VIEW "{t}" AS SELECT * FROM db."{t}"') except Exception: sconn = sqlite3.connect(path) tables = [ r[0] for r in sconn.execute( "SELECT name FROM sqlite_master WHERE type='table'" ).fetchall() ] for t in tables: info = sconn.execute(f'PRAGMA table_info("{t}")').fetchall() col_defs = ", ".join( f"{r[1]} {_normalize_sqlite_type(cast(str, r[2]))}" for r in info ) con.execute(f'CREATE TABLE "{t}" ({col_defs})') placeholders = ",".join("?" for _ in info) for row in sconn.execute(f'SELECT * FROM "{t}"'): con.execute(f'INSERT INTO "{t}" VALUES ({placeholders})', ro w) sconn.close() else: con = duckdb.connect(path) return con _REL_RE = re.compile( r"([+-]?\d+(?:\.\d*)?)\s*(hour|hours|day|days|week|weeks|fortnight|fortnight s)", re.IGNORECASE, ) def parse_time(val: str | None) -> str | None: """Parse an absolute or relative time string into ``YYYY-MM-DD HH:MM:SS``."" " if val is None or val == "": return None s = val.strip() if s.lower() == "now": dt = datetime.now(timezone.utc) return dt.replace(microsecond=0).strftime("%Y-%m-%d %H:%M:%S") m = _REL_RE.fullmatch(s) if m: qty = float(m.group(1)) unit = m.group(2).lower() delta: timedelta if unit.startswith("hour"): delta = timedelta(hours=qty) elif unit.startswith("day"): delta = timedelta(days=qty) elif unit.startswith("week"): delta = timedelta(weeks=qty) elif unit.startswith("fortnight"): delta = timedelta(weeks=2 * qty) else: # pragma: no cover - defensive raise ValueError(f"Unsupported unit: {unit}") dt = datetime.now(timezone.utc) + delta return dt.replace(microsecond=0).strftime("%Y-%m-%d %H:%M:%S") dt = dtparser.parse(s) return dt.replace(microsecond=0, tzinfo=None).strftime("%Y-%m-%d %H:%M:%S") def _granularity_seconds(granularity: str, start: str | None, end: str | None) - > int: gran = granularity.lower() mapping = { "1 second": 1, "5 seconds": 5, "10 seconds": 10, "30 seconds": 30, "1 minute": 60, "4 minutes": 240, "5 minutes": 300,
root@74ff72a61187:/workspace/scubaduck# grep -n '_load_database' -n scubaduck/se rver.py 68:def _load_database(path: Path) -> duckdb.DuckDBPyConnection: 310: con = _load_database(db_path)
root@74ff72a61187:/workspace/scubaduck# sed -n '86,140p' scubaduck/server.py "SELECT name FROM db.sqlite_master WHERE type='table'" ).fetchall() ] for t in tables: con.execute(f'CREATE VIEW "{t}" AS SELECT * FROM db."{t}"') except Exception: sconn = sqlite3.connect(path) tables = [ r[0] for r in sconn.execute( "SELECT name FROM sqlite_master WHERE type='table'" ).fetchall() ] for t in tables: info = sconn.execute(f'PRAGMA table_info("{t}")').fetchall() col_defs = ", ".join( f"{r[1]} {_normalize_sqlite_type(cast(str, r[2]))}" for r in info ) con.execute(f'CREATE TABLE "{t}" ({col_defs})') placeholders = ",".join("?" for _ in info) for row in sconn.execute(f'SELECT * FROM "{t}"'): con.execute(f'INSERT INTO "{t}" VALUES ({placeholders})', ro w) sconn.close() else: con = duckdb.connect(path) return con _REL_RE = re.compile( r"([+-]?\d+(?:\.\d*)?)\s*(hour|hours|day|days|week|weeks|fortnight|fortnight s)", re.IGNORECASE, ) def parse_time(val: str | None) -> str | None: """Parse an absolute or relative time string into ``YYYY-MM-DD HH:MM:SS``."" " if val is None or val == "": return None s = val.strip() if s.lower() == "now": dt = datetime.now(timezone.utc) return dt.replace(microsecond=0).strftime("%Y-%m-%d %H:%M:%S") m = _REL_RE.fullmatch(s) if m: qty = float(m.group(1)) unit = m.group(2).lower() delta: timedelta if unit.startswith("hour"): delta = timedelta(hours=qty) elif unit.startswith("day"): delta = timedelta(days=qty) elif unit.startswith("week"): delta = timedelta(weeks=qty) elif unit.startswith("fortnight"):

I think the issue arises when SQLite types get mapped incorrectly. I need to verify if "INTEGER" maps to 32-bit "INTEGER" in DuckDB, or should be "BIGINT" to avoid overflow.

