Parquet export IR #183
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Parquet export IR #183
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Exporting data through a CSV intermediary is subject to loss of specificity and type info. This is particularly noticable for read_pandas, where the resulting dataframe has every column of type `object` and NULLs are indistinguishable from zero values. I used a small hack to export data from Dolt into a DataFrame using parquet instead of CSV. This requires the pyarrow dependency. I left TODOs for improvements on the Dolt side that would make this code cleaner and Dolt issues for the associated features. There is one bug with NULL datetime values that I added a Dolt issue for.
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re: #179 |
Codecov Report
@@ Coverage Diff @@
## main #183 +/- ##
==========================================
+ Coverage 42.88% 43.98% +1.10%
==========================================
Files 23 23
Lines 977 998 +21
==========================================
+ Hits 419 439 +20
- Misses 558 559 +1
Continue to review full report at Codecov.
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Exporting data through a CSV intermediary is subject to loss
of specificity and type info. This is particularly noticable
for read_pandas, where the resulting dataframe has every column
of type
objectand NULLs are indistinguishable from zero values.I used a small hack to export data from Dolt into a DataFrame using parquet
instead of CSV. This requires the pyarrow dependency.
I left TODOs for improvements on the Dolt side that would make
this code cleaner and Dolt issues for the associated features.
There is one bug with NULL datetime values that I added a Dolt issue
for.