Codex Task Logs

Task ID: task_e_682cd22d9ea083239afb3c651409421d

Environment setup
Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (3/33) itsdangerous ------------------------------ 15.85 KiB/15.85 KiB execnet ------------------------------ 32.00 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 ------------------------------ 68.79 KiB/68.79 KiB click ------------------------------ 94.88 KiB/99.76 KiB flask ------------------------------ 64.00 KiB/100.88 KiB urllib3 ------------------------------ 78.00 KiB/125.66 KiB jinja2 ------------------------------ 32.00 KiB/131.74 KiB charset-normalizer ------------------------------ 124.25 KiB/145.08 KiB certifi ------------------------------ 155.88 KiB/155.88 KiB werkzeug ------------------------------ 92.02 KiB/219.24 KiB python-dateutil ------------------------------ 46.86 KiB/224.50 KiB pytest ------------------------------ 62.88 KiB/335.58 KiB greenlet ------------------------------ 157.36 KiB/589.71 KiB pyright ------------------------------ 14.90 KiB/5.31 MiB ruff ------------------------------ 253.78 KiB/11.02 MiB duckdb ------------------------------ 189.61 KiB/19.27 MiB playwright ------------------------------ 30.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (3/33) itsdangerous ------------------------------ 15.85 KiB/15.85 KiB execnet ------------------------------ 32.00 KiB/39.66 KiB pytest-xdist ------------------------------ 45.03 KiB/45.03 KiB requests ------------------------------ 63.41 KiB/63.41 KiB packaging ------------------------------ 48.00 KiB/64.91 KiB click ------------------------------ 94.88 KiB/99.76 KiB flask ------------------------------ 64.00 KiB/100.88 KiB urllib3 ------------------------------ 78.00 KiB/125.66 KiB jinja2 ------------------------------ 32.00 KiB/131.74 KiB charset-normalizer ------------------------------ 124.25 KiB/145.08 KiB certifi ------------------------------ 155.88 KiB/155.88 KiB werkzeug ------------------------------ 92.02 KiB/219.24 KiB python-dateutil ------------------------------ 46.86 KiB/224.50 KiB pytest ------------------------------ 77.87 KiB/335.58 KiB greenlet ------------------------------ 157.36 KiB/589.71 KiB pyright ------------------------------ 14.90 KiB/5.31 MiB ruff ------------------------------ 253.78 KiB/11.02 MiB duckdb ------------------------------ 189.61 KiB/19.27 MiB playwright ------------------------------ 30.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (3/33) execnet ------------------------------ 32.00 KiB/39.66 KiB pytest-xdist ------------------------------ 45.03 KiB/45.03 KiB requests ------------------------------ 63.41 KiB/63.41 KiB packaging ------------------------------ 48.00 KiB/64.91 KiB click ------------------------------ 94.88 KiB/99.76 KiB flask ------------------------------ 64.00 KiB/100.88 KiB urllib3 ------------------------------ 78.00 KiB/125.66 KiB jinja2 ------------------------------ 32.00 KiB/131.74 KiB charset-normalizer ------------------------------ 124.25 KiB/145.08 KiB certifi ------------------------------ 155.88 KiB/155.88 KiB werkzeug ------------------------------ 92.02 KiB/219.24 KiB python-dateutil ------------------------------ 46.86 KiB/224.50 KiB pytest ------------------------------ 77.87 KiB/335.58 KiB greenlet ------------------------------ 157.36 KiB/589.71 KiB pyright ------------------------------ 14.90 KiB/5.31 MiB ruff ------------------------------ 253.78 KiB/11.02 MiB duckdb ------------------------------ 189.61 KiB/19.27 MiB playwright ------------------------------ 30.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (3/33) execnet ------------------------------ 32.00 KiB/39.66 KiB pytest-xdist ------------------------------ 45.03 KiB/45.03 KiB requests ------------------------------ 63.41 KiB/63.41 KiB packaging ------------------------------ 48.00 KiB/64.91 KiB click ------------------------------ 94.88 KiB/99.76 KiB flask ------------------------------ 64.00 KiB/100.88 KiB urllib3 ------------------------------ 78.00 KiB/125.66 KiB jinja2 ------------------------------ 32.00 KiB/131.74 KiB charset-normalizer ------------------------------ 124.25 KiB/145.08 KiB certifi ------------------------------ 155.88 KiB/155.88 KiB werkzeug ------------------------------ 92.02 KiB/219.24 KiB python-dateutil ------------------------------ 46.86 KiB/224.50 KiB pytest ------------------------------ 77.87 KiB/335.58 KiB greenlet ------------------------------ 173.36 KiB/589.71 KiB pyright ------------------------------ 14.90 KiB/5.31 MiB ruff ------------------------------ 285.78 KiB/11.02 MiB duckdb ------------------------------ 205.61 KiB/19.27 MiB playwright ------------------------------ 30.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (3/33) execnet ------------------------------ 39.66 KiB/39.66 KiB pytest-xdist ------------------------------ 45.03 KiB/45.03 KiB requests ------------------------------ 63.41 KiB/63.41 KiB packaging ------------------------------ 64.91 KiB/64.91 KiB click ------------------------------ 99.76 KiB/99.76 KiB flask ------------------------------ 64.00 KiB/100.88 KiB urllib3 ------------------------------ 94.00 KiB/125.66 KiB jinja2 ------------------------------ 48.00 KiB/131.74 KiB charset-normalizer ------------------------------ 140.25 KiB/145.08 KiB werkzeug ------------------------------ 108.02 KiB/219.24 KiB python-dateutil ------------------------------ 78.86 KiB/224.50 KiB pytest ------------------------------ 77.87 KiB/335.58 KiB greenlet ------------------------------ 205.36 KiB/589.71 KiB pyright ------------------------------ 14.90 KiB/5.31 MiB ruff ------------------------------ 301.78 KiB/11.02 MiB duckdb ------------------------------ 237.61 KiB/19.27 MiB playwright ------------------------------ 30.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (3/33) execnet ------------------------------ 39.66 KiB/39.66 KiB pytest-xdist ------------------------------ 45.03 KiB/45.03 KiB packaging ------------------------------ 64.91 KiB/64.91 KiB click ------------------------------ 99.76 KiB/99.76 KiB flask ------------------------------ 80.00 KiB/100.88 KiB urllib3 ------------------------------ 94.00 KiB/125.66 KiB jinja2 ------------------------------ 79.73 KiB/131.74 KiB charset-normalizer ------------------------------ 140.25 KiB/145.08 KiB werkzeug ------------------------------ 108.02 KiB/219.24 KiB python-dateutil ------------------------------ 110.86 KiB/224.50 KiB pytest ------------------------------ 109.87 KiB/335.58 KiB greenlet ------------------------------ 317.36 KiB/589.71 KiB pyright ------------------------------ 14.90 KiB/5.31 MiB ruff ------------------------------ 413.78 KiB/11.02 MiB duckdb ------------------------------ 349.61 KiB/19.27 MiB playwright ------------------------------ 46.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (3/33) execnet ------------------------------ 39.66 KiB/39.66 KiB pytest-xdist ------------------------------ 45.03 KiB/45.03 KiB packaging ------------------------------ 64.91 KiB/64.91 KiB flask ------------------------------ 80.00 KiB/100.88 KiB urllib3 ------------------------------ 94.00 KiB/125.66 KiB jinja2 ------------------------------ 95.73 KiB/131.74 KiB charset-normalizer ------------------------------ 145.08 KiB/145.08 KiB werkzeug ------------------------------ 108.02 KiB/219.24 KiB python-dateutil ------------------------------ 158.86 KiB/224.50 KiB pytest ------------------------------ 125.87 KiB/335.58 KiB greenlet ------------------------------ 349.36 KiB/589.71 KiB pyright ------------------------------ 30.90 KiB/5.31 MiB ruff ------------------------------ 445.78 KiB/11.02 MiB duckdb ------------------------------ 381.61 KiB/19.27 MiB playwright ------------------------------ 46.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (3/33) execnet ------------------------------ 39.66 KiB/39.66 KiB packaging ------------------------------ 64.91 KiB/64.91 KiB flask ------------------------------ 80.00 KiB/100.88 KiB urllib3 ------------------------------ 94.00 KiB/125.66 KiB jinja2 ------------------------------ 95.73 KiB/131.74 KiB charset-normalizer ------------------------------ 145.08 KiB/145.08 KiB werkzeug ------------------------------ 124.02 KiB/219.24 KiB python-dateutil ------------------------------ 190.86 KiB/224.50 KiB pytest ------------------------------ 125.87 KiB/335.58 KiB greenlet ------------------------------ 381.36 KiB/589.71 KiB pyright ------------------------------ 30.90 KiB/5.31 MiB ruff ------------------------------ 477.78 KiB/11.02 MiB duckdb ------------------------------ 413.61 KiB/19.27 MiB playwright ------------------------------ 46.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (3/33) packaging ------------------------------ 64.91 KiB/64.91 KiB flask ------------------------------ 80.00 KiB/100.88 KiB urllib3 ------------------------------ 94.00 KiB/125.66 KiB jinja2 ------------------------------ 95.73 KiB/131.74 KiB charset-normalizer ------------------------------ 145.08 KiB/145.08 KiB werkzeug ------------------------------ 124.02 KiB/219.24 KiB python-dateutil ------------------------------ 190.86 KiB/224.50 KiB pytest ------------------------------ 125.87 KiB/335.58 KiB greenlet ------------------------------ 381.36 KiB/589.71 KiB pyright ------------------------------ 30.90 KiB/5.31 MiB ruff ------------------------------ 493.78 KiB/11.02 MiB duckdb ------------------------------ 413.61 KiB/19.27 MiB playwright ------------------------------ 46.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (3/33) flask ------------------------------ 80.00 KiB/100.88 KiB urllib3 ------------------------------ 94.00 KiB/125.66 KiB jinja2 ------------------------------ 95.73 KiB/131.74 KiB charset-normalizer ------------------------------ 145.08 KiB/145.08 KiB werkzeug ------------------------------ 124.02 KiB/219.24 KiB python-dateutil ------------------------------ 224.50 KiB/224.50 KiB pytest ------------------------------ 141.87 KiB/335.58 KiB greenlet ------------------------------ 413.36 KiB/589.71 KiB pyright ------------------------------ 62.90 KiB/5.31 MiB ruff ------------------------------ 525.78 KiB/11.02 MiB duckdb ------------------------------ 445.61 KiB/19.27 MiB playwright ------------------------------ 46.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (3/33) flask ------------------------------ 96.00 KiB/100.88 KiB urllib3 ------------------------------ 110.00 KiB/125.66 KiB jinja2 ------------------------------ 95.73 KiB/131.74 KiB charset-normalizer ------------------------------ 145.08 KiB/145.08 KiB werkzeug ------------------------------ 124.02 KiB/219.24 KiB python-dateutil ------------------------------ 224.50 KiB/224.50 KiB pytest ------------------------------ 141.87 KiB/335.58 KiB greenlet ------------------------------ 461.36 KiB/589.71 KiB pyright ------------------------------ 110.90 KiB/5.31 MiB ruff ------------------------------ 557.78 KiB/11.02 MiB duckdb ------------------------------ 493.61 KiB/19.27 MiB playwright ------------------------------ 62.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (3/33) flask ------------------------------ 96.00 KiB/100.88 KiB urllib3 ------------------------------ 110.00 KiB/125.66 KiB jinja2 ------------------------------ 127.73 KiB/131.74 KiB werkzeug ------------------------------ 140.02 KiB/219.24 KiB python-dateutil ------------------------------ 224.50 KiB/224.50 KiB pytest ------------------------------ 173.87 KiB/335.58 KiB greenlet ------------------------------ 461.36 KiB/589.71 KiB pyright ------------------------------ 190.90 KiB/5.31 MiB ruff ------------------------------ 637.78 KiB/11.02 MiB duckdb ------------------------------ 573.61 KiB/19.27 MiB playwright ------------------------------ 62.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (3/33) flask ------------------------------ 100.88 KiB/100.88 KiB urllib3 ------------------------------ 125.66 KiB/125.66 KiB jinja2 ------------------------------ 127.73 KiB/131.74 KiB werkzeug ------------------------------ 140.02 KiB/219.24 KiB pytest ------------------------------ 189.87 KiB/335.58 KiB greenlet ------------------------------ 461.36 KiB/589.71 KiB pyright ------------------------------ 281.81 KiB/5.31 MiB ruff ------------------------------ 733.78 KiB/11.02 MiB duckdb ------------------------------ 669.61 KiB/19.27 MiB playwright ------------------------------ 62.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (3/33) urllib3 ------------------------------ 125.66 KiB/125.66 KiB jinja2 ------------------------------ 127.73 KiB/131.74 KiB werkzeug ------------------------------ 140.02 KiB/219.24 KiB pytest ------------------------------ 189.87 KiB/335.58 KiB greenlet ------------------------------ 477.36 KiB/589.71 KiB pyright ------------------------------ 345.81 KiB/5.31 MiB ruff ------------------------------ 797.78 KiB/11.02 MiB duckdb ------------------------------ 733.61 KiB/19.27 MiB playwright ------------------------------ 62.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (3/33) jinja2 ------------------------------ 131.74 KiB/131.74 KiB werkzeug ------------------------------ 156.02 KiB/219.24 KiB pytest ------------------------------ 189.87 KiB/335.58 KiB greenlet ------------------------------ 477.36 KiB/589.71 KiB pyright ------------------------------ 425.81 KiB/5.31 MiB ruff ------------------------------ 877.78 KiB/11.02 MiB duckdb ------------------------------ 797.61 KiB/19.27 MiB playwright ------------------------------ 78.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (3/33) werkzeug ------------------------------ 156.02 KiB/219.24 KiB pytest ------------------------------ 189.87 KiB/335.58 KiB greenlet ------------------------------ 477.36 KiB/589.71 KiB pyright ------------------------------ 441.81 KiB/5.31 MiB ruff ------------------------------ 893.78 KiB/11.02 MiB duckdb ------------------------------ 813.61 KiB/19.27 MiB playwright ------------------------------ 78.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠹ Preparing packages... (3/33) werkzeug ------------------------------ 156.02 KiB/219.24 KiB pytest ------------------------------ 221.87 KiB/335.58 KiB greenlet ------------------------------ 477.36 KiB/589.71 KiB pyright ------------------------------ 489.81 KiB/5.31 MiB ruff ------------------------------ 941.78 KiB/11.02 MiB duckdb ------------------------------ 877.61 KiB/19.27 MiB playwright ------------------------------ 94.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠸ Preparing packages... (25/33) werkzeug ------------------------------ 219.24 KiB/219.24 KiB pytest ------------------------------ 285.87 KiB/335.58 KiB greenlet ------------------------------ 493.36 KiB/589.71 KiB pyright ------------------------------ 996.81 KiB/5.31 MiB ruff ------------------------------ 1.40 MiB/11.02 MiB duckdb ------------------------------ 1.34 MiB/19.27 MiB playwright ------------------------------ 126.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠸ Preparing packages... (25/33) pytest ------------------------------ 285.87 KiB/335.58 KiB greenlet ------------------------------ 493.36 KiB/589.71 KiB pyright ------------------------------ 1.03 MiB/5.31 MiB ruff ------------------------------ 1.46 MiB/11.02 MiB duckdb ------------------------------ 1.40 MiB/19.27 MiB playwright ------------------------------ 190.91 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠸ Preparing packages... (25/33) pytest ------------------------------ 335.58 KiB/335.58 KiB greenlet ------------------------------ 541.36 KiB/589.71 KiB pyright ------------------------------ 1.41 MiB/5.31 MiB ruff ------------------------------ 1.96 MiB/11.02 MiB duckdb ------------------------------ 1.92 MiB/19.27 MiB playwright ------------------------------ 664.56 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠸ Preparing packages... (25/33) greenlet ------------------------------ 557.36 KiB/589.71 KiB pyright ------------------------------ 1.50 MiB/5.31 MiB ruff ------------------------------ 2.05 MiB/11.02 MiB duckdb ------------------------------ 2.00 MiB/19.27 MiB playwright ------------------------------ 760.56 KiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠸ Preparing packages... (25/33) greenlet ------------------------------ 589.71 KiB/589.71 KiB pyright ------------------------------ 1.79 MiB/5.31 MiB ruff ------------------------------ 2.61 MiB/11.02 MiB duckdb ------------------------------ 2.54 MiB/19.27 MiB playwright ------------------------------ 1.30 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠸ Preparing packages... (25/33) pyright ------------------------------ 1.79 MiB/5.31 MiB ruff ------------------------------ 2.81 MiB/11.02 MiB duckdb ------------------------------ 2.75 MiB/19.27 MiB playwright ------------------------------ 1.50 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠸ Preparing packages... (25/33) pyright ------------------------------ 1.81 MiB/5.31 MiB ruff ------------------------------ 3.26 MiB/11.02 MiB duckdb ------------------------------ 3.22 MiB/19.27 MiB playwright ------------------------------ 1.97 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠸ Preparing packages... (25/33) pyright ------------------------------ 1.84 MiB/5.31 MiB ruff ------------------------------ 3.94 MiB/11.02 MiB duckdb ------------------------------ 3.91 MiB/19.27 MiB playwright ------------------------------ 2.59 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠼ Preparing packages... (28/33) pyright ------------------------------ 1.89 MiB/5.31 MiB ruff ------------------------------ 4.63 MiB/11.02 MiB duckdb ------------------------------ 4.59 MiB/19.27 MiB playwright ------------------------------ 3.30 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠼ Preparing packages... (28/33) pyright ------------------------------ 1.92 MiB/5.31 MiB ruff ------------------------------ 5.38 MiB/11.02 MiB duckdb ------------------------------ 5.34 MiB/19.27 MiB playwright ------------------------------ 4.05 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠼ Preparing packages... (28/33) pyright ------------------------------ 1.95 MiB/5.31 MiB ruff ------------------------------ 6.14 MiB/11.02 MiB duckdb ------------------------------ 6.10 MiB/19.27 MiB playwright ------------------------------ 4.78 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠼ Preparing packages... (28/33) pyright ------------------------------ 1.98 MiB/5.31 MiB ruff ------------------------------ 6.78 MiB/11.02 MiB duckdb ------------------------------ 6.75 MiB/19.27 MiB playwright ------------------------------ 5.45 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠴ Preparing packages... (28/33) pyright ------------------------------ 2.02 MiB/5.31 MiB ruff ------------------------------ 7.47 MiB/11.02 MiB duckdb ------------------------------ 7.43 MiB/19.27 MiB playwright ------------------------------ 6.14 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠴ Preparing packages... (28/33) pyright ------------------------------ 2.05 MiB/5.31 MiB ruff ------------------------------ 8.18 MiB/11.02 MiB duckdb ------------------------------ 8.14 MiB/19.27 MiB playwright ------------------------------ 6.84 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠴ Preparing packages... (28/33) pyright ------------------------------ 2.08 MiB/5.31 MiB ruff ------------------------------ 8.95 MiB/11.02 MiB duckdb ------------------------------ 8.90 MiB/19.27 MiB playwright ------------------------------ 7.61 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠴ Preparing packages... (28/33) pyright ------------------------------ 2.11 MiB/5.31 MiB ruff ------------------------------ 9.72 MiB/11.02 MiB duckdb ------------------------------ 9.66 MiB/19.27 MiB playwright ------------------------------ 8.36 MiB/43.05 MiB Building scubaduck @ file:///workspace/scubaduck ⠦ Preparing packages... (28/33) pyright ------------------------------ 2.13 MiB/5.31 MiB ruff ------------------------------ 10.42 MiB/11.02 MiB duckdb ------------------------------ 10.38 MiB/19.27 MiB playwright ------------------------------ 9.10 MiB/43.05 MiB Built scubaduck @ file:///workspace/scubaduck ⠦ Preparing packages... (28/33) pyright ------------------------------ 2.14 MiB/5.31 MiB ruff ------------------------------ 10.72 MiB/11.02 MiB duckdb ------------------------------ 10.66 MiB/19.27 MiB playwright ------------------------------ 9.38 MiB/43.05 MiB ⠦ Preparing packages... (28/33) pyright ------------------------------ 2.14 MiB/5.31 MiB duckdb ------------------------------ 11.05 MiB/19.27 MiB playwright ------------------------------ 9.77 MiB/43.05 MiB ⠦ Preparing packages... (28/33) pyright ------------------------------ 2.14 MiB/5.31 MiB duckdb ------------------------------ 11.08 MiB/19.27 MiB playwright ------------------------------ 9.78 MiB/43.05 MiB ⠦ Preparing packages... (28/33) pyright ------------------------------ 2.16 MiB/5.31 MiB duckdb ------------------------------ 12.16 MiB/19.27 MiB playwright ------------------------------ 10.89 MiB/43.05 MiB ⠦ Preparing packages... (28/33) pyright ------------------------------ 2.18 MiB/5.31 MiB duckdb ------------------------------ 13.31 MiB/19.27 MiB playwright ------------------------------ 12.03 MiB/43.05 MiB ⠧ Preparing packages... (30/33) pyright ------------------------------ 2.19 MiB/5.31 MiB duckdb ------------------------------ 14.48 MiB/19.27 MiB playwright ------------------------------ 13.21 MiB/43.05 MiB ⠧ Preparing packages... (30/33) pyright ------------------------------ 2.21 MiB/5.31 MiB duckdb ------------------------------ 15.66 MiB/19.27 MiB playwright ------------------------------ 14.35 MiB/43.05 MiB ⠧ Preparing packages... (30/33) pyright ------------------------------ 2.22 MiB/5.31 MiB duckdb ------------------------------ 16.81 MiB/19.27 MiB playwright ------------------------------ 15.53 MiB/43.05 MiB ⠧ Preparing packages... (30/33) pyright ------------------------------ 2.24 MiB/5.31 MiB duckdb ------------------------------ 17.97 MiB/19.27 MiB playwright ------------------------------ 16.67 MiB/43.05 MiB ⠇ Preparing packages... (30/33) pyright ------------------------------ 2.25 MiB/5.31 MiB duckdb ------------------------------ 19.05 MiB/19.27 MiB playwright ------------------------------ 17.73 MiB/43.05 MiB ⠇ Preparing packages... (30/33) pyright ------------------------------ 2.30 MiB/5.31 MiB duckdb ------------------------------ 19.27 MiB/19.27 MiB playwright ------------------------------ 19.38 MiB/43.05 MiB ⠇ Preparing packages... (30/33) pyright ------------------------------ 2.33 MiB/5.31 MiB playwright ------------------------------ 19.61 MiB/43.05 MiB ⠇ Preparing packages... (30/33) pyright ------------------------------ 2.36 MiB/5.31 MiB playwright ------------------------------ 21.34 MiB/43.05 MiB ⠇ Preparing packages... (30/33) pyright ------------------------------ 2.41 MiB/5.31 MiB playwright ------------------------------ 23.58 MiB/43.05 MiB ⠋ Preparing packages... (31/33) pyright ------------------------------ 2.43 MiB/5.31 MiB playwright ------------------------------ 25.73 MiB/43.05 MiB ⠋ Preparing packages... (31/33) pyright ------------------------------ 2.44 MiB/5.31 MiB playwright ------------------------------ 28.02 MiB/43.05 MiB ⠋ Preparing packages... (31/33) pyright ------------------------------ 2.47 MiB/5.31 MiB playwright ------------------------------ 30.50 MiB/43.05 MiB ⠋ Preparing packages... (31/33) pyright ------------------------------ 2.49 MiB/5.31 MiB playwright ------------------------------ 32.62 MiB/43.05 MiB ⠙ Preparing packages... (31/33) pyright ------------------------------ 2.52 MiB/5.31 MiB playwright ------------------------------ 34.84 MiB/43.05 MiB ⠙ Preparing packages... (31/33) pyright ------------------------------ 2.57 MiB/5.31 MiB playwright ------------------------------ 36.83 MiB/43.05 MiB ⠙ Preparing packages... (31/33) pyright ------------------------------ 2.58 MiB/5.31 MiB playwright ------------------------------ 38.98 MiB/43.05 MiB ⠙ Preparing packages... (31/33) pyright ------------------------------ 2.61 MiB/5.31 MiB playwright ------------------------------ 40.84 MiB/43.05 MiB ⠹ Preparing packages... (31/33) pyright ------------------------------ 2.71 MiB/5.31 MiB playwright ------------------------------ 41.39 MiB/43.05 MiB ⠹ Preparing packages... (31/33) pyright ------------------------------ 2.75 MiB/5.31 MiB playwright ------------------------------ 42.29 MiB/43.05 MiB ⠹ Preparing packages... (31/33) pyright ------------------------------ 2.78 MiB/5.31 MiB ⠹ Preparing packages... (31/33) pyright ------------------------------ 2.85 MiB/5.31 MiB ⠹ Preparing packages... (31/33) pyright ------------------------------ 2.99 MiB/5.31 MiB ⠸ Preparing packages... (32/33) pyright ------------------------------ 3.14 MiB/5.31 MiB ⠸ Preparing packages... (32/33) pyright ------------------------------ 3.25 MiB/5.31 MiB ⠸ Preparing packages... (32/33) pyright ------------------------------ 3.38 MiB/5.31 MiB ⠸ Preparing packages... (32/33) pyright ------------------------------ 3.54 MiB/5.31 MiB ⠼ Preparing packages... (32/33) pyright ------------------------------ 3.76 MiB/5.31 MiB ⠼ Preparing packages... (32/33) pyright ------------------------------ 3.92 MiB/5.31 MiB ⠼ Preparing packages... (32/33) pyright ------------------------------ 4.20 MiB/5.31 MiB ⠴ Preparing packages... (32/33) pyright ------------------------------ 4.37 MiB/5.31 MiB ⠴ Preparing packages... (32/33) pyright ------------------------------ 4.50 MiB/5.31 MiB ⠴ Preparing packages... (32/33) pyright ------------------------------ 5.29 MiB/5.31 MiB ⠴ Preparing packages... (32/33) Prepared 33 packages in 2.70s ░░░░░░░░░░░░░░░░░░░░ [0/0] Installing wheels... ░░░░░░░░░░░░░░░░░░░░ [0/33] Installing wheels... ░░░░░░░░░░░░░░░░░░░░ [0/33] typing-extensions==4.13.2 ░░░░░░░░░░░░░░░░░░░░ [1/33] typing-extensions==4.13.2 ░░░░░░░░░░░░░░░░░░░░ [1/33] blinker==1.9.0 █░░░░░░░░░░░░░░░░░░░ [2/33] blinker==1.9.0 █░░░░░░░░░░░░░░░░░░░ [2/33] click==8.2.0 █░░░░░░░░░░░░░░░░░░░ [3/33] click==8.2.0 █░░░░░░░░░░░░░░░░░░░ [3/33] pluggy==1.6.0 ██░░░░░░░░░░░░░░░░░░ [4/33] pluggy==1.6.0 ██░░░░░░░░░░░░░░░░░░ [4/33] markupsafe==3.0.2 ███░░░░░░░░░░░░░░░░░ [5/33] markupsafe==3.0.2 ███░░░░░░░░░░░░░░░░░ [5/33] iniconfig==2.1.0 ███░░░░░░░░░░░░░░░░░ [6/33] iniconfig==2.1.0 ███░░░░░░░░░░░░░░░░░ [6/33] pytest-xdist==3.6.1 ████░░░░░░░░░░░░░░░░ [7/33] pytest-xdist==3.6.1 ████░░░░░░░░░░░░░░░░ [7/33] pyee==13.0.0 ████░░░░░░░░░░░░░░░░ [8/33] pyee==13.0.0 ████░░░░░░░░░░░░░░░░ [8/33] pytest-base-url==2.1.0 █████░░░░░░░░░░░░░░░ [9/33] pytest-base-url==2.1.0 ███████████████████░ [32/33] pyright==1.1.400 ████████████████████ [33/33] pyright==1.1.400 Installed 33 packages in 114ms + 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/RXNkcr-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:3437PYENV_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:3437PYENV_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% 27.7s167.7 MiB [] 0% 23.3s167.7 MiB [] 0% 16.5s167.7 MiB [] 0% 10.0s167.7 MiB [] 1% 7.7s167.7 MiB [] 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Downloading Chromium Headless Shell 136.0.7103.25 (playwright build v1169) from https://cdn.playwright.dev/dbazure/download/playwright/builds/chromium/1169/chromium-headless-shell-linux.zip 101.4 MiB [] 0% 0.0s101.4 MiB [] 0% 22.4s101.4 MiB [] 0% 14.6s101.4 MiB [] 0% 7.8s101.4 MiB [] 1% 5.7s101.4 MiB [] 1% 4.8s101.4 MiB [] 3% 3.1s101.4 MiB [] 5% 2.4s101.4 MiB [] 7% 1.8s101.4 MiB [] 8% 1.7s101.4 MiB [] 9% 1.7s101.4 MiB [] 10% 1.7s101.4 MiB [] 12% 1.5s101.4 MiB [] 14% 1.3s101.4 MiB [] 16% 1.2s101.4 MiB [] 18% 1.2s101.4 MiB [] 20% 1.1s101.4 MiB [] 21% 1.0s101.4 MiB [] 24% 0.9s101.4 MiB [] 26% 0.9s101.4 MiB [] 28% 0.9s101.4 MiB [] 30% 0.8s101.4 MiB [] 31% 0.8s101.4 MiB [] 33% 0.8s101.4 MiB [] 34% 0.8s101.4 MiB [] 36% 0.8s101.4 MiB [] 37% 0.7s101.4 MiB [] 38% 0.7s101.4 MiB [] 40% 0.7s101.4 MiB [] 41% 0.7s101.4 MiB [] 42% 0.7s101.4 MiB [] 44% 0.7s101.4 MiB [] 46% 0.7s101.4 MiB [] 49% 0.6s101.4 MiB [] 53% 0.5s101.4 MiB [] 57% 0.5s101.4 MiB [] 61% 0.4s101.4 MiB [] 64% 0.4s101.4 MiB [] 67% 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Internet turned off
We need to make the database we're going to load configurable. We want to support csv, sqlite and native duckdb database. We should be able to specify the database via filename passed on command line. The type of database should be automatically inferred. Add tests for all of these cases.
shell
bash: .venv/bin/activate: No such file or directory root@585f5e72dcd0:/workspace# ls scubaduck
root@585f5e72dcd0:/workspace# cd scubaduck root@585f5e72dcd0:/workspace/scubaduck# ls AGENTS.md codex_setup.sh scubaduck tests README.md pyproject.toml stubs uv.lock
root@585f5e72dcd0:/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
root@585f5e72dcd0:/workspace/scubaduck# ls -R | head .: AGENTS.md README.md codex_setup.sh pyproject.toml scubaduck stubs tests uv.lock
root@585f5e72dcd0:/workspace/scubaduck# cat README.md | head -n 40 I really like Scuba (Meta's internal real-time database system). The distributed , real-time database part of Scuba is quite difficult (and expensive) to replica te, but I also really like Scuba's UI for doing queries, and I have found myself wishing that I have access to it even for "small" databases, e.g., I have a sql ite dataset I want to explore. Pivotal ideas: * Time series by default. In the dedicated "time series" view, there are many fe atures specifically oriented towards working towards tables that represent event s that occurred over time: the start, end, compare, aggregate and granularity fi elds all specially privilege the timestamp field. In fact, you can't log events to Scuba's backing data store without a timestamp, they always come with one. (S cuba also supports other views that don't presuppose a time series, but the time series is the most beloved and well used view.) This is in contrast to typical software which tries to generalize to arbitrary data first, with time series bei ng added on later. * It's all about exploration. Scuba is predicated on the idea that you don't kno w what you're looking for, that you are going to spend time tweaking queries and changing filters/grouping as part of an investigation to figure out why a syste m behaves the way it is. So the filters/comparisons/groupings you want to edit a re always visible on the left sidebar, with the expectation that you're going to tweak the query to look at something else. Similarly, all the parameters of you r query get saved into your URL, so your browser history can double up as a quer y history / you can easily share a query with someone else. This is contrast to typical software which is often oriented to making pretty dashboards and reports . (This function is important too, but it's not what I want in exploration mode! ) * You can fix data problems in the query editor. It's pretty common to have mess ed up and ended up with a database that doesn't have exactly the columns you nee d, or some columns that are corrupted in some way. Scuba has pretty robust suppo rt for defining custom columns with arbitrary SQL functions, grouping over them as if they were native functions, and doing so with minimal runtime cost (Scuba aims to turn around your query in milliseconds!) Having to go and run a huge dat a pipeline to fix your data is a big impediment to exploration; quick and easy c ustom columns means you can patch over problems when you're investigating and fi x them for real later. We're going to build a exploratory data analysis tool like Scuba for time series database (i.e., a database with a mandatory timestamp representing the time an event occurred). We'll use DuckDB as the underlying SQL engine served from a Py thon server, and render the GUI/results as a webpage with vanilla HTML and JS. W e'll use choices.js to support token inputs. We define a token input to mean a text input element where as you type a dropdown displays with valid values, and if you select one or press enter, the selection turns into a token/chip that can only be deleted as one unit. To start, we are going to support one views: samples. The samples view only all ows you to view individual samples from the database, subject to a filter. Our m ain UI concept is that there is a left sidebar that is the query editor, and the right side that shows the view. The sidebar is always visible and defaults to the query parameters of the current view. After you make changes to the query, clicking the "Dive" button updates the view. The URL of the page encodes all of the values of the query (and gets updated when you Dive), so the browser's back button lets you view previous queries. The query editor's job is to generate a SQL query, which then is applied on the database, and then the result visualized according to the view. Here are the settings you can apply to the query. The help text should show up w hen you mouse over the field name: * Start/End - Help text: "Sets the start/end of the time range to query. Can be any kind of datetime string. For example: 'April 23, 2014' or 'yesterday'." The UI for this selector supports both relative selections (now, -1 hour, -3 hours, -12 hours, -1 day, -3 days, -1 week, -1 fortnight, -30 days, -90 days) as well a s specifying an absolute date. The way this field is rendered is there is a fre e form text box, a drop down arrow (for the relative selectors), and then a cale ndar button (for date selection). * Order By - Help text: "Choose a column to sort results by." There is an ASC/D ESC toggle next to it. * 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.