shell
root@74ff72a61187:/workspace/scubaduck# grep -n "_normalize_sqlite_type" -n -r scubaduck/server.py:48:def _normalize_sqlite_type(sql: str) -> str: scubaduck/server.py:102: f"{r[1]} {_normalize_sqlite_type(cas t(str, r[2]))}" for r in info
root@74ff72a61187:/workspace/scubaduck# sed -n '40,70p' scubaduck/server.py aggregate: str | None = None show_hits: bool = False x_axis: str | None = None granularity: str = "Auto" fill: str = "0" table: str = "events" def _normalize_sqlite_type(sql: str) -> str: """Map arbitrary SQLite column types to DuckDB-compatible types.""" t = sql.strip().upper() if "(" in t: t = t.split("(", 1)[0] if "INT" in t: return "INTEGER" if any(key in t for key in ("CHAR", "CLOB", "TEXT")): return "VARCHAR" if "BLOB" in t: return "BLOB" if any(key in t for key in ("DOUBLE", "REAL", "FLOA", "NUMERIC", "DECIMAL")) : return "DOUBLE" if "BOOL" in t: return "BOOLEAN" if "DATE" in t or "TIME" in t: return "TIMESTAMP" if "TIME" in t else "DATE" return "VARCHAR" def _load_database(path: Path) -> duckdb.DuckDBPyConnection: if not path.exists(): raise FileNotFoundError(path)

I'll replace "INTEGER" with "BIGINT" and check for tests related to that update.

shell
root@74ff72a61187:/workspace/scubaduck# ls tests conftest.py test_server.py test_web.py
root@74ff72a61187:/workspace/scubaduck# sed -n '1,160p' tests/test_server.py from __future__ import annotations import json from pathlib import Path from typing import cast import duckdb from scubaduck import server import pytest def test_basic_query() -> None: app = server.app client = app.test_client() payload = { "table": "events", "start": "2024-01-01 00:00:00", "end": "2024-01-02 00:00:00", "order_by": "timestamp", "order_dir": "ASC", "limit": 10, "columns": ["timestamp", "event", "value", "user"], "filters": [], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert data rows = data["rows"] # We expect first three rows (until 2024-01-02 00:00:00) assert len(rows) == 3 assert rows[0][1] == "login" assert rows[1][1] == "logout" def test_js_served() -> None: app = server.app client = app.test_client() rv = client.get("/js/chip_input.js") assert rv.status_code == 200 assert b"initChipInput" in rv.data def test_filter_multi_token() -> None: app = server.app client = app.test_client() payload = { "table": "events", "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 = { "table": "events", "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 = { "table": "events", "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 { "table": "events", "start": "2024-01-01 00:00:00",

I'm reviewing tests to find any integer operations or column type references.

shell
root@74ff72a61187:/workspace/scubaduck# sed -n '160,320p' tests/test_server.py "start": "2024-01-01 00:00:00", "end": "2024-01-02 00:00:00", "order_by": "timestamp", "order_dir": "ASC", "limit": 10, "columns": ["timestamp", "event", "value", "user"], "filters": [], } def test_database_types(tmp_path: Path) -> None: csv_file = tmp_path / "events.csv" csv_file.write_text(Path("scubaduck/sample.csv").read_text()) sqlite_file = tmp_path / "events.sqlite" import sqlite3 conn = sqlite3.connect(sqlite_file) conn.execute( "CREATE TABLE events (timestamp TEXT, event TEXT, value INTEGER, user TE XT)" ) with open(csv_file) as f: next(f) for line in f: ts, ev, val, user = line.strip().split(",") conn.execute( "INSERT INTO events VALUES (?, ?, ?, ?)", (ts, ev, int(val), use r) ) conn.commit() conn.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcce ssIssue] duckdb_file = tmp_path / "events.duckdb" con = duckdb.connect(duckdb_file) con.execute( f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{csv_file.as_posix ()}')" ) con.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcces sIssue] for db in (csv_file, sqlite_file, duckdb_file): app = server.create_app(db) client = app.test_client() payload = _make_payload() rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/js on" ) rows = rv.get_json()["rows"] assert len(rows) == 3 def test_sqlite_longvarchar(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None: sqlite_file = tmp_path / "events.sqlite" import sqlite3 conn = sqlite3.connect(sqlite_file) conn.execute( "CREATE TABLE events (timestamp TEXT, url LONGVARCHAR, title VARCHAR(10) )" ) conn.execute( "INSERT INTO events VALUES ('2024-01-01 00:00:00', 'https://a.com', 'Hom e')" ) conn.commit() conn.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcce ssIssue] from typing import Any real_connect = duckdb.connect def failing_connect(*args: Any, **kwargs: Any) -> Any: real = real_connect(*args, **kwargs) class Wrapper: def __init__(self, con: duckdb.DuckDBPyConnection) -> None: self.con = con self._failed = False def execute(self, sql: str, *a: Any, **kw: Any): if not self._failed and sql == "LOAD sqlite": self._failed = True raise RuntimeError("fail") return self.con.execute(sql, *a, **kw) def __getattr__(self, name: str) -> object: return getattr(self.con, name) return Wrapper(real) monkeypatch.setattr(server.duckdb, "connect", failing_connect) app = server.create_app(sqlite_file) client = app.test_client() payload = { "table": "events", "start": "2024-01-01 00:00:00", "end": "2024-01-01 01:00:00", "order_by": "timestamp", "columns": ["timestamp", "url", "title"], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert rv.status_code == 200 assert data["rows"][0][1] == "https://a.com" def test_envvar_db(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: csv_file = tmp_path / "custom.csv" csv_file.write_text("timestamp,event,value,user\n2024-01-01 00:00:00,login,5 ,bob\n") monkeypatch.setenv("SCUBADUCK_DB", str(csv_file)) app = server.create_app() client = app.test_client() payload = _make_payload() rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) rows = rv.get_json()["rows"] assert len(rows) == 1 def test_envvar_db_missing(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> N one: missing = tmp_path / "missing.sqlite" monkeypatch.setenv("SCUBADUCK_DB", str(missing)) with pytest.raises(FileNotFoundError): server.create_app() def test_group_by_table() -> None: app = server.app client = app.test_client() payload = { "table": "events", "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]

