The data is the output of TimeGapSplit.summary(df)

From here
https://github.com/koaning/scikit-lego/blob/main/sklego/model_selection.py

The dataframe supplied to summary is quite trivial. Think your example + some datetime column

exact scenario:

i have a task_1, which runs successfully with MyParam=['111'] i have a pipeline controller which runs successfully with task_1 as a step_1
If i use parameter_override for step_1 with value MyParam=999 (yes, not a dict), and run the pipeline, it fails (outputs this error in console logs), then reuses the ['111'] value and completes successfully. And i want it to fail completely, not reuse the safe default historic value

hope it clarifies

Upd: fixed the error, it was in some unrelated code

Upd: cant reproduce "rendered on some iterations", now its only: not rendered until run is completed.

CostlyOstrich36

Updated.

They are rendered on some iterations, especially early iterations. Rest is correct

The testing runs are short but real runs will be long so its very undesirable

CostlyOstrich36 yes i tried, it does nothing

namely, changing this value does nothing, doesn't even affect the running tasktask = Task.get_task(task_id="...") # valid task task._data.configuration['schedule'].value # the value of config that contains schedule
2. tried to make schedule modifiable via Task.connect + TaskScheduler.add_task , no result
` scheduler_clearml_dict = {"config connected": [1, 2]}
task.connect(scheduler_clearml_dict) # <- this config is later modified...

AgitatedDove14 sorry if this was confusing, i try to clarify:

1. i don't use matplotlib period, hence don;t use report_matplotlib_figure . i use report_plotly

2. the separator doesn't do the trick when there's just 1 plot in a row. and 1 plot in a row seems to be a "deeply" default behavior - i.e. would require ugly workarounds on our side like adding empty plots

3. i explicitly set the dimensions in the plotly via the code above, before passing it to ` report_plo...

AgitatedDove14
Sure!

Btw on "some layout properties should not be there". if you use px API of Plotly , create some figure and check fig.layout you'll see it's quite populated. It'll be empty if the low-level go API of Plotly is used.

AgitatedDove14 sounds great!

Hi SuccessfulKoala55
Author of the figures above here

The problem is, that it doesn't help. Left one - IPython render (what a dev sees in the notebook). Right one - what gets rendered in the web UI. Also it's built in Plotly , not Matplotlib

the code that is used for axes:
` ...
fig.update_layout(height=900, width=600)
fig.update_xaxes(
scaleanchor="y",
scaleratio=1,
row=1,
col=1,
)
fig.update_xaxes(range=[0.0, 1.0])
fig.u...

ExasperatedCrab78 the problem is it is saved, rendered and copied to clipboard via a button as a git diff stdout, not as a valid python code

bump

Yes i see it, but where's the endpoint to modify a config? TaskScheduler doesn't have any getters or setters for that

Getting id of the TaskScheduler doesn't lead to anything, since you dont have a getter like TaskScheduler.get_task(), you only have Task.get_task(), but there's no way to do .add_step() or .remove_step() because Task doesn't have such methods

User config is no-op, the schedule appears to be contained in some json configuration object created under the hood. Maybe this co...

ExasperatedCrab78 Such a git patch appeared to track a lot of unrelated unexecuted stuff. And was whimsical when being applied - it errored on all those unrelated code files as far as i could tell so i had to use --reject in git apply --reject --whitespace=fix experiment-a1fbb0ecfc4e4d698e017d8356d8be52.patch

I get that this feature is probably coming from a robust reproducibility design perspective. If only there'd be a shortcut tho. For example, official Python VSCode e...