The README is lengthy; I’ll narrow down the search for specific guidance.

shell
root@585f5e72dcd0:/workspace/scubaduck# grep -n "instruction" -n README.md

I'll start by taking a look at the repository to understand its contents.

shell
root@585f5e72dcd0:/workspace/scubaduck# ls scubaduck __init__.py sample.csv server.py static
root@585f5e72dcd0:/workspace/scubaduck# ls scubaduck/static | head index.html
root@585f5e72dcd0:/workspace/scubaduck# cat scubaduck/server.py | head from __future__ import annotations from dataclasses import dataclass, field from typing import Any, Dict, Tuple, List import time import duckdb from flask import Flask, jsonify, request, send_from_directory
root@585f5e72dcd0:/workspace/scubaduck# sed -n '1,200p' scubaduck/server.py from __future__ import annotations from dataclasses import dataclass, field from typing import Any, Dict, Tuple, List import time import duckdb from flask import Flask, jsonify, request, send_from_directory app = Flask(__name__, static_folder="static") # Initialize DuckDB in-memory and load sample data con = duckdb.connect() con.execute( "CREATE TABLE IF NOT EXISTS events AS SELECT * FROM read_csv_auto('scubaduck /sample.csv')" ) _column_types: Dict[str, str] = { r[1]: r[2] for r in con.execute("PRAGMA table_info(events)").fetchall() } @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: {}) @app.route("/") def index() -> Any: assert app.static_folder is not None return send_from_directory(app.static_folder, "index.html") @app.route("/api/columns") def columns() -> Any: rows = con.execute("PRAGMA table_info(events)").fetchall() return jsonify([{"name": r[1], "type": r[2]} for r in rows]) # Simple in-memory LRU cache for sample value queries _SAMPLE_CACHE: Dict[Tuple[str, str], Tuple[List[str], float]] = {} _CACHE_TTL = 60.0 _CACHE_LIMIT = 200 def _cache_get(key: Tuple[str, str]) -> List[str] | None: item = _SAMPLE_CACHE.get(key) if item is None: return None vals, ts = item if time.time() - ts > _CACHE_TTL: del _SAMPLE_CACHE[key] return None _SAMPLE_CACHE[key] = (vals, time.time()) return vals def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: _SAMPLE_CACHE[key] = (vals, time.time()) if len(_SAMPLE_CACHE) > _CACHE_LIMIT: oldest = min(_SAMPLE_CACHE.items(), key=lambda kv: kv[1][1])[0] del _SAMPLE_CACHE[oldest] @app.route("/api/samples") def sample_values() -> Any: column = request.args.get("column") substr = request.args.get("q", "") if not column or column not in _column_types: return jsonify([]) ctype = _column_types[column].upper() if "CHAR" not in ctype and "STRING" not in ctype and "VARCHAR" not in ctype: return jsonify([]) key = (column, substr) cached = _cache_get(key) if cached is not None: return jsonify(cached) rows = con.execute( f"SELECT DISTINCT {column} FROM events WHERE CAST({column} AS VARCHAR) I LIKE '%' || ? || '%' LIMIT 20", [substr], ).fetchall() values = [r[0] for r in rows] _cache_set(key, values) return jsonify(values) def build_query(params: QueryParams) -> str: select_parts = [*params.columns] for name, expr in params.derived_columns.items(): select_parts.append(f"{expr} AS {name}") select_clause = ", ".join(select_parts) if select_parts else "*" query = f"SELECT {select_clause} FROM events" where_parts: list[str] = [] if params.start: where_parts.append(f"timestamp >= '{params.start}'") if params.end: where_parts.append(f"timestamp <= '{params.end}'") for f in params.filters: op = f.op if op in {"empty", "!empty"}: val = "''" else: if f.value is None: continue if isinstance(f.value, list): if not f.value: continue if op == "=": vals = " OR ".join(f"{f.column} = '{v}'" for v in f.value) where_parts.append(f"({vals})") continue val = f"'{f.value}'" if isinstance(f.value, str) else str(f.value) if op == "contains": where_parts.append(f"{f.column} ILIKE '%' || {val} || '%'") elif op == "!contains": where_parts.append(f"{f.column} NOT ILIKE '%' || {val} || '%'") elif op == "empty": where_parts.append(f"{f.column} = {val}") elif op == "!empty": where_parts.append(f"{f.column} != {val}") else: where_parts.append(f"{f.column} {op} {val}") if where_parts: query += " WHERE " + " AND ".join(where_parts) if params.order_by: query += f" ORDER BY {params.order_by} {params.order_dir}" if params.limit is not None: query += f" LIMIT {params.limit}" return query @app.route("/api/query", methods=["POST"]) def query() -> Any: payload = request.get_json(force=True) params = QueryParams( start=payload.get("start"), end=payload.get("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", {}), ) for f in payload.get("filters", []): params.filters.append(Filter(f["column"], f["op"], f.get("value"))) sql = build_query(params) rows = con.execute(sql).fetchall() return jsonify({"sql": sql, "rows": rows}) if __name__ == "__main__": app.run(debug=True)

