dbnl.report_results(
    *,
    run: Run,
    data: pandas.DataFrame,
) -> None:

import dbnl
import pandas as pd
dbnl.login()


proj1 = dbnl.get_or_create_project(name="test_p1")
runcfg1 = dbnl.create_run_config(project=proj1, columns=[{"name": "error", "type": "float"}])
run1 = dbnl.create_run(project=proj1, run_config=runcfg1)

data = pd.DataFrame({"error": [0.11, 0.33, 0.52, 0.24]})
dbnl.report_column_results(run=run1, data=data)

dbnl.report_scalar_results(
    *,
    run: Run,
    Union[dict[str, Any], pd.DataFrame]
) -> None:

import dbnl
import pandas as pd
dbnl.login()


proj1 = dbnl.get_or_create_project(name="test_p1")
runcfg1 = dbnl.create_run_config(
    project=proj1, 
    columns=[{"name": "error", "type": "float"}],
    scalars=[{"name": "rmse": "type": "float"}],
)
run1 = dbnl.create_run(project=proj1, run_config=runcfg1)
dbnl.report_scalar_results(run=run1, data={"rmse": 0.37})

dbnl.get_scalar_results(
    *,
    run: Run,
) -> pandas.DataFrame:

import dbnl
import pandas as pd
dbnl.login()

proj1 = dbnl.get_or_create_project(name="test_p1")

data = pd.DataFrame({"error": [0.11, 0.33, 0.52, 0.24]})
run = dbnl.report_run_with_results(
    project=proj,
    column_results=data,
    scalar_results={"rmse": 0.37}
)

downloaded_scalars = dbnl.get_scalar_results(run=run)

dbnl.get_results(
    *,
    run: Run,
) -> ResultData:

import dbnl
import pandas as pd
dbnl.login()


proj = dbnl.get_or_create_project(name="test_p1")

uploaded_data = pd.DataFrame({"error": [0.11, 0.33, 0.52, 0.24]})
run = dbnl.report_run_with_results(
    project=proj,
    column_results=uploaded_data,
)

downloaded_data = dbnl.get_results(run=run)
assert downloaded_data.columns.equals(uploaded_data)

dbnl.report_results(
    *,
    run: Run,
    column_data: pandas.DataFrame,
    scalar_data: dict[str, Any] | pandas.DataFrame | None = None
) -> None:

import dbnl
import pandas as pd
dbnl.login()


proj1 = dbnl.get_or_create_project(name="test_p1")
runcfg1 = dbnl.create_run_config(project=proj1, columns=[{"name": "error", "type": "float"}])
run1 = dbnl.create_run(project=proj1, run_config=runcfg1)

data = pd.DataFrame({"error": [0.11, 0.33, 0.52, 0.24]})
dbnl.report_results(run=run1, column_data=data)


import dbnl
import pandas as pd
dbnl.login()


proj1 = dbnl.get_or_create_project(name="test_p1")
runcfg1 = dbnl.create_run_config(
    project=proj1, 
    columns=[{"name": "error", "type": "float"}],
    scalars=[{"name": "rmse": "type": "float"}],
)
run1 = dbnl.create_run(project=proj1, run_config=runcfg1)
data = pd.DataFrame({"error": [0.11, 0.33, 0.52, 0.24]})
dbnl.report_results(run=run1, column_data=data, scalar_data={"rmse": 0.37})

dbnl.get_column_results(
    *,
    run: Run,
) -> pandas.DataFrame:

import dbnl
import pandas as pd
dbnl.login()


proj = dbnl.get_or_create_project(name="test_p1")
uploaded_data = pd.DataFrame({"error": [0.11, 0.33, 0.52, 0.24]})
run = dbnl.report_run_with_results(
    project=proj,
    column_results=test_data,
)

downloaded_data = dbnl.get_column_results(run=run)
assert downloaded_data.equals(uploaded_data)