DEPR offsets: rename 'M' to 'ME' #52064

natmokval · 2023-03-18T14:26:46Z

This pr is related to issue #9586.

Added warning to to_offset(freq) in case freq='M'. This is the first step to deprecate 'M' for MonthEnd.
TODO: let 'M' keep working for Period

example to reproduce:

for orig_freq, target_freq in [('10D', '1M'), ('3M', 'Y')]:
    print(f"{orig_freq}->{target_freq}")
    ind = pd.date_range('2022-01-01', freq=orig_freq, periods=5)
    s = pd.Series(np.arange(5), ind)
    print(s) 
    print(s.resample(target_freq, closed='right').asfreq())

both date_range and resample produce warnings.

pandas/core/resample.py:1604: UserWarning: 'M' will be deprecated, please use 'ME' for 'month end'
  freq = to_offset(freq)

natmokval · 2023-03-21T20:33:47Z

The _prefix in the class MonthEnd is redefined from “M” to "ME”.
In to_offset we check, if “M” is passed, then raise a warning and change “M” to “ME”.

Now we can apply both, “M” and “ME”. The example below raises one warning for freq=‘3M’

for orig_freq, target_freq in [('10D', '1ME'), ('3M', 'Y')]:
    print(f"{orig_freq}->{target_freq}")
    ind = pd.date_range('2022-01-01', freq=orig_freq, periods=5)
    s = pd.Series(np.arange(5), ind)
    print(s) 
    print(s.resample(target_freq, closed='right').asfreq())

In order to reduce the number of test errors I also changed “M” to “ME” in pandas/tests/arrays/test_datetimelike.py:35

@pytest.fixture(params=["D", "B", "W", "ME", "Q", "Y"])

This reduced number of test errors from 1400 to 68.

MarcoGorelli

Nice, thanks for having started this!

So, this correctly throws a warning for date_range and resample with 'ME'

However, it also throws a warning for PeriodIndex(..., freq='M'), which as per #9586 (comment) we need to keep working

So, we need to figure out how to pass 'M' to PeriodIndex without it warning, but such that passing 'M' to date_range would warn

MarcoGorelli · 2023-03-22T16:35:00Z

Maybe to_offset could have a is_period boolean argument, which would be passed as True when called when instantiating a Period, i.e.

pandas/pandas/core/arrays/period.py

Line 965 in 52c653b

freq = to_offset(freq) # type: ignore[assignment]

And then, instead of warning if name == 'M', if you warn if name == 'M' and not is_period

natmokval · 2023-03-27T13:59:11Z

However, it also throws a warning for PeriodIndex(..., freq='M'), which as per #9586 (comment) we need to keep working

So, we need to figure out how to pass 'M' to PeriodIndex without it warning, but such that passing 'M' to date_range would warn

Thanks for helping me with the issue.

I noticed the same inconsistency for Period. It also throws a warning for Period(..., freq='M'):

>>> pd.Period('2017Q3', freq='M')
Period('2017-07', 'ME')

I will work on fixing it.

MarcoGorelli · 2023-03-27T14:21:48Z

we might need to update

pandas/pandas/_libs/tslibs/period.pyx

Lines 2304 to 2307 in 072402b

    
           def __repr__(self) -> str: 
        
               base = self._dtype._dtype_code 
        
               formatted = period_format(self.ordinal, base) 
        
               return f"Period('{formatted}', '{self.freqstr}')"

so that, when it's printed, it still shows 'M'

pandas/_libs/tslibs/offsets.pyx

pandas/conftest.py

pandas/core/indexes/period.py

pandas/_libs/tslibs/offsets.pyx

…aily-frequencies

…ip ci]

