/
regex.py
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/
regex.py
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from __future__ import absolute_import, print_function, division
import re
import operator
from petl.compat import next, text_type
from petl.errors import ArgumentError
from petl.util.base import Table, asindices
from petl.transform.basics import TransformError
from petl.transform.conversions import convert
def capture(table, field, pattern, newfields=None, include_original=False,
flags=0, fill=None):
"""
Add one or more new fields with values captured from an existing field
searched via a regular expression. E.g.::
>>> import petl as etl
>>> table1 = [['id', 'variable', 'value'],
... ['1', 'A1', '12'],
... ['2', 'A2', '15'],
... ['3', 'B1', '18'],
... ['4', 'C12', '19']]
>>> table2 = etl.capture(table1, 'variable', '(\\w)(\\d+)',
... ['treat', 'time'])
>>> table2
+-----+-------+-------+------+
| id | value | treat | time |
+=====+=======+=======+======+
| '1' | '12' | 'A' | '1' |
+-----+-------+-------+------+
| '2' | '15' | 'A' | '2' |
+-----+-------+-------+------+
| '3' | '18' | 'B' | '1' |
+-----+-------+-------+------+
| '4' | '19' | 'C' | '12' |
+-----+-------+-------+------+
>>> # using the include_original argument
... table3 = etl.capture(table1, 'variable', '(\\w)(\\d+)',
... ['treat', 'time'],
... include_original=True)
>>> table3
+-----+----------+-------+-------+------+
| id | variable | value | treat | time |
+=====+==========+=======+=======+======+
| '1' | 'A1' | '12' | 'A' | '1' |
+-----+----------+-------+-------+------+
| '2' | 'A2' | '15' | 'A' | '2' |
+-----+----------+-------+-------+------+
| '3' | 'B1' | '18' | 'B' | '1' |
+-----+----------+-------+-------+------+
| '4' | 'C12' | '19' | 'C' | '12' |
+-----+----------+-------+-------+------+
By default the field on which the capture is performed is omitted. It can
be included using the `include_original` argument.
The ``fill`` parameter can be used to provide a list or tuple of values to
use if the regular expression does not match. The ``fill`` parameter
should contain as many values as there are capturing groups in the regular
expression. If ``fill`` is ``None`` (default) then a
``petl.transform.TransformError`` will be raised on the first non-matching
value.
"""
return CaptureView(table, field, pattern,
newfields=newfields,
include_original=include_original,
flags=flags,
fill=fill)
Table.capture = capture
class CaptureView(Table):
def __init__(self, source, field, pattern, newfields=None,
include_original=False, flags=0, fill=None):
self.source = source
self.field = field
self.pattern = pattern
self.newfields = newfields
self.include_original = include_original
self.flags = flags
self.fill = fill
def __iter__(self):
return itercapture(self.source, self.field, self.pattern,
self.newfields, self.include_original, self.flags,
self.fill)
def itercapture(source, field, pattern, newfields, include_original, flags,
fill):
it = iter(source)
prog = re.compile(pattern, flags)
hdr = next(it)
flds = list(map(text_type, hdr))
if isinstance(field, int) and field < len(hdr):
field_index = field
elif field in flds:
field_index = flds.index(field)
else:
raise ArgumentError('field invalid: must be either field name or index')
# determine output fields
outhdr = list(flds)
if not include_original:
outhdr.remove(field)
if newfields:
outhdr.extend(newfields)
yield tuple(outhdr)
# construct the output data
for row in it:
value = row[field_index]
if include_original:
out_row = list(row)
else:
out_row = [v for i, v in enumerate(row) if i != field_index]
match = prog.search(value)
if match is None:
if fill is not None:
out_row.extend(fill)
else:
raise TransformError('value %r did not match pattern %r'
% (value, pattern))
else:
out_row.extend(match.groups())
yield tuple(out_row)
def split(table, field, pattern, newfields=None, include_original=False,
maxsplit=0, flags=0):
"""
Add one or more new fields with values generated by splitting an
existing value around occurrences of a regular expression. E.g.::
>>> import petl as etl
>>> table1 = [['id', 'variable', 'value'],
... ['1', 'parad1', '12'],
... ['2', 'parad2', '15'],
... ['3', 'tempd1', '18'],
... ['4', 'tempd2', '19']]
>>> table2 = etl.split(table1, 'variable', 'd', ['variable', 'day'])
>>> table2
+-----+-------+----------+-----+
| id | value | variable | day |
+=====+=======+==========+=====+
| '1' | '12' | 'para' | '1' |
+-----+-------+----------+-----+
| '2' | '15' | 'para' | '2' |
+-----+-------+----------+-----+
| '3' | '18' | 'temp' | '1' |
+-----+-------+----------+-----+
| '4' | '19' | 'temp' | '2' |
+-----+-------+----------+-----+
By default the field on which the split is performed is omitted. It can
be included using the `include_original` argument.
