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# -*- coding: utf-8 -*-
"""
Code for computing the type score.
Author: Gertjan van den Burg
"""
import json
from typing import Dict
from typing import List
from typing import Optional
from typing import Pattern
from ._regexes import DEFAULT_TYPE_REGEXES
from .cparser_util import parse_string
from .dialect import SimpleDialect
DEFAULT_EPS_TYPE: float = 1e-10
class TypeDetector:
def __init__(
self,
patterns: Optional[Dict[str, Pattern[str]]] = None,
strip_whitespace: bool = True,
) -> None:
self.patterns = patterns or DEFAULT_TYPE_REGEXES.copy()
self.strip_whitespace = strip_whitespace
self._register_type_tests()
def _register_type_tests(self) -> None:
self._type_tests = [
("empty", self.is_empty),
("url", self.is_url),
("email", self.is_email),
("ipv4", self.is_ipv4),
("number", self.is_number),
("time", self.is_time),
("percentage", self.is_percentage),
("currency", self.is_currency),
("unix_path", self.is_unix_path),
("nan", self.is_nan),
("date", self.is_date),
("datetime", self.is_datetime),
("unicode_alphanum", self.is_unicode_alphanum),
("bytearray", self.is_bytearray),
("json", self.is_json_obj),
]
def list_known_types(self) -> List[str]:
return [tt[0] for tt in self._type_tests]
def is_known_type(self, cell: str, is_quoted: bool = False) -> bool:
return self.detect_type(cell, is_quoted=is_quoted) is not None
def detect_type(self, cell: str, is_quoted: bool = False) -> Optional[str]:
cell = cell.strip() if self.strip_whitespace else cell
for name, func in self._type_tests:
if func(cell, is_quoted=is_quoted):
return name
return None
def _run_regex(self, cell: str, patname: str) -> bool:
cell = cell.strip() if self.strip_whitespace else cell
pat = self.patterns.get(patname, None)
assert pat is not None
match = pat.fullmatch(cell)
return match is not None
def is_number(self, cell: str, is_quoted: bool = False) -> bool:
if cell == "":
return False
if self._run_regex(cell, "number_1"):
return True
if self._run_regex(cell, "number_2"):
return True
if self._run_regex(cell, "number_3"):
return True
return False
def is_ipv4(self, cell: str, is_quoted: bool = False) -> bool:
return self._run_regex(cell, "ipv4")
def is_url(self, cell: str, is_quoted: bool = False) -> bool:
return self._run_regex(cell, "url")
def is_email(self, cell: str, is_quoted: bool = False) -> bool:
return self._run_regex(cell, "email")
def is_unicode_alphanum(self, cell: str, is_quoted: bool = False) -> bool:
if is_quoted:
return self._run_regex(cell, "unicode_alphanum_quoted")
return self._run_regex(cell, "unicode_alphanum")
def is_date(self, cell: str, is_quoted: bool = False) -> bool:
# This function assumes the cell is not a number.
cell = cell.strip() if self.strip_whitespace else cell
if not cell:
return False
if not cell[0].isdigit():
return False
return self._run_regex(cell, "date")
def is_time(self, cell: str, is_quoted: bool = False) -> bool:
cell = cell.strip() if self.strip_whitespace else cell
if not cell:
return False
if not cell[0].isdigit():
return False
return (
self._run_regex(cell, "time_hmm")
or self._run_regex(cell, "time_hhmm")
or self._run_regex(cell, "time_hhmmss")
or self._run_regex(cell, "time_hhmmsszz")
)
def is_empty(self, cell: str, is_quoted: bool = False) -> bool:
return cell == ""
def is_percentage(self, cell: str, is_quoted: bool = False) -> bool:
return cell.endswith("%") and self.is_number(cell.rstrip("%"))
def is_currency(self, cell: str, is_quoted: bool = False) -> bool:
pat = self.patterns.get("currency", None)
assert pat is not None
m = pat.fullmatch(cell)
if m is None:
return False
grp = m.group(1)
if not self.is_number(grp):
return False
return True
def is_datetime(self, cell: str, is_quoted: bool = False) -> bool:
# Takes care of cells with '[date] [time]' and '[date]T[time]' (iso)
if not cell:
return False
if not cell[0].isdigit():
return False
if " " in cell:
parts = cell.split(" ")
if len(parts) > 2:
return False
return self.is_date(parts[0]) and self.is_time(parts[1])
elif "T" in cell:
parts = cell.split("T")
if len(parts) > 2:
return False
isdate = self.is_date(parts[0])
if not isdate:
return False
# [date]T[time] or [date]T[time]Z
if parts[1].endswith("Z") and self.is_time(parts[1][:-1]):
return True
if self.is_time(parts[1]):
return True
# [date]T[time][+-][time]
if "+" in parts[1]:
subparts = parts[1].split("+")
istime1 = self.is_time(subparts[0])
if not istime1:
return False
istime2 = self.is_time(subparts[1])
if istime2:
return True
if self._run_regex(subparts[1], "time_HHMM"):
return True
if self._run_regex(subparts[1], "time_HH"):
return True
elif "-" in parts[1]:
subparts = parts[1].split("-")
istime1 = self.is_time(subparts[0])
if not istime1:
return False
istime2 = self.is_time(subparts[1])
if istime2:
return True
if self._run_regex(subparts[1], "time_HHMM"):
return True
if self._run_regex(subparts[1], "time_HH"):
return True
return False
def is_nan(self, cell: str, is_quoted: bool = False) -> bool:
if cell.lower() in ["n/a", "na", "nan"]:
return True
return False
def is_unix_path(self, cell: str, is_quoted: bool = False) -> bool:
return self._run_regex(cell, "unix_path")
def is_bytearray(self, cell: str, is_quoted: bool = False) -> bool:
return cell.startswith("bytearray(b") and cell.endswith(")")
def is_json_obj(self, cell: str, is_quoted: bool = False) -> bool:
if not (cell.startswith("{") and cell.endswith("}")):
return False
try:
_ = json.loads(cell)
except json.JSONDecodeError:
return False
return True
def gen_known_type(cells):
"""
Utility that yields a generator over whether or not the provided cells are
of a known type or not.
"""
td = TypeDetector()
for cell in cells:
yield td.is_known_type(cell)
def type_score(
data: str, dialect: SimpleDialect, eps: float = DEFAULT_EPS_TYPE
) -> float:
"""
Compute the type score as the ratio of cells with a known type.
Parameters
----------
data: str
the data as a single string
dialect: SimpleDialect
the dialect to use
eps: float
the minimum value of the type score
Returns
-------
type_score: float
The computed type score
"""
total = 0
known = 0
td = TypeDetector()
for row in parse_string(data, dialect, return_quoted=True):
for cell, is_quoted in row:
total += 1
known += td.is_known_type(cell, is_quoted=is_quoted)
if total == 0:
return eps
return max(eps, known / total)
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