I'm paging through the tests to make sure I reach the end and confirm everything.

shell
root@74ff72a61187:/workspace/scubaduck# sed -n '320,640p' tests/test_server.py 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 = { "table": "events", "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 = { "table": "events", "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 = { "table": "events", "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 = { "table": "events", "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 = { "table": "events", "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() 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 = { "table": "events", "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" ... 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"]) == 2 assert all(r[1] == "alice" for r in data["rows"]) def test_timeseries_auto_and_fine_buckets() -> None: app = server.app client = app.test_client() def run(gran: str) -> None: payload = { "start": "2024-01-01 00:00:00", "end": "2024-01-02 03:00:00", "graph_type": "timeseries", "columns": ["value"], "x_axis": "timestamp", "granularity": gran, } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/js on" ) data = rv.get_json() assert rv.status_code == 200 from dateutil import parser start = parser.parse(cast(str, payload["start"])).replace(tzinfo=None) buckets = [ parser.parse(cast(str, r[0])).replace(tzinfo=None) for r in data["ro ws"] ] assert buckets[0] == start if len(buckets) > 1: step = (buckets[1] - buckets[0]).total_seconds() assert step % data["bucket_size"] == 0 assert any(r[1] != 0 for r in data["rows"]) run("Auto") run("Fine") def test_timeseries_string_column_error() -> None: app = server.app client = app.test_client() payload = { "table": "events", "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/json" ) data = rv.get_json() assert rv.status_code == 400 assert "Aggregate" in data["error"] def test_derived_column_basic() -> None: app = server.app client = app.test_client() payload = { "table": "events", "start": "2024-01-01 00:00:00", "end": "2024-01-03 00:00:00", "limit": 10, "columns": ["timestamp"], "derived_columns": {"val2": "value * 2"}, "filters": [], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert rv.status_code == 200 assert data["rows"][0][1] == 20 def test_timeseries_derived_column() -> None: app = server.app client = app.test_client() payload = { "table": "events", "start": "2024-01-01 00:00:00", "end": "2024-01-03 00:00:00", "graph_type": "timeseries", "granularity": "1 hour", "limit": 7, "columns": ["value"], "derived_columns": {"derived_1": "value * 2"}, } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert rv.status_code == 200 rows = data["rows"] assert all(r[2] == r[1] * 2 for r in rows) def test_default_start_end_returned() -> None: app = server.app client = app.test_client() payload = { "table": "events", "order_by": "timestamp", "limit": 5, "columns": ["timestamp"], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert rv.status_code == 200 assert data["start"] == "2024-01-01 00:00:00" assert data["end"] == "2024-01-02 03:00:00"

I'm skimming to the end of the tests to see if anything else is there.

shell
root@74ff72a61187:/workspace/scubaduck# sed -n '640,960p' tests/test_server.py

I'll adjust _normalize_sqlite_type to return "BIGINT" and verify the tests pass.

shell
root@74ff72a61187:/workspace/scubaduck# cat scubaduck/sample.csv 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

The issue occurs when SQLite has big integers, causing DuckDB to fail in fallback. I'll add a test to simulate this.

shell
root@74ff72a61187:/workspace/scubaduck# grep -n 'longvarchar' -n tests/test_serv er.py 209:def test_sqlite_longvarchar(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
root@74ff72a61187:/workspace/scubaduck# sed -n '200,240p' tests/test_server.py client = app.test_client() payload = _make_payload() rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/js on" ) rows = rv.get_json()["rows"] assert len(rows) == 3 def test_sqlite_longvarchar(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None: sqlite_file = tmp_path / "events.sqlite" import sqlite3 conn = sqlite3.connect(sqlite_file) conn.execute( "CREATE TABLE events (timestamp TEXT, url LONGVARCHAR, title VARCHAR(10) )" ) conn.execute( "INSERT INTO events VALUES ('2024-01-01 00:00:00', 'https://a.com', 'Hom e')" ) conn.commit() conn.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcce ssIssue] from typing import Any real_connect = duckdb.connect def failing_connect(*args: Any, **kwargs: Any) -> Any: real = real_connect(*args, **kwargs) class Wrapper: def __init__(self, con: duckdb.DuckDBPyConnection) -> None: self.con = con self._failed = False def execute(self, sql: str, *a: Any, **kw: Any): if not self._failed and sql == "LOAD sqlite": self._failed = True raise RuntimeError("fail") return self.con.execute(sql, *a, **kw)
return getattr(self.con, name) return Wrapper(real) monkeypatch.setattr(server.duckdb, "connect", failing_connect) app = server.create_app(sqlite_file) client = app.test_client() payload = { "table": "events", "start": "2024-01-01 00:00:00", "end": "2024-01-01 01:00:00", "order_by": "timestamp", "columns": ["timestamp", "url", "title"], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert rv.status_code == 200 assert data["rows"][0][1] == "https://a.com" def test_envvar_db(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: csv_file = tmp_path / "custom.csv" csv_file.write_text("timestamp,event,value,user\n2024-01-01 00:00:00,login,5 ,bob\n") monkeypatch.setenv("SCUBADUCK_DB", str(csv_file)) app = server.create_app() client = app.test_client() payload = _make_payload() rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) rows = rv.get_json()["rows"] assert len(rows) == 1 def test_envvar_db_missing(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> N one: missing = tmp_path / "missing.sqlite" monkeypatch.setenv("SCUBADUCK_DB", str(missing)) with pytest.raises(FileNotFoundError): server.create_app() def test_group_by_table() -> None: app = server.app client = app.test_client() payload = { "table": "events", "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]

