platypush/platypush/plugins/csv.py
Fabio Manganiello 1f1fefca9d Tensorflow plugin implementation WIP [#121]
TODO: Extend neural network implementation to work
also with e.g. input from images, sounds or binary
2020-03-21 19:50:59 +01:00

177 lines
6.3 KiB
Python

import csv
import os
from typing import Optional, List, Any, Union, Dict
from typing.io import TextIO
from platypush.plugins import Plugin, action
class CsvPlugin(Plugin):
"""
A plugin for managing CSV files.
"""
@classmethod
def _get_path(cls, filename: str) -> str:
return os.path.abspath(os.path.expanduser(filename))
@staticmethod
def reversed_blocks(f: TextIO, blocksize=4096):
""" Generate blocks of file's contents in reverse order. """
f.seek(0, os.SEEK_END)
here = f.tell()
while 0 < here:
delta = min(blocksize, here)
here -= delta
f.seek(here, os.SEEK_SET)
yield f.read(delta)
@classmethod
def lines(cls, f: TextIO, reverse: bool = False):
if not reverse:
for line in f:
yield line
else:
part = ''
quoting = False
for block in cls.reversed_blocks(f):
for c in reversed(block):
if c == '"':
quoting = not quoting
elif c == '\n' and part and not quoting:
yield part[::-1]
part = ''
part += c
if part:
yield part[::-1]
@staticmethod
def _parse_header(filename: str, **csv_args) -> List[str]:
column_names = []
with open(filename, 'r', newline='') as f:
try:
has_header = csv.Sniffer().has_header(f.read(1024))
except csv.Error:
has_header = False
if has_header:
with open(filename, 'r', newline='') as f:
for row in csv.reader(f, **csv_args):
column_names = row
break
return column_names
@action
def read(self,
filename: str,
delimiter: str = ',',
quotechar: Optional[str] = '"',
start: int = 0,
limit: Optional[int] = None,
reverse: bool = False,
has_header: bool = None,
column_names: Optional[List[str]] = None,
dialect: str = 'excel'):
"""
Gets the content of a CSV file.
:param filename: Path of the file.
:param delimiter: Field delimiter (default: ``,``).
:param quotechar: Quote character (default: ``"``).
:param start: (Zero-based) index of the first line to be read (starting from the last if ``reverse`` is True)
(default: 0).
:param limit: Maximum number of lines to be read (default: all).
:param reverse: If True then the lines will be read starting from the last (default: False).
:param has_header: Set to True if the first row of the file is a header, False if the first row
isn't expected to be a header (default: None, the method will scan the first chunk of the file
and estimate whether the first line is a header).
:param column_names: Specify if the file has no header or you want to override the column names.
:param dialect: CSV dialect (default: ``excel``).
"""
filename = self._get_path(filename)
column_names = column_names or []
csv_args = {
'delimiter': delimiter,
'quotechar': quotechar,
'dialect': dialect,
}
if has_header is None and not column_names:
column_names = self._parse_header(filename, **csv_args)
has_header = len(column_names) > 0
rows = []
with open(filename, 'r', newline='') as f:
for i, row in enumerate(csv.reader(self.lines(f, reverse=reverse), **csv_args)):
if not row or i < start:
continue
if limit and len(rows) >= limit + (1 if has_header else 0):
break
rows.append(dict(zip(column_names, row)) if column_names else row)
if has_header:
rows.pop(-1 if reverse else 0)
return rows
@action
def write(self,
filename: str,
rows: List[Union[List[Any], Dict[str, Any]]],
truncate: bool = False,
delimiter: str = ',',
quotechar: Optional[str] = '"',
dialect: str = 'excel'):
"""
Writes lines to a CSV file.
:param filename: Path of the CSV file.
:param rows: Rows to write. It can be a list of lists or a key->value dictionary where the keys match
the names of the columns. If the rows are dictionaries then a header with the column names will be
written to the file if not available already, otherwise no header will be written.
:param truncate: If True then any previous file content will be removed, otherwise the new rows will be
appended to the file (default: False).
:param delimiter: Field delimiter (default: ``,``).
:param quotechar: Quote character (default: ``"``).
:param dialect: CSV dialect (default: ``excel``).
"""
filename = self._get_path(filename)
file_exists = os.path.isfile(filename)
column_names = []
csv_args = {
'delimiter': delimiter,
'quotechar': quotechar,
'dialect': dialect,
}
if file_exists:
column_names = self._parse_header(filename, **csv_args)
elif rows and isinstance(rows[0], dict):
column_names = rows[0].keys()
column_name_to_idx = {name: i for i, name in enumerate(column_names)}
if truncate:
file_exists = False
with open(filename, 'w' if truncate else 'a', newline='') as f:
writer = csv.writer(f, **csv_args)
if not file_exists and column_names:
writer.writerow(column_names)
for row in rows:
if isinstance(row, dict):
flat_row = [None] * len(column_names)
for column, value in row.items():
assert column in column_name_to_idx, \
'No such column available in the CSV file: {}'.format(column)
idx = column_name_to_idx[column]
flat_row[idx] = value
row = flat_row
writer.writerow(row)
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