"""
return SplitView(table, field, pattern, newfields, include_original,
maxsplit, flags)
Table.split = split
class SplitView(Table):
def __init__(self, source, field, pattern, newfields=None,
include_original=False, maxsplit=0, flags=0):
self.source = source
self.field = field
self.pattern = pattern
self.newfields = newfields
self.include_original = include_original
self.maxsplit = maxsplit
self.flags = flags
def __iter__(self):
return itersplit(self.source, self.field, self.pattern, self.newfields,
self.include_original, self.maxsplit, self.flags)
def itersplit(source, field, pattern, newfields, include_original, maxsplit,
flags):
it = iter(source)
prog = re.compile(pattern, flags)
hdr = next(it)
flds = list(map(text_type, hdr))
if isinstance(field, int) and field < len(hdr):
field_index = field
field = hdr[field_index]
elif field in flds:
field_index = flds.index(field)
else:
raise ArgumentError('field invalid: must be either field name or index')
# determine output fields
outhdr = list(flds)
if not include_original:
outhdr.remove(field)
if newfields:
outhdr.extend(newfields)
yield tuple(outhdr)
# construct the output data
for row in it:
value = row[field_index]
if include_original:
out_row = list(row)
else:
out_row = [v for i, v in enumerate(row) if i != field_index]
out_row.extend(prog.split(value, maxsplit))
yield tuple(out_row)
def sub(table, field, pattern, repl, count=0, flags=0):
"""
Convenience function to convert values under the given field using a
regular expression substitution. See also :func:`re.sub`.
"""
prog = re.compile(pattern, flags)
conv = lambda v: prog.sub(repl, v, count=count)
return convert(table, field, conv)
Table.sub = sub
def search(table, *args, **kwargs):
"""
Perform a regular expression search, returning rows that match a given
pattern, either anywhere in the row or within a specific field. E.g.::
>>> import petl as etl
>>> table1 = [['foo', 'bar', 'baz'],
... ['orange', 12, 'oranges are nice fruit'],
... ['mango', 42, 'I like them'],
... ['banana', 74, 'lovely too'],
... ['cucumber', 41, 'better than mango']]
>>> # search any field
... table2 = etl.search(table1, '.g.')
>>> table2
+------------+-----+--------------------------+
| foo | bar | baz |
+============+=====+==========================+
| 'orange' | 12 | 'oranges are nice fruit' |
+------------+-----+--------------------------+
| 'mango' | 42 | 'I like them' |
+------------+-----+--------------------------+
| 'cucumber' | 41 | 'better than mango' |
+------------+-----+--------------------------+
>>> # search a specific field
... table3 = etl.search(table1, 'foo', '.g.')
>>> table3
+----------+-----+--------------------------+
| foo | bar | baz |
+==========+=====+==========================+
| 'orange' | 12 | 'oranges are nice fruit' |
+----------+-----+--------------------------+
| 'mango' | 42 | 'I like them' |
+----------+-----+--------------------------+
The complement can be found via
:func:`petl.transform.regex.searchcomplement`.
"""
if len(args) == 1:
field = None
pattern = args[0]
elif len(args) == 2:
field = args[0]
pattern = args[1]
else:
raise ArgumentError('expected 1 or 2 positional arguments')
return SearchView(table, pattern, field=field, **kwargs)
Table.search = search
class SearchView(Table):
def __init__(self, table, pattern, field=None, flags=0, complement=False):
self.table = table
self.pattern = pattern
self.field = field
self.flags = flags
self.complement = complement
def __iter__(self):
return itersearch(self.table, self.pattern, self.field, self.flags,
self.complement)
def itersearch(table, pattern, field, flags, complement):
prog = re.compile(pattern, flags)
it = iter(table)
hdr = next(it)
flds = list(map(text_type, hdr))
yield tuple(hdr)
if field is None:
# search whole row
test = lambda r: any(prog.search(text_type(v)) for v in r)
else:
indices = asindices(hdr, field)
if len(indices) == 1:
index = indices[0]
test = lambda r: prog.search(text_type(r[index]))
else:
getvals = operator.itemgetter(*indices)
test = lambda r: any(prog.search(text_type(v)) for v in getvals(r))
# complement==False, return rows that match
if not complement:
for row in it:
if test(row):
yield tuple(row)
# complement==True, return rows that do not match
else:
for row in it:
if not test(row):
yield tuple(row)
def searchcomplement(table, *args, **kwargs):
"""
Perform a regular expression search, returning rows that **do not**
match a given pattern, either anywhere in the row or within a specific
field. E.g.::
>>> import petl as etl
>>> table1 = [['foo', 'bar', 'baz'],
... ['orange', 12, 'oranges are nice fruit'],
... ['mango', 42, 'I like them'],
... ['banana', 74, 'lovely too'],
... ['cucumber', 41, 'better than mango']]
>>> # search any field
... table2 = etl.searchcomplement(table1, '.g.')
>>> table2
+----------+-----+--------------+
| foo | bar | baz |
+==========+=====+==============+
| 'banana' | 74 | 'lovely too' |
+----------+-----+--------------+
>>> # search a specific field
... table3 = etl.searchcomplement(table1, 'foo', '.g.')
>>> table3
+------------+-----+---------------------+
| foo | bar | baz |
+============+=====+=====================+
| 'banana' | 74 | 'lovely too' |
+------------+-----+---------------------+
| 'cucumber' | 41 | 'better than mango' |
+------------+-----+---------------------+
This returns the complement of :func:`petl.transform.regex.search`.
"""
return search(table, *args, complement=True, **kwargs)
Table.searchcomplement = searchcomplement