CLN: ASV ctors benchmark
I think this these asvs should be enhanced or reorganized to other files in the future, but in the meantime:

- Added `np.random.seed(1234)` in setup classes where random data is created xref #8144

- Ran flake8 and replaced star imports

```
$ asv run -q -b ^ctors
[  0.00%] ·· Benchmarking conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
[ 20.00%] ··· Running ctors.Constructors.time_dtindex_from_index_with_series                                         99.0μs
[ 40.00%] ··· Running ctors.Constructors.time_dtindex_from_series                                                    59.5μs
[ 60.00%] ··· Running ctors.Constructors.time_frame_from_ndarray                                                      237μs
[ 80.00%] ··· Running ctors.Constructors.time_index_from_array_string                                                 101μs
[100.00%] ··· Running ctors.Constructors.time_series_from_ndarray                                                    61.2μs
```
