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198 lines
6.2 KiB
Python
198 lines
6.2 KiB
Python
""" io on the clipboard """
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from __future__ import annotations
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from io import StringIO
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from typing import TYPE_CHECKING
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import warnings
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from pandas._libs import lib
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from pandas.util._exceptions import find_stack_level
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from pandas.util._validators import check_dtype_backend
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from pandas.core.dtypes.generic import ABCDataFrame
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from pandas import (
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get_option,
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option_context,
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)
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if TYPE_CHECKING:
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from pandas._typing import DtypeBackend
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def read_clipboard(
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sep: str = r"\s+",
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dtype_backend: DtypeBackend | lib.NoDefault = lib.no_default,
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**kwargs,
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): # pragma: no cover
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r"""
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Read text from clipboard and pass to :func:`~pandas.read_csv`.
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Parses clipboard contents similar to how CSV files are parsed
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using :func:`~pandas.read_csv`.
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Parameters
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----------
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sep : str, default '\\s+'
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A string or regex delimiter. The default of ``'\\s+'`` denotes
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one or more whitespace characters.
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dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
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Back-end data type applied to the resultant :class:`DataFrame`
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(still experimental). Behaviour is as follows:
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* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
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(default).
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* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
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DataFrame.
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.. versionadded:: 2.0
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**kwargs
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See :func:`~pandas.read_csv` for the full argument list.
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Returns
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-------
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DataFrame
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A parsed :class:`~pandas.DataFrame` object.
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See Also
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--------
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DataFrame.to_clipboard : Copy object to the system clipboard.
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read_csv : Read a comma-separated values (csv) file into DataFrame.
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read_fwf : Read a table of fixed-width formatted lines into DataFrame.
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Examples
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--------
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>>> df = pd.DataFrame([[1, 2, 3], [4, 5, 6]], columns=['A', 'B', 'C'])
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>>> df.to_clipboard() # doctest: +SKIP
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>>> pd.read_clipboard() # doctest: +SKIP
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A B C
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0 1 2 3
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1 4 5 6
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"""
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encoding = kwargs.pop("encoding", "utf-8")
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# only utf-8 is valid for passed value because that's what clipboard
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# supports
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if encoding is not None and encoding.lower().replace("-", "") != "utf8":
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raise NotImplementedError("reading from clipboard only supports utf-8 encoding")
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check_dtype_backend(dtype_backend)
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from pandas.io.clipboard import clipboard_get
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from pandas.io.parsers import read_csv
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text = clipboard_get()
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# Try to decode (if needed, as "text" might already be a string here).
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try:
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text = text.decode(kwargs.get("encoding") or get_option("display.encoding"))
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except AttributeError:
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pass
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# Excel copies into clipboard with \t separation
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# inspect no more then the 10 first lines, if they
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# all contain an equal number (>0) of tabs, infer
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# that this came from excel and set 'sep' accordingly
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lines = text[:10000].split("\n")[:-1][:10]
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# Need to remove leading white space, since read_csv
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# accepts:
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# a b
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# 0 1 2
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# 1 3 4
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counts = {x.lstrip(" ").count("\t") for x in lines}
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if len(lines) > 1 and len(counts) == 1 and counts.pop() != 0:
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sep = "\t"
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# check the number of leading tabs in the first line
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# to account for index columns
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index_length = len(lines[0]) - len(lines[0].lstrip(" \t"))
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if index_length != 0:
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kwargs.setdefault("index_col", list(range(index_length)))
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# Edge case where sep is specified to be None, return to default
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if sep is None and kwargs.get("delim_whitespace") is None:
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sep = r"\s+"
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# Regex separator currently only works with python engine.
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# Default to python if separator is multi-character (regex)
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if len(sep) > 1 and kwargs.get("engine") is None:
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kwargs["engine"] = "python"
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elif len(sep) > 1 and kwargs.get("engine") == "c":
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warnings.warn(
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"read_clipboard with regex separator does not work properly with c engine.",
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stacklevel=find_stack_level(),
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)
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return read_csv(StringIO(text), sep=sep, dtype_backend=dtype_backend, **kwargs)
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def to_clipboard(
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obj, excel: bool | None = True, sep: str | None = None, **kwargs
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) -> None: # pragma: no cover
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"""
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Attempt to write text representation of object to the system clipboard
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The clipboard can be then pasted into Excel for example.
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Parameters
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----------
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obj : the object to write to the clipboard
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excel : bool, defaults to True
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if True, use the provided separator, writing in a csv
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format for allowing easy pasting into excel.
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if False, write a string representation of the object
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to the clipboard
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sep : optional, defaults to tab
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other keywords are passed to to_csv
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Notes
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-----
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Requirements for your platform
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- Linux: xclip, or xsel (with PyQt4 modules)
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- Windows:
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- OS X:
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"""
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encoding = kwargs.pop("encoding", "utf-8")
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# testing if an invalid encoding is passed to clipboard
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if encoding is not None and encoding.lower().replace("-", "") != "utf8":
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raise ValueError("clipboard only supports utf-8 encoding")
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from pandas.io.clipboard import clipboard_set
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if excel is None:
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excel = True
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if excel:
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try:
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if sep is None:
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sep = "\t"
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buf = StringIO()
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# clipboard_set (pyperclip) expects unicode
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obj.to_csv(buf, sep=sep, encoding="utf-8", **kwargs)
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text = buf.getvalue()
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clipboard_set(text)
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return
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except TypeError:
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warnings.warn(
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"to_clipboard in excel mode requires a single character separator.",
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stacklevel=find_stack_level(),
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)
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elif sep is not None:
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warnings.warn(
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"to_clipboard with excel=False ignores the sep argument.",
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stacklevel=find_stack_level(),
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)
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if isinstance(obj, ABCDataFrame):
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# str(df) has various unhelpful defaults, like truncation
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with option_context("display.max_colwidth", None):
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objstr = obj.to_string(**kwargs)
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else:
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objstr = str(obj)
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clipboard_set(objstr)
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