I'm planning a test using SQLite's events table with a large integer, 13385262862605259. I'll simulate the error from the longvarchar test by setting up duckdb.connect to fail. Then, I'll query the table to verify the integer retrieval works as expected. Searching for _make_payload to check column setup.

shell
root@74ff72a61187:/workspace/scubaduck# grep -n '_make_payload' -n tests/test_se rver.py 157:def _make_payload() -> dict[str, object]: 201: payload = _make_payload() 271: payload = _make_payload()
return { "table": "events", "start": "2024-01-01 00:00:00", "end": "2024-01-02 00:00:00", "order_by": "timestamp", "order_dir": "ASC", "limit": 10, "columns": ["timestamp", "event", "value", "user"], "filters": [], } def test_database_types(tmp_path: Path) -> None: csv_file = tmp_path / "events.csv" csv_file.write_text(Path("scubaduck/sample.csv").read_text()) sqlite_file = tmp_path / "events.sqlite" import sqlite3 conn = sqlite3.connect(sqlite_file) conn.execute( "CREATE TABLE events (timestamp TEXT, event TEXT, value INTEGER, user TE XT)" ) with open(csv_file) as f: next(f) for line in f: ts, ev, val, user = line.strip().split(",") conn.execute( "INSERT INTO events VALUES (?, ?, ?, ?)", (ts, ev, int(val), use r) ) conn.commit() conn.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcce ssIssue] duckdb_file = tmp_path / "events.duckdb" con = duckdb.connect(duckdb_file) con.execute( f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{csv_file.as_posix ()}')" ) con.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcces sIssue] for db in (csv_file, sqlite_file, duckdb_file): app = server.create_app(db) client = app.test_client() payload = _make_payload() rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/js on" ) rows = rv.get_json()["rows"] assert len(rows) == 3

I’ll create a new test for the big integer in a table, using SQLite with minimal payload.

I’ll check whether a timestamp is needed or if default start/end handles it automatically.

shell
root@74ff72a61187:/workspace/scubaduck# grep -n 'default_start_end' -n scubaduck /server.py

I'll take a look around the server.create_app to understand its structure.

shell
root@74ff72a61187:/workspace/scubaduck# grep -n 'create_app' -n scubaduck/server .py 303:def create_app(db_file: str | Path | None = None) -> Flask: 571:app = create_app()
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}" elif params.graph_type == "timeseries": query += " ORDER BY bucket" 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") if db_file is None: env_db = os.environ.get("SCUBADUCK_DB") if env_db: db_file = env_db db_path = Path(db_file or Path(__file__).with_name("sample.csv")).resolve() con = _load_database(db_path) tables = [r[0] for r in con.execute("SHOW TABLES").fetchall()] if not tables: raise ValueError("No tables found in database") default_table = tables[0] columns_cache: Dict[str, Dict[str, str]] = {} def get_columns(table: str) -> Dict[str, str]: if table not in columns_cache: rows = con.execute(f'PRAGMA table_info("{table}")').fetchall() if not rows: raise ValueError(f"Unknown table: {table}") columns_cache[table] = {r[1]: r[2] for r in rows} return columns_cache[table] sample_cache: Dict[Tuple[str, str, str], Tuple[List[str], float]] = {} CACHE_TTL = 60.0 CACHE_LIMIT = 200 @app.route("/") def index() -> Any: # pyright: ignore[reportUnusedFunction] assert app.static_folder is not None return send_from_directory(app.static_folder, "index.html") @app.route("/js/<path:filename>") def js(filename: str) -> Any: # pyright: ignore[reportUnusedFunction] assert app.static_folder is not None

I'm moving up to look at the _construct_query function now.

shell
root@74ff72a61187:/workspace/scubaduck# grep -n '_construct_query' -n scubaduck/ server.py

I'll check more lines, around 120 to 200, to find the query-building functions.

shell
root@74ff72a61187:/workspace/scubaduck# grep -n 'get_columns' -n scubaduck/serve r.py 317: def get_columns(table: str) -> Dict[str, str]: 372: column_types = get_columns(table) 422: column_types = get_columns(params.table)
root@74ff72a61187:/workspace/scubaduck# sed -n '360,444p' scubaduck/server.py def _cache_set(key: Tuple[str, str, str], vals: List[str]) -> None: sample_cache[key] = (vals, time.time()) if len(sample_cache) > CACHE_LIMIT: oldest = min(sample_cache.items(), key=lambda kv: kv[1][1])[0] del sample_cache[oldest] @app.route("/api/samples") def sample_values() -> Any: # pyright: ignore[reportUnusedFunction] table = request.args.get("table", default_table) column = request.args.get("column") substr = request.args.get("q", "") column_types = get_columns(table) if not column or column not in column_types: return jsonify([]) ctype = column_types[column].upper() if "CHAR" not in ctype and "STRING" not in ctype and "VARCHAR" not in ct ype: return jsonify([]) key = (table, column, substr) cached = _cache_get(key) if cached is not None: return jsonify(cached) rows = con.execute( f"SELECT DISTINCT {column} FROM \"{table}\" WHERE CAST({column} AS V ARCHAR) 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"), table=payload.get("table", default_table), ) for f in payload.get("filters", []): params.filters.append(Filter(f["column"], f["op"], f.get("value"))) if params.table not in tables: return jsonify({"error": "Invalid table"}), 400 column_types = get_columns(params.table) 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()) valid_cols.update(params.derived_columns.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:

