applying formats using fetch or to_frame makes all DataFrame columns objects

If you have formats on only a few columns in a CAS table and try to apply the formats to the SASDataFrame, the swat package converts all columns to objects, even if the column is a simple number.

For example:

Packages

import swat
import pandas as pd

Connect to CAS

conn = ##connection info

load data to CAS

data = r'https://support.sas.com/documentation/onlinedoc/viya/exampledatasets/cars.csv'
tbl = conn.upload_file(data,
casout = {'name':'cars_upload', 'caslib':'casuser','replace':True},
importoptions={
'stripBlanks':True,
'guessRows':200,
'vars':{
'MSRP':{'format':'dollar16.'},
'Weight':{'format':'comma16.'}
}})

Only the MSRP and Weight columns have a format

tbl.columnInfo()

Pull the CAS table to the client as a SASDataFrame and apply the formats. This works as expected

df = tbl.to_frame(format=True)
df.head()

View the data types of the SASDataFrame

Everything turns into an object. It seems like only the formatted columns should be converted. Numeric columns without formats should remain numbers.

Start by reproducing the behavior with tbl.to_frame(format=True) using the cars example and inspect the resulting SASDataFrame dtypes. Trace the formatting path used by to_frame or fetch, then add coverage showing that only formatted columns become objects while unformatted numeric columns retain numeric types.