179 lines
5.6 KiB
Python
179 lines
5.6 KiB
Python
""" io on the clipboard """
|
|
from __future__ import annotations
|
|
|
|
from io import StringIO
|
|
from typing import TYPE_CHECKING
|
|
import warnings
|
|
|
|
from pandas._libs import lib
|
|
from pandas.util._exceptions import find_stack_level
|
|
from pandas.util._validators import check_dtype_backend
|
|
|
|
from pandas.core.dtypes.generic import ABCDataFrame
|
|
|
|
from pandas import (
|
|
get_option,
|
|
option_context,
|
|
)
|
|
|
|
if TYPE_CHECKING:
|
|
from pandas._typing import DtypeBackend
|
|
|
|
|
|
def read_clipboard(
|
|
sep: str = r"\s+",
|
|
dtype_backend: DtypeBackend | lib.NoDefault = lib.no_default,
|
|
**kwargs,
|
|
): # pragma: no cover
|
|
r"""
|
|
Read text from clipboard and pass to read_csv.
|
|
|
|
Parameters
|
|
----------
|
|
sep : str, default '\s+'
|
|
A string or regex delimiter. The default of '\s+' denotes
|
|
one or more whitespace characters.
|
|
|
|
dtype_backend : {"numpy_nullable", "pyarrow"}, defaults to NumPy backed DataFrames
|
|
Which dtype_backend to use, e.g. whether a DataFrame should have NumPy
|
|
arrays, nullable dtypes are used for all dtypes that have a nullable
|
|
implementation when "numpy_nullable" is set, pyarrow is used for all
|
|
dtypes if "pyarrow" is set.
|
|
|
|
The dtype_backends are still experimential.
|
|
|
|
.. versionadded:: 2.0
|
|
|
|
**kwargs
|
|
See read_csv for the full argument list.
|
|
|
|
Returns
|
|
-------
|
|
DataFrame
|
|
A parsed DataFrame object.
|
|
"""
|
|
encoding = kwargs.pop("encoding", "utf-8")
|
|
|
|
# only utf-8 is valid for passed value because that's what clipboard
|
|
# supports
|
|
if encoding is not None and encoding.lower().replace("-", "") != "utf8":
|
|
raise NotImplementedError("reading from clipboard only supports utf-8 encoding")
|
|
|
|
check_dtype_backend(dtype_backend)
|
|
|
|
from pandas.io.clipboard import clipboard_get
|
|
from pandas.io.parsers import read_csv
|
|
|
|
text = clipboard_get()
|
|
|
|
# Try to decode (if needed, as "text" might already be a string here).
|
|
try:
|
|
text = text.decode(kwargs.get("encoding") or get_option("display.encoding"))
|
|
except AttributeError:
|
|
pass
|
|
|
|
# Excel copies into clipboard with \t separation
|
|
# inspect no more then the 10 first lines, if they
|
|
# all contain an equal number (>0) of tabs, infer
|
|
# that this came from excel and set 'sep' accordingly
|
|
lines = text[:10000].split("\n")[:-1][:10]
|
|
|
|
# Need to remove leading white space, since read_csv
|
|
# accepts:
|
|
# a b
|
|
# 0 1 2
|
|
# 1 3 4
|
|
|
|
counts = {x.lstrip(" ").count("\t") for x in lines}
|
|
if len(lines) > 1 and len(counts) == 1 and counts.pop() != 0:
|
|
sep = "\t"
|
|
# check the number of leading tabs in the first line
|
|
# to account for index columns
|
|
index_length = len(lines[0]) - len(lines[0].lstrip(" \t"))
|
|
if index_length != 0:
|
|
kwargs.setdefault("index_col", list(range(index_length)))
|
|
|
|
# Edge case where sep is specified to be None, return to default
|
|
if sep is None and kwargs.get("delim_whitespace") is None:
|
|
sep = r"\s+"
|
|
|
|
# Regex separator currently only works with python engine.
|
|
# Default to python if separator is multi-character (regex)
|
|
if len(sep) > 1 and kwargs.get("engine") is None:
|
|
kwargs["engine"] = "python"
|
|
elif len(sep) > 1 and kwargs.get("engine") == "c":
|
|
warnings.warn(
|
|
"read_clipboard with regex separator does not work properly with c engine.",
|
|
stacklevel=find_stack_level(),
|
|
)
|
|
|
|
return read_csv(StringIO(text), sep=sep, dtype_backend=dtype_backend, **kwargs)
|
|
|
|
|
|
def to_clipboard(
|
|
obj, excel: bool | None = True, sep: str | None = None, **kwargs
|
|
) -> None: # pragma: no cover
|
|
"""
|
|
Attempt to write text representation of object to the system clipboard
|
|
The clipboard can be then pasted into Excel for example.
|
|
|
|
Parameters
|
|
----------
|
|
obj : the object to write to the clipboard
|
|
excel : bool, defaults to True
|
|
if True, use the provided separator, writing in a csv
|
|
format for allowing easy pasting into excel.
|
|
if False, write a string representation of the object
|
|
to the clipboard
|
|
sep : optional, defaults to tab
|
|
other keywords are passed to to_csv
|
|
|
|
Notes
|
|
-----
|
|
Requirements for your platform
|
|
- Linux: xclip, or xsel (with PyQt4 modules)
|
|
- Windows:
|
|
- OS X:
|
|
"""
|
|
encoding = kwargs.pop("encoding", "utf-8")
|
|
|
|
# testing if an invalid encoding is passed to clipboard
|
|
if encoding is not None and encoding.lower().replace("-", "") != "utf8":
|
|
raise ValueError("clipboard only supports utf-8 encoding")
|
|
|
|
from pandas.io.clipboard import clipboard_set
|
|
|
|
if excel is None:
|
|
excel = True
|
|
|
|
if excel:
|
|
try:
|
|
if sep is None:
|
|
sep = "\t"
|
|
buf = StringIO()
|
|
|
|
# clipboard_set (pyperclip) expects unicode
|
|
obj.to_csv(buf, sep=sep, encoding="utf-8", **kwargs)
|
|
text = buf.getvalue()
|
|
|
|
clipboard_set(text)
|
|
return
|
|
except TypeError:
|
|
warnings.warn(
|
|
"to_clipboard in excel mode requires a single character separator.",
|
|
stacklevel=find_stack_level(),
|
|
)
|
|
elif sep is not None:
|
|
warnings.warn(
|
|
"to_clipboard with excel=False ignores the sep argument.",
|
|
stacklevel=find_stack_level(),
|
|
)
|
|
|
|
if isinstance(obj, ABCDataFrame):
|
|
# str(df) has various unhelpful defaults, like truncation
|
|
with option_context("display.max_colwidth", None):
|
|
objstr = obj.to_string(**kwargs)
|
|
else:
|
|
objstr = str(obj)
|
|
clipboard_set(objstr)
|