I'm moving ahead to see more content.

shell
root@74ff72a61187:/workspace/scubaduck# sed -n '444,528p' scubaduck/server.py 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 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 if c not in column_types: 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, ) if params.start is None or params.end is None: axis = params.x_axis or "timestamp" row = cast( tuple[datetime | None, datetime | None], con.execute( f'SELECT min({axis}), max({axis}) FROM "{params.table}"' ).fetchall()[0], ) mn, mx = row if params.start is None and mn is not None: params.start = ( mn.strftime("%Y-%m-%d %H:%M:%S") if not isinstance(mn, str) else mn ) if params.end is None and mx is not None: params.end = ( mx.strftime("%Y-%m-%d %H:%M:%S") if not isinstance(mx, str) else mx ) bucket_size: int | None = None if params.graph_type == "timeseries": bucket_size = _granularity_seconds( params.granularity,

I need to scroll a little more to capture all the relevant content.

shell
root@74ff72a61187:/workspace/scubaduck# sed -n '528,612p' scubaduck/server.py params.granularity, params.start if isinstance(params.start, str) else None, params.end if isinstance(params.end, str) else None, ) if ( params.limit is not None and params.start is not None and params.end is not None ): try: start_dt = dtparser.parse(params.start) end_dt = dtparser.parse(params.end) buckets = math.ceil( (end_dt - start_dt).total_seconds() / bucket_size ) if buckets > 1: params.limit *= buckets except Exception: pass sql = build_query(params, column_types) try: rows = con.execute(sql).fetchall() except Exception as exc: tb = traceback.format_exc() print(f"Query failed:\n{sql}\n{tb}") return ( jsonify({"sql": sql, "error": str(exc), "traceback": tb}), 400, ) result: Dict[str, Any] = {"sql": sql, "rows": rows} if params.start is not None: result["start"] = str(params.start) if params.end is not None: result["end"] = str(params.end) if bucket_size is not None: result["bucket_size"] = bucket_size return jsonify(result) return app app = create_app() if __name__ == "__main__": app.run(debug=True)

I'll create a table, insert a row with a big integer, and test database loading.

I'll create a minimal dataset with a big integer to test SQLite to DuckDB loading.

I'll update the mapping to return "BIGINT" for "INT" types, handling edge cases along the way.

shell
, 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. * Limit - Help text: "Choose the maximum number of results 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." * Filters - You can create as many filters as you want. You can either write a f ilter using a UI or manual SQL. In the UI, filter consists of a column name, a r elation (e.g., =, !=, <, >) and then a text field. The text field is a token inp ut. It accepts multiple tokens for = relation, in which case we match using an O R for all options. There is also a "Columns" tab which lets you view all fields in the table, organ ized by their type. You can also define derived columns, by specifying a column name and SQL expression. Derived columns can be used for all parts of the UI, in cluding filters/group by/etc. Columns have checkboxes indicating if we should SE LECT them or not. Each selected column shows up in the graph. There is an All/N one link which can be used to select/deselect all checkboxes. The query UI constructs a SQL query that intuitively has this form: ``` SELECT column, column, ..., FROM table WHERE time >= min-timestamp AND time <= max-timestamp [AND condition ...] ORDER BY aggregate(column) LIMIT number ``` You should write tests for the server backend, demonstrating that at specific qu ery values we get back the correct rows of data. ## Running the server Activate the virtual environment and run the Flask development server: ```bash flask --app scubaduck.server run --debug ``` By default the server loads `sample.csv`. Set the `SCUBADUCK_DB` environment variable to point at a different database file (CSV, SQLite or DuckDB) if you want to use another dataset. If the file does not exist, the server will raise a `FileNotFoundError` during startup.

I checked the first 265 lines of the README and want to inspect the remainder.

shell
root@74ff72a61187:/workspace/scubaduck# tail -n 20 README.md AND time <= max-timestamp [AND condition ...] ORDER BY aggregate(column) LIMIT number ``` You should write tests for the server backend, demonstrating that at specific qu ery values we get back the correct rows of data. ## Running the server Activate the virtual environment and run the Flask development server: ```bash flask --app scubaduck.server run --debug ``` By default the server loads `sample.csv`. Set the `SCUBADUCK_DB` environment variable to point at a different database file (CSV, SQLite or DuckDB) if you want to use another dataset. If the file does not exist, the server will raise a `FileNotFoundError` during startup.