MarcoGorelli · 2023-04-03T18:09:01Z

Looks like this one might need updating

pandas/pandas/_libs/tslibs/dtypes.pyx

Lines 143 to 155 in 8e2b974

    
           # Map attribute-name resolutions to resolution abbreviations 
        
           _attrname_to_abbrevs = { 
        
               "year": "A", 
        
               "quarter": "Q", 
        
               "month": "M", 
        
               "day": "D", 
        
               "hour": "H", 
        
               "minute": "T", 
        
               "second": "S", 
        
               "millisecond": "L", 
        
               "microsecond": "U", 
        
               "nanosecond": "N", 
        
           }

natmokval · 2023-04-04T19:42:13Z

Looks like this one might need updating

pandas/pandas/_libs/tslibs/dtypes.pyx

Lines 143 to 155 in 8e2b974

# Map attribute-name resolutions to resolution abbreviations

_attrname_to_abbrevs = {

"year": "A",

"quarter": "Q",

"month": "M",

"day": "D",

"hour": "H",

"minute": "T",

"second": "S",

"millisecond": "L",

"microsecond": "U",

"nanosecond": "N",

}

Thank you, I updated _attrname_to_abbrevs as you suggested and

pandas/pandas/_libs/tslibs/dtypes.pyx

Line 104 in 8e2b974

"M": PeriodDtypeCode.M, # Monthly

and

pandas/pandas/_libs/tslibs/dtypes.pyx

Lines 306 to 325 in 8e2b974

    
           cpdef str npy_unit_to_abbrev(NPY_DATETIMEUNIT unit): 
        
               if unit == NPY_DATETIMEUNIT.NPY_FR_ns or unit == NPY_DATETIMEUNIT.NPY_FR_GENERIC: 
        
                   # generic -> default to nanoseconds 
        
                   return "ns" 
        
               elif unit == NPY_DATETIMEUNIT.NPY_FR_us: 
        
                   return "us" 
        
               elif unit == NPY_DATETIMEUNIT.NPY_FR_ms: 
        
                   return "ms" 
        
               elif unit == NPY_DATETIMEUNIT.NPY_FR_s: 
        
                   return "s" 
        
               elif unit == NPY_DATETIMEUNIT.NPY_FR_m: 
        
                   return "m" 
        
               elif unit == NPY_DATETIMEUNIT.NPY_FR_h: 
        
                   return "h" 
        
               elif unit == NPY_DATETIMEUNIT.NPY_FR_D: 
        
                   return "D" 
        
               elif unit == NPY_DATETIMEUNIT.NPY_FR_W: 
        
                   return "W" 
        
               elif unit == NPY_DATETIMEUNIT.NPY_FR_M: 
        
                   return "M"

and

pandas/pandas/_libs/tslibs/dtypes.pyx

Lines 342 to 345 in 8e2b974

    
           cpdef NPY_DATETIMEUNIT abbrev_to_npy_unit(str abbrev): 
        
               if abbrev == "Y": 
        
                   return NPY_DATETIMEUNIT.NPY_FR_Y 
        
               elif abbrev == "M":

as well
and it fixed my tests.

but I still have failures in some other tests and I keep working on fixing them.

MarcoGorelli · 2023-04-05T09:38:30Z

thanks @natmokval - looks like CI didn't run for some reason, could you fetch and merge upstream/main please so I can take a look at any test failures? or just let me know which tests are failing for you and I'll try running them

pandas/_libs/tslibs/timedeltas.pyx

natmokval · 2023-04-05T21:14:05Z

thanks @natmokval - looks like CI didn't run for some reason, could you fetch and merge upstream/main please so I can take a look at any test failures? or just let me know which tests are failing for you and I'll try running them

Because I didn't want to run CI, I added '[skip ci]' to the commit message. Maybe it's better to run CI for every commit.