I'll check the tests directory to see if any tests are present for sample.csv.

shell
root@585f5e72dcd0:/workspace/scubaduck# ls tests conftest.py test_server.py test_web.py
root@585f5e72dcd0:/workspace/scubaduck# sed -n '1,200p' tests/test_server.py from __future__ import annotations import json from scubaduck import server def test_basic_query() -> None: app = server.app client = app.test_client() payload = { "start": "2024-01-01 00:00:00", "end": "2024-01-02 00:00:00", "order_by": "timestamp", "order_dir": "ASC", "limit": 10, "columns": ["timestamp", "event", "value", "user"], "filters": [], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert data rows = data["rows"] # We expect first three rows (until 2024-01-02 00:00:00) assert len(rows) == 3 assert rows[0][1] == "login" assert rows[1][1] == "logout" def test_filter_multi_token() -> None: app = server.app client = app.test_client() payload = { "start": "2024-01-01 00:00:00", "end": "2024-01-02 03:00:00", "order_by": "timestamp", "limit": 10, "columns": ["timestamp", "event", "value", "user"], "filters": [{"column": "user", "op": "=", "value": ["alice", "charlie"]} ], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert data rows = data["rows"] # Should only return rows for alice and charlie assert len(rows) == 3 assert rows[0][3] == "alice" assert rows[-1][3] == "charlie" def test_empty_filter_is_noop() -> None: app = server.app client = app.test_client() base_payload = { "start": "2024-01-01 00:00:00", "end": "2024-01-03 00:00:00", "order_by": "timestamp", "limit": 100, "columns": ["timestamp", "event", "value", "user"], } no_filter = {**base_payload, "filters": []} empty_filter = { **base_payload, "filters": [{"column": "user", "op": "=", "value": None}], } rv1 = client.post( "/api/query", data=json.dumps(no_filter), content_type="application/json " ) rv2 = client.post( "/api/query", data=json.dumps(empty_filter), content_type="application/j son" ) rows1 = rv1.get_json()["rows"] rows2 = rv2.get_json()["rows"] assert rows1 == rows2 def test_select_columns() -> None: app = server.app client = app.test_client() payload = { "start": "2024-01-01 00:00:00", "end": "2024-01-03 00:00:00", "order_by": "timestamp", "limit": 10, "columns": ["timestamp", "user"], "filters": [], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert data rows = data["rows"] assert len(rows[0]) == 2 assert rows[0][1] == "alice" def test_string_filter_ops() -> None: app = server.app client = app.test_client() base = { "start": "2024-01-01 00:00:00", "end": "2024-01-03 00:00:00", "order_by": "timestamp", "limit": 100, "columns": ["timestamp", "event", "value", "user"], } contains = { **base, "filters": [{"column": "user", "op": "contains", "value": "ali"}], } rv = client.post( "/api/query", data=json.dumps(contains), content_type="application/json" ) rows = rv.get_json()["rows"] assert all("ali" in r[3] for r in rows) regex = { **base, "filters": [{"column": "user", "op": "~", "value": "^a.*"}], } rv = client.post( "/api/query", data=json.dumps(regex), content_type="application/json" ) rows = rv.get_json()["rows"] assert all(r[3].startswith("a") for r in rows) assert len(rows) == 2 not_empty = {**base, "filters": [{"column": "user", "op": "!empty"}]} rv = client.post( "/api/query", data=json.dumps(not_empty), content_type="application/json " ) assert len(rv.get_json()["rows"]) == 4
root@585f5e72dcd0:/workspace/scubaduck# sed -n '200,400p' tests/test_server.py
root@585f5e72dcd0:/workspace/scubaduck# sed -n '1,200p' tests/test_web.py from __future__ import annotations from typing import Any def run_query( page: Any, url: str, *, start: str | None = None, end: str | None = None, order_by: str | None = None, order_dir: str | None = "ASC", limit: int | None = None, ) -> dict[str, Any]: page.goto(url) page.wait_for_selector("#order_by option", state="attached") page.wait_for_selector("#order_dir", state="attached") if start is not None: page.fill("#start", start) if end is not None: page.fill("#end", end) if order_by is not None: page.select_option("#order_by", order_by) if order_dir is not None and order_dir == "DESC": page.click("#order_dir") if limit is not None: page.fill("#limit", str(limit)) page.evaluate("window.lastResults = undefined") page.click("text=Dive") page.wait_for_function("window.lastResults !== undefined") return page.evaluate("window.lastResults") def test_range_filters(page: Any, server_url: str) -> None: data = run_query( page, server_url, start="2024-01-02 00:00:00", end="2024-01-02 04:00:00", order_by="timestamp", limit=100, ) assert len(data["rows"]) == 2 from dateutil import parser timestamps = [parser.parse(row[0]).replace(tzinfo=None) for row in data["row s"]] assert timestamps == [ parser.parse("2024-01-02 00:00:00"), parser.parse("2024-01-02 03:00:00"), ] def test_order_by(page: Any, server_url: str) -> None: data = run_query( page, server_url, start="2024-01-01 00:00:00", end="2024-01-03 00:00:00", order_by="value", order_dir="DESC", limit=100, ) values = [row[2] for row in data["rows"]] assert values == sorted(values, reverse=True) def test_limit(page: Any, server_url: str) -> None: data = run_query( page, server_url, start="2024-01-01 00:00:00", end="2024-01-03 00:00:00", order_by="timestamp", limit=2, ) assert len(data["rows"]) == 2 def test_simple_filter(page: Any, server_url: str) -> None: page.goto(server_url) page.wait_for_selector("#order_by option", state="attached") page.click("text=Add Filter") filter_el = page.query_selector("#filters .filter:last-child") assert filter_el filter_el.query_selector(".f-col").select_option("user") val_input = filter_el.query_selector(".f-val") val_input.click() page.keyboard.type("alice") page.keyboard.press("Enter") page.click("text=Dive") page.wait_for_function("window.lastResults !== undefined") data = page.evaluate("window.lastResults") assert len(data["rows"]) == 2 assert all(row[3] == "alice" for row in data["rows"]) def test_default_filter_and_layout(page: Any, server_url: str) -> None: page.goto(server_url) page.wait_for_selector("#order_by option", state="attached") count = page.evaluate("document.querySelectorAll('#filters .filter').length" ) assert count == 1 last_is_button = page.evaluate( "document.querySelector('#filters').lastElementChild.id === 'add_filter' " ) assert last_is_button position = page.evaluate( "getComputedStyle(document.querySelector('#filters .filter button.remove ')).position" ) assert position == "static" def test_header_and_tabs(page: Any, server_url: str) -> None: page.goto(server_url) page.wait_for_selector("#order_by option", state="attached") header = page.text_content("#header") assert "sample.csv" in header assert "events" in header assert page.is_visible("#settings") assert page.is_hidden("#columns") page.click("text=Columns") assert page.is_visible("#columns") cols = [c.strip() for c in page.locator("#column_groups li").all_inner_texts ()] assert "timestamp" in cols assert "event" in cols page.click("text=View Settings") assert page.is_visible("#settings") btn_color = page.evaluate( "getComputedStyle(document.querySelector('#dive')).backgroundColor" ) assert "rgb(0, 128, 0)" == btn_color sidebar_overflow = page.evaluate( "getComputedStyle(document.querySelector('#sidebar')).overflowY" ) view_overflow = page.evaluate( "getComputedStyle(document.querySelector('#view')).overflowY" ) assert sidebar_overflow == "auto" assert view_overflow == "auto" def test_help_and_alignment(page: Any, server_url: str) -> None: page.goto(server_url) page.wait_for_selector("#order_by option", state="attached") titles = page.evaluate( "Array.from(document.querySelectorAll('#settings .help')).map(e => e.tit le)" ) assert any("start/end of the time range" in t for t in titles) text_align = page.evaluate( "getComputedStyle(document.querySelector('#settings label')).textAlign" ) assert text_align == "right" def test_table_sorting(page: Any, server_url: str) -> None: run_query( page, server_url, start="2024-01-01 00:00:00", end="2024-01-03 00:00:00", order_by="timestamp", order_dir="ASC", limit=100, ) # header alignment align = page.evaluate( "getComputedStyle(document.querySelector('#results th')).textAlign" ) assert align == "right" header = page.locator("#results th").nth(3) def values() -> list[str]: return page.locator("#results td:nth-child(4)").all_inner_texts() orig_rows = values() assert orig_rows == ["alice", "bob", "alice", "charlie"] first_sql = page.evaluate("window.lastResults.sql") header.click() assert values() == sorted(orig_rows) assert header.inner_text().endswith("▲") color = page.evaluate( "getComputedStyle(document.querySelector('#results th:nth-child(4)')).co lor" ) assert "0, 0, 255" in color assert page.evaluate("window.lastResults.sql") == first_sql header.click() assert values() == sorted(orig_rows, reverse=True) assert header.inner_text().endswith("▼") header.click() assert values() == orig_rows

I need to continue scrolling to capture the additional info I need.

shell
root@585f5e72dcd0:/workspace/scubaduck# sed -n '200,400p' tests/test_web.py assert values() == orig_rows assert header.inner_text() == "user" color = page.evaluate( "getComputedStyle(document.querySelector('#results th:nth-child(4)')).co lor" ) assert "0, 0, 255" not in color def test_relative_dropdown(page: Any, server_url: str) -> None: page.goto(server_url) page.wait_for_selector("#order_by option", state="attached") btn = page.query_selector('[data-target="start-select"]') assert btn btn.click() page.select_option("#start-select", "-3 hours") assert page.input_value("#start") == "-3 hours" def test_column_toggle_and_selection(page: Any, server_url: str) -> None: page.goto(server_url) page.wait_for_selector("#order_by option", state="attached") page.click("text=Columns") page.wait_for_selector("#column_groups input", state="attached") count = page.evaluate( "document.querySelectorAll('#column_groups input:checked').length" ) assert count == 4 page.click("#columns_none") count = page.evaluate( "document.querySelectorAll('#column_groups input:checked').length" ) assert count == 0 page.click("#columns_all") count = page.evaluate( "document.querySelectorAll('#column_groups input:checked').length" ) assert count == 4 page.uncheck("#column_groups input[value='value']") page.click("text=View Settings") page.fill("#start", "2024-01-01 00:00:00") page.fill("#end", "2024-01-02 00:00:00") page.select_option("#order_by", "timestamp") page.fill("#limit", "10") page.evaluate("window.lastResults = undefined") page.click("text=Dive") page.wait_for_function("window.lastResults !== undefined") data = page.evaluate("window.lastResults") assert len(data["rows"][0]) == 3 headers = page.locator("#results th").all_inner_texts() assert "value" not in headers def test_columns_links_alignment(page: Any, server_url: str) -> None: page.goto(server_url) page.wait_for_selector("#order_by option", state="attached") page.click("text=Columns") page.wait_for_selector("#column_groups input", state="attached") tag = page.evaluate("document.getElementById('columns_all').tagName") assert tag == "A" align = page.evaluate( "getComputedStyle(document.querySelector('#column_actions')).textAlign" ) assert align == "right" def test_chip_dropdown_navigation(page: Any, server_url: str) -> None: page.goto(server_url) page.wait_for_selector("#order_by option", state="attached") page.click("text=Add Filter") f = page.query_selector("#filters .filter:last-child") assert f f.query_selector(".f-col").select_option("user") inp = f.query_selector(".f-val") inp.click() page.wait_for_selector("#filters .filter:last-child .chip-dropdown div") page.keyboard.type("ali") page.wait_for_selector("text=alice") page.keyboard.press("ArrowDown") page.keyboard.press("Enter") chips = page.evaluate( "Array.from(document.querySelectorAll('#filters .filter:last-child .chip ')).map(c => c.firstChild.textContent)" ) assert chips == ["ali"] page.click("#filters .filter:last-child .chip .x") page.wait_for_selector(".chip", state="detached") def test_chip_copy_and_paste(page: Any, server_url: str) -> None: page.goto(server_url) page.wait_for_selector("#order_by option", state="attached") page.evaluate( "Object.defineProperty(navigator, 'clipboard', {value:{ _data: '', write Text(t){ this._data = t; }, readText(){ return Promise.resolve(this._data); } }} )" ) page.click("text=Add Filter") f = page.query_selector("#filters .filter:last-child") assert f f.query_selector(".f-col").select_option("user") inp = f.query_selector(".f-val") inp.click() page.keyboard.type("alice") page.keyboard.press("Enter") page.keyboard.type("bob") page.keyboard.press("Enter") f.query_selector(".chip-copy").click() assert page.evaluate("navigator.clipboard._data") == "alice,bob" page.evaluate( "var f=document.querySelector('#filters .filter:last-child'); f.chips=[] ; f.querySelectorAll('.chip').forEach(c=>c.remove())" ) page.wait_for_selector("#filters .chip", state="detached") inp.click() page.evaluate( "var dt=new DataTransfer(); dt.setData('text/plain','alice,bob'); var e= new ClipboardEvent('paste',{clipboardData:dt}); document.querySelector('#filters .filter:last-child .f-val').dispatchEvent(e);" ) chips = page.evaluate( "Array.from(document.querySelectorAll('#filters .filter:last-child .chip ')).map(c => c.firstChild.textContent)" ) assert chips[:2] == ["alice", "bob"] page.evaluate( "var f=document.querySelector('#filters .filter:last-child'); f.chips=[] ; f.querySelectorAll('.chip').forEach(c=>c.remove())" ) page.wait_for_selector("#filters .chip", state="detached") inp.click() page.evaluate( "var dt=new DataTransfer(); dt.setData('text/plain','alice,bob'); var e= new ClipboardEvent('paste',{clipboardData:dt}); Object.defineProperty(e,'shiftKe y',{value:true}); document.querySelector('#filters .filter:last-child .f-val').d ispatchEvent(e);" ) chips = page.evaluate( "Array.from(document.querySelectorAll('#filters .filter:last-child .chip ')).map(c => c.firstChild.textContent)" ) assert chips[-1] == "alice,bob" def test_chip_dropdown_hides_on_outside_click(page: Any, server_url: str) -> Non e: page.goto(server_url) page.wait_for_selector("#order_by option", state="attached") page.click("text=Add Filter") f = page.query_selector("#filters .filter:last-child") assert f f.query_selector(".f-col").select_option("user") inp = f.query_selector(".f-val") inp.click() page.wait_for_selector("#filters .filter:last-child .chip-dropdown div") page.click("#header") page.wait_for_selector("#filters .filter:last-child .chip-dropdown", state=" hidden") def test_chip_input_no_outline(page: Any, server_url: str) -> None: page.goto(server_url) page.wait_for_selector("#order_by option", state="attached") page.click("text=Add Filter") inp = page.query_selector("#filters .filter:last-child .f-val") assert inp inp.click() outline = page.evaluate( "getComputedStyle(document.querySelector('#filters .filter:last-child .f -val')).outlineStyle" ) assert outline == "none" def test_table_enhancements(page: Any, server_url: str) -> None: run_query( page, server_url, start="2024-01-01 00:00:00", end="2024-01-03 00:00:00", order_by="timestamp", limit=10, ) border = page.evaluate( "getComputedStyle(document.querySelector('#results td')).borderStyle" ) assert border == "solid" color1 = page.evaluate( "getComputedStyle(document.querySelector('#results tr:nth-child(2) td')) .backgroundColor" ) color2 = page.evaluate( "getComputedStyle(document.querySelector('#results tr:nth-child(3) td')) .backgroundColor" ) assert color1 != color2 page.hover("#results tr:nth-child(2)") hover_color = page.evaluate( "getComputedStyle(document.querySelector('#results tr:nth-child(2) td')) .backgroundColor" ) assert hover_color != color1 page.click("#results tr:nth-child(2)") selected_color = page.evaluate( "getComputedStyle(document.querySelector('#results tr:nth-child(2) td')) .backgroundColor" ) assert "189, 228, 255" in selected_color overflow = page.evaluate( "var v=document.getElementById('view'); v.scrollWidth > v.clientWidth" ) assert not overflow

I’ll explore the codebase to find tests or features related to databases.

shell
root@585f5e72dcd0:/workspace/scubaduck# grep -n "sample.csv" -R . ./scubaduck/server.py:16: "CREATE TABLE IF NOT EXISTS events AS SELECT * FROM read_csv_auto('scubaduck/sample.csv')" ./scubaduck/static/index.html:79: <div id="header">sample.csv - events</div>

I'll take a look at index.html to see what’s going on there.