I'll implement the fix and run ruff check, ruff format, and pyright.

shell
root@74ff72a61187:/workspace/scubaduck# git status --short
root@74ff72a61187:/workspace/scubaduck# source .venv/bin/activate
(scubaduck) root@74ff72a61187:/workspace/scubaduck# ruff check All checks passed!
(scubaduck) root@74ff72a61187:/workspace/scubaduck# ruff format --check 6 files already formatted
(scubaduck) root@74ff72a61187:/workspace/scubaduck# pyright
0 errors, 0 warnings, 0 informations (scubaduck) root@74ff72a61187:/workspace/scubaduck#

The baseline tests are passing, so I'll go ahead and make changes to server.py.

shell
(scubaduck) root@74ff72a61187:/workspace/scubaduck# sed -n '54,60p' scubaduck/se rver.py return "INTEGER" if any(key in t for key in ("CHAR", "CLOB", "TEXT")): return "VARCHAR" if "BLOB" in t: return "BLOB" if any(key in t for key in ("DOUBLE", "REAL", "FLOA", "NUMERIC", "DECIMAL")) : return "DOUBLE"
(scubaduck) root@74ff72a61187:/workspace/scubaduck# sed -n '50,66p' scubaduck/se rver.py t = sql.strip().upper() if "(" in t: t = t.split("(", 1)[0] if "INT" in t: return "INTEGER" if any(key in t for key in ("CHAR", "CLOB", "TEXT")): return "VARCHAR" if "BLOB" in t: return "BLOB" if any(key in t for key in ("DOUBLE", "REAL", "FLOA", "NUMERIC", "DECIMAL")) : return "DOUBLE" if "BOOL" in t: return "BOOLEAN" if "DATE" in t or "TIME" in t: return "TIMESTAMP" if "TIME" in t else "DATE" return "VARCHAR" (scubaduck) root@74ff72a61187:/workspace/scubaduck#

I’ll modify the return statement to give "BIGINT" as the output.

shell
(scubaduck) root@74ff72a61187:/workspace/scubaduck# apply_patch<<'PATCH' > *** Begin Patch > *** Update File: scubaduck/server.py > @@ > t = sql.strip().upper() > if "(" in t: > t = t.split("(", 1)[0] > if "INT" in t: > - return "INTEGER" > + # SQLite only has a single INTEGER type which is always 64-bit. > + # Use DuckDB's BIGINT to avoid overflow when values exceed INT32. > + return "BIGINT" > *** End Patch > PATCH Success. Updated the following files: M scubaduck/server.py (scubaduck) root@74ff72a61187:/workspace/scubaduck#

I’ll open lines 200-240 in test_server.py to replicate the failing wrapper for the big int test.

shell
_server.py client = app.test_client() payload = _make_payload() rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/js on" ) rows = rv.get_json()["rows"] assert len(rows) == 3 def test_sqlite_longvarchar(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None: sqlite_file = tmp_path / "events.sqlite" import sqlite3 conn = sqlite3.connect(sqlite_file) conn.execute( "CREATE TABLE events (timestamp TEXT, url LONGVARCHAR, title VARCHAR(10) )" ) conn.execute( "INSERT INTO events VALUES ('2024-01-01 00:00:00', 'https://a.com', 'Hom e')" ) conn.commit() conn.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcce ssIssue] from typing import Any real_connect = duckdb.connect def failing_connect(*args: Any, **kwargs: Any) -> Any: real = real_connect(*args, **kwargs) class Wrapper: def __init__(self, con: duckdb.DuckDBPyConnection) -> None: self.con = con self._failed = False def execute(self, sql: str, *a: Any, **kw: Any): if not self._failed and sql == "LOAD sqlite": self._failed = True raise RuntimeError("fail") return self.con.execute(sql, *a, **kw)
(scubaduck) root@74ff72a61187:/workspace/scubaduck# sed -n '240,280p' tests/test _server.py def __getattr__(self, name: str) -> object: return getattr(self.con, name) return Wrapper(real) monkeypatch.setattr(server.duckdb, "connect", failing_connect) app = server.create_app(sqlite_file) client = app.test_client() payload = { "table": "events", "start": "2024-01-01 00:00:00", "end": "2024-01-01 01:00:00", "order_by": "timestamp", "columns": ["timestamp", "url", "title"], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert rv.status_code == 200 assert data["rows"][0][1] == "https://a.com" def test_envvar_db(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: csv_file = tmp_path / "custom.csv" csv_file.write_text("timestamp,event,value,user\n2024-01-01 00:00:00,login,5 ,bob\n") monkeypatch.setenv("SCUBADUCK_DB", str(csv_file)) app = server.create_app() client = app.test_client() payload = _make_payload() rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) rows = rv.get_json()["rows"] assert len(rows) == 1 def test_envvar_db_missing(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> N one: missing = tmp_path / "missing.sqlite"
with pytest.raises(FileNotFoundError): server.create_app() def test_group_by_table() -> None: app = server.app client = app.test_client() payload = { "table": "events", "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 = { "table": "events", "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 = { "table": "events", "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 (scubaduck) root@74ff72a61187:/workspace/scubaduck#

I'll add a new test after test_sqlite_longvarchar and craft the patch.

shell
(scubaduck) root@74ff72a61187:/workspace/scubaduck# grep -n 'test_sqlite_longvar char' -n -n tests/test_server.py 209:def test_sqlite_longvarchar(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None: (scubaduck) root@74ff72a61187:/workspace/scubaduck#

Time to open the patch and add the new test.