I did fetch, merge main, and made a new commit. Could you please take a look at the tests:
pandas/tests/indexes/period/test_indexing.py
and
pandas/tests/groupby/test_timegrouper.py

pandas/tests/indexes/period/test_indexing.py

MarcoGorelli · 2023-04-06T11:12:58Z

You'll need to update

pandas/pandas/core/resample.py

Line 1602 in 8e2b974

end_types = {"M", "A", "Q", "BM", "BA", "BQ", "W"}

too

For how I found this: the failing test has df.groupby(Grouper(freq="6M")). So I looked at the definition of Grouper, which led to TimeGrouper, which led to that line

pandas/_libs/tslibs/timestamps.pyx

…aily-frequencies

MarcoGorelli · 2023-10-20T15:17:12Z

pandas/_libs/tslibs/offsets.pyx

+                    warnings.warn(
+                        "\'M\' will be deprecated, please use \'ME\' "
+                        "for \'month end\'",
+                        UserWarning,


sorry I'd missed this when reviewing, this should have been FutureWarning

rhshadrach · 2023-10-20T20:27:47Z

This patch may have induced a performance regression. If it was a necessary behavior change, this may have been expected and everything is okay.

Please check the links below. If any ASVs are parameterized, the combinations of parameters that a regression has been detected for appear as subbullets.

Subsequent benchmarks may have skipped some commits. The link below lists the commits that are between the two benchmark runs where the regression was identified.

61a6335...a98be06

spencerkclark · 2023-10-29T23:24:18Z

Oh nice, thanks, I hadn't noticed that! Yes, that fixes most of the failures. The remaining ones seem to be a little more subtle; I will try and isolate how they relate to pandas when I get a chance.

@MarcoGorelli sorry for taking a while to get back on this — I have one more kind of example that seems to have been tripped up by this PR (note the presence of the offset parameter in this example):

Prior to this PR

>>> import numpy as np; import pandas as pd
>>> index = pd.date_range("2000", periods=5, freq="5D")
>>> series = pd.Series(np.arange(index.size), index=index)
>>> series.resample("2D", closed="right", label="right", offset="1s").mean()
2000-01-01 00:00:01    0.0
2000-01-03 00:00:01    NaN
2000-01-05 00:00:01    1.0
2000-01-07 00:00:01    NaN
2000-01-09 00:00:01    NaN
2000-01-11 00:00:01    2.0
2000-01-13 00:00:01    NaN
2000-01-15 00:00:01    3.0
2000-01-17 00:00:01    NaN
2000-01-19 00:00:01    NaN
2000-01-21 00:00:01    4.0
Freq: 2D, dtype: float64

On `main` as of 2023-10-29

>>> import numpy as np; import pandas as pd
>>> index = pd.date_range("2000", periods=5, freq="5D")
>>> series = pd.Series(np.arange(index.size), index=index)
>>> series.resample("2D", closed="right", label="right", offset="1s").mean()
2000-01-01 00:00:01    0.0
2000-01-03 00:00:01    NaN
2000-01-05 00:00:01    NaN
2000-01-07 00:00:01    1.0
2000-01-09 00:00:01    NaN
2000-01-11 00:00:01    2.0
2000-01-13 00:00:01    NaN
2000-01-15 00:00:01    NaN
2000-01-17 00:00:01    3.0
2000-01-19 00:00:01    NaN
2000-01-21 00:00:01    4.0
Freq: 2D, dtype: float64

Thanks again for your help!

MarcoGorelli · 2023-10-30T19:23:11Z

Hey @spencerkclark

thanks again for the report - you trying things out on main so we can fix them before they reach users really makes my day!

So, let's have a look at what's going on. We've put closed='right' and label='right', so I'd expect the windows to look like this:

2000-01-01 00:00:01: (1999-12-30 00:00:01, 2000-01-01 00:00:01]. [0]
2000-01-03 00:00:01: (2000-01-01 00:00:01, 2000-01-03 00:00:01]. []
2000-01-05 00:00:01: (2000-01-03 00:00:01, 2000-01-05 00:00:01]. []
2000-01-07 00:00:01: (2000-01-05 00:00:01, 2000-01-07 00:00:01]. [1]
2000-01-09 00:00:01: (2000-01-07 00:00:01, 2000-01-09 00:00:01]. []
2000-01-11 00:00:01: (2000-01-09 00:00:01, 2000-01-11 00:00:01]. [2]
2000-01-13 00:00:01: (2000-01-11 00:00:01, 2000-01-13 00:00:01]. []
...

