BUG: pandas.read_sql_table() returns incorrect data types

[Alper2022]

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Reproducible Example

### Push this to Postgresql ###
create table product(
product_id varchar(255) primary key not null,
price varchar(255) not null,
gender varchar(255),
name varchar(255) not null,
recommendable boolean not null,
is_active boolean  not null,
fk_event_number integer references event(event_number) not null
);

### call pandas function ###

df_products_db = pd.read_sql_table("product",engine.connect())

print(df_products_db.dtypes) # returns 4 object data types, should be strings

Issue Description

When using pandas.read_sql_table() to request data from a (in my case) localhost postgres database, the data types returned are different then the data types specified in the postgresql enviorment

Expected Behavior

Data types should be strings (as they are varchar(255) in the database), but return as object types

Installed Versions

INSTALLED VERSIONS

commit : 2e218d1
python : 3.10.6.final.0
python-bits : 64
OS : Linux
OS-release : 5.19.0-35-generic
Version : #36~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Fri Feb 17 15:17:25 UTC 2
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.5.3
numpy : 1.24.1
pytz : 2022.1
dateutil : 2.8.1
setuptools : 59.6.0
pip : 22.0.2
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.8.0
html5lib : 1.1
pymysql : None
psycopg2 : 2.9.5
jinja2 : 3.1.2
IPython : None
pandas_datareader: None
bs4 : 4.10.0
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.6.3
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : 2.0.6
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None
tzdata : None

[asishm]

object is the default data type for strings, so this is expected until the default changes.

[Alper2022]

Where could i change this default?

[phofl]

You can use convert_dtypes or set the dtype_backend option starting with pandas 2.0