shell
_server.py def test_sqlite_longvarchar(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None: sqlite_file = tmp_path / "events.sqlite" import sqlite3 conn = sqlite3.connect(sqlite_file) conn.execute( "CREATE TABLE events (timestamp TEXT, url LONGVARCHAR, title VARCHAR(10) )" ) conn.execute( "INSERT INTO events VALUES ('2024-01-01 00:00:00', 'https://a.com', 'Hom e')" ) conn.commit() conn.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcce ssIssue] from typing import Any real_connect = duckdb.connect def failing_connect(*args: Any, **kwargs: Any) -> Any: real = real_connect(*args, **kwargs) class Wrapper: def __init__(self, con: duckdb.DuckDBPyConnection) -> None: self.con = con self._failed = False def execute(self, sql: str, *a: Any, **kw: Any): if not self._failed and sql == "LOAD sqlite": self._failed = True raise RuntimeError("fail") return self.con.execute(sql, *a, **kw)
(scubaduck) root@74ff72a61187:/workspace/scubaduck# sed -n '240,266p' tests/test _server.py def __getattr__(self, name: str) -> object: return getattr(self.con, name) return Wrapper(real) monkeypatch.setattr(server.duckdb, "connect", failing_connect) app = server.create_app(sqlite_file) client = app.test_client() payload = { "table": "events", "start": "2024-01-01 00:00:00", "end": "2024-01-01 01:00:00", "order_by": "timestamp", "columns": ["timestamp", "url", "title"], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert rv.status_code == 200 assert data["rows"][0][1] == "https://a.com" def test_envvar_db(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: csv_file = tmp_path / "custom.csv" (scubaduck) root@74ff72a61187:/workspace/scubaduck#

I'll add the new test right after test_sqlite_longvarchar, at line 236 or 255.

shell
_server.py conn.commit() conn.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAcce ssIssue] from typing import Any real_connect = duckdb.connect def failing_connect(*args: Any, **kwargs: Any) -> Any: real = real_connect(*args, **kwargs) class Wrapper: def __init__(self, con: duckdb.DuckDBPyConnection) -> None: self.con = con self._failed = False def execute(self, sql: str, *a: Any, **kw: Any): if not self._failed and sql == "LOAD sqlite": self._failed = True raise RuntimeError("fail") return self.con.execute(sql, *a, **kw) def __getattr__(self, name: str) -> object: return getattr(self.con, name) return Wrapper(real) monkeypatch.setattr(server.duckdb, "connect", failing_connect) app = server.create_app(sqlite_file) client = app.test_client() payload = { "table": "events", "start": "2024-01-01 00:00:00", "end": "2024-01-01 01:00:00", "order_by": "timestamp", "columns": ["timestamp", "url", "title"], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json()
data = rv.get_json() assert rv.status_code == 200 assert data["rows"][0][1] == "https://a.com" def test_envvar_db(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: csv_file = tmp_path / "custom.csv" csv_file.write_text("timestamp,event,value,user\n2024-01-01 00:00:00,login,5 ,bob\n") monkeypatch.setenv("SCUBADUCK_DB", str(csv_file)) app = server.create_app() client = app.test_client() payload = _make_payload() rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) rows = rv.get_json()["rows"] assert len(rows) == 1 def test_envvar_db_missing(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> N one: missing = tmp_path / "missing.sqlite" monkeypatch.setenv("SCUBADUCK_DB", str(missing)) with pytest.raises(FileNotFoundError): server.create_app() def test_group_by_table() -> None: app = server.app client = app.test_client() payload = { "table": "events", "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, } (scubaduck) root@74ff72a61187:/workspace/scubaduck#

I'll add a new test after asserting the URL at data['rows'][0][1].

shell
> *** Update File: tests/test_server.py > @@ > assert data["rows"][0][1] == "https://a.com" > + > + > +def test_sqlite_bigint(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> No ne: > + sqlite_file = tmp_path / "big.sqlite" > + import sqlite3 > + > + conn = sqlite3.connect(sqlite_file) > + conn.execute( > + "CREATE TABLE events (timestamp TEXT, value INTEGER)" > + ) > + big_value = 13385262862605259 > + conn.execute( > + "INSERT INTO events VALUES ('2024-01-01 00:00:00', ?)", > + (big_value,), > + ) > + conn.commit() > + conn.close() # pyright: ignore[reportUnknownMemberType, reportAttributeA ccessIssue] > + > + from typing import Any > + > + real_connect = duckdb.connect > + > + def failing_connect(*args: Any, **kwargs: Any) -> Any: > + real = real_connect(*args, **kwargs) > + > + class Wrapper: > + def __init__(self, con: duckdb.DuckDBPyConnection) -> None: > + self.con = con > + self._failed = False > + > + def execute(self, sql: str, *a: Any, **kw: Any): > + if not self._failed and sql == "LOAD sqlite": > + self._failed = True > + raise RuntimeError("fail") > + return self.con.execute(sql, *a, **kw) > + > + def __getattr__(self, name: str) -> object: > + return getattr(self.con, name) > + > + return Wrapper(real) > + > + monkeypatch.setattr(server.duckdb, "connect", failing_connect) > + > + app = server.create_app(sqlite_file) > + client = app.test_client() > + payload = { > + "table": "events", > + "order_by": "timestamp", > + "columns": ["timestamp", "value"], > + } > + rv = client.post( > + "/api/query", data=json.dumps(payload), content_type="application/jso n" > + ) > + data = rv.get_json() > + assert rv.status_code == 200 > + assert data["rows"][0][1] == big_value > *** End Patch > PATCH Success. Updated the following files: M tests/test_server.py (scubaduck) root@74ff72a61187:/workspace/scubaduck#

Time to use ruff format and clean up the code automatically.

shell
(scubaduck) root@74ff72a61187:/workspace/scubaduck# ruff format scubaduck/server .py tests/test_server.py 1 file reformatted, 1 file left unchanged (scubaduck) root@74ff72a61187:/workspace/scubaduck#

I need to perform a ruff check on the code now.

shell
(scubaduck) root@74ff72a61187:/workspace/scubaduck# ruff check scubaduck/server. py tests/test_server.py All checks passed!
(scubaduck) root@74ff72a61187:/workspace/scubaduck# pyright
0 errors, 0 warnings, 0 informations
(scubaduck) root@74ff72a61187:/workspace/scubaduck# pytest -q
bringing up nodes...