shell
sed -n '70,90p' scubaduck/static/index.html
grep: ./.git/index: binary file matches ./tests/test_web.py:118: assert "sample.csv" in header root@585f5e72dcd0:/workspace/scubaduck# sed -n '70,90p' scubaduck/static/index.h tml margin-bottom: 5px; } #column_actions a { margin-left: 5px; } /* Column resizer removed */ </style> </head> <body> <div id="header">sample.csv - events</div> <div id="content"> <div id="sidebar"> <div id="tabs"> <button class="tab active" data-tab="settings">View Settings</button> <button class="tab" data-tab="columns">Columns</button> <button id="dive" onclick="dive()">Dive</button> </div> <div id="settings" class="tab-content active"> <div class="field"> <label>Start<span class="help" title="Sets the start/end of the time r ange to query. Can be any kind of datetime string. For example: 'April 23, 2014' or 'yesterday'.">[?]</span></label> <input id="start" type="text" /> root@585f5e72dcd0:/workspace/scubaduck# sed -n '70,110p' scubaduck/static/index. html margin-bottom: 5px; } #column_actions a { margin-left: 5px; } /* Column resizer removed */ </style> </head> <body> <div id="header">sample.csv - events</div> <div id="content"> <div id="sidebar"> <div id="tabs"> <button class="tab active" data-tab="settings">View Settings</button> <button class="tab" data-tab="columns">Columns</button> <button id="dive" onclick="dive()">Dive</button> </div> <div id="settings" class="tab-content active"> <div class="field"> <label>Start<span class="help" title="Sets the start/end of the time r ange to query. Can be any kind of datetime string. For example: 'April 23, 2014' or 'yesterday'.">[?]</span></label> <input id="start" type="text" /> <button type="button" class="rel-btn" data-target="start-select">&#966 0;</button> <select id="start-select" class="rel-select" data-input="start" style= "display:none"> <option value="-1 hour">-1 hour</option> <option value="-3 hours">-3 hours</option> <option value="-12 hours">-12 hours</option> <option value="-1 day">-1 day</option> <option value="-3 days">-3 days</option> <option value="-1 week">-1 week</option> <option value="-1 fortnight">-1 fortnight</option> <option value="-30 days">-30 days</option> <option value="-90 days">-90 days</option> </select> </div> <div class="field"> <label>End<span class="help" title="Sets the start/end of the time ran ge to query. Can be any kind of datetime string. For example: 'April 23, 2014' o r 'yesterday'.">[?]</span></label> <input id="end" type="text" /> <button type="button" class="rel-btn" data-target="end-select">&#9660; </button> <select id="end-select" class="rel-select" data-input="end" style="dis play:none"> <option value="-1 hour">-1 hour</option> <option value="-3 hours">-3 hours</option>

The header mentions "sample.csv" and events. I'll check the script in index.html for dynamic specifics.

shell
root@585f5e72dcd0:/workspace/scubaduck# grep -n "header" -n scubaduck/static/ind ex.html 8: #header { padding: 10px; font-weight: bold; border-bottom: 1px solid #ccc; } 79: <div id="header">sample.csv - events</div> 217: const header = document.createElement('div'); 218: header.textContent = g.name + ': '; 225: header.appendChild(allBtn); 226: header.appendChild(noneBtn); 227: div.appendChild(header); 555: fetch('/api/query', {method:'POST', headers:{'Content-Type':'application/j son'}, body:JSON.stringify(payload)}) 570: const header = document.createElement('tr'); 581: header.appendChild(th); 583: table.appendChild(header);
root@585f5e72dcd0:/workspace/scubaduck# sed -n '210,250p' scubaduck/static/index .html orderSelect.appendChild(o); } }); Object.keys(groups).forEach(key => { const g = groups[key]; const div = document.createElement('div'); div.className = 'col-group'; const header = document.createElement('div'); header.textContent = g.name + ': '; const allBtn = document.createElement('button'); allBtn.type = 'button'; allBtn.textContent = 'All'; const noneBtn = document.createElement('button'); noneBtn.type = 'button'; noneBtn.textContent = 'None'; header.appendChild(allBtn); header.appendChild(noneBtn); div.appendChild(header); const ul = document.createElement('ul'); g.ul = ul; g.cols.forEach(name => { const li = document.createElement('li'); const label = document.createElement('label'); const cb = document.createElement('input'); cb.type = 'checkbox'; cb.value = name; cb.checked = true; cb.addEventListener('change', updateSelectedColumns); label.appendChild(cb); label.appendChild(document.createTextNode(' ' + name)); li.appendChild(label); ul.appendChild(li); }); allBtn.addEventListener('click', () => { ul.querySelectorAll('input').forEach(cb => (cb.checked = true)); updateSelectedColumns(); }); noneBtn.addEventListener('click', () => { ul.querySelectorAll('input').forEach(cb => (cb.checked = false)); updateSelectedColumns(); });
root@585f5e72dcd0:/workspace/scubaduck# sed -n '520,590p' scubaduck/static/index .html box.style.display = op === 'empty' || op === '!empty' ? 'none' : 'block'; } colSel.addEventListener('change', populateOps); container.querySelector('.f-op').addEventListener('change', updateInputVis); populateOps(); document.getElementById('filter_list').appendChild(container); initChipInput(container); } let lastQueryTime = 0; let queryStart = 0; function dive() { updateSelectedColumns(); const payload = { start: document.getElementById('start').value, end: document.getElementById('end').value, order_by: document.getElementById('order_by').value, order_dir: orderDir, limit: parseInt(document.getElementById('limit').value, 10), columns: selectedColumns }; payload.filters = Array.from(document.querySelectorAll('#filters .filter')).ma p(f => { const chips = f.chips || []; const op = f.querySelector('.f-op').value; let value = null; if (op !== 'empty' && op !== '!empty') { value = chips.length === 0 ? null : (chips.length === 1 ? chips[0] : chips ); } return {column: f.querySelector('.f-col').value, op, value}; }); const view = document.getElementById('view'); view.innerHTML = '<p>Loading...</p>'; queryStart = performance.now(); fetch('/api/query', {method:'POST', headers:{'Content-Type':'application/json' }, body:JSON.stringify(payload)}) .then(r=>r.json()) .then(data => { lastQueryTime = Math.round(performance.now() - queryStart); showResults(data); }); } let originalRows = []; let sortState = {index: null, dir: null}; function renderTable(rows) { const table = document.getElementById('results'); table.innerHTML = ''; if (rows.length === 0) return; const header = document.createElement('tr'); selectedColumns.forEach((col, i) => { const th = document.createElement('th'); th.textContent = col; th.dataset.index = i; th.addEventListener('click', handleSort); if (sortState.index === i) { th.classList.add('sorted'); th.textContent = col + (sortState.dir === 'desc' ? ' \u25BC' : ' \u25B2'); } if (!isStringColumn(col)) th.style.textAlign = 'right'; header.appendChild(th); }); table.appendChild(header); rows.forEach(row => { const tr = document.createElement('tr'); tr.addEventListener('click', () => { tr.classList.toggle('selected'); }); row.forEach((v, i) => { const col = selectedColumns[i];

I'll update the header to show the actual file and modify server.py for CLI database connection.

shell
root@585f5e72dcd0:/workspace/scubaduck# cat pyproject.toml [project] name = "scubaduck" version = "0.1.0" description = "Scuba on DuckDB" readme = "README.md" requires-python = ">=3.12" license = {text = "MIT"} dependencies = [ "duckdb", "flask", "python-dateutil>=2.9.0.post0", ] [build-system] requires = ["hatchling"] build-backend = "hatchling.build" [tool.pytest.ini_options] addopts = "-n auto --tb=native" [tool.pyright] # Pyright configuration with strict settings include = ["scubaduck", "tests"] exclude = ["**/__pycache__", "dist"] stubPath = "stubs" venvPath = "." venv = ".venv" reportMissingImports = true reportMissingTypeStubs = true pythonVersion = "3.12" pythonPlatform = "All" typeCheckingMode = "strict" reportUnknownMemberType = true reportUnknownParameterType = true reportUnknownVariableType = true reportUnknownArgumentType = true reportPrivateImportUsage = true reportUntypedFunctionDecorator = true reportFunctionMemberAccess = true reportIncompatibleMethodOverride = true [tool.ruff] target-version = "py312" [tool.uv] dev-dependencies = [ "pytest>=8.3.5", "ruff>=0.11.2", "pytest-xdist>=3.6.1", "playwright>=1.52.0", "pyright>=1.1.350", "pytest-playwright>=0.7.0", ]

I'll run some tests to establish the baseline before proceeding.

shell
root@585f5e72dcd0:/workspace/scubaduck# source .venv/bin/activate (scubaduck) root@585f5e72dcd0:/workspace/scubaduck# pytest -q
bringing up nodes...


...................... [100%] 22 passed in 6.55s (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'll make the database configurable and support CSV, SQLite, and DuckDB via filename input.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# python - <<'PY' > import duckdb > con = duckdb.connect() > print(duckdb.__version__) > try: > con.execute("INSTALL sqlite") > print('Install success') > except Exception as e: > print('Install failed', e) > try: > con.execute("LOAD sqlite") > con.execute("SELECT sqlite_version()") > print('Load success', con.fetchall()) > except Exception as e: > print('Load failed', e) > PY 1.2.2 Install failed IO Error: Failed to download extension "sqlite_scanner" at URL "h ttp://extensions.duckdb.org/v1.2.2/linux_amd64_gcc4/sqlite_scanner.duckdb_extens ion.gz" Extension "sqlite_scanner" is an existing extension. For more info, visit https://duckdb.org/docs/extensions/troubleshooting/?version =v1.2.2&platform=linux_amd64_gcc4&extension=sqlite_scanner (ERROR Could not esta blish connection) Load failed IO Error: Failed to download extension "sqlite_scanner" at URL "http ://extensions.duckdb.org/v1.2.2/linux_amd64_gcc4/sqlite_scanner.duckdb_extension .gz" Extension "sqlite_scanner" is an existing extension. For more info, visit https://duckdb.org/docs/extensions/troubleshooting/?version =v1.2.2&platform=linux_amd64_gcc4&extension=sqlite_scanner (ERROR Could not esta blish connection) (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

Network failure prevents automatic DuckDB extension load. I'll use Python's sqlite3 to transfer data.

shell
(scubaduck) root@585f5e72dcd0:/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 (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'm weighing options to load data—SQLite3, CSV, or custom bridging with Arrow or DuckDB.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# pip show pyarrow >/dev/null && echo yes
WARNING: Package(s) not found: pyarrow (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

No pyarrow, but I can try bridging with simple methods like execute for sql and CSV.

I'll adapt server.py to load from SQLite or DuckDB, supporting CSV, SQLite, or .duckdb files.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# cat scubaduck/__init__.py def hello() -> str: return "Hello from scubaduck!" (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'll search for tests or imports of server.create_app to find its usage.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# grep -n "create_app" -R .venv/lib/python3.12/site-packages/flask/cli.py:67: for attr_name in ("create _app", "make_app"): .venv/lib/python3.12/site-packages/flask/cli.py:308: create_app: t.Callab le[..., Flask] | None = None, .venv/lib/python3.12/site-packages/flask/cli.py:316: self.create_app = cr eate_app .venv/lib/python3.12/site-packages/flask/cli.py:341: if self.create_app i s not None: .venv/lib/python3.12/site-packages/flask/cli.py:342: app = self.creat e_app() .venv/lib/python3.12/site-packages/flask/cli.py:459: " 'app', 'applicatio n', 'create_app', or 'make_app', and can be 'name(args)' to" .venv/lib/python3.12/site-packages/flask/cli.py:541: :param create_app: an op tional callback that is passed the script info and .venv/lib/python3.12/site-packages/flask/cli.py:566: create_app: t.Callab le[..., Flask] | None = None, .venv/lib/python3.12/site-packages/flask/cli.py:589: self.create_app = cr eate_app .venv/lib/python3.12/site-packages/flask/cli.py:679: create_app=s elf.create_app, grep: .venv/lib/python3.12/site-packages/flask/__pycache__/testing.cpython-312.p yc: binary file matches grep: .venv/lib/python3.12/site-packages/flask/__pycache__/cli.cpython-312.pyc: binary file matches .venv/lib/python3.12/site-packages/flask/testing.py:296: kwargs["obj" ] = ScriptInfo(create_app=lambda: self.app)

I'm thinking of adding a function to make the app configurable by database file.

I'll modify index.html to dynamically load dataset name and table info from the server.

I’ll keep the "sample.csv" header static but adjust tests for dynamic databases paths.

shell
.venv/lib/python3.12/site-packages/werkzeug/serving.py:11: from myapp import create_app grep: .venv/lib/python3.12/site-packages/werkzeug/__pycache__/serving.cpython-31 2.pyc: binary file matches .venv/lib64/python3.12/site-packages/flask/cli.py:67: for attr_name in ("crea te_app", "make_app"): .venv/lib64/python3.12/site-packages/flask/cli.py:308: create_app: t.Call able[..., Flask] | None = None, .venv/lib64/python3.12/site-packages/flask/cli.py:316: self.create_app = create_app .venv/lib64/python3.12/site-packages/flask/cli.py:341: if self.create_app is not None: .venv/lib64/python3.12/site-packages/flask/cli.py:342: app = self.cre ate_app() .venv/lib64/python3.12/site-packages/flask/cli.py:459: " 'app', 'applicat ion', 'create_app', or 'make_app', and can be 'name(args)' to" .venv/lib64/python3.12/site-packages/flask/cli.py:541: :param create_app: an optional callback that is passed the script info and .venv/lib64/python3.12/site-packages/flask/cli.py:566: create_app: t.Call able[..., Flask] | None = None, .venv/lib64/python3.12/site-packages/flask/cli.py:589: self.create_app = create_app .venv/lib64/python3.12/site-packages/flask/cli.py:679: create_app =self.create_app, grep: .venv/lib64/python3.12/site-packages/flask/__pycache__/testing.cpython-312 .pyc: binary file matches grep: .venv/lib64/python3.12/site-packages/flask/__pycache__/cli.cpython-312.pyc : binary file matches .venv/lib64/python3.12/site-packages/flask/testing.py:296: kwargs["ob j"] = ScriptInfo(create_app=lambda: self.app) .venv/lib64/python3.12/site-packages/werkzeug/serving.py:11: from myapp impor t create_app grep: .venv/lib64/python3.12/site-packages/werkzeug/__pycache__/serving.cpython- 312.pyc: binary file matches (scubaduck) root@585f5e72dcd0:/workspace/scubaduck# cat tests/conftest.py from __future__ import annotations import threading from collections.abc import Iterator import pytest from werkzeug.serving import make_server from scubaduck.server import app @pytest.fixture() def server_url() -> Iterator[str]: httpd = make_server("127.0.0.1", 0, app) port = httpd.server_port thread = threading.Thread(target=httpd.serve_forever) thread.start() try: yield f"http://127.0.0.1:{port}" finally: httpd.shutdown() thread.join() (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I’m thinking of creating a new create_app() to handle different DB paths while keeping default behavior. This would help us test loading from custom databases like SQLite. I'll inspect any changes and adapt the server app's API. Time to implement!

I'm adapting the load_db function to support SQLite, CSV, and DuckDB with custom handling for file paths. I need to update create_app to use these connections and manage global types carefully. Time to handle SQLite specifics and tweak file resolution.

I'll write tests for CSV, SQLite, and DuckDB support, ensuring automatic DB inference works correctly.

I'll replicate sample.csv for each DB test and implement simple setup for SQLite and DuckDB. Time to adjust the code to handle sample data efficiently.

shell
from flask import Flask, jsonify, request, send_from_directory app = Flask(__name__, static_folder="static") # Initialize DuckDB in-memory and load sample data con = duckdb.connect() con.execute( "CREATE TABLE IF NOT EXISTS events AS SELECT * FROM read_csv_auto('scubaduck /sample.csv')" ) _column_types: Dict[str, str] = { r[1]: r[2] for r in con.execute("PRAGMA table_info(events)").fetchall() } @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: {}) @app.route("/") def index() -> Any: assert app.static_folder is not None return send_from_directory(app.static_folder, "index.html") @app.route("/api/columns") def columns() -> Any: rows = con.execute("PRAGMA table_info(events)").fetchall() return jsonify([{"name": r[1], "type": r[2]} for r in rows]) # Simple in-memory LRU cache for sample value queries _SAMPLE_CACHE: Dict[Tuple[str, str], Tuple[List[str], float]] = {} _CACHE_TTL = 60.0 _CACHE_LIMIT = 200 def _cache_get(key: Tuple[str, str]) -> List[str] | None: item = _SAMPLE_CACHE.get(key) if item is None: return None vals, ts = item if time.time() - ts > _CACHE_TTL: del _SAMPLE_CACHE[key] return None _SAMPLE_CACHE[key] = (vals, time.time()) return vals def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: _SAMPLE_CACHE[key] = (vals, time.time()) if len(_SAMPLE_CACHE) > _CACHE_LIMIT: oldest = min(_SAMPLE_CACHE.items(), key=lambda kv: kv[1][1])[0] del _SAMPLE_CACHE[oldest] @app.route("/api/samples") def sample_values() -> Any: column = request.args.get("column") substr = request.args.get("q", "") if not column or column not in _column_types: return jsonify([]) ctype = _column_types[column].upper() if "CHAR" not in ctype and "STRING" not in ctype and "VARCHAR" not in ctype: return jsonify([]) key = (column, substr) cached = _cache_get(key) if cached is not None: return jsonify(cached) rows = con.execute( f"SELECT DISTINCT {column} FROM events WHERE CAST({column} AS VARCHAR) I LIKE '%' || ? || '%' LIMIT 20", [substr], ).fetchall() values = [r[0] for r in rows] _cache_set(key, values) return jsonify(values) def build_query(params: QueryParams) -> str: select_parts = [*params.columns] for name, expr in params.derived_columns.items(): select_parts.append(f"{expr} AS {name}") select_clause = ", ".join(select_parts) if select_parts else "*" query = f"SELECT {select_clause} FROM events" where_parts: list[str] = [] if params.start: where_parts.append(f"timestamp >= '{params.start}'") if params.end: where_parts.append(f"timestamp <= '{params.end}'") for f in params.filters: op = f.op if op in {"empty", "!empty"}: val = "''" else: if f.value is None: continue if isinstance(f.value, list): if not f.value: continue if op == "=": vals = " OR ".join(f"{f.column} = '{v}'" for v in f.value) where_parts.append(f"({vals})") continue val = f"'{f.value}'" if isinstance(f.value, str) else str(f.value) if op == "contains": where_parts.append(f"{f.column} ILIKE '%' || {val} || '%'") elif op == "!contains": where_parts.append(f"{f.column} NOT ILIKE '%' || {val} || '%'") elif op == "empty": where_parts.append(f"{f.column} = {val}") elif op == "!empty": where_parts.append(f"{f.column} != {val}") else: where_parts.append(f"{f.column} {op} {val}") if where_parts: query += " WHERE " + " AND ".join(where_parts) if params.order_by: query += f" ORDER BY {params.order_by} {params.order_dir}" if params.limit is not None: query += f" LIMIT {params.limit}" return query @app.route("/api/query", methods=["POST"]) def query() -> Any: payload = request.get_json(force=True) params = QueryParams( start=payload.get("start"), end=payload.get("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", {}), ) for f in payload.get("filters", []): params.filters.append(Filter(f["column"], f["op"], f.get("value"))) sql = build_query(params) rows = con.execute(sql).fetchall() return jsonify({"sql": sql, "rows": rows}) if __name__ == "__main__": app.run(debug=True) (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'm simplifying the app: I’ll use closures to store connection and column_types.

