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| 1 | +#!/usr/bin/env python3 |
| 2 | +"""An example of using Rich Tables within a cmd2 application for displaying tabular data. |
| 3 | +
|
| 4 | +While you can use any Python library for displaying tabular data within a cmd2 application, |
| 5 | +we recommend using rich since that is built into cmd2. |
| 6 | +
|
| 7 | +Data comes from World Population Review: https://worldpopulationreview.com/ |
| 8 | +and https://en.wikipedia.org/wiki/List_of_countries_by_GDP_(nominal) |
| 9 | +""" |
| 10 | + |
| 11 | +from rich.table import Table |
| 12 | + |
| 13 | +import cmd2 |
| 14 | +from cmd2.colors import Color |
| 15 | + |
| 16 | +CITY_HEADERS = ['Flag', 'City', 'Country', '2025 Population'] |
| 17 | +CITY_DATA = [ |
| 18 | + ["🇯🇵", "Tokyo (東京)", "Japan", 37_036_200], |
| 19 | + ["🇮🇳", "Delhi", "India", 34_665_600], |
| 20 | + ["🇨🇳", "Shanghai (上海)", "China", 30_482_100], |
| 21 | + ["🇧🇩", "Dhaka", "Bangladesh", 24_652_900], |
| 22 | + ["🇪🇬", "Cairo (القاهرة)", "Egypt", 23_074_200], |
| 23 | + ["🇪🇬", "São Paulo", "Brazil", 22_990_000], |
| 24 | + ["🇲🇽", "Mexico City", "Mexico", 22_752_400], |
| 25 | + ["🇨🇳", "Beijing (北京)", "China", 22_596_500], |
| 26 | + ["🇮🇳", "Mumbai", "India", 22_089_000], |
| 27 | + ["🇯🇵", "Osaka (大阪)", "Japan", 18_921_600], |
| 28 | +] |
| 29 | +CITY_TITLE = "10 Largest Cities by Population 2025" |
| 30 | +CITY_CAPTION = "Data from https://worldpopulationreview.com/" |
| 31 | + |
| 32 | +COUNTRY_HEADERS = [ |
| 33 | + 'Flag', |
| 34 | + 'Country', |
| 35 | + '2025 Population', |
| 36 | + 'Area (M km^2)', |
| 37 | + 'Population Density (/km^2)', |
| 38 | + 'GDP (million US$)', |
| 39 | + 'GDP per capita (US$)', |
| 40 | +] |
| 41 | +COUNTRY_DATA = [ |
| 42 | + ["🇮🇳", "India", 1_463_870_000, 3.3, 492, 4_187_017, 2_878], |
| 43 | + ["🇨🇳", "China (中国)", 1_416_100_000, 9.7, 150, 19_231_705, 13_687], |
| 44 | + ["🇺🇸", "United States", 347_276_000, 9.4, 38, 30_507_217, 89_105], |
| 45 | + ["🇮🇩", "Indonesia", 285_721_000, 1.9, 152, 1_429_743, 5_027], |
| 46 | + ["🇵🇰", "Pakistan", 255_220_000, 0.9, 331, 373_072, 1_484], |
| 47 | + ["🇳🇬", "Nigeria", 237_528_000, 0.9, 261, 188_271, 807], |
| 48 | + ["🇧🇷", "Brazil", 212_812_000, 8.5, 25, 2_125_958, 9_964], |
| 49 | + ["🇧🇩", "Bangladesh", 175_687_000, 0.1, 1_350, 467_218, 2_689], |
| 50 | + ["🇷🇺", "Russia (россия)", 143_997_000, 17.1, 9, 2_076_396, 14_258], |
| 51 | + ["🇪🇹", "Ethiopia (እትዮጵያ)", 135_472_000, 1.1, 120, 117_457, 1_066], |
| 52 | +] |
| 53 | +COUNTRY_TITLE = "10 Largest Countries by Population 2025" |
| 54 | +COUNTRY_CAPTION = "Data from https://worldpopulationreview.com/ and Wikipedia" |
| 55 | + |
| 56 | + |
| 57 | +class TableApp(cmd2.Cmd): |
| 58 | + """Cmd2 application to demonstrate displaying tabular data using rich.""" |
| 59 | + |
| 60 | + TABLE_CATEGORY = 'Table Commands' |
| 61 | + |
| 62 | + def __init__(self) -> None: |
| 63 | + """Initialize the cmd2 application.""" |
| 64 | + super().__init__() |
| 65 | + |
| 66 | + # Prints an intro banner once upon application startup |
| 67 | + self.intro = 'Are you curious which countries and cities on Earth have the largest populations?' |
| 68 | + |
| 69 | + # Set the default category name |
| 70 | + self.default_category = 'cmd2 Built-in Commands' |
| 71 | + |
| 72 | + @cmd2.with_category(TABLE_CATEGORY) |
| 73 | + def do_cities(self, _: cmd2.Statement) -> None: |
| 74 | + """Display the cities with the largest population.""" |
| 75 | + table = Table(title=CITY_TITLE, caption=CITY_CAPTION) |
| 76 | + |
| 77 | + for header in CITY_HEADERS: |
| 78 | + table.add_column(header) |
| 79 | + |
| 80 | + for row in CITY_DATA: |
| 81 | + # Convert integers or floats to strings, since rich tables can not render int/float |
| 82 | + str_row = [f"{item:,}" if isinstance(item, int) else str(item) for item in row] |
| 83 | + table.add_row(*str_row) |
| 84 | + |
| 85 | + self.poutput(table) |
| 86 | + |
| 87 | + @cmd2.with_category(TABLE_CATEGORY) |
| 88 | + def do_countries(self, _: cmd2.Statement) -> None: |
| 89 | + """Display the countries with the largest population.""" |
| 90 | + table = Table(title=COUNTRY_TITLE, caption=COUNTRY_CAPTION) |
| 91 | + |
| 92 | + for header in COUNTRY_HEADERS: |
| 93 | + justify = "right" |
| 94 | + header_style = None |
| 95 | + style = None |
| 96 | + match header: |
| 97 | + case population if "2025 Population" in population: |
| 98 | + header_style = Color.BRIGHT_BLUE |
| 99 | + style = Color.BLUE |
| 100 | + case density if "Density" in density: |
| 101 | + header_style = Color.BRIGHT_RED |
| 102 | + style = Color.RED |
| 103 | + case percap if "per capita" in percap: |
| 104 | + header_style = Color.BRIGHT_GREEN |
| 105 | + style = Color.GREEN |
| 106 | + case flag if 'Flag' in flag: |
| 107 | + justify = "center" |
| 108 | + case country if 'Country' in country: |
| 109 | + justify = "left" |
| 110 | + |
| 111 | + table.add_column(header, justify=justify, header_style=header_style, style=style) |
| 112 | + |
| 113 | + for row in COUNTRY_DATA: |
| 114 | + # Convert integers or floats to strings, since rich tables can not render int/float |
| 115 | + str_row = [f"{item:,}" if isinstance(item, int) else str(item) for item in row] |
| 116 | + table.add_row(*str_row) |
| 117 | + |
| 118 | + self.poutput(table) |
| 119 | + |
| 120 | + |
| 121 | +if __name__ == '__main__': |
| 122 | + app = TableApp() |
| 123 | + app.cmdloop() |
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