Looks like this matches the current output, and that the previous one was incorrect?

Furthermore, Polars agrees with the current pandas output:

In [31]: dfpl = pl.from_pandas(series.to_frame().reset_index().rename(columns={0: 'value'}))

In [32]: dfpl.sort('index').group_by_dynamic(
    ...:     'index',
    ...:     every='2d',
    ...:     offset=timedelta(seconds=1)-timedelta(days=1),
    ...:     closed='right',
    ...:     label='right').agg(pl.col('value'))
Out[32]:
shape: (5, 2)
┌─────────────────────┬───────────┐
│ index               ┆ value     │
│ ---                 ┆ ---       │
│ datetime[ns]        ┆ list[i64] │
╞═════════════════════╪═══════════╡
│ 2000-01-01 00:00:01 ┆ [0]       │
│ 2000-01-07 00:00:01 ┆ [1]       │
│ 2000-01-11 00:00:01 ┆ [2]       │
│ 2000-01-17 00:00:01 ┆ [3]       │
│ 2000-01-21 00:00:01 ┆ [4]       │
└─────────────────────┴───────────┘

Anyway, I think was most likely fixed by #55283, not by this PR

spencerkclark · 2023-10-30T22:38:39Z

Ah this all makes sense now — I hadn't fully appreciated that #55283 also provided a bug fix and didn't think to question the original output. Thanks for that detailed explanation. Indeed #55283 is what I should be looking at and provides an illustration for how we should fix this in our implementation in xarray — I can confirm locally that the previously failing tests pass!

jbrockmendel · 2023-12-07T03:10:29Z

pandas/core/resample.py

@@ -2729,6 +2743,9 @@ def asfreq(
        if how is None:
            how = "E"

+        if isinstance(freq, BaseOffset):
+            freq = freq_to_period_freqstr(freq.n, freq.name)


i think if a user tries to use a period-invalid freq with a PeriodIndex we would want to raise/warn here wouldn't we?

it already raises doesn't it?

