[BUG] Error handling timezones

[Jmbols]

Description
There is an error trying to construct an update patch when the x-axis are dates with a specified timezone.
The error is when trying to compare timezones. Pandas pd.to_datetime() by default will convert a timezone to a fixed off-set, whereas the timezone in the x-axis has a different format. The off-set is the same because the data is created based on the same timezone.

/.pyenv/versions/3.11.1/envs/clearview-dash-311/lib/python3.11/site-packages/plotly_resampler/aggregation/plotly_aggregator_parser.py", line 41, in to_same_tz
assert ts.tz.str() == reference_tz.str()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Reproducing the bug 🔍
This code snippet reproduces the bug

import pandas as pd
import numpy as np
import plotly.graph_objects as go

from plotly_resampler import FigureResampler


fig = FigureResampler()

x = pd.date_range("2024-04-01T00:00:00", "2025-01-01T00:00:00", freq="H")
x = x.tz_localize("Asia/Taipei")
y = np.random.randn(len(x))

fig.add_trace(
    go.Scattergl(x=x, y=y, name="demo", mode="lines+markers"),
    max_n_samples=int(len(x) * 0.2),
)

relayout_data = {
    "xaxis.range[0]": "2024-04-27T08:00:00+08:00",
    "xaxis.range[1]": "2024-05-04T17:15:39.491031+08:00",
}

fig.construct_update_data_patch(relayout_data)

Environment information

• OS: Ubuntu 22.04
• Python version: 3.11
• plotly-resampler environment: python and dash
• plotly-resampler version: 0.9.2

[Jmbols]

Can be fixed by tz_convert before passing relayout_data to fig.construct_update_data_patch(relayout_data), but the default behaviour interacting with dash is this error.

[Jmbols]

But fix only works when there is no switch to DST. Timezone Canada/Pacific, for example, changes timezone upon switch to and from DST, so if the above code is run like

import pandas as pd
import numpy as np
import plotly.graph_objects as go

from plotly_resampler import FigureResampler


fig = FigureResampler()

x = pd.date_range("2024-04-01T00:00:00", "2025-01-01T00:00:00", freq="H")
x = x.tz_localize("UTC")
x = x.tz_convert("Canada/Pacific")
y = np.random.randn(len(x))

fig.add_trace(
    go.Scattergl(x=x, y=y, name="demo", mode="lines+markers"),
    max_n_samples=int(len(x) * 0.2),
)

relayout_data = {
    "xaxis.range[0]": pd.Timestamp("2024-03-01T00:00:00").tz_localize("Canada/Pacific"),
    "xaxis.range[1]": pd.Timestamp("2024-03-31T00:00:00").tz_localize("Canada/Pacific"),
}

fig.construct_update_data_patch(relayout_data)

you get the error:
site-packages/plotly_resampler/aggregation/plotly_aggregator_parser.py", line 81, in get_start_end_indices
assert start.tz == end.tz
^^^^^^^^^^^^^^^^^^

Is there a reason not to use assert start.tz.__str__() == end.tz.__str__()? That would solve the assertion error at least with DST if the name of the timezone is the same.

[DHRUVCHARNE]

You can also try using the pytz library to handle timezone conversions and DST transitions. Here's an example:

import pytz

...

x = pd.date_range("2024-04-01T00:00:00", "2025-01-01T00:00:00", freq="H")
x = x.tz_localize("UTC")
x = x.tz_convert(pytz.timezone("Canada/Pacific"))

...

relayout_data = {
"xaxis.range[0]": pd.Timestamp("2024-03-01T00:00:00").tz_localize(pytz.timezone("Canada/Pacific")),
"xaxis.range[1]": pd.Timestamp("2024-03-31T00:00:00").tz_localize(pytz.timezone("Canada/Pacific")),
}

[jonasvdd]

