wehub-resource-sync
105 lines
4.4 KiB
Python
105 lines
4.4 KiB
Python
# ruff: noqa: E501 -- ASCII output tables below need wide lines
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"""Sample snippets highlighting common performance-related improvements"""
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import tempfile
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from pathlib import Path
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from datafusion import col
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import rerun as rr
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TMP_FILE = tempfile.NamedTemporaryFile(suffix=".rrd")
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RRD_PATH = TMP_FILE.name
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# region: get_dataset
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sample_dataset_path = (
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Path(__file__).parents[4] / "tests" / "assets" / "rrd" / "dataset"
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)
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server = rr.server.Server(datasets={"dataset": sample_dataset_path})
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# Using OSS server for demonstration but in practice replace with
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# the URL of your cloud instance
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CATALOG_URL = server.url()
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client = rr.catalog.CatalogClient(CATALOG_URL)
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dataset = client.get_dataset(name="dataset")
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# endregion: get_dataset
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# region: view_index_ranges
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(
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dataset
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.get_index_ranges()
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.select(
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"rerun_segment_id",
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"time_1:start",
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"time_1:end",
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"time_2:start",
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"time_2:end",
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"time_3:start",
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"time_3:end",
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)
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.sort("rerun_segment_id")
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.show()
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)
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# endregion: view_index_ranges
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# region: original_data
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time_index = "time_3"
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columns_of_interest = [
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"rerun_segment_id",
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time_index,
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"/obj1:Points3D:positions",
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"/obj2:Points3D:positions",
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"/obj3:Points3D:positions",
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]
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(
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dataset
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.reader(index=time_index)
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.select(*columns_of_interest)
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.sort("rerun_segment_id", time_index)
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.show()
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)
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# +----------------------------------+--------+--------------------------+--------------------------+--------------------------+
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# | rerun_segment_id | time_3 | /obj1:Points3D:positions | /obj2:Points3D:positions | /obj3:Points3D:positions |
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# +----------------------------------+--------+--------------------------+--------------------------+--------------------------+
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# | 141a866deb2d49f69eb3215e8a404ffc | 1 | [[49.0, 0.0, 0.0]] | [[44.0, 1.0, 0.0]] | [[1.0, 2.0, 0.0]] |
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# | 141a866deb2d49f69eb3215e8a404ffc | 2 | [[27.0, 0.0, 0.0]] | [[42.0, 1.0, 0.0]] | |
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# | 141a866deb2d49f69eb3215e8a404ffc | 3 | [[25.0, 0.0, 0.0]] | [[30.0, 1.0, 0.0]] | [[3.0, 2.0, 0.0]] |
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# | 141a866deb2d49f69eb3215e8a404ffc | 4 | [[38.0, 0.0, 0.0]] | [[19.0, 1.0, 0.0]] | |
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# | 141a866deb2d49f69eb3215e8a404ffc | 5 | [[17.0, 0.0, 0.0]] | [[5.0, 1.0, 0.0]] | [[5.0, 2.0, 0.0]] |
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# | 141a866deb2d49f69eb3215e8a404ffc | 6 | [[2.0, 0.0, 0.0]] | [[35.0, 1.0, 0.0]] | |
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# | 141a866deb2d49f69eb3215e8a404ffc | 7 | [[44.0, 0.0, 0.0]] | [[4.0, 1.0, 0.0]] | [[7.0, 2.0, 0.0]] |
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# endregion: original_data
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# region: resampled_data
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resample_column = "/obj3:Points3D:positions"
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times_of_interest = (
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dataset
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.reader(index=time_index)
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.filter(col(resample_column).is_not_null())
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.select("rerun_segment_id", time_index)
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)
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(
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dataset
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.reader(
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index=time_index,
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using_index_values=times_of_interest,
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fill_latest_at=True,
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)
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.select(*columns_of_interest)
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.sort("rerun_segment_id", time_index)
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.show()
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)
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# +----------------------------------+--------+--------------------------+--------------------------+--------------------------+
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# | rerun_segment_id | time_3 | /obj1:Points3D:positions | /obj2:Points3D:positions | /obj3:Points3D:positions |
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# +----------------------------------+--------+--------------------------+--------------------------+--------------------------+
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# | 141a866deb2d49f69eb3215e8a404ffc | 1 | [[49.0, 0.0, 0.0]] | [[44.0, 1.0, 0.0]] | [[1.0, 2.0, 0.0]] |
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# | 141a866deb2d49f69eb3215e8a404ffc | 3 | [[25.0, 0.0, 0.0]] | [[30.0, 1.0, 0.0]] | [[3.0, 2.0, 0.0]] |
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# | 141a866deb2d49f69eb3215e8a404ffc | 5 | [[17.0, 0.0, 0.0]] | [[5.0, 1.0, 0.0]] | [[5.0, 2.0, 0.0]] |
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# | 141a866deb2d49f69eb3215e8a404ffc | 7 | [[44.0, 0.0, 0.0]] | [[4.0, 1.0, 0.0]] | [[7.0, 2.0, 0.0]] |
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# | 141a866deb2d49f69eb3215e8a404ffc | 10 | [[12.0, 0.0, 0.0]] | [[6.0, 1.0, 0.0]] | [[10.0, 2.0, 0.0]] |
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# | 141a866deb2d49f69eb3215e8a404ffc | 12 | [[13.0, 0.0, 0.0]] | [[17.0, 1.0, 0.0]] | [[12.0, 2.0, 0.0]] |
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# | 141a866deb2d49f69eb3215e8a404ffc | 13 | [[20.0, 0.0, 0.0]] | [[32.0, 1.0, 0.0]] | [[13.0, 2.0, 0.0]] |
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# endregion: resampled_data
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