In [1]: In [10]: df = pd.DataFrame({'ts': pd.period_range('2000', periods=3), 'val': [1,2,3]}) ...: ...: In [11]: df.set_index('ts').resample('MS').mean() --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) File period.pyx:2854, in pandas._libs.tslibs.period.freq_to_dtype_code() AttributeError: 'pandas._libs.tslibs.offsets.MonthBegin' object has no attribute '_period_dtype_code' The above exception was the direct cause of the following exception: ValueError Traceback (most recent call last) Cell In[1], line 3 1 df = pd.DataFrame({'ts': pd.period_range('2000', periods=3), 'val': [1,2,3]}) ----> 3 df.set_index('ts').resample('MS').mean() File ~/tmp/.venv/lib/python3.10/site-packages/pandas/core/generic.py:9788, in NDFrame.resample(self, rule, axis, closed, label, convention, kind, on, level, origin, offset, group_keys) 9785 else: 9786 kind = None -> 9788 return get_resampler( 9789 cast("Series | DataFrame", self), 9790 freq=rule, 9791 label=label, 9792 closed=closed, 9793 axis=axis, 9794 kind=kind, 9795 convention=convention, 9796 key=on, 9797 level=level, 9798 origin=origin, 9799 offset=offset, 9800 group_keys=group_keys, 9801 ) File ~/tmp/.venv/lib/python3.10/site-packages/pandas/core/resample.py:2038, in get_resampler(obj, kind, **kwds) 2034 """ 2035 Create a TimeGrouper and return our resampler. 2036 """ 2037 tg = TimeGrouper(obj, **kwds) # type: ignore[arg-type] -> 2038 return tg._get_resampler(obj, kind=kind) File ~/tmp/.venv/lib/python3.10/site-packages/pandas/core/resample.py:2227, in TimeGrouper._get_resampler(self, obj, kind) 2218 return DatetimeIndexResampler( 2219 obj, 2220 timegrouper=self, (...) 2224 gpr_index=ax, 2225 ) 2226 elif isinstance(ax, PeriodIndex) or kind == "period": -> 2227 return PeriodIndexResampler( 2228 obj, 2229 timegrouper=self, 2230 kind=kind, 2231 axis=self.axis, 2232 group_keys=self.group_keys, 2233 gpr_index=ax, 2234 ) 2235 elif isinstance(ax, TimedeltaIndex): 2236 return TimedeltaIndexResampler( 2237 obj, 2238 timegrouper=self, (...) 2241 gpr_index=ax, 2242 ) File ~/tmp/.venv/lib/python3.10/site-packages/pandas/core/resample.py:185, in Resampler.__init__(self, obj, timegrouper, axis, kind, gpr_index, group_keys, selection, include_groups) 180 self.include_groups = include_groups 182 self.obj, self.ax, self._indexer = self._timegrouper._set_grouper( 183 self._convert_obj(obj), sort=True, gpr_index=gpr_index 184 ) --> 185 self.binner, self.grouper = self._get_binner() 186 self._selection = selection 187 if self._timegrouper.key is not None: File ~/tmp/.venv/lib/python3.10/site-packages/pandas/core/resample.py:250, in Resampler._get_binner(self) 244 @final 245 def _get_binner(self): 246 """ 247 Create the BinGrouper, assume that self.set_grouper(obj) 248 has already been called. 249 """ --> 250 binner, bins, binlabels = self._get_binner_for_time() 251 assert len(bins) == len(binlabels) 252 bin_grouper = BinGrouper(bins, binlabels, indexer=self._indexer) File ~/tmp/.venv/lib/python3.10/site-packages/pandas/core/resample.py:1884, in PeriodIndexResampler._get_binner_for_time(self) 1882 if self.kind == "timestamp": 1883 return super()._get_binner_for_time() -> 1884 return self._timegrouper._get_period_bins(self.ax) File ~/tmp/.venv/lib/python3.10/site-packages/pandas/core/resample.py:2451, in TimeGrouper._get_period_bins(self, ax) 2447 return binner, bins, labels 2449 freq_mult = self.freq.n -> 2451 start = ax.min().asfreq(self.freq, how=self.convention) 2452 end = ax.max().asfreq(self.freq, how="end") 2453 bin_shift = 0 File period.pyx:1945, in pandas._libs.tslibs.period._Period.asfreq() File period.pyx:2856, in pandas._libs.tslibs.period.freq_to_dtype_code() ValueError: Invalid frequency: <MonthBegin>

jbrockmendel · 2023-12-07T03:13:10Z

pandas/core/generic.py


        if isinstance(index, PeriodIndex):
            orig_freq = to_offset(index.freq)
            if freq != orig_freq:
                assert orig_freq is not None  # for mypy
                raise ValueError(
-                    f"Given freq {freq.rule_code} does not match "
-                    f"PeriodIndex freq {orig_freq.rule_code}"
+                    f"Given freq {freq_to_period_freqstr(freq.n, freq.name)} "


can we avoid the freq_to_period_freqstr by using is_period=True in to_offset a few lines up?

jbrockmendel · 2023-12-07T03:25:03Z

pandas/_libs/tslibs/dtypes.pyx

+}
+cdef dict c_OFFSET_TO_PERIOD_FREQSTR = OFFSET_TO_PERIOD_FREQSTR
+
+cpdef freq_to_period_freqstr(freq_n, freq_name):


would it be viable to get away from this entirely and use PeriodDtype(Base)._freqstr?

The PRs pandas-dev#55792 (Y), pandas-dev#52064 (Q), and pandas-dev#55553 (M) deprecated the single letter version of the aliases in favour of the -end version of them. This table was missed as part of that work.

The PRs pandas-dev#55792 (Y), pandas-dev#52064 (Q), and pandas-dev#55553 (M) deprecated the single letter version of the aliases in favour of the -end version of them. Add a note to the offset table about deprecations.

