- Dependencies updates:
pandas
-> == 1.3.4
- Dependencies updates:
numpy
-> >= 1.19
- Dependencies updates:
slackclient
-> 2.9.3numpy
-> >= 1.20.1pandas
-> >=1.2.2dask[complete]
-> 2021.2.0pyarrow
-> >= 2.0.0
- Dependencies updates:
slackclient
-> 2.5.0numpy
-> 1.18.1pandas
-> 1.0.1dask[complete]
-> 2.10.1pyarrow
-> 0.16.0
- Dependencies updates:
- Locks
pyarrow
to0.12.0
to avoid segfault as described in pytorch/pytorch#13039 (comment)
- Fixes kwargs passed along to pyarrow/fastparquet engines in
read_df_parquet
andread_ddf_parquet
- Updates
write_df_parquet
andwrite_ddf_parquet
to handlefastparquet
engine
read_df_parquet
andread_ddf_parquet
now take optionalengine
argument to allow to usepyarrow
orfastparquet
engines for reading parquet files.
- Updates
slackclient
dependency to2.0.1
and handles migration of api to v2 (https://github.com/slackapi/python-slackclient/wiki/Migrating-to-2.x)
- Updates requirements for
pandas
,numpy
,dask
, andpyarrow
- Updates requirements for pandas, numpy, scikit-learn, and pyarrow
- Updates
pyarrow
requirement to0.11
- Changes
nthreads
inread_df_parquet
touse_threads
to match https://arrow.apache.org/docs/python/generated/pyarrow.parquet.ParquetFile.html#pyarrow.parquet.ParquetFile.read
SDLog
logs traceback up to 10 levels deep as text to Slack.
SDLog
will now also log error traceback to Slack (before it was only the type and the value).
- Updated
pandas
,dask
, andnumpy
versions.
SDLog
now uses a classlog_message
method to log -- this now supports a custom logging interface by inheriting fromSDLog
or replacinglog_message
in an application.
class MyTestLogger(SDLog):
@classmethod
def log_message(cls, message: str, **kwargs):
print('SPECIAL LOGGER', message)
This class will print 'SPECIAL LOGGER' before all messages, but otherwise
act the same as the normal SDLog
. As another example, the log_message
method could connect to and log to a database for non-console-based
logging.