Metadata-Version: 2.1
Name: pyfathom
Version: 0.0.1
Summary: Text comprehension library for Python
Home-page: https://github.com/jeremyorme/pyfathom
Author: Jeremy Orme
Author-email: me@jeremyorme.com
License: UNKNOWN
Description: # pyfathom
        Text comprehension library for python
        
        ## Example
        Given a collection of input strings with varying syntax:
        ```
            '180g | 1 cup uncooked brown rice',
            '½ small butternut squash , cubed',
            '5½ tablespoons tahini (you can sub cashew butter)',
            'pecans 125g',
            'flat-leaf parsley a bunch, roughly chopped',
            'rocket 70g',
            'leftover marinade from the mushrooms',
            '15 oz (425 g) black beans, drained (reserve ¼ cup (60 ml) of the juice) and rinsed well',
            '1/4 teaspoon Garam Masala, for garnish',
            '2 tablespoons chopped cilantro, for garnish',
        ```
        and a set of "knowledge" rules defining what is known about the inputs, e.g.:
        ```
        /\d+/ is number
        number,/-|–/,number is range
        /tbsp/ is unit
        /cups?/ is unit
        range|number,unit,/of/? is amount
        amount,/\w+/+ is ,ingredient
        ```
        PyFathom attempts to label each part of the string with a type name:
        ```
            '<amount><number>180</number><unit>g</unit><amount>|<amount><number>1</number><unit>cup</unit></amount><ingredient>uncooked brown rice</ingredient>',
            '<amount><number>½</number></amount><ingredient>small butternut squash</ingredient>,<ingredient>cubed</ingredient>',
            '<amount><number>5½<number><unit>tablespoons</unit></amount><ingredient>tahini</ingredient>(<ingredient>you can sub cashew butter</ingredient>)',
            '<ingredient>pecans</ingredient><amount><number>125</number><unit>g</unit></amount>',
            '<ingredient>flat-leaf parsley a bunch</ingredient>,<ingredient>roughly chopped</ingredient>',
            '<ingredient>rocket</ingredient><amount><number>70</number><unit>g</unit></amount>',
            '<ingredient>leftover marinade from the mushrooms</ingredient>',
            '<amount><number>15<number><unit>oz</unit></amount>(<amount><number>425</number><unit>g</unit></amount>)<ingredient>black beans</ingredient>,<ingredient>drained</ingredient>(<ingredient>reserve</ingredient><amount><number>¼</number><unit>cup</unit></amount>(<amount><number>60<number><unit>ml</unit></amount>)<ingredient>of the juice</ingredient>)<ingredient>and rinsed well</ingredient>',
            '<amount><number>1/4</number><unit>teaspoon</unit></amount><ingredient>Garam Masala</ingredient>,<ingredient>for garnish</ingredient>',
            '<amount><number>2<number><unit>tablespoons</unit></amount><ingredient>chopped cilantro</ingredient>,<ingredient>for garnish</ingredient>',
        ```
        and can extract the parts of a particular type, e.g. ingredient:
        ```
            'uncooked brown rice',
            'small butternut squash',
            'tahini',
            'pecans',
            'flat-leaf parsley a bunch',
            'rocket',
            'leftover marinade from the mushrooms',
            'black beans',
            'Garam Masala',
            'chopped cilantro',
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