DOC: Add note about alias deprecations The PRs #55792 (Y), #52064 (Q), and #55553 (M) deprecated the single letter version of the aliases in favour of the -end version of them. Add a note to the offset table about deprecations.

natmokval added 2 commits March 18, 2023 15:18

Frequency: raise warnings when using ‘M’ frequency

d21c195

Frequency: raise warnings when using ‘M’ frequency II

6522436

MarcoGorelli requested changes Mar 22, 2023

View reviewed changes

MarcoGorelli reviewed Mar 28, 2023

View reviewed changes

pandas/_libs/tslibs/offsets.pyx Outdated Show resolved Hide resolved

pandas/conftest.py Outdated Show resolved Hide resolved

pandas/core/indexes/period.py Outdated Show resolved Hide resolved

MarcoGorelli reviewed Mar 29, 2023

View reviewed changes

pandas/_libs/tslibs/offsets.pyx Outdated Show resolved Hide resolved

natmokval added 3 commits March 30, 2023 12:54

Merge branch 'main' into 9586-inconsistent-labeling-sub-daily-super-d…

8e2b974

…aily-frequencies

remove is_period and change str representation for freq in Period [sk…

184debf

…ip ci]

remove is_period and fix some tests [skip ci]

e1d82cb

natmokval force-pushed the 9586-inconsistent-labeling-sub-daily-super-daily-frequencies branch from b07c569 to e1d82cb Compare March 30, 2023 21:44

fix some tests

55c4d76

MarcoGorelli changed the title ~~Frequency: raise warnings when using ‘M’ frequency~~ DEPR offsets: rename 'M' to 'ME' Mar 31, 2023

fix some tests II

24756bc

fix tests in pandas/tests/indexes/period/ [skip ci]

989db20

MarcoGorelli reviewed Apr 5, 2023

View reviewed changes

pandas/_libs/tslibs/timedeltas.pyx Outdated Show resolved Hide resolved

natmokval added 2 commits April 5, 2023 21:24

fix tests in pandas/tests/indexes/period/ and correct timedeltas.pyx

253b823

fix tests in pandas/tests/indexes/period/ and correct timedeltas.pyx

bfb59ae

natmokval marked this pull request as ready for review April 5, 2023 20:34

MarcoGorelli reviewed Apr 6, 2023

View reviewed changes

pandas/tests/indexes/period/test_indexing.py Outdated Show resolved Hide resolved

MarcoGorelli reviewed Apr 6, 2023

View reviewed changes

pandas/_libs/tslibs/timestamps.pyx Outdated Show resolved Hide resolved

natmokval added 2 commits April 6, 2023 20:48

update frequencies.py, resample.py, and fix some tests

266c480

Merge branch 'main' into 9586-inconsistent-labeling-sub-daily-super-d…

c204645

…aily-frequencies

This was referenced Oct 16, 2023

DEPR offsets: rename 'Q' to 'QE' #55553

Merged

BUG: conversion a JSON field descriptor into pandas type for deprecated offsets frequency 'M' #55581

Merged

MarcoGorelli reviewed Oct 20, 2023

View reviewed changes

natmokval mentioned this pull request Oct 22, 2023

DEPR: correct class of Warning for offsets deprecated frequency ('M' to 'ME') #55636

Merged

spencerkclark mentioned this pull request Oct 31, 2023

Port fix from pandas-dev/pandas#55283 to cftime resample pydata/xarray#8393

Merged

2 tasks

This was referenced Nov 1, 2023

DEPR offsets: rename ‘Y’ to ‘YE' #55792

Merged

BUG: QuarterBegin Does not work with Period #55785

Closed

This was referenced Nov 13, 2023

ENH: Improve error message when constructing period with invalid freq #55940

Merged

DEPR: rename BQ to BQE for offsets #55978

Merged

DEPR offsets: rename 'SM' to 'SME' #56050

Merged

natmokval mentioned this pull request Dec 5, 2023

DEPR: lower/uppercase strings such as 'y', 'q', 'H', 'MIN', etc. denoting freqs/units for time series, period, and timedelta #56346