@Jmbols, @DHRUVCHARNE,

I tried to fix this behavior in #318 by catching the legacy tz-string assert (see ⬇️), and then compare for offsets (see ⬇️ ⬇️ )

• legacy tz-string assert
  

  plotly-resampler/plotly_resampler/aggregation/plotly_aggregator_parser.py

  Lines 40 to 41 in 74d4c2b

  	if ts.tz is not None:
  	assert ts.tz.__str__() == reference_tz.__str__()

• catching assert and compare for offset
  

  plotly-resampler/plotly_resampler/aggregation/plotly_aggregator_parser.py

  Lines 40 to 45 in 1f88adb

  	if ts.tz is not None:
  	# compare if these two have the same timezone / offset
  	try:
  	assert ts.tz.__str__() == reference_tz.__str__()
  	except AssertionError:
  	assert ts.utcoffset() == reference_tz.utcoffset(ts.tz_convert(None))

However, this introduces the possibly unwanted behavior, that different timezones with the same offset, are considered valid. (e.g. "Europe/Brussels" and "Europe/Amsterdam" are two different timezone objects / strings, but with the same offset -> so they are considered as equal.)

This is also expressed in the following tests:

plotly-resampler/tests/test_figure_resampler.py

Lines 1051 to 1098 in 1f88adb

	def test_time_tz_slicing_different_timestamp():
	# construct a time indexed series with UTC timezone
	n = 60 * 60 * 24 * 3
	dr = pd.Series(
	index=pd.date_range("2022-02-14", freq="s", periods=n, tz="UTC"),
	data=np.random.randn(n),
	)
	# create multiple other time zones
	cs = [
	dr,
	dr.tz_localize(None).tz_localize("Europe/Amsterdam"),
	dr.tz_convert("Europe/Lisbon"),
	dr.tz_convert("Australia/Perth"),
	dr.tz_convert("Australia/Canberra"),
	]
	for i, s in enumerate(cs):
	t_start, t_stop = sorted(s.iloc[np.random.randint(0, n, 2)].index)
	t_start = t_start.tz_convert(cs[(i + 1) % len(cs)].index.tz)
	t_stop = t_stop.tz_convert(cs[(i + 1) % len(cs)].index.tz)
	# As each timezone in CS tz aware, using other timezones in `t_start` & `t_stop`
	# will raise an AssertionError
	with pytest.raises(AssertionError):
	hf_data_dict = construct_hf_data_dict(s.index, s.values)
	start_idx, end_idx = PlotlyAggregatorParser.get_start_end_indices(
	hf_data_dict, hf_data_dict["axis_type"], t_start, t_stop
	)
	# THESE have the same timezone offset -> no AssertionError should be raised
	cs = [
	dr.tz_localize(None).tz_localize("Europe/Amsterdam"),
	dr.tz_convert("Europe/Brussels"),
	dr.tz_convert("Europe/Oslo"),
	dr.tz_convert("Europe/Paris"),
	dr.tz_convert("Europe/Rome"),
	]
	for i, s in enumerate(cs):
	t_start, t_stop = sorted(s.iloc[np.random.randint(0, n, 2)].index)
	t_start = t_start.tz_convert(cs[(i + 1) % len(cs)].index.tz)
	t_stop = t_stop.tz_convert(cs[(i + 1) % len(cs)].index.tz)
	hf_data_dict = construct_hf_data_dict(s.index, s.values)
	start_idx, end_idx = PlotlyAggregatorParser.get_start_end_indices(
	hf_data_dict, hf_data_dict["axis_type"], t_start, t_stop
	)

I would like to hear your opinion on this matter before continuing on this PR.

[jonasvdd]

@Jmbols @DHRUVCHARNE, any thoughts/remarks on my above comment?

[Jmbols]

This is the behaviour I would expect. "Europe/Brussels" and "Europe/Amsterdam" are equivalent for all intents and purposes. The main issue I can see with that is if they have different dates when switching to and from DST, but presumably this would be caught by the offset check?