Move remaining conversion functions to tslibs.conversion #18358
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Codecov Report
@@ Coverage Diff @@
## master #18358 +/- ##
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- Coverage 91.38% 91.36% -0.02%
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Files 164 164
Lines 49790 49791 +1
==========================================
- Hits 45501 45493 -8
- Misses 4289 4298 +9
Continue to review full report at Codecov.
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Codecov Report
@@ Coverage Diff @@
## master #18358 +/- ##
==========================================
- Coverage 91.38% 91.36% -0.02%
==========================================
Files 164 164
Lines 49790 49791 +1
==========================================
- Hits 45501 45493 -8
- Misses 4289 4298 +9
Continue to review full report at Codecov.
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pandas/_libs/tslibs/conversion.pyx
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| @@ -73,6 +73,86 @@ cdef inline int64_t get_datetime64_nanos(object val) except? -1: | |||
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| return ival | |||
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| def cast_to_nanoseconds(ndarray arr): | |||
| cdef: | |||
pandas/_libs/tslibs/conversion.pyx
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| def datetime_to_datetime64(ndarray[object] values): | ||
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pandas/_libs/tslibs/conversion.pyx
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| cdef inline _to_i8(object val): | ||
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doc-string.
can you rename this to something else. maybe datetime_to_i8
pandas/_libs/index.pyx
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| @@ -13,7 +13,7 @@ cimport util | |||
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| import numpy as np | |||
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| from tslib cimport _to_i8 | |||
| from tslibs.conversion cimport _maybe_datetimelike_to_i8 | |||
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note to de-private this at some point as well
pandas/_libs/tslibs/conversion.pyx
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| @@ -73,6 +73,123 @@ cdef inline int64_t get_datetime64_nanos(object val) except? -1: | |||
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| return ival | |||
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| def cast_to_nanoseconds(ndarray arr): | |||
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let's rename this maybe ensure_datetime64ns
| if len(iresult) == 0: | ||
| return result | ||
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| unit = get_datetime64_unit(arr.flat[0]) |
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prob should add some checks around this, IOW this could already be ns (TODO ok)
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Yah, this check is done elsewhere, will not be hard to implement.
If it weren't for datetime64[Y] and datetime64[M] we could take the pandas_datetime_to_datetimestruct out of these funcs altogether, avoid converting back and forth.
pandas/_libs/tslibs/conversion.pyx
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| Returns | ||
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| result : ndarray witth dtype int64 |
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thanks! |
Slightly more efficient implementation of
_to_i8.Importantly (or at least satisfyingly) gets
pandas_datetime_to_datetimestructusage centralized in conversion.