BUG: read_csv does not raise UnicodeDecodeError on non utf-8 characters

[DrGFreeman]

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.
  Bug exists in 1.2.1, not in <=1.2.0

• (optional) I have confirmed this bug exists on the master branch of pandas.

---

Note: Please read this guide detailing how to provide the necessary information for us to reproduce your bug.

Code Sample, a copy-pastable example

from pathlib import Path

import pandas as pd

file = Path("non-utf8.csv")
file.write_bytes(b"\xe4\na\n1")  # non utf-8 character

df = pd.read_csv(file)

Output:

   �
0  a
1  1

Problem description

In pandas version 1.2.1, reading a csv file containing non utf-8 characters does not raise a UnicodeDecoreError. In version 1.2.0 and earlier, a UnicodeDecodeError is raised, allowing proper exception handling in application code.

Expected Output

Expect a UnicodeDecodeError to be raised.

Output of pd.show_versions()

INSTALLED VERSIONS
------------------
commit           : 9d598a5e1eee26df95b3910e3f2934890d062caa
python           : 3.8.5.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.17763
machine          : AMD64
processor        : Intel64 Family 6 Model 158 Stepping 9, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : French_Canada.1252

pandas           : 1.2.1
numpy            : 1.19.2
pytz             : 2020.5
dateutil         : 2.8.1
pip              : 20.3.3
setuptools       : 52.0.0.post20210125
Cython           : None
pytest           : 6.2.2
hypothesis       : None
sphinx           : 3.4.3
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.19.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : 0.8.3
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.2
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 0.15.1
pyxlsb           : None
s3fs             : None
scipy            : 1.5.2
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : 0.51.2

[twoertwein]

I will have time to check this later: I would have expected that you didn't get an error in <1.2 and >=1.2.1 (#38989), but you get an error only for 1.2.0.

[phofl]

Yeah would have expected the same, but this is raising for me too on 1.1.5

[DrGFreeman]

It is my understanding that there should be an exception raised for non-unicode characters (except if in skipped_rows, ref. #38989).

I used many versions between 0.23 and 1.2.0 (inclusive) and the exception was always raised.

When I updated to 1.2.1, the exception stopped being raised which I noticed from failed unit tests in my application (testing that the exception is raised and handled properly).

[twoertwein]

I will try to understand the pre 1.2 behavior. I assume that #38997 overshot: restored some old behavior (#38989) but also introduced some new behavior (this issue).

[twoertwein]

@DrGFreeman can you confirm that on 1.1.5 you get the error only when using the "c" engine? When I run your example on 1.1.5 with the python engine, I do not get an error. On 1.2.1 your example should fail with both engines, if you explicitly specify encoding when calling read_csv.

I made changes in 1.2.0 to share more file opening code between the c and python engine. The good news is that they raise errors in a more consistent way :)

Is there a way to fix this issue and to keep #38989 fixed?

In case there is no good solution for 1.2x: What would be the best solution for >=1.3? Default to errors='strict' but expose errors in read_csv and read_json (and any other text-reading function)?

[DrGFreeman]

@DrGFreeman can you confirm that on 1.1.5 you get the error only when using the "c" engine? When I run your example on 1.1.5 with the python engine, I do not get an error. On 1.2.1 your example should fail with both engines, if you explicitly specify encoding when calling read_csv.

@twoertwein, below are the results I get with versions 1.1.5 and 1.2.1 and different parameters:

pandas==1.1.5

pd.read_csv(file) : UnicodeDecodeError raised
pd.read_csv(file, engine="c") : UnicodeDecodeError raised
pd.read_csv(file, engine="c", encoding="utf-8") : UnicodeDecodeError raised
pd.read_csv(file, engine="python") : No exception raised
pd.read_csv(file, engine="python", encoding="utf-8") : UnicodeDecodeErrorraised

pandas==1.2.1

pd.read_csv(file) : No exception raised
pd.read_csv(file, engine="c") : No exception raised
pd.read_csv(file, engine="c", encoding="utf-8") : UnicodeDecodeError raised
pd.read_csv(file, engine="python") : No exception raised
pd.read_csv(file, engine="python", encoding="utf-8") : UnicodeDecodeErrorraised

[twoertwein]

To summarize:

1. In all versions/engines: When an encoding is specified, errors="strict"
2. There is one inconsistency between the c and python engine when no encoding is specified in versions <1.2.0:
   a. c engine raised an error for encoding errors, python engine did not
3. In <1.2.0, skipping lines ignored errors only when no encoding is specified
4. In 1.2.0: The c and python engine use the file opening code from the python engine and mistakenly errors="strict" even when no encoding specified
5. In 1.2.1: errors="replace" when no encoding specified

If we assume the python behavior is "correct", everythig works as expected in 1.2.1. If we assume that the c behavior (default engine!) is "correct", then we need to implement code to 1) always set errors="strict" 2) but use errors="replace" for skipped rows.

I think the only way to implement the c behavior is to follow this stackoverflow answer:

Note that decoding takes place per buffered block of data, not per textual line. If you must detect errors on a line-by-line basis, use the surrogateescape handler and test each line read for codepoints in the surrogate range:

[phofl]

I think exposing the errors keyword would make sense and set the default to strict? But I think it would also be reasonable to raise only if encoding is specified

[twoertwein]

Do the following points sound like a good plan? I assume we cannot introduce a new argument in 1.2.x.

1. for 1.2.2: update "encoding" documentation for read_csv to make clear that files will be opened with errors="replace" unless an encoding is specified
2. for 1.3.0: all read_* that read text (are there more than read_csv and read_json?) will have a new errors argument that defaults to "strict" (it is probably a bad idea to push errors into storage_options)

[jreback]

Do the following points sound like a good plan? I assume we cannot introduce a new argument in 1.2.x.

1. for 1.2.2: update "encoding" documentation for read_csv to make clear that files will be opened with errors="replace" unless an encoding is specified
2. for 1.3.0: all read_* that read text (are there more than read_csv and read_json?) will have a new errors argument that defaults to "strict" (it is probably a bad idea to push errors into storage_options)

+1 to the plan

[phofl]

Sounds good to me too