I'll write tests for CSV, sqlite, and duckdb, comparing data to expected results.

shell
> import csv > import pathlib > from datetime import datetime > rows = [] > with open('scubaduck/sample.csv') as f: > for row in csv.DictReader(f): > rows.append(row) > print(rows) > PY [{'timestamp': '2024-01-01 00:00:00', 'event': 'login', 'value': '10', 'user': ' alice'}, {'timestamp': '2024-01-01 01:00:00', 'event': 'logout', 'value': '20', 'user': 'bob'}, {'timestamp': '2024-01-02 00:00:00', 'event': 'login', 'value': '30', 'user': 'alice'}, {'timestamp': '2024-01-02 03:00:00', 'event': 'login', ' value': '40', 'user': 'charlie'}] (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I’ll adjust tests for the dynamic path and call create_app explicitly without cross-contamination.

shell
> *** Update File: scubaduck/server.py > @@ > -from flask import Flask, jsonify, request, send_from_directory > - > -app = Flask(__name__, static_folder="static") > - > -# Initialize DuckDB in-memory and load sample data > -con = duckdb.connect() > -con.execute( > - "CREATE TABLE IF NOT EXISTS events AS SELECT * FROM read_csv_auto('scubad uck/sample.csv')" > -) > -_column_types: Dict[str, str] = { > - r[1]: r[2] for r in con.execute("PRAGMA table_info(events)").fetchall() > -} > +from pathlib import Path > +import sqlite3 > +from flask import Flask, jsonify, request, send_from_directory > + > + > +def _load_database(path: Path) -> duckdb.DuckDBPyConnection: > + ext = path.suffix.lower() > + if ext == ".csv": > + con = duckdb.connect() > + con.execute( > + f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{path.as_po six()}')" > + ) > + elif ext in {".db", ".sqlite"}: > + con = duckdb.connect() > + sconn = sqlite3.connect(path) > + info = sconn.execute("PRAGMA table_info(events)").fetchall() > + col_defs = ", ".join(f"{r[1]} {r[2]}" for r in info) > + con.execute(f"CREATE TABLE events ({col_defs})") > + placeholders = ",".join("?" for _ in info) > + for row in sconn.execute("SELECT * FROM events"): > + con.execute(f"INSERT INTO events VALUES ({placeholders})", row) > + sconn.close() > + else: > + con = duckdb.connect(path) > + return con > + > + > +def create_app(db_file: str | Path | None = None) -> Flask: > + app = Flask(__name__, static_folder="static") > + db_path = Path(db_file or Path(__file__).with_name("sample.csv")).resolve () > + con = _load_database(db_path) > + column_types: Dict[str, str] = { > + r[1]: r[2] for r in con.execute("PRAGMA table_info(events)").fetchall () > + } > + > + # Simple in-memory LRU cache for sample value queries > + sample_cache: Dict[Tuple[str, str], Tuple[List[str], float]] = {} > + CACHE_TTL = 60.0 > + CACHE_LIMIT = 200 > *** End Patch > PATCH Success. Updated the following files: M scubaduck/server.py (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'll keep updating the rest of the file with the necessary changes.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# grep -n "sample_cache" -n sc ubaduck/server.py 45: sample_cache: Dict[Tuple[str, str], Tuple[List[str], float]] = {} (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'll check the context after making those changes.

shell
from pathlib import Path import sqlite3 from flask import Flask, jsonify, request, send_from_directory def _load_database(path: Path) -> duckdb.DuckDBPyConnection: ext = path.suffix.lower() if ext == ".csv": con = duckdb.connect() con.execute( f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{path.as_posix ()}')" ) elif ext in {".db", ".sqlite"}: con = duckdb.connect() sconn = sqlite3.connect(path) info = sconn.execute("PRAGMA table_info(events)").fetchall() col_defs = ", ".join(f"{r[1]} {r[2]}" for r in info) con.execute(f"CREATE TABLE events ({col_defs})") placeholders = ",".join("?" for _ in info) for row in sconn.execute("SELECT * FROM events"): con.execute(f"INSERT INTO events VALUES ({placeholders})", row) sconn.close() else: con = duckdb.connect(path) return con def create_app(db_file: str | Path | None = None) -> Flask: app = Flask(__name__, static_folder="static") db_path = Path(db_file or Path(__file__).with_name("sample.csv")).resolve() con = _load_database(db_path) column_types: Dict[str, str] = { r[1]: r[2] for r in con.execute("PRAGMA table_info(events)").fetchall() } # Simple in-memory LRU cache for sample value queries sample_cache: Dict[Tuple[str, str], Tuple[List[str], float]] = {} CACHE_TTL = 60.0 CACHE_LIMIT = 200 @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: {}) @app.route("/") def index() -> Any: assert app.static_folder is not None return send_from_directory(app.static_folder, "index.html") @app.route("/api/columns") def columns() -> Any: rows = con.execute("PRAGMA table_info(events)").fetchall() return jsonify([{"name": r[1], "type": r[2]} for r in rows]) # Simple in-memory LRU cache for sample value queries _SAMPLE_CACHE: Dict[Tuple[str, str], Tuple[List[str], float]] = {} _CACHE_TTL = 60.0 _CACHE_LIMIT = 200 def _cache_get(key: Tuple[str, str]) -> List[str] | None: item = _SAMPLE_CACHE.get(key) if item is None: return None vals, ts = item if time.time() - ts > _CACHE_TTL: del _SAMPLE_CACHE[key] return None _SAMPLE_CACHE[key] = (vals, time.time()) return vals def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: _SAMPLE_CACHE[key] = (vals, time.time()) if len(_SAMPLE_CACHE) > _CACHE_LIMIT: oldest = min(_SAMPLE_CACHE.items(), key=lambda kv: kv[1][1])[0] del _SAMPLE_CACHE[oldest] @app.route("/api/samples") def sample_values() -> Any: column = request.args.get("column") substr = request.args.get("q", "") if not column or column not in _column_types: return jsonify([]) ctype = _column_types[column].upper() if "CHAR" not in ctype and "STRING" not in ctype and "VARCHAR" not in ctype: return jsonify([]) key = (column, substr) cached = _cache_get(key) if cached is not None: return jsonify(cached) rows = con.execute( f"SELECT DISTINCT {column} FROM events WHERE CAST({column} AS VARCHAR) I LIKE '%' || ? || '%' LIMIT 20", (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

The patch is incomplete; I’ll open the full file to apply the patch.

shell
f"SELECT DISTINCT {column} FROM events WHERE CAST({column} AS VARCHAR) I LIKE '%' || ? || '%' LIMIT 20", [substr], ).fetchall() values = [r[0] for r in rows] _cache_set(key, values) return jsonify(values) def build_query(params: QueryParams) -> str: select_parts = [*params.columns] for name, expr in params.derived_columns.items(): select_parts.append(f"{expr} AS {name}") select_clause = ", ".join(select_parts) if select_parts else "*" query = f"SELECT {select_clause} FROM events" where_parts: list[str] = [] if params.start: where_parts.append(f"timestamp >= '{params.start}'") if params.end: where_parts.append(f"timestamp <= '{params.end}'") for f in params.filters: op = f.op if op in {"empty", "!empty"}: val = "''" else: if f.value is None: continue if isinstance(f.value, list): if not f.value: continue if op == "=": vals = " OR ".join(f"{f.column} = '{v}'" for v in f.value) where_parts.append(f"({vals})") continue val = f"'{f.value}'" if isinstance(f.value, str) else str(f.value) if op == "contains": where_parts.append(f"{f.column} ILIKE '%' || {val} || '%'") elif op == "!contains": where_parts.append(f"{f.column} NOT ILIKE '%' || {val} || '%'") elif op == "empty": where_parts.append(f"{f.column} = {val}") elif op == "!empty": where_parts.append(f"{f.column} != {val}") else: where_parts.append(f"{f.column} {op} {val}") if where_parts: query += " WHERE " + " AND ".join(where_parts) if params.order_by: query += f" ORDER BY {params.order_by} {params.order_dir}" if params.limit is not None: query += f" LIMIT {params.limit}" return query @app.route("/api/query", methods=["POST"]) def query() -> Any: payload = request.get_json(force=True) params = QueryParams( start=payload.get("start"), end=payload.get("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", {}), ) for f in payload.get("filters", []): params.filters.append(Filter(f["column"], f["op"], f.get("value"))) sql = build_query(params) rows = con.execute(sql).fetchall() return jsonify({"sql": sql, "rows": rows}) if __name__ == "__main__": app.run(debug=True) (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

The file still uses global variables—I'll rewrite it to use closure variables instead.

shell
def _load_database(path: Path) -> duckdb.DuckDBPyConnection: ext = path.suffix.lower() if ext == ".csv": con = duckdb.connect() con.execute( f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{path.as_posix ()}')" ) elif ext in {".db", ".sqlite"}: con = duckdb.connect() sconn = sqlite3.connect(path) info = sconn.execute("PRAGMA table_info(events)").fetchall() col_defs = ", ".join(f"{r[1]} {r[2]}" for r in info) con.execute(f"CREATE TABLE events ({col_defs})") placeholders = ",".join("?" for _ in info) for row in sconn.execute("SELECT * FROM events"): con.execute(f"INSERT INTO events VALUES ({placeholders})", row) sconn.close() else: con = duckdb.connect(path) return con def create_app(db_file: str | Path | None = None) -> Flask: app = Flask(__name__, static_folder="static") db_path = Path(db_file or Path(__file__).with_name("sample.csv")).resolve() con = _load_database(db_path) column_types: Dict[str, str] = { r[1]: r[2] for r in con.execute("PRAGMA table_info(events)").fetchall() } # Simple in-memory LRU cache for sample value queries sample_cache: Dict[Tuple[str, str], Tuple[List[str], float]] = {} CACHE_TTL = 60.0 CACHE_LIMIT = 200 @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: {}) @app.route("/") def index() -> Any: assert app.static_folder is not None return send_from_directory(app.static_folder, "index.html") @app.route("/api/columns") def columns() -> Any: rows = con.execute("PRAGMA table_info(events)").fetchall() return jsonify([{"name": r[1], "type": r[2]} for r in rows]) # Simple in-memory LRU cache for sample value queries _SAMPLE_CACHE: Dict[Tuple[str, str], Tuple[List[str], float]] = {} _CACHE_TTL = 60.0 _CACHE_LIMIT = 200 def _cache_get(key: Tuple[str, str]) -> List[str] | None: item = _SAMPLE_CACHE.get(key) if item is None: return None vals, ts = item if time.time() - ts > _CACHE_TTL: del _SAMPLE_CACHE[key] return None _SAMPLE_CACHE[key] = (vals, time.time()) return vals def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: _SAMPLE_CACHE[key] = (vals, time.time()) if len(_SAMPLE_CACHE) > _CACHE_LIMIT: oldest = min(_SAMPLE_CACHE.items(), key=lambda kv: kv[1][1])[0] del _SAMPLE_CACHE[oldest] @app.route("/api/samples") def sample_values() -> Any: column = request.args.get("column") substr = request.args.get("q", "") if not column or column not in _column_types: return jsonify([]) ctype = _column_types[column].upper() if "CHAR" not in ctype and "STRING" not in ctype and "VARCHAR" not in ctype: return jsonify([]) key = (column, substr) cached = _cache_get(key) if cached is not None: return jsonify(cached) rows = con.execute( f"SELECT DISTINCT {column} FROM events WHERE CAST({column} AS VARCHAR) I LIKE '%' || ? || '%' LIMIT 20", [substr], ).fetchall() values = [r[0] for r in rows] _cache_set(key, values) return jsonify(values) def build_query(params: QueryParams) -> str: select_parts = [*params.columns] for name, expr in params.derived_columns.items(): select_parts.append(f"{expr} AS {name}") select_clause = ", ".join(select_parts) if select_parts else "*" query = f"SELECT {select_clause} FROM events" where_parts: list[str] = [] if params.start: where_parts.append(f"timestamp >= '{params.start}'") if params.end: where_parts.append(f"timestamp <= '{params.end}'") for f in params.filters: op = f.op if op in {"empty", "!empty"}: val = "''" else: if f.value is None: continue if isinstance(f.value, list): if not f.value: continue if op == "=": vals = " OR ".join(f"{f.column} = '{v}'" for v in f.value) where_parts.append(f"({vals})") continue val = f"'{f.value}'" if isinstance(f.value, str) else str(f.value) if op == "contains": where_parts.append(f"{f.column} ILIKE '%' || {val} || '%'") elif op == "!contains": where_parts.append(f"{f.column} NOT ILIKE '%' || {val} || '%'") elif op == "empty": where_parts.append(f"{f.column} = {val}") elif op == "!empty": where_parts.append(f"{f.column} != {val}") else: where_parts.append(f"{f.column} {op} {val}") if where_parts: query += " WHERE " + " AND ".join(where_parts) if params.order_by: query += f" ORDER BY {params.order_by} {params.order_dir}" if params.limit is not None: query += f" LIMIT {params.limit}" return query @app.route("/api/query", methods=["POST"]) def query() -> Any: payload = request.get_json(force=True) params = QueryParams( start=payload.get("start"), end=payload.get("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", {}), ) for f in payload.get("filters", []): params.filters.append(Filter(f["column"], f["op"], f.get("value"))) sql = build_query(params) rows = con.execute(sql).fetchall() return jsonify({"sql": sql, "rows": rows}) if __name__ == "__main__": app.run(debug=True) (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'm checking the first lines of the file—looks like import duckdb is missing!

shell
py from __future__ import annotations from dataclasses import dataclass, field from typing import Any, Dict, Tuple, List import time import duckdb from pathlib import Path import sqlite3 from flask import Flask, jsonify, request, send_from_directory def _load_database(path: Path) -> duckdb.DuckDBPyConnection: ext = path.suffix.lower() (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I need to remove the unnecessary "py" and check the unused global variables.

shell
from dataclasses import dataclass, field from typing import Any, Dict, Tuple, List import time import duckdb from pathlib import Path import sqlite3 from flask import Flask, jsonify, request, send_from_directory def _load_database(path: Path) -> duckdb.DuckDBPyConnection: ext = path.suffix.lower() if ext == ".csv": con = duckdb.connect() con.execute( f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{path.as_posix ()}')" ) elif ext in {".db", ".sqlite"}: con = duckdb.connect() sconn = sqlite3.connect(path) info = sconn.execute("PRAGMA table_info(events)").fetchall() col_defs = ", ".join(f"{r[1]} {r[2]}" for r in info) con.execute(f"CREATE TABLE events ({col_defs})") placeholders = ",".join("?" for _ in info) for row in sconn.execute("SELECT * FROM events"): con.execute(f"INSERT INTO events VALUES ({placeholders})", row) sconn.close() else: con = duckdb.connect(path) return con def create_app(db_file: str | Path | None = None) -> Flask: app = Flask(__name__, static_folder="static") db_path = Path(db_file or Path(__file__).with_name("sample.csv")).resolve() con = _load_database(db_path) column_types: Dict[str, str] = { r[1]: r[2] for r in con.execute("PRAGMA table_info(events)").fetchall() } # Simple in-memory LRU cache for sample value queries sample_cache: Dict[Tuple[str, str], Tuple[List[str], float]] = {} CACHE_TTL = 60.0 CACHE_LIMIT = 200 @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 (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I think I missed where "py" is. Let me open the full file to check.

shell
ver.py from __future__ import annotations from dataclasses import dataclass, field from typing import Any, Dict, Tuple, List import time import duckdb from pathlib import Path import sqlite3 (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

Hmm, the file displayed oddly, it might have been truncated. I’ll try opening it again.

shell
y | cat -n 1 from __future__ import annotations 2 3 from dataclasses import dataclass, field 4 from typing import Any, Dict, Tuple, List 5 (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I suspect the previous command caused issues. I'll confirm by inspecting the first 20 lines.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# sed -n '1,20p' scubaduck/ser ver.py from __future__ import annotations from dataclasses import dataclass, field from typing import Any, Dict, Tuple, List import time import duckdb from pathlib import Path import sqlite3 from flask import Flask, jsonify, request, send_from_directory def _load_database(path: Path) -> duckdb.DuckDBPyConnection: ext = path.suffix.lower() if ext == ".csv": con = duckdb.connect() con.execute( f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{path.as_posix ()}')" ) (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

The file got cut off; I need to see more lines to view the patch fully.

shell
con = duckdb.connect() sconn = sqlite3.connect(path) info = sconn.execute("PRAGMA table_info(events)").fetchall() col_defs = ", ".join(f"{r[1]} {r[2]}" for r in info) con.execute(f"CREATE TABLE events ({col_defs})") placeholders = ",".join("?" for _ in info) for row in sconn.execute("SELECT * FROM events"): con.execute(f"INSERT INTO events VALUES ({placeholders})", row) sconn.close() else: con = duckdb.connect(path) return con def create_app(db_file: str | Path | None = None) -> Flask: app = Flask(__name__, static_folder="static") db_path = Path(db_file or Path(__file__).with_name("sample.csv")).resolve() con = _load_database(db_path) column_types: Dict[str, str] = { r[1]: r[2] for r in con.execute("PRAGMA table_info(events)").fetchall() } # Simple in-memory LRU cache for sample value queries sample_cache: Dict[Tuple[str, str], Tuple[List[str], float]] = {} CACHE_TTL = 60.0 CACHE_LIMIT = 200 @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: {}) @app.route("/") def index() -> Any: assert app.static_folder is not None return send_from_directory(app.static_folder, "index.html") @app.route("/api/columns") def columns() -> Any: rows = con.execute("PRAGMA table_info(events)").fetchall() return jsonify([{"name": r[1], "type": r[2]} for r in rows]) (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I stopped at 80 lines, but I still need to check further.

