BUG: list-like objects are broadcast to each row (1.3 regression)
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [x] (optional) I have confirmed this bug exists on the master branch of pandas.

---

#### Code Sample, a copy-pastable example

This requires both pandas and grpcio-tools.

```python
import subprocess
import sys

import pandas as pd

proto = """
syntax="proto3";

message Data {
  repeated float values = 1;
}
"""

with open('data.proto', 'w') as f:
    f.write(proto)

subprocess.run([
    sys.executable, '-m', 'grpc_tools.protoc', '-I.',
    '--python_out=.', '--grpc_python_out=.', 'data.proto'
])

from data_pb2 import Data

proto_data = Data(values=range(3))
print(proto_data.values)
print(type(proto_data.values))
df = pd.DataFrame(index=range(3), data={'a': proto_data.values})
print(df)
```

#### Problem description

On 1.3.0 and the master branch this code prints:
```
[0.0, 1.0, 2.0]
<class 'google.protobuf.pyext._message.RepeatedScalarContainer'>
                 a
0  [0.0, 1.0, 2.0]
1  [0.0, 1.0, 2.0]
2  [0.0, 1.0, 2.0]
```

The issue seems to arise from #41592. In 1.2.x this object was handled by `_try_cast` in [this else clause](https://github.com/pandas-dev/pandas/blob/1.2.x/pandas/core/construction.py#L495-L496). After that change, it's handled by `construct_1d_arraylike_from_scalar` because [`is_list_like(data)` returns False](https://github.com/pandas-dev/pandas/blob/master/pandas/core/construction.py#L511-L515). Note that [RepeatedScalarContainer](https://github.com/protocolbuffers/protobuf/blob/master/python/google/protobuf/pyext/repeated_scalar_container.cc#L767-L781) implements `PyTypeObject.tp_as_sequence` but not `PyTypeObject.tp_iter`, so `list(proto_data.values)` works fine, but the [`hasattr(obj, "__iter__")` check in `is_list_like`](https://github.com/pandas-dev/pandas/blob/master/pandas/_libs/lib.pyx#L1092-L1102) is False.

Based on all this, I suspect that this same issue will occur on any object which implements `PyTypeObject.tp_as_sequence` but not `PyTypeObject.tp_iter`, however this protobuf object the only example I have right now so I can't test further.

I'm not familiar enough with Cython to provide a full fix, but is there some way to examine the struct fields of `obj` in `is_list_like`? If so, that function could be amended to check `hasattr(obj, "__iter__") or hasattr(obj, "tp_as_sequence")`. If not I think the logic of `sanitize_array` needs to be amended. 

#### Expected Output

On 1.2.x this prints:
```
[0.0, 1.0, 2.0]
<class 'google.protobuf.pyext._message.RepeatedScalarContainer'>
     a
0  0.0
1  1.0
2  2.0
```

#### Output of ``pd.show_versions()``

<details>
INSTALLED VERSIONS
------------------
commit           : f00ed8f47020034e752baf0250483053340971b0
python           : 3.8.6.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 20.3.0
Version          : Darwin Kernel Version 20.3.0: Thu Jan 21 00:07:06 PST 2021; root:xnu-7195.81.3~1/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.3.0
numpy            : 1.20.3
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.0.1
setuptools       : 53.0.0
Cython           : 0.29.22
pytest           : 6.2.2
hypothesis       : 6.3.4
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.3
IPython          : 7.20.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.4
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 3.0.0
pyxlsb           : None
s3fs             : None
scipy            : 1.6.0
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
