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c_parser_wrapper.py
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import pandas._libs.parsers as parsers
from pandas._typing import FilePathOrBuffer
from pandas.core.indexes.api import ensure_index_from_sequences
from pandas.io.parsers.base_parser import (
ParserBase,
is_index_col,
)
class CParserWrapper(ParserBase):
def __init__(self, src: FilePathOrBuffer, **kwds):
self.kwds = kwds
kwds = kwds.copy()
ParserBase.__init__(self, kwds)
# #2442
# error: Cannot determine type of 'index_col'
kwds["allow_leading_cols"] = (
self.index_col is not False # type: ignore[has-type]
)
# GH20529, validate usecol arg before TextReader
kwds["usecols"] = self.usecols
# open handles
self._open_handles(src, kwds)
assert self.handles is not None
for key in ("storage_options", "encoding", "memory_map", "compression"):
kwds.pop(key, None)
try:
self._reader = parsers.TextReader(self.handles.handle, **kwds)
except Exception:
self.handles.close()
raise
self.unnamed_cols = self._reader.unnamed_cols
# error: Cannot determine type of 'names'
passed_names = self.names is None # type: ignore[has-type]
if self._reader.header is None:
self.names = None
else:
if len(self._reader.header) > 1:
# we have a multi index in the columns
# error: Cannot determine type of 'names'
# error: Cannot determine type of 'index_names'
# error: Cannot determine type of 'col_names'
(
self.names, # type: ignore[has-type]
self.index_names,
self.col_names,
passed_names,
) = self._extract_multi_indexer_columns(
self._reader.header,
self.index_names, # type: ignore[has-type]
self.col_names, # type: ignore[has-type]
passed_names,
)
else:
# error: Cannot determine type of 'names'
self.names = list(self._reader.header[0]) # type: ignore[has-type]
# error: Cannot determine type of 'names'
if self.names is None: # type: ignore[has-type]
if self.prefix:
# error: Cannot determine type of 'names'
self.names = [ # type: ignore[has-type]
f"{self.prefix}{i}" for i in range(self._reader.table_width)
]
else:
# error: Cannot determine type of 'names'
self.names = list( # type: ignore[has-type]
range(self._reader.table_width)
)
# gh-9755
#
# need to set orig_names here first
# so that proper indexing can be done
# with _set_noconvert_columns
#
# once names has been filtered, we will
# then set orig_names again to names
# error: Cannot determine type of 'names'
self.orig_names = self.names[:] # type: ignore[has-type]
if self.usecols:
usecols = self._evaluate_usecols(self.usecols, self.orig_names)
# GH 14671
# assert for mypy, orig_names is List or None, None would error in issubset
assert self.orig_names is not None
if self.usecols_dtype == "string" and not set(usecols).issubset(
self.orig_names
):
self._validate_usecols_names(usecols, self.orig_names)
# error: Cannot determine type of 'names'
if len(self.names) > len(usecols): # type: ignore[has-type]
# error: Cannot determine type of 'names'
self.names = [ # type: ignore[has-type]
n
# error: Cannot determine type of 'names'
for i, n in enumerate(self.names) # type: ignore[has-type]
if (i in usecols or n in usecols)
]
# error: Cannot determine type of 'names'
if len(self.names) < len(usecols): # type: ignore[has-type]
# error: Cannot determine type of 'names'
self._validate_usecols_names(
usecols,
self.names, # type: ignore[has-type]
)
# error: Cannot determine type of 'names'
self._validate_parse_dates_presence(self.names) # type: ignore[has-type]
self._set_noconvert_columns()
# error: Cannot determine type of 'names'
self.orig_names = self.names # type: ignore[has-type]
if not self._has_complex_date_col:
# error: Cannot determine type of 'index_col'
if self._reader.leading_cols == 0 and is_index_col(
self.index_col # type: ignore[has-type]
):
self._name_processed = True
(
index_names,
# error: Cannot determine type of 'names'
self.names, # type: ignore[has-type]
self.index_col,
) = self._clean_index_names(
# error: Cannot determine type of 'names'
self.names, # type: ignore[has-type]
# error: Cannot determine type of 'index_col'
self.index_col, # type: ignore[has-type]
self.unnamed_cols,
)
if self.index_names is None:
self.index_names = index_names
if self._reader.header is None and not passed_names:
assert self.index_names is not None
self.index_names = [None] * len(self.index_names)
self._implicit_index = self._reader.leading_cols > 0
def close(self) -> None:
super().close()
# close additional handles opened by C parser
try:
self._reader.close()
except ValueError:
pass
def _set_noconvert_columns(self):
"""
Set the columns that should not undergo dtype conversions.
