Tabulator包中的tblless包装了unix column命令，并且还对数值列进行对齐。

在python中有一个简短的命令行脚本:https://github.com/rgrp/csv2ascii/blob/master/csv2ascii.py

只需下载并放置在您的路径。用法就像

csv2ascii.py [options] csv-file-path

转换csv文件在csv-file-path到ascii形式返回的结果 stdout。如果csv-file-path = '-'则从stdin读取。

选项:

  -h, --help            show this help message and exit
  -w WIDTH, --width=WIDTH
                        Width of ascii output
  -c COLUMNS, --columns=COLUMNS
                        Only display this number of columns

Tabview:轻量级的python curses命令行CSV文件查看器(以及其他表格式python数据，如列表中的列表)在Github上

特点:

Python 2.7+, 3.x Unicode support Spreadsheet-like view for easily visualizing tabular data Vim-like navigation (h,j,k,l, g(top), G(bottom), 12G goto line 12, m - mark, ' - goto mark, etc.) Toggle persistent header row Dynamically resize column widths and gap Sort ascending or descending by any column. 'Natural' order sort for numeric values. Full-text search, n and p to cycle between search results 'Enter' to view the full cell contents Yank cell contents to clipboard F1 or ? for keybindings Can also use from python command line to visualize any tabular data (e.g. list-of-lists)

看看csvkit。它提供了一组遵循UNIX哲学的工具(这意味着它们很小、简单、用途单一，并且可以组合使用)。

下面是一个例子，它从免费的Maxmind世界城市数据库中提取了德国人口最多的十个城市，并以控制台可读的格式显示结果:

$ csvgrep -e iso-8859-1 -c 1 -m "de" worldcitiespop | csvgrep -c 5 -r "\d+" 
  | csvsort -r -c 5 -l | csvcut -c 1,2,4,6 | head -n 11 | csvlook
-----------------------------------------------------
|  line_number | Country | AccentCity | Population  |
-----------------------------------------------------
|  1           | de      | Berlin     | 3398362     |
|  2           | de      | Hamburg    | 1733846     |
|  3           | de      | Munich     | 1246133     |
|  4           | de      | Cologne    | 968823      |
|  5           | de      | Frankfurt  | 648034      |
|  6           | de      | Dortmund   | 594255      |
|  7           | de      | Stuttgart  | 591688      |
|  8           | de      | Düsseldorf | 577139      |
|  9           | de      | Essen      | 576914      |
|  10          | de      | Bremen     | 546429      |
-----------------------------------------------------

Csvkit是平台独立的，因为它是用Python编写的。

我写了这个csv_view.sh来从命令行格式化csv，这读取整个文件来找出每列的最佳宽度(需要perl，假设字段中没有逗号，也使用较少):

#!/bin/bash

perl -we '
  sub max( @ ) {
    my $max = shift;

    map { $max = $_ if $_ > $max } @_;
    return $max;
  }

  sub transpose( @ ) {
    my @matrix = @_;
    my $width  = scalar @{ $matrix[ 0 ] };
    my $height = scalar @matrix;

    return map { my $x = $_; [ map { $matrix[ $_ ][ $x ] } 0 .. $height - 1 ] } 0 .. $width - 1;
  }

  # Read all lines, as arrays of fields
  my @lines = map { s/\r?\n$//; [ split /,/ ] } ;

  my $widths =
    # Build a pack expression based on column lengths
    join "",

    # For each column get the longest length plus 1
    map { 'A' . ( 1 + max map { length } @$_ ) }

    # Get arrays of columns
    transpose

    @lines
  ;

  # Format all lines with pack
  map { print pack( $widths, @$_ ) . "\n" } @lines;
' $1 | less -NS

我为这些(和其他)目的创建了一个表。安装与

pip install tablign

and

$ cat test.csv
Header1,Header2,Header3
Pizza,Artichoke dip,Bob's Special of the Day
BLT,Ham on rye with the works,

$ tablign test.csv
Header1 , Header2                   , Header3
Pizza   , Artichoke dip             , Bob's Special of the Day
BLT     , Ham on rye with the works ,

如果数据由逗号以外的其他东西分隔，也适用。最重要的是，它保留了分隔符，因此您还可以使用它来设置ASCII表的样式，而不牺牲[Markdown,CSV,LaTeX]语法。