shell
def _cache_get(key: Tuple[str, str]) -> List[str] | None: item = _SAMPLE_CACHE.get(key) if item is None: return None vals, ts = item if time.time() - ts > _CACHE_TTL: del _SAMPLE_CACHE[key] return None _SAMPLE_CACHE[key] = (vals, time.time()) return vals def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: _SAMPLE_CACHE[key] = (vals, time.time()) if len(_SAMPLE_CACHE) > _CACHE_LIMIT: oldest = min(_SAMPLE_CACHE.items(), key=lambda kv: kv[1][1])[0] del _SAMPLE_CACHE[oldest] @app.route("/api/samples") def sample_values() -> Any: column = request.args.get("column") substr = request.args.get("q", "") if not column or column not in _column_types: return jsonify([]) ctype = _column_types[column].upper() if "CHAR" not in ctype and "STRING" not in ctype and "VARCHAR" not in ctype: return jsonify([]) key = (column, substr) cached = _cache_get(key) if cached is not None: return jsonify(cached) rows = con.execute( f"SELECT DISTINCT {column} FROM events WHERE CAST({column} AS VARCHAR) I LIKE '%' || ? || '%' LIMIT 20", [substr], ).fetchall() values = [r[0] for r in rows] _cache_set(key, values) return jsonify(values) def build_query(params: QueryParams) -> str: select_parts = [*params.columns] for name, expr in params.derived_columns.items(): select_parts.append(f"{expr} AS {name}") select_clause = ", ".join(select_parts) if select_parts else "*" query = f"SELECT {select_clause} FROM events" where_parts: list[str] = [] if params.start: where_parts.append(f"timestamp >= '{params.start}'") if params.end: where_parts.append(f"timestamp <= '{params.end}'") for f in params.filters: op = f.op if op in {"empty", "!empty"}: val = "''" else: if f.value is None: continue if isinstance(f.value, list): if not f.value: continue if op == "=": vals = " OR ".join(f"{f.column} = '{v}'" for v in f.value) where_parts.append(f"({vals})") continue val = f"'{f.value}'" if isinstance(f.value, str) else str(f.value) if op == "contains": where_parts.append(f"{f.column} ILIKE '%' || {val} || '%'") elif op == "!contains": where_parts.append(f"{f.column} NOT ILIKE '%' || {val} || '%'") elif op == "empty": where_parts.append(f"{f.column} = {val}") (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'm still working on replacing _SAMPLE_CACHE with local sample_cache variables. Let's continue.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# sed -n '160,320p' scubaduck/ server.py where_parts.append(f"{f.column} = {val}") elif op == "!empty": where_parts.append(f"{f.column} != {val}") else: where_parts.append(f"{f.column} {op} {val}") if where_parts: query += " WHERE " + " AND ".join(where_parts) if params.order_by: query += f" ORDER BY {params.order_by} {params.order_dir}" if params.limit is not None: query += f" LIMIT {params.limit}" return query @app.route("/api/query", methods=["POST"]) def query() -> Any: payload = request.get_json(force=True) params = QueryParams( start=payload.get("start"), end=payload.get("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", {}), ) for f in payload.get("filters", []): params.filters.append(Filter(f["column"], f["op"], f.get("value"))) sql = build_query(params) rows = con.execute(sql).fetchall() return jsonify({"sql": sql, "rows": rows}) if __name__ == "__main__": app.run(debug=True) (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

The global variables like _SAMPLE_CACHE need to be replaced with local versions. I'll update imports too.

shell
> *** Begin Patch > *** Update File: scubaduck/server.py > @@ > -import time > - > -import duckdb > -from pathlib import Path > -import sqlite3 > -from flask import Flask, jsonify, request, send_from_directory > +import time > + > +import duckdb > +from pathlib import Path > +import sqlite3 > +from flask import Flask, jsonify, request, send_from_directory > *** End Patch > PATCH Success. Updated the following files: M scubaduck/server.py (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

It looks like no change is needed. I'll focus on fixing the rest.

shell
> *** Begin Patch > *** Update File: scubaduck/server.py > @@ > - sample_cache: Dict[Tuple[str, str], Tuple[List[str], float]] = {} > - CACHE_TTL = 60.0 > - CACHE_LIMIT = 200 > + sample_cache: Dict[Tuple[str, str], Tuple[List[str], float]] = {} > + CACHE_TTL = 60.0 > + CACHE_LIMIT = 200 > *** End Patch > PATCH Success. Updated the following files: M scubaduck/server.py (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

The patch adjusted spaces, but I’ll also update references to _SAMPLE_CACHE and _CACHE_TTL.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# grep -n "_SAMPLE_CACHE" -n s cubaduck/server.py 82:_SAMPLE_CACHE: Dict[Tuple[str, str], Tuple[List[str], float]] = {} 88: item = _SAMPLE_CACHE.get(key) 93: del _SAMPLE_CACHE[key] 95: _SAMPLE_CACHE[key] = (vals, time.time()) 100: _SAMPLE_CACHE[key] = (vals, time.time()) 101: if len(_SAMPLE_CACHE) > _CACHE_LIMIT: 102: oldest = min(_SAMPLE_CACHE.items(), key=lambda kv: kv[1][1])[0] 103: del _SAMPLE_CACHE[oldest] (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I’ll update the code to use sample_cache and replace _CACHE_TTL and related parts.

shell
@app.route("/api/columns") def columns() -> Any: rows = con.execute("PRAGMA table_info(events)").fetchall() return jsonify([{"name": r[1], "type": r[2]} for r in rows]) # Simple in-memory LRU cache for sample value queries _SAMPLE_CACHE: Dict[Tuple[str, str], Tuple[List[str], float]] = {} _CACHE_TTL = 60.0 _CACHE_LIMIT = 200 def _cache_get(key: Tuple[str, str]) -> List[str] | None: item = _SAMPLE_CACHE.get(key) if item is None: return None vals, ts = item if time.time() - ts > _CACHE_TTL: del _SAMPLE_CACHE[key] return None _SAMPLE_CACHE[key] = (vals, time.time()) return vals def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: _SAMPLE_CACHE[key] = (vals, time.time()) if len(_SAMPLE_CACHE) > _CACHE_LIMIT: oldest = min(_SAMPLE_CACHE.items(), key=lambda kv: kv[1][1])[0] del _SAMPLE_CACHE[oldest] @app.route("/api/samples") def sample_values() -> Any: column = request.args.get("column") substr = request.args.get("q", "") if not column or column not in _column_types: (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I’ll go ahead and apply the patch.

shell
> *** Update File: scubaduck/server.py > @@ > -# Simple in-memory LRU cache for sample value queries > -_SAMPLE_CACHE: Dict[Tuple[str, str], Tuple[List[str], float]] = {} > -_CACHE_TTL = 60.0 > -_CACHE_LIMIT = 200 > +# Simple in-memory LRU cache for sample value queries > + def _cache_get(key: Tuple[str, str]) -> List[str] | None: > + item = sample_cache.get(key) > + if item is None: > + return None > + vals, ts = item > + if time.time() - ts > CACHE_TTL: > + del sample_cache[key] > + return None > + sample_cache[key] = (vals, time.time()) > + return vals > + > + def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: > + sample_cache[key] = (vals, time.time()) > + if len(sample_cache) > CACHE_LIMIT: > + oldest = min(sample_cache.items(), key=lambda kv: kv[1][1])[0] > + del sample_cache[oldest] > *** End Patch > PATCH Success. Updated the following files: M scubaduck/server.py (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I replaced the original functions but need to verify that no old definitions remain.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# grep -n "def _cache_get" -n scubaduck/server.py 82: def _cache_get(key: Tuple[str, str]) -> List[str] | None: 100:def _cache_get(key: Tuple[str, str]) -> List[str] | None: (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I see two definitions because the patch added new ones without removing the old. Let's highlight those lines!

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# sed -n '80,115p' scubaduck/s erver.py # Simple in-memory LRU cache for sample value queries def _cache_get(key: Tuple[str, str]) -> List[str] | None: item = sample_cache.get(key) if item is None: return None vals, ts = item if time.time() - ts > CACHE_TTL: del sample_cache[key] return None sample_cache[key] = (vals, time.time()) return vals def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: sample_cache[key] = (vals, time.time()) if len(sample_cache) > CACHE_LIMIT: oldest = min(sample_cache.items(), key=lambda kv: kv[1][1])[0] del sample_cache[oldest] def _cache_get(key: Tuple[str, str]) -> List[str] | None: item = _SAMPLE_CACHE.get(key) if item is None: return None vals, ts = item if time.time() - ts > _CACHE_TTL: del _SAMPLE_CACHE[key] return None _SAMPLE_CACHE[key] = (vals, time.time()) return vals def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: _SAMPLE_CACHE[key] = (vals, time.time()) if len(_SAMPLE_CACHE) > _CACHE_LIMIT: oldest = min(_SAMPLE_CACHE.items(), key=lambda kv: kv[1][1])[0] (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I need to patch the old code now, removing redundant LRU cache definitions.

shell
if item is None: return None vals, ts = item if time.time() - ts > _CACHE_TTL: del _SAMPLE_CACHE[key] return None _SAMPLE_CACHE[key] = (vals, time.time()) return vals def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: _SAMPLE_CACHE[key] = (vals, time.time()) if len(_SAMPLE_CACHE) > _CACHE_LIMIT: oldest = min(_SAMPLE_CACHE.items(), key=lambda kv: kv[1][1])[0] del _SAMPLE_CACHE[oldest] @app.route("/api/samples") def sample_values() -> Any: column = request.args.get("column") substr = request.args.get("q", "") if not column or column not in _column_types: return jsonify([]) ctype = _column_types[column].upper() if "CHAR" not in ctype and "STRING" not in ctype and "VARCHAR" not in ctype: return jsonify([]) key = (column, substr) cached = _cache_get(key) if cached is not None: return jsonify(cached) rows = con.execute( f"SELECT DISTINCT {column} FROM events WHERE CAST({column} AS VARCHAR) I LIKE '%' || ? || '%' LIMIT 20", [substr], ).fetchall() values = [r[0] for r in rows] _cache_set(key, values) return jsonify(values) (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

Time to remove the old functions and patch from the new ones' line onward.

shell
> *** Update File: scubaduck/server.py > @@ > - def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: > - sample_cache[key] = (vals, time.time()) > - if len(sample_cache) > CACHE_LIMIT: > - oldest = min(sample_cache.items(), key=lambda kv: kv[1][1])[0] > - del sample_cache[oldest] > - > - > -def _cache_get(key: Tuple[str, str]) -> List[str] | None: > - item = _SAMPLE_CACHE.get(key) > - if item is None: > - return None > - vals, ts = item > - if time.time() - ts > _CACHE_TTL: > - del _SAMPLE_CACHE[key] > - return None > - _SAMPLE_CACHE[key] = (vals, time.time()) > - return vals > - > - > -def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: > - _SAMPLE_CACHE[key] = (vals, time.time()) > - if len(_SAMPLE_CACHE) > _CACHE_LIMIT: > - oldest = min(_SAMPLE_CACHE.items(), key=lambda kv: kv[1][1])[0] > - del _SAMPLE_CACHE[oldest] > + def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: > + sample_cache[key] = (vals, time.time()) > + if len(sample_cache) > CACHE_LIMIT: > + oldest = min(sample_cache.items(), key=lambda kv: kv[1][1])[0] > + del sample_cache[oldest] > *** End Patch > PATCH Success. Updated the following files: M scubaduck/server.py (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I think I missed some references to _SAMPLE_CACHE. Let me search again.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# grep -n "_SAMPLE_CACHE" -n s cubaduck/server.py (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'll update the sample_values function to rely on local variables instead of _SAMPLE_CACHE.

shell
sample_cache[key] = (vals, time.time()) return vals def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: sample_cache[key] = (vals, time.time()) if len(sample_cache) > CACHE_LIMIT: oldest = min(sample_cache.items(), key=lambda kv: kv[1][1])[0] del sample_cache[oldest] @app.route("/api/samples") def sample_values() -> Any: column = request.args.get("column") substr = request.args.get("q", "") if not column or column not in _column_types: return jsonify([]) ctype = _column_types[column].upper() if "CHAR" not in ctype and "STRING" not in ctype and "VARCHAR" not in ctype: return jsonify([]) key = (column, substr) cached = _cache_get(key) if cached is not None: return jsonify(cached) rows = con.execute( f"SELECT DISTINCT {column} FROM events WHERE CAST({column} AS VARCHAR) I LIKE '%' || ? || '%' LIMIT 20", [substr], ).fetchall() values = [r[0] for r in rows] _cache_set(key, values) return jsonify(values) def build_query(params: QueryParams) -> str: select_parts = [*params.columns] for name, expr in params.derived_columns.items(): select_parts.append(f"{expr} AS {name}") select_clause = ", ".join(select_parts) if select_parts else "*" query = f"SELECT {select_clause} FROM events" where_parts: list[str] = [] if params.start: where_parts.append(f"timestamp >= '{params.start}'") if params.end: where_parts.append(f"timestamp <= '{params.end}'") for f in params.filters: op = f.op if op in {"empty", "!empty"}: val = "''" else: if f.value is None: continue if isinstance(f.value, list): (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'll update function references to use the correct local variable, column_types.

shell
cubaduck/server.py 104: if not column or column not in _column_types: 106: ctype = _column_types[column].upper() (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

Looks like I defined 'column_types' but forgot to update it in the functions.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# apply_patch<<'PATCH' > *** Begin Patch > *** Update File: scubaduck/server.py > @@ > - if not column or column not in _column_types: > + if not column or column not in column_types: > return jsonify([]) > - ctype = _column_types[column].upper() > + ctype = column_types[column].upper() > *** End Patch > PATCH Success. Updated the following files: M scubaduck/server.py (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I’ll look for any remaining references to _column_types just to be sure.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# grep -n "_column_types" -n s cubaduck/server.py (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I need to search for and remove any leftover _CACHE_TTL constants after replacing them.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# grep -n "_CACHE" -n scubaduc k/server.py (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I need to review the last lines to see if I replaced the main statement.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# tail -n 20 scubaduck/server. py def query() -> Any: payload = request.get_json(force=True) params = QueryParams( start=payload.get("start"), end=payload.get("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", {}), ) for f in payload.get("filters", []): params.filters.append(Filter(f["column"], f["op"], f.get("value"))) sql = build_query(params) rows = con.execute(sql).fetchall() return jsonify({"sql": sql, "rows": rows}) if __name__ == "__main__": app.run(debug=True) (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

The functions at the bottom should be inside create_app to access local variables. Let me recheck.

shell
@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: {}) @app.route("/") def index() -> Any: assert app.static_folder is not None return send_from_directory(app.static_folder, "index.html") @app.route("/api/columns") def columns() -> Any: rows = con.execute("PRAGMA table_info(events)").fetchall() return jsonify([{"name": r[1], "type": r[2]} for r in rows]) # Simple in-memory LRU cache for sample value queries def _cache_get(key: Tuple[str, str]) -> List[str] | None: item = sample_cache.get(key) if item is None: return None vals, ts = item if time.time() - ts > CACHE_TTL: del sample_cache[key] return None sample_cache[key] = (vals, time.time()) (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'm double-checking where "app = Flask" is placed and inspecting the indentation of functions.

shell
aduck/server.py 36:def create_app(db_file: str | Path | None = None) -> Flask:
return con def create_app(db_file: str | Path | None = None) -> Flask: app = Flask(__name__, static_folder="static") db_path = Path(db_file or Path(__file__).with_name("sample.csv")).resolve() con = _load_database(db_path) column_types: Dict[str, str] = { r[1]: r[2] for r in con.execute("PRAGMA table_info(events)").fetchall() } # Simple in-memory LRU cache for sample value queries sample_cache: Dict[Tuple[str, str], Tuple[List[str], float]] = {} CACHE_TTL = 60.0 CACHE_LIMIT = 200 @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: {}) @app.route("/") def index() -> Any: (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I need to scroll a little more to capture everything I need.

shell
@app.route("/api/columns") def columns() -> Any: rows = con.execute("PRAGMA table_info(events)").fetchall() return jsonify([{"name": r[1], "type": r[2]} for r in rows]) # Simple in-memory LRU cache for sample value queries def _cache_get(key: Tuple[str, str]) -> List[str] | None: item = sample_cache.get(key) if item is None: return None vals, ts = item if time.time() - ts > CACHE_TTL: del sample_cache[key] return None sample_cache[key] = (vals, time.time()) return vals def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: sample_cache[key] = (vals, time.time()) if len(sample_cache) > CACHE_LIMIT: oldest = min(sample_cache.items(), key=lambda kv: kv[1][1])[0] del sample_cache[oldest] @app.route("/api/samples") def sample_values() -> Any: column = request.args.get("column") substr = request.args.get("q", "") if not column or column not in column_types: return jsonify([]) ctype = column_types[column].upper() if "CHAR" not in ctype and "STRING" not in ctype and "VARCHAR" not in ctype: return jsonify([]) key = (column, substr) cached = _cache_get(key) if cached is not None: return jsonify(cached) rows = con.execute( f"SELECT DISTINCT {column} FROM events WHERE CAST({column} AS VARCHAR) I LIKE '%' || ? || '%' LIMIT 20", [substr], ).fetchall() values = [r[0] for r in rows] _cache_set(key, values) return jsonify(values) def build_query(params: QueryParams) -> str: select_parts = [*params.columns] for name, expr in params.derived_columns.items(): select_parts.append(f"{expr} AS {name}") select_clause = ", ".join(select_parts) if select_parts else "*" query = f"SELECT {select_clause} FROM events" where_parts: list[str] = [] if params.start: where_parts.append(f"timestamp >= '{params.start}'") (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'm noticing some indentation issues. Let me inspect the lines closely with line numbers.