........................................................................ [ 94%] .... [100%] 76 passed in 10.72s (scubaduck) root@74ff72a61187:/workspace/scubaduck#

Tests are good, so I'll go ahead and commit the changes now.

shell
(scubaduck) root@74ff72a61187:/workspace/scubaduck# git status --short M scubaduck/server.py M tests/test_server.py
(scubaduck) root@74ff72a61187:/workspace/scubaduck# git add scubaduck/server.py tests/test_server.py
(scubaduck) root@74ff72a61187:/workspace/scubaduck# git commit -m "fix: support large integers from sqlite" && git status --short [work a0093fe] fix: support large integers from sqlite 2 files changed, 57 insertions(+), 1 deletion(-)
(scubaduck) root@74ff72a61187:/workspace/scubaduck# git status --short (scubaduck) root@74ff72a61187:/workspace/scubaduck#

I'll write the PR message and reference the changed lines in server.py.

shell
(scubaduck) root@74ff72a61187:/workspace/scubaduck# nl -ba scubaduck/server.py | sed -n '50,62p' 50 t = sql.strip().upper() 51 if "(" in t: 52 t = t.split("(", 1)[0] 53 if "INT" in t: 54 # SQLite only has a single INTEGER type which is always 64-bit. 55 # Use DuckDB's BIGINT to avoid overflow when values exceed INT32 . 56 return "BIGINT" 57 if any(key in t for key in ("CHAR", "CLOB", "TEXT")): 58 return "VARCHAR" 59 if "BLOB" in t: 60 return "BLOB" 61 if any(key in t for key in ("DOUBLE", "REAL", "FLOA", "NUMERIC", "DE CIMAL")): 62 return "DOUBLE" (scubaduck) root@74ff72a61187:/workspace/scubaduck#

I'm starting on the new test lines now.

shell
(scubaduck) root@74ff72a61187:/workspace/scubaduck# nl -ba tests/test_server.py | sed -n '236,316p' 236 if not self._failed and sql == "LOAD sqlite": 237 self._failed = True 238 raise RuntimeError("fail") 239 return self.con.execute(sql, *a, **kw) 240 241 def __getattr__(self, name: str) -> object: 242 return getattr(self.con, name) 243 244 return Wrapper(real) 245 246 monkeypatch.setattr(server.duckdb, "connect", failing_connect) 247 248 app = server.create_app(sqlite_file) 249 client = app.test_client() 250 payload = { 251 "table": "events", 252 "start": "2024-01-01 00:00:00", 253 "end": "2024-01-01 01:00:00", 254 "order_by": "timestamp", 255 "columns": ["timestamp", "url", "title"], 256 } 257 rv = client.post( 258 "/api/query", data=json.dumps(payload), content_type="applicatio n/json" 259 ) 260 data = rv.get_json() 261 assert rv.status_code == 200 262 assert data["rows"][0][1] == "https://a.com" 263 264 265 def test_sqlite_bigint(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None: 266 sqlite_file = tmp_path / "big.sqlite" 267 import sqlite3 268 269 conn = sqlite3.connect(sqlite_file) 270 conn.execute("CREATE TABLE events (timestamp TEXT, value INTEGER)") 271 big_value = 13385262862605259 272 conn.execute( 273 "INSERT INTO events VALUES ('2024-01-01 00:00:00', ?)", 274 (big_value,), 275 ) 276 conn.commit() 277 conn.close() # pyright: ignore[reportUnknownMemberType, reportAttri buteAccessIssue] 278 279 from typing import Any 280 281 real_connect = duckdb.connect 282 283 def failing_connect(*args: Any, **kwargs: Any) -> Any: 284 real = real_connect(*args, **kwargs) 285 286 class Wrapper: 287 def __init__(self, con: duckdb.DuckDBPyConnection) -> None: 288 self.con = con 289 self._failed = False 290 291 def execute(self, sql: str, *a: Any, **kw: Any): 292 if not self._failed and sql == "LOAD sqlite": 293 self._failed = True 294 raise RuntimeError("fail") 295 return self.con.execute(sql, *a, **kw) 296 297 def __getattr__(self, name: str) -> object: 298 return getattr(self.con, name) 299 300 return Wrapper(real) 301 302 monkeypatch.setattr(server.duckdb, "connect", failing_connect) 303 304 app = server.create_app(sqlite_file) 305 client = app.test_client() 306 payload = { 307 "table": "events", 308 "order_by": "timestamp", 309 "columns": ["timestamp", "value"], 310 } 311 rv = client.post( 312 "/api/query", data=json.dumps(payload), content_type="applicatio n/json" 313 ) 314 data = rv.get_json() 315 assert rv.status_code == 200 316 assert data["rows"][0][1] == big_value (scubaduck) root@74ff72a61187:/workspace/scubaduck#

I'll summarize the changes and include the user's message in the PR body.