BUG: pd.read_sql returns empty list if query has no results and chunksize is set · Issue #34411 · pandas-dev/pandas (original) (raw)
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- [ x] I have confirmed this bug exists on the latest version of pandas.
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Code Sample, a copy-pastable example
import pandas as pd import sqlite3
Create empty test table in memory
conn = sqlite3.connect(':memory:') conn.cursor().execute('CREATE TABLE test (column_1 INTEGER);')
Run the query without chunksize, works as expected
pd.read_sql('select * from test', conn)
Run the query with chunksize, returns generator as expected
pd.read_sql('select * from test', conn, chunksize=5)
However, the generator is empty
list(pd.read_sql('select * from test', conn, chunksize=5))
I would expect, that for all cases where chunksize isn't necessary,
than the following two lines would return exactly the same
result, but the second throws "ValueError: No objects to concatenate"
pd.read_sql('select * from test', conn)
pd.concat(pd.read_sql('select * from test', conn, chunksize=5))
Problem description
In many cases, returning zero rows is an expected result, and the code should run fine on the returned DataFrame (iterating over it, getting all values in a row, etc.).
The current behaviour instead returns an empty list, with no information about for example the columns in the dataframe.
Expected Output
The expected output would be a list containing a single empty dataframe, with the correct column metadata. I would expect that for all queries that run fine without chunkbite being set, the following equality should hold:
pd.testing.assert_frame_equal(
pd.read_sql(query, conn),
pd.concat(pd.read_sql(query, conn, chunksize=5))
)
Output of pd.show_versions()
INSTALLED VERSIONS
commit : 333db4b
python : 3.8.2.final.0
python-bits : 64
OS : Darwin
OS-release : 18.7.0
Version : Darwin Kernel Version 18.7.0: Thu Jan 23 06:52:12 PST 2020; root:xnu-4903.278.25~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8
pandas : 1.1.0.dev0+1685.g333db4b76.dirty
numpy : 1.18.4
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1.1
setuptools : 46.4.0.post20200518
Cython : 0.29.19
pytest : 5.4.2
hypothesis : 5.16.0
sphinx : 3.0.4
blosc : None
feather : None
xlsxwriter : 1.2.8
lxml.etree : 4.5.1
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.14.0
pandas_datareader: None
bs4 : 4.9.1
bottleneck : 1.3.2
fastparquet : 0.4.0
gcsfs : None
matplotlib : 3.2.1
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.3
pandas_gbq : None
pyarrow : 0.17.1
pytables : None
pyxlsb : None
s3fs : 0.4.2
scipy : 1.4.1
sqlalchemy : 1.3.17
tables : 3.6.1
tabulate : 0.8.7
xarray : 0.15.1
xlrd : 1.2.0
xlwt : 1.3.0
numba : 0.48.0