shell
sed -n '32,120p' 32 con = duckdb.connect(path) 33 return con 34 35 36 def create_app(db_file: str | Path | None = None) -> Flask: 37 app = Flask(__name__, static_folder="static") 38 db_path = Path(db_file or Path(__file__).with_name("sample.csv")).re solve() 39 con = _load_database(db_path) 40 column_types: Dict[str, str] = { 41 r[1]: r[2] for r in con.execute("PRAGMA table_info(events)").fet chall() 42 } 43 44 # Simple in-memory LRU cache for sample value queries 45 sample_cache: Dict[Tuple[str, str], Tuple[List[str], float]] = {} 46 CACHE_TTL = 60.0 47 CACHE_LIMIT = 200 48 49 50 @dataclass 51 class Filter: 52 column: str 53 op: str 54 value: str | int | float | list[str] | None 55 56 57 @dataclass 58 class QueryParams: 59 start: str | None = None 60 end: str | None = None 61 order_by: str | None = None 62 order_dir: str = "ASC" 63 limit: int | None = None 64 columns: list[str] = field(default_factory=lambda: []) 65 filters: list[Filter] = field(default_factory=lambda: []) 66 derived_columns: dict[str, str] = field(default_factory=lambda: {}) 67 68 69 @app.route("/") 70 def index() -> Any: 71 assert app.static_folder is not None 72 return send_from_directory(app.static_folder, "index.html") 73 74 75 @app.route("/api/columns") 76 def columns() -> Any: 77 rows = con.execute("PRAGMA table_info(events)").fetchall() 78 return jsonify([{"name": r[1], "type": r[2]} for r in rows]) 79 80 81 # Simple in-memory LRU cache for sample value queries 82 def _cache_get(key: Tuple[str, str]) -> List[str] | None: 83 item = sample_cache.get(key) 84 if item is None: 85 return None 86 vals, ts = item 87 if time.time() - ts > CACHE_TTL: 88 del sample_cache[key] 89 return None 90 sample_cache[key] = (vals, time.time()) 91 return vals 92 93 def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: 94 sample_cache[key] = (vals, time.time()) 95 if len(sample_cache) > CACHE_LIMIT: 96 oldest = min(sample_cache.items(), key=lambda kv: kv[1][1])[ 0] 97 del sample_cache[oldest] 98 99 100 @app.route("/api/samples") 101 def sample_values() -> Any: 102 column = request.args.get("column") 103 substr = request.args.get("q", "") 104 if not column or column not in column_types: 105 return jsonify([]) 106 ctype = column_types[column].upper() 107 if "CHAR" not in ctype and "STRING" not in ctype and "VARCHAR" not i n ctype: 108 return jsonify([]) 109 key = (column, substr) 110 cached = _cache_get(key) 111 if cached is not None: 112 return jsonify(cached) 113 rows = con.execute( 114 f"SELECT DISTINCT {column} FROM events WHERE CAST({column} AS VA RCHAR) ILIKE '%' || ? || '%' LIMIT 20", 115 [substr], 116 ).fetchall() 117 values = [r[0] for r in rows] 118 _cache_set(key, values) 119 return jsonify(values) 120 (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'm double-checking the indentation; some lines seem off due to 'nl -ba' formatting.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# sed -n '34,40p' scubaduck/se rver.py | cat -n 1 2 3 def create_app(db_file: str | Path | None = None) -> Flask: 4 app = Flask(__name__, static_folder="static") 5 db_path = Path(db_file or Path(__file__).with_name("sample.csv")).re solve() 6 con = _load_database(db_path) 7 column_types: Dict[str, str] = { (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I need to confirm if the dataclasses and routes are indented inside create_app.

shell
def create_app(db_file: str | Path | None = None) -> Flask: app = Flask(__name__, static_folder="static") db_path = Path(db_file or Path(__file__).with_name("sample.csv")).resolve() con = _load_database(db_path) column_types: Dict[str, str] = { r[1]: r[2] for r in con.execute("PRAGMA table_info(events)").fetchall() } # Simple in-memory LRU cache for sample value queries sample_cache: Dict[Tuple[str, str], Tuple[List[str], float]] = {} CACHE_TTL = 60.0 CACHE_LIMIT = 200 @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: {}) @app.route("/") def index() -> Any: assert app.static_folder is not None return send_from_directory(app.static_folder, "index.html") @app.route("/api/columns") def columns() -> Any: rows = con.execute("PRAGMA table_info(events)").fetchall() return jsonify([{"name": r[1], "type": r[2]} for r in rows]) # Simple in-memory LRU cache for sample value queries def _cache_get(key: Tuple[str, str]) -> List[str] | None: item = sample_cache.get(key) if item is None: return None vals, ts = item if time.time() - ts > CACHE_TTL: del sample_cache[key] return None sample_cache[key] = (vals, time.time()) return vals def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: sample_cache[key] = (vals, time.time()) if len(sample_cache) > CACHE_LIMIT: oldest = min(sample_cache.items(), key=lambda kv: kv[1][1])[0] del sample_cache[oldest] @app.route("/api/samples") def sample_values() -> Any: column = request.args.get("column") substr = request.args.get("q", "") if not column or column not in column_types: return jsonify([]) ctype = column_types[column].upper() if "CHAR" not in ctype and "STRING" not in ctype and "VARCHAR" not in ctype: return jsonify([]) key = (column, substr) cached = _cache_get(key) if cached is not None: return jsonify(cached) rows = con.execute( f"SELECT DISTINCT {column} FROM events WHERE CAST({column} AS VARCHAR) I LIKE '%' || ? || '%' LIMIT 20", [substr], ).fetchall() values = [r[0] for r in rows] _cache_set(key, values) return jsonify(values) (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

Hmm, the dataclass is at column 0 instead of being indented within create_app. Let's review.

shell
erver.py | cat -n 1 con = duckdb.connect(path) 2 return con 3 4 5 def create_app(db_file: str | Path | None = None) -> Flask: 6 app = Flask(__name__, static_folder="static") 7 db_path = Path(db_file or Path(__file__).with_name("sample.csv")).re solve() 8 con = _load_database(db_path) 9 column_types: Dict[str, str] = { 10 r[1]: r[2] for r in con.execute("PRAGMA table_info(events)").fet chall() 11 } 12 13 # Simple in-memory LRU cache for sample value queries 14 sample_cache: Dict[Tuple[str, str], Tuple[List[str], float]] = {} 15 CACHE_TTL = 60.0 16 CACHE_LIMIT = 200 17 18 19 @dataclass 20 class Filter: 21 column: str 22 op: str 23 value: str | int | float | list[str] | None 24 25 26 @dataclass 27 class QueryParams: 28 start: str | None = None 29 end: str | None = None 30 order_by: str | None = None 31 order_dir: str = "ASC" 32 limit: int | None = None 33 columns: list[str] = field(default_factory=lambda: []) 34 filters: list[Filter] = field(default_factory=lambda: []) 35 derived_columns: dict[str, str] = field(default_factory=lambda: {}) 36 37 38 @app.route("/") 39 def index() -> Any: 40 assert app.static_folder is not None 41 return send_from_directory(app.static_folder, "index.html") 42 43 44 @app.route("/api/columns") 45 def columns() -> Any: 46 rows = con.execute("PRAGMA table_info(events)").fetchall() 47 return jsonify([{"name": r[1], "type": r[2]} for r in rows]) 48 49 50 # Simple in-memory LRU cache for sample value queries 51 def _cache_get(key: Tuple[str, str]) -> List[str] | None: 52 item = sample_cache.get(key) 53 if item is None: 54 return None 55 vals, ts = item 56 if time.time() - ts > CACHE_TTL: 57 del sample_cache[key] 58 return None 59 sample_cache[key] = (vals, time.time()) 60 return vals 61 62 def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: 63 sample_cache[key] = (vals, time.time()) 64 if len(sample_cache) > CACHE_LIMIT: 65 oldest = min(sample_cache.items(), key=lambda kv: kv[1][1])[ 0] 66 del sample_cache[oldest] 67 68 69 @app.route("/api/samples") 70 def sample_values() -> Any: 71 column = request.args.get("column") 72 substr = request.args.get("q", "") 73 if not column or column not in column_types: 74 return jsonify([]) 75 ctype = column_types[column].upper() 76 if "CHAR" not in ctype and "STRING" not in ctype and "VARCHAR" not i n ctype: 77 return jsonify([]) 78 key = (column, substr) 79 cached = _cache_get(key) 80 if cached is not None: 81 return jsonify(cached) 82 rows = con.execute( 83 f"SELECT DISTINCT {column} FROM events WHERE CAST({column} AS VA RCHAR) ILIKE '%' || ? || '%' LIMIT 20", 84 [substr], 85 ).fetchall() 86 values = [r[0] for r in rows] 87 _cache_set(key, values) 88 return jsonify(values) 89 (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I notice some inconsistency in indentation between dataclasses and functions. Let me investigate.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# sed -n '36p' scubaduck/serve r.py | od -c 0000000 d e f c r e a t e _ a p p ( d 0000020 b _ f i l e : s t r | P a 0000040 t h | N o n e = N o n e 0000060 ) - > F l a s k : \n 0000074 (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

Dataclasses and build_query stay at the module level, other routes should stay inside create_app.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# wc -l scubaduck/server.py 188 scubaduck/server.py (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

It's 188 lines, so it makes sense to create a whole new file with the updates.

Time to replace the entire file with the new server.py implementation. Looks solid!

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# apply_patch<<'PATCH' > *** Begin Patch > *** Delete File: scubaduck/server.py > *** End Patch > PATCH Success. Updated the following files: D scubaduck/server.py (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

The file was removed, so now it's time to add a new one.

shell
> + > +from dataclasses import dataclass, field > +from typing import Any, Dict, List, Tuple > + olumns") + def columns() -> Any: + rows = con.execute("PRAGMA table_info(events)").fetchall() + return jsonify([{"name": r[1], "type": r[2]} f> +import time > +from pathlib import Path > +import sqlite3 Tuple[str, st> + r]> +import duckdb ist[str] > +from flask import Flask, jsonify, request, send_from_directory if item i> + s > + > +@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: {}) > + > + > +def _load_database(path: Path) -> duckdb.DuckDBPyConnection: > + ext = path.suffix.lower() > + if ext == ".csv": "> + con = duckdb.connect() > + con.execute( > + f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{path.as_po six()}')" > + ) ctype> + elif ext in {".db", ".sqlite"}: > + con = duckdb.connect() > + sconn = sqlite3.connect(path) > + info = sconn.execute("PRAGMA table_info(events)").fetchall() > + col_defs = ", ".join(f"{r[1]} {r[2]}" for r in info) > + con.execute(f"CREATE TABLE events ({col_defs})") > + placeholders = ",".join("?" for _ in info) > + for row in sconn.execute("SELECT * FROM events"): VARCHAR) ILIKE '%' ||> + con.execute(f"INSERT INTO events VALUES ({p laceholders})", row) > + sconn.close() r r in r> + else: > + con = duckdb.connect(path) > + return con > + > + ue> +def build_query(params: QueryParams) -> str: thods=["P> + select_parts = [*params.columns] > + for name, expr in params.derived_columns.items(): > + select_parts.append(f"{expr} AS {name}") > + select_clause = ", ".join(select_parts) if select_parts else "*" > + query = f"SELECT {select_clause} FROM events" > + where_parts: list[str] = [] > + if params.start: > + where_parts.append(f"timestamp >= '{params.start}'") > + if params.end: > + where_parts.append(f"timestamp <= '{params.end}'") > + for f in params.filters: > + op = f.op > + if op in {"empty", "!empty"}: > + val = "''" > + else: > + if f.value is None: > + continue > + if isinstance(f.value, list): > + if not f.value: > + continue > + if op == "=": > + vals = " OR ".join(f"{f.column} = '{v}'" for v in f.value ) > + where_parts.append(f"({vals})") > + continue > + val = f"'{f.value}'" if isinstance(f.value, str) else str(f.value ) > + > + if op == "contains": > + where_parts.append(f"{f.column} ILIKE '%' || {val} || '%'") > + elif op == "!contains": > + where_parts.append(f"{f.column} NOT ILIKE '%' || {val} || '%'") > + elif op == "empty": > + where_parts.append(f"{f.column} = {val}") > + elif op == "!empty": > + where_parts.append(f"{f.column} != {val}") > + else: > + where_parts.append(f"{f.column} {op} {val}") > + if where_parts: > + query += " WHERE " + " AND ".join(where_parts) > + if params.order_by: > + query += f" ORDER BY {params.order_by} {params.order_dir}" > + if params.limit is not None: > + query += f" LIMIT {params.limit}" > + return query > + > + > +def create_app(db_file: str | Path | None = None) -> Flask: > + app = Flask(__name__, static_folder="static") > + db_path = Path(db_file or Path(__file__).with_name("sample.csv")).resolve () > + con = _load_database(db_path) > + column_types: Dict[str, str] = { > + r[1]: r[2] for r in con.execute("PRAGMA table_info(events)").fetchall () > + } > + > + sample_cache: Dict[Tuple[str, str], Tuple[List[str], float]] = {} > + CACHE_TTL = 60.0 > + CACHE_LIMIT = 200 > + > + @app.route("/") > + def index() -> Any: > + assert app.static_folder is not None > + return send_from_directory(app.static_folder, "index.html") > + > + @app.route("/api/columns") > + def columns() -> Any: > + rows = con.execute("PRAGMA table_info(events)").fetchall() > + return jsonify([{"name": r[1], "type": r[2]} for r in rows]) > + > + def _cache_get(key: Tuple[str, str]) -> List[str] | None: > + item = sample_cache.get(key) > + if item is None: > + return None > + vals, ts = item > + if time.time() - ts > CACHE_TTL: > + del sample_cache[key] > + return None > + sample_cache[key] = (vals, time.time()) > + return vals > + > + def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: > + sample_cache[key] = (vals, time.time()) > + if len(sample_cache) > CACHE_LIMIT: > + oldest = min(sample_cache.items(), key=lambda kv: kv[1][1])[0] > + del sample_cache[oldest] > + > + @app.route("/api/samples") > + def sample_values() -> Any: > + column = request.args.get("column") > + substr = request.args.get("q", "") > + if not column or column not in column_types: > + return jsonify([]) > + ctype = column_types[column].upper() > + if "CHAR" not in ctype and "STRING" not in ctype and "VARCHAR" not in ctype: > + return jsonify([]) > + key = (column, substr) > + cached = _cache_get(key) > + if cached is not None: > + return jsonify(cached) > + rows = con.execute( > + f"SELECT DISTINCT {column} FROM events WHERE CAST({column} AS VAR CHAR) 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: > + payload = request.get_json(force=True) > + params = QueryParams( > + start=payload.get("start"), > + end=payload.get("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", {}), > + ) > + for f in payload.get("filters", []): > + params.filters.append(Filter(f["column"], f["op"], f.get("value") )) > + sql = build_query(params) > + rows = con.execute(sql).fetchall() > + return jsonify({"sql": sql, "rows": rows}) > + > + return app > + > + > +app = create_app() > + > + > +if __name__ == "__main__": > + app.run(debug=True) > + > *** End Patch > PATCH Success. Updated the following files: A scubaduck/server.py (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I’m checking the file for any leftover artifacts or truncated lines. Let’s open it.

shell
from typing import Any, Dict, List, Tuple import time from pathlib import Path import sqlite3 import duckdb 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: {}) def _load_database(path: Path) -> duckdb.DuckDBPyConnection: ext = path.suffix.lower() if ext == ".csv": con = duckdb.connect() con.execute( f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{path.as_posix ()}')" ) elif ext in {".db", ".sqlite"}: con = duckdb.connect() sconn = sqlite3.connect(path) info = sconn.execute("PRAGMA table_info(events)").fetchall() col_defs = ", ".join(f"{r[1]} {r[2]}" for r in info) con.execute(f"CREATE TABLE events ({col_defs})") placeholders = ",".join("?" for _ in info) for row in sconn.execute("SELECT * FROM events"): con.execute(f"INSERT INTO events VALUES ({placeholders})", row) sconn.close() else: con = duckdb.connect(path) return con def build_query(params: QueryParams) -> str: select_parts = [*params.columns] for name, expr in params.derived_columns.items(): select_parts.append(f"{expr} AS {name}") select_clause = ", ".join(select_parts) if select_parts else "*" query = f"SELECT {select_clause} FROM events" (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I might've missed displaying from __future__ import annotations at the top—let's confirm.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# head -n 3 scubaduck/server.p y from __future__ import annotations from dataclasses import dataclass, field
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# head -n 1 scubaduck/server.p y | od -c 0000000 f r o m _ _ f u t u r e _ _ 0000020 i m p o r t a n n o t a t i o 0000040 n s \n 0000043 (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

The first line looks fine; the extra 'y' was caused by quoting. Let's check more.

shell
erver.py query = f"SELECT {select_clause} FROM events" where_parts: list[str] = [] if params.start: where_parts.append(f"timestamp >= '{params.start}'") if params.end: where_parts.append(f"timestamp <= '{params.end}'") for f in params.filters: op = f.op if op in {"empty", "!empty"}: val = "''" else: if f.value is None: continue if isinstance(f.value, list): if not f.value: continue if op == "=": vals = " OR ".join(f"{f.column} = '{v}'" for v in f.value) where_parts.append(f"({vals})") continue val = f"'{f.value}'" if isinstance(f.value, str) else str(f.value) if op == "contains": where_parts.append(f"{f.column} ILIKE '%' || {val} || '%'") elif op == "!contains": where_parts.append(f"{f.column} NOT ILIKE '%' || {val} || '%'") elif op == "empty": where_parts.append(f"{f.column} = {val}") elif op == "!empty": where_parts.append(f"{f.column} != {val}") else: where_parts.append(f"{f.column} {op} {val}") if where_parts: query += " WHERE " + " AND ".join(where_parts) if params.order_by: query += f" ORDER BY {params.order_by} {params.order_dir}" if params.limit is not None: query += f" LIMIT {params.limit}" return query def create_app(db_file: str | Path | None = None) -> Flask: app = Flask(__name__, static_folder="static") db_path = Path(db_file or Path(__file__).with_name("sample.csv")).resolve() con = _load_database(db_path) column_types: Dict[str, str] = { r[1]: r[2] for r in con.execute("PRAGMA table_info(events)").fetchall() } sample_cache: Dict[Tuple[str, str], Tuple[List[str], float]] = {} CACHE_TTL = 60.0 CACHE_LIMIT = 200 @app.route("/") def index() -> Any: assert app.static_folder is not None return send_from_directory(app.static_folder, "index.html") @app.route("/api/columns") def columns() -> Any: rows = con.execute("PRAGMA table_info(events)").fetchall() (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I need to go deeper to find the relevant section.

shell
server.py rows = con.execute("PRAGMA table_info(events)").fetchall() return jsonify([{"name": r[1], "type": r[2]} for r in rows]) def _cache_get(key: Tuple[str, str]) -> List[str] | None: item = sample_cache.get(key) if item is None: return None vals, ts = item if time.time() - ts > CACHE_TTL: del sample_cache[key] return None sample_cache[key] = (vals, time.time()) return vals def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: sample_cache[key] = (vals, time.time()) if len(sample_cache) > CACHE_LIMIT: oldest = min(sample_cache.items(), key=lambda kv: kv[1][1])[0] del sample_cache[oldest] @app.route("/api/samples") def sample_values() -> Any: column = request.args.get("column") substr = request.args.get("q", "") if not column or column not in column_types: return jsonify([]) ctype = column_types[column].upper() if "CHAR" not in ctype and "STRING" not in ctype and "VARCHAR" not in ct ype: return jsonify([]) key = (column, substr) cached = _cache_get(key) if cached is not None: return jsonify(cached) rows = con.execute( f"SELECT DISTINCT {column} FROM events WHERE CAST({column} AS VARCHA R) ILIKE '%' || ? || '%' LIMIT 20", [substr], ).fetchall() values = [r[0] for r in rows] _cache_set(key, values) return jsonify(values) @app.route("/api/query", methods=["POST"]) def query() -> Any: payload = request.get_json(force=True) params = QueryParams( start=payload.get("start"), end=payload.get("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", {}), ) for f in payload.get("filters", []): params.filters.append(Filter(f["column"], f["op"], f.get("value"))) sql = build_query(params) rows = con.execute(sql).fetchall() return jsonify({"sql": sql, "rows": rows}) return app app = create_app() if __name__ == "__main__": app.run(debug=True) (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'll open tests/test_server.py and add tests to verify loading CSV, SQLite, and DuckDB.

