Rebase TSV parser on CSV parser

Overview

test.py

from dataflows import Flow, load


file_path = "/path/to/test.tsv"
flows = [load(file_path, name="res", format="tsv", skip_rows=["#"])]
print(Flow(*flows).results())

with file test.tsv:

#  This is a comment
#  
Lat	Lon
33.6062	-117.9312
33.6062	-117.9312
33.6062	-117.9312

I get the error:

Traceback (most recent call last):
  File "/home/conrad/.virtualenvs/laminar/lib/python3.8/site-packages/tabulator/stream.py", line 757, in __extract_sample
    row_number, headers, row = next(self.__parser.extended_rows)
  File "/home/conrad/.virtualenvs/laminar/lib/python3.8/site-packages/tabulator/parsers/tsv.py", line 65, in __iter_extended_rows
    for row_number, item in enumerate(items, start=1):
  File "/home/conrad/.virtualenvs/laminar/lib/python3.8/site-packages/tsv.py", line 51, in un
    if check_line_consistency(columns, values, i, error_bad_lines):
  File "/home/conrad/.virtualenvs/laminar/lib/python3.8/site-packages/tsv.py", line 84, in check_line_consistency
    raise ValueError(message)
ValueError: Expected 1 fields in line 3, saw 2

It seems like the TSV parser strictly sets the the number of fields allowed when it is initialized (https://github.com/frictionlessdata/tabulator-py/blob/master/tabulator/parsers/tsv.py#L63). Since the first item in this file is a comment with no tabs, it errors when a line shows up with a seemingly larger number of fields.

I would fall back to just using the CSV module and use \t as the delimiter (https://stackoverflow.com/questions/42358259/how-to-parse-tsv-file-with-python) but I keep getting the error "delimiter" must be a 1-character string - not sure if that a result of custom code or not.

---

Please preserve this line to notify @roll (lead of this repository)

[cschloer]

Just to follow back on this, I realized that some front end library I was using was changing “\t” to “\\t” before making the request to the server. Just a note that \t is now working, but it is still not possible to delimit on a mulitcharacter string.

[roll]

MEGED into https://github.com/frictionlessdata/frictionless-py/issues/398