202 lines
6.5 KiB
Python
202 lines
6.5 KiB
Python
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"""
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Module for formatting output data in console (to string).
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"""
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from shutil import get_terminal_size
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from typing import Iterable, List, Optional
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import numpy as np
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from pandas.io.formats.format import DataFrameFormatter
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from pandas.io.formats.printing import pprint_thing
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class StringFormatter:
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"""Formatter for string representation of a dataframe."""
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def __init__(self, fmt: DataFrameFormatter, line_width: Optional[int] = None):
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self.fmt = fmt
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self.adj = fmt.adj
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self.frame = fmt.frame
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self.line_width = line_width
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def to_string(self) -> str:
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text = self._get_string_representation()
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if self.fmt.should_show_dimensions:
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text = "".join([text, self.fmt.dimensions_info])
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return text
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def _get_strcols(self) -> List[List[str]]:
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strcols = self.fmt.get_strcols()
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if self.fmt.is_truncated:
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strcols = self._insert_dot_separators(strcols)
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return strcols
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def _get_string_representation(self) -> str:
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if self.fmt.frame.empty:
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return self._empty_info_line
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strcols = self._get_strcols()
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if self.line_width is None:
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# no need to wrap around just print the whole frame
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return self.adj.adjoin(1, *strcols)
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if self._need_to_wrap_around:
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return self._join_multiline(strcols)
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return self._fit_strcols_to_terminal_width(strcols)
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@property
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def _empty_info_line(self) -> str:
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return (
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f"Empty {type(self.frame).__name__}\n"
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f"Columns: {pprint_thing(self.frame.columns)}\n"
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f"Index: {pprint_thing(self.frame.index)}"
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)
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@property
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def _need_to_wrap_around(self) -> bool:
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return bool(self.fmt.max_cols is None or self.fmt.max_cols > 0)
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def _insert_dot_separators(self, strcols: List[List[str]]) -> List[List[str]]:
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str_index = self.fmt._get_formatted_index(self.fmt.tr_frame)
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index_length = len(str_index)
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if self.fmt.is_truncated_horizontally:
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strcols = self._insert_dot_separator_horizontal(strcols, index_length)
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if self.fmt.is_truncated_vertically:
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strcols = self._insert_dot_separator_vertical(strcols, index_length)
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return strcols
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def _insert_dot_separator_horizontal(
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self, strcols: List[List[str]], index_length: int
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) -> List[List[str]]:
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strcols.insert(self.fmt.tr_col_num + 1, [" ..."] * index_length)
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return strcols
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def _insert_dot_separator_vertical(
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self, strcols: List[List[str]], index_length: int
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) -> List[List[str]]:
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n_header_rows = index_length - len(self.fmt.tr_frame)
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row_num = self.fmt.tr_row_num
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for ix, col in enumerate(strcols):
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cwidth = self.adj.len(col[row_num])
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if self.fmt.is_truncated_horizontally:
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is_dot_col = ix == self.fmt.tr_col_num + 1
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else:
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is_dot_col = False
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if cwidth > 3 or is_dot_col:
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dots = "..."
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else:
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dots = ".."
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if ix == 0:
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dot_mode = "left"
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elif is_dot_col:
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cwidth = 4
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dot_mode = "right"
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else:
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dot_mode = "right"
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dot_str = self.adj.justify([dots], cwidth, mode=dot_mode)[0]
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col.insert(row_num + n_header_rows, dot_str)
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return strcols
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def _join_multiline(self, strcols_input: Iterable[List[str]]) -> str:
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lwidth = self.line_width
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adjoin_width = 1
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strcols = list(strcols_input)
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if self.fmt.index:
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idx = strcols.pop(0)
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lwidth -= np.array([self.adj.len(x) for x in idx]).max() + adjoin_width
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col_widths = [
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np.array([self.adj.len(x) for x in col]).max() if len(col) > 0 else 0
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for col in strcols
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]
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assert lwidth is not None
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col_bins = _binify(col_widths, lwidth)
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nbins = len(col_bins)
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if self.fmt.is_truncated_vertically:
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assert self.fmt.max_rows_fitted is not None
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nrows = self.fmt.max_rows_fitted + 1
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else:
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nrows = len(self.frame)
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str_lst = []
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start = 0
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for i, end in enumerate(col_bins):
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row = strcols[start:end]
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if self.fmt.index:
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row.insert(0, idx)
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if nbins > 1:
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if end <= len(strcols) and i < nbins - 1:
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row.append([" \\"] + [" "] * (nrows - 1))
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else:
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row.append([" "] * nrows)
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str_lst.append(self.adj.adjoin(adjoin_width, *row))
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start = end
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return "\n\n".join(str_lst)
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def _fit_strcols_to_terminal_width(self, strcols: List[List[str]]) -> str:
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from pandas import Series
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lines = self.adj.adjoin(1, *strcols).split("\n")
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max_len = Series(lines).str.len().max()
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# plus truncate dot col
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width, _ = get_terminal_size()
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dif = max_len - width
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# '+ 1' to avoid too wide repr (GH PR #17023)
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adj_dif = dif + 1
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col_lens = Series([Series(ele).apply(len).max() for ele in strcols])
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n_cols = len(col_lens)
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counter = 0
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while adj_dif > 0 and n_cols > 1:
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counter += 1
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mid = int(round(n_cols / 2.0))
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mid_ix = col_lens.index[mid]
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col_len = col_lens[mid_ix]
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# adjoin adds one
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adj_dif -= col_len + 1
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col_lens = col_lens.drop(mid_ix)
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n_cols = len(col_lens)
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# subtract index column
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max_cols_fitted = n_cols - self.fmt.index
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# GH-21180. Ensure that we print at least two.
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max_cols_fitted = max(max_cols_fitted, 2)
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self.fmt.max_cols_fitted = max_cols_fitted
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# Call again _truncate to cut frame appropriately
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# and then generate string representation
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self.fmt.truncate()
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strcols = self._get_strcols()
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return self.adj.adjoin(1, *strcols)
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def _binify(cols: List[int], line_width: int) -> List[int]:
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adjoin_width = 1
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bins = []
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curr_width = 0
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i_last_column = len(cols) - 1
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for i, w in enumerate(cols):
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w_adjoined = w + adjoin_width
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curr_width += w_adjoined
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if i_last_column == i:
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wrap = curr_width + 1 > line_width and i > 0
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else:
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wrap = curr_width + 2 > line_width and i > 0
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if wrap:
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bins.append(i)
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curr_width = w_adjoined
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bins.append(len(cols))
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return bins
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