Closed

jbrockmendel reviewed Dec 7, 2023

View reviewed changes

This was referenced Dec 13, 2023

DEPR: raise ValueError if invalid period freq pass to asfreq #56489

Merged

CLN: replace unnecessary freq_to_period_freqstr with PeriodDtype constructor #56550

Merged

This was referenced Jan 8, 2024

DOC: add to to_offset the missing parameter is_period and examples #56789

Merged

DEPR: rename offset alias ‘MS’ to ‘MB’ #56840

Open

natmokval mentioned this pull request Jan 25, 2024

BUG: PeriodIndex.asfreq silently converts offset to period #57075

Closed

natmokval mentioned this pull request Feb 6, 2024

ENH: raise ValueError if invalid period freq pass to asfreq when the index of df is a PeriodIndex #56945

Merged

natmokval mentioned this pull request Mar 17, 2024

CLN: replace deprecated freqs H/M with h/ME in tests for plotting #57877

Merged

natmokval mentioned this pull request Mar 24, 2024

CLN: enforce deprecation of frequencies deprecated for offsets #57986

Merged

tacaswell mentioned this pull request May 29, 2024

DOC: Add note about deprecated offset aliases #58861

Merged

5 tasks

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

DEPR offsets: rename 'M' to 'ME' #52064

DEPR offsets: rename 'M' to 'ME' #52064

natmokval commented Mar 18, 2023 •

edited

Loading

natmokval commented Mar 21, 2023

MarcoGorelli left a comment

MarcoGorelli commented Mar 22, 2023

natmokval commented Mar 27, 2023

MarcoGorelli commented Mar 27, 2023

MarcoGorelli commented Apr 3, 2023

natmokval commented Apr 4, 2023

MarcoGorelli commented Apr 5, 2023

natmokval commented Apr 5, 2023

MarcoGorelli commented Apr 6, 2023

MarcoGorelli Oct 20, 2023

rhshadrach commented Oct 20, 2023

spencerkclark commented Oct 29, 2023

MarcoGorelli commented Oct 30, 2023

spencerkclark commented Oct 30, 2023

jbrockmendel Dec 7, 2023

MarcoGorelli Dec 7, 2023 •

edited

Loading

jbrockmendel Dec 7, 2023

jbrockmendel Dec 7, 2023

DEPR offsets: rename 'M' to 'ME' #52064

DEPR offsets: rename 'M' to 'ME' #52064

Conversation

natmokval commented Mar 18, 2023 • edited Loading

natmokval commented Mar 21, 2023

MarcoGorelli left a comment

Choose a reason for hiding this comment

MarcoGorelli commented Mar 22, 2023

natmokval commented Mar 27, 2023

MarcoGorelli commented Mar 27, 2023

MarcoGorelli commented Apr 3, 2023

natmokval commented Apr 4, 2023

MarcoGorelli commented Apr 5, 2023

natmokval commented Apr 5, 2023

MarcoGorelli commented Apr 6, 2023

MarcoGorelli Oct 20, 2023

Choose a reason for hiding this comment

rhshadrach commented Oct 20, 2023

spencerkclark commented Oct 29, 2023

Prior to this PR

On main as of 2023-10-29

MarcoGorelli commented Oct 30, 2023

spencerkclark commented Oct 30, 2023

jbrockmendel Dec 7, 2023

Choose a reason for hiding this comment

MarcoGorelli Dec 7, 2023 • edited Loading

Choose a reason for hiding this comment

jbrockmendel Dec 7, 2023

Choose a reason for hiding this comment

jbrockmendel Dec 7, 2023

Choose a reason for hiding this comment

natmokval commented Mar 18, 2023 •

edited

Loading

On `main` as of 2023-10-29

MarcoGorelli Dec 7, 2023 •

edited

Loading