shell
import json from scubaduck import server def test_basic_query() -> None: app = server.app client = app.test_client() payload = { "start": "2024-01-01 00:00:00", "end": "2024-01-02 00:00:00", "order_by": "timestamp", "order_dir": "ASC", "limit": 10, "columns": ["timestamp", "event", "value", "user"], "filters": [], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert data rows = data["rows"] # We expect first three rows (until 2024-01-02 00:00:00) assert len(rows) == 3 assert rows[0][1] == "login" assert rows[1][1] == "logout" def test_filter_multi_token() -> None: app = server.app client = app.test_client() payload = { "start": "2024-01-01 00:00:00", "end": "2024-01-02 03:00:00", "order_by": "timestamp", "limit": 10, "columns": ["timestamp", "event", "value", "user"], "filters": [{"column": "user", "op": "=", "value": ["alice", "charlie"]} ], } rv = client.post( "/api/query", data=json.dumps(payload), content_type="application/json" ) data = rv.get_json() assert data rows = data["rows"] # Should only return rows for alice and charlie assert len(rows) == 3 assert rows[0][3] == "alice" assert rows[-1][3] == "charlie" def test_empty_filter_is_noop() -> None: app = server.app client = app.test_client() base_payload = { "start": "2024-01-01 00:00:00", "end": "2024-01-03 00:00:00", "order_by": "timestamp",
_server.py 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 (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I think there might be more tests past line 120, so I'll open the rest.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# sed -n '240,320p' tests/test _server.py (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

The file ends before 240 lines, so I'll integrate new tests at the bottom.

shell
.py 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 (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'll add some new tests after completing this patch.

shell
> *** Update File: tests/test_server.py > @@ > def test_string_filter_ops() -> None: > @@ > assert len(rv.get_json()["rows"]) == 4 > + > + > +def _make_payload() -> dict[str, object]: > + return { > + "start": "2024-01-01 00:00:00", > + "end": "2024-01-02 00:00:00", > + "order_by": "timestamp", > + "order_dir": "ASC", > + "limit": 10, > + "columns": ["timestamp", "event", "value", "user"], > + "filters": [], > + } > + > + > +def test_database_types(tmp_path: Path) -> None: > + csv_file = tmp_path / "events.csv" > + csv_file.write_text(Path("scubaduck/sample.csv").read_text()) > + > + sqlite_file = tmp_path / "events.sqlite" > + import sqlite3 > + > + conn = sqlite3.connect(sqlite_file) > + conn.execute( > + "CREATE TABLE events (timestamp TEXT, event TEXT, value INTEGER, user TEXT)" > + ) > + 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), user) > + ) > + conn.commit() > + conn.close() > + > + 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_po six()}')" > + ) > + con.close() > + > + 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 /json" > + ) > + rows = rv.get_json()["rows"] > + assert len(rows) == 3 > *** End Patch > PATCH Success. Updated the following files: M tests/test_server.py (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I see I forgot to add the imports at the top—I'll include Path and duckdb.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# head -n 5 tests/test_server. py from __future__ import annotations import json from scubaduck import server (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'll import Path and duckdb, then proceed with patching.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# apply_patch<<'PATCH' > *** Begin Patch > *** Update File: tests/test_server.py > @@ > -from scubaduck import server > +from pathlib import Path > + > +import duckdb > +from scubaduck import server > *** End Patch > PATCH Success. Updated the following files: M tests/test_server.py (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'll run ruff format and ruff check now to ensure the code is clean.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# ruff format scubaduck/server .py tests/test_server.py 1 file reformatted, 1 file left unchanged
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# ruff check scubaduck/server. py tests/test_server.py All checks passed! (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

Time to run pyright and check for any type-related issues in the code.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# pyright
/workspace/scubaduck/scubaduck/server.py /workspace/scubaduck/scubaduck/server.py:114:9 - error: Function "index" is no t accessed (reportUnusedFunction) /workspace/scubaduck/scubaduck/server.py:119:9 - error: Function "columns" is not accessed (reportUnusedFunction) /workspace/scubaduck/scubaduck/server.py:141:9 - error: Function "sample_value s" is not accessed (reportUnusedFunction) /workspace/scubaduck/scubaduck/server.py:162:9 - error: Function "query" is no t accessed (reportUnusedFunction) /workspace/scubaduck/tests/test_server.py /workspace/scubaduck/tests/test_server.py:182:5 - error: Type of "close" is un known (reportUnknownMemberType) /workspace/scubaduck/tests/test_server.py:182:9 - error: Cannot access attribu te "close" for class "DuckDBPyConnection"   Attribute "close" is unknown (reportAttributeAccessIssue) 6 errors, 0 warnings, 0 informations (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

Pyright flags unused functions due to nesting. I'll silence them with # pyright: ignore.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# grep -n "def index" -n scuba duck/server.py 114: def index() -> Any: (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'll go ahead and add a comment to clarify the code.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# sed -n '112,170p' scubaduck/ server.py @app.route("/") def index() -> Any: assert app.static_folder is not None return send_from_directory(app.static_folder, "index.html") @app.route("/api/columns") def columns() -> Any: rows = con.execute("PRAGMA table_info(events)").fetchall() return jsonify([{"name": r[1], "type": r[2]} for r in rows]) def _cache_get(key: Tuple[str, str]) -> List[str] | None: item = sample_cache.get(key) if item is None: return None vals, ts = item if time.time() - ts > CACHE_TTL: del sample_cache[key] return None sample_cache[key] = (vals, time.time()) return vals def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: sample_cache[key] = (vals, time.time()) if len(sample_cache) > CACHE_LIMIT: oldest = min(sample_cache.items(), key=lambda kv: kv[1][1])[0] del sample_cache[oldest] @app.route("/api/samples") def sample_values() -> Any: column = request.args.get("column") substr = request.args.get("q", "") if not column or column not in column_types: return jsonify([]) ctype = column_types[column].upper() if "CHAR" not in ctype and "STRING" not in ctype and "VARCHAR" not in ct ype: return jsonify([]) key = (column, substr) cached = _cache_get(key) if cached is not None: return jsonify(cached) rows = con.execute( f"SELECT DISTINCT {column} FROM events WHERE CAST({column} AS VARCHA R) ILIKE '%' || ? || '%' LIMIT 20", [substr], ).fetchall() values = [r[0] for r in rows] _cache_set(key, values) return jsonify(values) @app.route("/api/query", methods=["POST"]) def query() -> Any: payload = request.get_json(force=True) params = QueryParams( start=payload.get("start"), end=payload.get("end"), order_by=payload.get("order_by"), order_dir=payload.get("order_dir", "ASC"), limit=payload.get("limit"), columns=payload.get("columns", []),
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# apply_patch<<'PATCH' > *** Begin Patch > *** Update File: scubaduck/server.py > @@ > - @app.route("/") > - def index() -> Any: > + @app.route("/") > + def index() -> Any: # pyright: ignore[reportUnusedFunction] > @@ > - @app.route("/api/columns") > - def columns() -> Any: > + @app.route("/api/columns") > + def columns() -> Any: # pyright: ignore[reportUnusedFunction] > @@ > - @app.route("/api/samples") > - def sample_values() -> Any: > + @app.route("/api/samples") > + def sample_values() -> Any: # pyright: ignore[reportUnusedFunction] > @@ > - @app.route("/api/query", methods=["POST"]) > - def query() -> Any: > + @app.route("/api/query", methods=["POST"]) > + def query() -> Any: # pyright: ignore[reportUnusedFunction] > *** End Patch > PATCH Success. Updated the following files: M scubaduck/server.py (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I’ll patch the tests to resolve the pyright warnings related to DuckDBPyConnection.close.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# grep -n "close()" -n tests/t est_server.py 175: conn.close() 182: con.close() (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I need to open connections around lines 175 and 182 where they’re closed.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# sed -n '168,190p' tests/test _server.py 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() 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() 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" ) (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'll ignore the pyright warnings by commenting # pyright: ignore on the lines.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# apply_patch<<'PATCH' > *** Begin Patch > *** Update File: tests/test_server.py > @@ > - conn.close() > + conn.close() # pyright: ignore[reportUnknownMemberType, reportAttributeA ccessIssue] > @@ > - con.close() > + con.close() # pyright: ignore[reportUnknownMemberType, reportAttributeAc cessIssue] > *** End Patch > PATCH Success. Updated the following files: M tests/test_server.py (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'll run ruff format again to check the consistency of the tests.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# ruff format scubaduck/server .py tests/test_server.py 2 files left unchanged
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# ruff check scubaduck/server. py tests/test_server.py All checks passed! (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

Let me run pyright again to check for any issues.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# pyright
0 errors, 0 warnings, 0 informations (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

Tests passed with Pyright. Now, let's run pytest to confirm!

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# pytest -q bringing up nodes...


....................... [100%] 23 passed in 5.36s (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

Tests pass. No need to modify index.html since header remains unchanged; server tests are updated.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# git status --short M scubaduck/server.py M tests/test_server.py
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# git add scubaduck/server.py tests/test_server.py
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# git commit -m "feat(server): load configurable databases" && git status --short [work 688deaf] feat(server): load configurable databases 2 files changed, 159 insertions(+), 86 deletions(-)
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# git status --short (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I’ll grab lines from server.py related to create_app and _load_database, etc.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# nl -ba scubaduck/server.py | sed -n '1,40p' 1 from __future__ import annotations 2 3 from dataclasses import dataclass, field 4 from typing import Any, Dict, List, Tuple 5 6 import time 7 from pathlib import Path 8 import sqlite3 9 10 import duckdb 11 from flask import Flask, jsonify, request, send_from_directory 12 13 14 @dataclass 15 class Filter: 16 column: str 17 op: str 18 value: str | int | float | list[str] | None 19 20 21 @dataclass 22 class QueryParams: 23 start: str | None = None 24 end: str | None = None 25 order_by: str | None = None 26 order_dir: str = "ASC" 27 limit: int | None = None 28 columns: list[str] = field(default_factory=lambda: []) 29 filters: list[Filter] = field(default_factory=lambda: []) 30 derived_columns: dict[str, str] = field(default_factory=lambda: {}) 31 32 33 def _load_database(path: Path) -> duckdb.DuckDBPyConnection: 34 ext = path.suffix.lower() 35 if ext == ".csv": 36 con = duckdb.connect() 37 con.execute( 38 f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{path. as_posix()}')" 39 ) 40 elif ext in {".db", ".sqlite"}:
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# nl -ba scubaduck/server.py | sed -n '32,80p' 32 33 def _load_database(path: Path) -> duckdb.DuckDBPyConnection: 34 ext = path.suffix.lower() 35 if ext == ".csv": 36 con = duckdb.connect() 37 con.execute( 38 f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{path. as_posix()}')" 39 ) 40 elif ext in {".db", ".sqlite"}: 41 con = duckdb.connect() 42 sconn = sqlite3.connect(path) 43 info = sconn.execute("PRAGMA table_info(events)").fetchall() 44 col_defs = ", ".join(f"{r[1]} {r[2]}" for r in info) 45 con.execute(f"CREATE TABLE events ({col_defs})") 46 placeholders = ",".join("?" for _ in info) 47 for row in sconn.execute("SELECT * FROM events"): 48 con.execute(f"INSERT INTO events VALUES ({placeholders})", r ow) 49 sconn.close() 50 else: 51 con = duckdb.connect(path) 52 return con 53 54 55 def build_query(params: QueryParams) -> str: 56 select_parts = [*params.columns] 57 for name, expr in params.derived_columns.items(): 58 select_parts.append(f"{expr} AS {name}") 59 select_clause = ", ".join(select_parts) if select_parts else "*" 60 query = f"SELECT {select_clause} FROM events" 61 where_parts: list[str] = [] 62 if params.start: 63 where_parts.append(f"timestamp >= '{params.start}'") 64 if params.end: 65 where_parts.append(f"timestamp <= '{params.end}'") 66 for f in params.filters: 67 op = f.op 68 if op in {"empty", "!empty"}: 69 val = "''" 70 else: 71 if f.value is None: 72 continue 73 if isinstance(f.value, list): 74 if not f.value: 75 continue 76 if op == "=": 77 vals = " OR ".join(f"{f.column} = '{v}'" for v in f. value) 78 where_parts.append(f"({vals})") 79 continue 80 val = f"'{f.value}'" if isinstance(f.value, str) else str(f. value) (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I'll scroll further to view the remaining lines.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# nl -ba scubaduck/server.py | sed -n '80,160p' 80 val = f"'{f.value}'" if isinstance(f.value, str) else str(f. value) 81 82 if op == "contains": 83 where_parts.append(f"{f.column} ILIKE '%' || {val} || '%'") 84 elif op == "!contains": 85 where_parts.append(f"{f.column} NOT ILIKE '%' || {val} || '% '") 86 elif op == "empty": 87 where_parts.append(f"{f.column} = {val}") 88 elif op == "!empty": 89 where_parts.append(f"{f.column} != {val}") 90 else: 91 where_parts.append(f"{f.column} {op} {val}") 92 if where_parts: 93 query += " WHERE " + " AND ".join(where_parts) 94 if params.order_by: 95 query += f" ORDER BY {params.order_by} {params.order_dir}" 96 if params.limit is not None: 97 query += f" LIMIT {params.limit}" 98 return query 99 100 101 def create_app(db_file: str | Path | None = None) -> Flask: 102 app = Flask(__name__, static_folder="static") 103 db_path = Path(db_file or Path(__file__).with_name("sample.csv")).re solve() 104 con = _load_database(db_path) 105 column_types: Dict[str, str] = { 106 r[1]: r[2] for r in con.execute("PRAGMA table_info(events)").fet chall() 107 } 108 109 sample_cache: Dict[Tuple[str, str], Tuple[List[str], float]] = {} 110 CACHE_TTL = 60.0 111 CACHE_LIMIT = 200 112 113 @app.route("/") 114 def index() -> Any: # pyright: ignore[reportUnusedFunction] 115 assert app.static_folder is not None 116 return send_from_directory(app.static_folder, "index.html") 117 118 @app.route("/api/columns") 119 def columns() -> Any: # pyright: ignore[reportUnusedFunction] 120 rows = con.execute("PRAGMA table_info(events)").fetchall() 121 return jsonify([{"name": r[1], "type": r[2]} for r in rows]) 122 123 def _cache_get(key: Tuple[str, str]) -> List[str] | None: 124 item = sample_cache.get(key) 125 if item is None: 126 return None 127 vals, ts = item 128 if time.time() - ts > CACHE_TTL: 129 del sample_cache[key] 130 return None 131 sample_cache[key] = (vals, time.time()) 132 return vals 133 134 def _cache_set(key: Tuple[str, str], vals: List[str]) -> None: 135 sample_cache[key] = (vals, time.time()) 136 if len(sample_cache) > CACHE_LIMIT: 137 oldest = min(sample_cache.items(), key=lambda kv: kv[1][1])[ 0] 138 del sample_cache[oldest] 139 140 @app.route("/api/samples") 141 def sample_values() -> Any: # pyright: ignore[reportUnusedFunction] 142 column = request.args.get("column") 143 substr = request.args.get("q", "") 144 if not column or column not in column_types: 145 return jsonify([]) 146 ctype = column_types[column].upper() 147 if "CHAR" not in ctype and "STRING" not in ctype and "VARCHAR" n ot in ctype: 148 return jsonify([]) 149 key = (column, substr) 150 cached = _cache_get(key) 151 if cached is not None: 152 return jsonify(cached) 153 rows = con.execute( 154 f"SELECT DISTINCT {column} FROM events WHERE CAST({column} A S VARCHAR) ILIKE '%' || ? || '%' LIMIT 20", 155 [substr], 156 ).fetchall() 157 values = [r[0] for r in rows] 158 _cache_set(key, values) 159 return jsonify(values) 160
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# nl -ba scubaduck/server.py | sed -n '160,220p' 160 161 @app.route("/api/query", methods=["POST"]) 162 def query() -> Any: # pyright: ignore[reportUnusedFunction] 163 payload = request.get_json(force=True) 164 params = QueryParams( 165 start=payload.get("start"), 166 end=payload.get("end"), 167 order_by=payload.get("order_by"), 168 order_dir=payload.get("order_dir", "ASC"), 169 limit=payload.get("limit"), 170 columns=payload.get("columns", []), 171 derived_columns=payload.get("derived_columns", {}), 172 ) 173 for f in payload.get("filters", []): 174 params.filters.append(Filter(f["column"], f["op"], f.get("va lue"))) 175 sql = build_query(params) 176 rows = con.execute(sql).fetchall() 177 return jsonify({"sql": sql, "rows": rows}) 178 179 return app 180 181 182 app = create_app() 183 184 185 if __name__ == "__main__": 186 app.run(debug=True) (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

I’ll check the lines in the test files next.

shell
(scubaduck) root@585f5e72dcd0:/workspace/scubaduck# nl -ba tests/test_server.py | sed -n '160,220p' 160 sqlite_file = tmp_path / "events.sqlite" 161 import sqlite3 162 163 conn = sqlite3.connect(sqlite_file) 164 conn.execute( 165 "CREATE TABLE events (timestamp TEXT, event TEXT, value INTEGER, user TEXT)" 166 ) 167 with open(csv_file) as f: 168 next(f) 169 for line in f: 170 ts, ev, val, user = line.strip().split(",") 171 conn.execute( 172 "INSERT INTO events VALUES (?, ?, ?, ?)", (ts, ev, int(v al), user) 173 ) 174 conn.commit() 175 conn.close() # pyright: ignore[reportUnknownMemberType, reportAttri buteAccessIssue] 176 177 duckdb_file = tmp_path / "events.duckdb" 178 con = duckdb.connect(duckdb_file) 179 con.execute( 180 f"CREATE TABLE events AS SELECT * FROM read_csv_auto('{csv_file. as_posix()}')" 181 ) 182 con.close() # pyright: ignore[reportUnknownMemberType, reportAttrib uteAccessIssue] 183 184 for db in (csv_file, sqlite_file, duckdb_file): 185 app = server.create_app(db) 186 client = app.test_client() 187 payload = _make_payload() 188 rv = client.post( 189 "/api/query", data=json.dumps(payload), content_type="applic ation/json" 190 ) 191 rows = rv.get_json()["rows"] 192 assert len(rows) == 3 (scubaduck) root@585f5e72dcd0:/workspace/scubaduck#

The commit is ready, and now it's time to prepare the PR.