Currently, any column that is involved with date parsing will not
undergo such conversions.
"""
assert self.orig_names is not None
# error: Cannot determine type of 'names'
col_indices = [
self.orig_names.index(x) for x in self.names # type: ignore[has-type]
]
# error: Cannot determine type of 'names'
noconvert_columns = self._set_noconvert_dtype_columns(
col_indices,
self.names, # type: ignore[has-type]
)
for col in noconvert_columns:
self._reader.set_noconvert(col)
def set_error_bad_lines(self, status):
self._reader.set_error_bad_lines(int(status))
def read(self, nrows=None):
try:
data = self._reader.read(nrows)
except StopIteration:
# error: Cannot determine type of '_first_chunk'
if self._first_chunk: # type: ignore[has-type]
self._first_chunk = False
names = self._maybe_dedup_names(self.orig_names)
index, columns, col_dict = self._get_empty_meta(
names,
self.index_col,
self.index_names,
dtype=self.kwds.get("dtype"),
)
columns = self._maybe_make_multi_index_columns(columns, self.col_names)
if self.usecols is not None:
columns = self._filter_usecols(columns)
col_dict = {k: v for k, v in col_dict.items() if k in columns}
return index, columns, col_dict
else:
self.close()
raise
# Done with first read, next time raise StopIteration
self._first_chunk = False
# error: Cannot determine type of 'names'
names = self.names # type: ignore[has-type]
if self._reader.leading_cols:
if self._has_complex_date_col:
raise NotImplementedError("file structure not yet supported")
# implicit index, no index names
arrays = []
for i in range(self._reader.leading_cols):
if self.index_col is None:
values = data.pop(i)
else:
values = data.pop(self.index_col[i])
values = self._maybe_parse_dates(values, i, try_parse_dates=True)
arrays.append(values)
index = ensure_index_from_sequences(arrays)
if self.usecols is not None:
names = self._filter_usecols(names)
names = self._maybe_dedup_names(names)
# rename dict keys
data_tups = sorted(data.items())
data = {k: v for k, (i, v) in zip(names, data_tups)}
names, data = self._do_date_conversions(names, data)
else:
# rename dict keys
data_tups = sorted(data.items())
# ugh, mutation
# assert for mypy, orig_names is List or None, None would error in list(...)
assert self.orig_names is not None
names = list(self.orig_names)
names = self._maybe_dedup_names(names)
if self.usecols is not None:
names = self._filter_usecols(names)
# columns as list
alldata = [x[1] for x in data_tups]
data = {k: v for k, (i, v) in zip(names, data_tups)}
names, data = self._do_date_conversions(names, data)
index, names = self._make_index(data, alldata, names)
# maybe create a mi on the columns
names = self._maybe_make_multi_index_columns(names, self.col_names)
return index, names, data
def _filter_usecols(self, names):
# hackish
usecols = self._evaluate_usecols(self.usecols, names)
if usecols is not None and len(names) != len(usecols):
names = [
name for i, name in enumerate(names) if i in usecols or name in usecols
]
return names
def _get_index_names(self):
names = list(self._reader.header[0])
idx_names = None
if self._reader.leading_cols == 0 and self.index_col is not None:
(idx_names, names, self.index_col) = self._clean_index_names(
names, self.index_col, self.unnamed_cols
)
return names, idx_names
def _maybe_parse_dates(self, values, index, try_parse_dates=True):
if try_parse_dates and self._should_parse_dates(index):
values = self._date_conv(values)
return values