chrislit /
abydos
| Conditions | 15 |
| Total Lines | 53 |
| Code Lines | 20 |
| Lines | 0 |
| Ratio | 0 % |
| Tests | 16 |
| CRAP Score | 15 |
| Changes | 0 | ||
Small methods make your code easier to understand, in particular if combined with a good name. Besides, if your method is small, finding a good name is usually much easier.
For example, if you find yourself adding comments to a method's body, this is usually a good sign to extract the commented part to a new method, and use the comment as a starting point when coming up with a good name for this new method.
Commonly applied refactorings include:
If many parameters/temporary variables are present:
Complex classes like abydos.stemmer._clef_german_plus.CLEFGermanPlus.stem() often do a lot of different things. To break such a class down, we need to identify a cohesive component within that class. A common approach to find such a component is to look for fields/methods that share the same prefixes, or suffixes.
Once you have determined the fields that belong together, you can apply the Extract Class refactoring. If the component makes sense as a sub-class, Extract Subclass is also a candidate, and is often faster.
| 1 | # -*- coding: utf-8 -*- |
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| 52 | 1 | def stem(self, word): |
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| 53 | """Return 'CLEF German stemmer plus' stem. |
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| 54 | |||
| 55 | Parameters |
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| 56 | ---------- |
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| 57 | word : str |
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| 58 | The word to stem |
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| 59 | |||
| 60 | Returns |
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| 61 | ------- |
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| 62 | str |
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| 63 | Word stem |
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| 64 | |||
| 65 | Examples |
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| 66 | -------- |
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| 67 | >>> stmr = CLEFGermanPlus() |
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| 68 | >>> clef_german_plus('lesen') |
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| 69 | 'les' |
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| 70 | >>> clef_german_plus('graues') |
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| 71 | 'grau' |
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| 72 | >>> clef_german_plus('buchstabieren') |
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| 73 | 'buchstabi' |
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| 74 | |||
| 75 | """ |
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| 76 | # lowercase, normalize, and compose |
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| 77 | 1 | word = normalize('NFC', text_type(word.lower())) |
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| 78 | |||
| 79 | # remove umlauts |
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| 80 | 1 | word = word.translate(self._accents) |
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| 81 | |||
| 82 | # Step 1 |
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| 83 | 1 | wlen = len(word) - 1 |
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| 84 | 1 | if wlen > 4 and word[-3:] == 'ern': |
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| 85 | 1 | word = word[:-3] |
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| 86 | 1 | elif wlen > 3 and word[-2:] in {'em', 'en', 'er', 'es'}: |
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| 87 | 1 | word = word[:-2] |
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| 88 | 1 | elif wlen > 2 and ( |
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| 89 | word[-1] == 'e' |
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| 90 | or (word[-1] == 's' and word[-2] in self._st_ending) |
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| 91 | ): |
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| 92 | 1 | word = word[:-1] |
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| 93 | |||
| 94 | # Step 2 |
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| 95 | 1 | wlen = len(word) - 1 |
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| 96 | 1 | if wlen > 4 and word[-3:] == 'est': |
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| 97 | 1 | word = word[:-3] |
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| 98 | 1 | elif wlen > 3 and ( |
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| 99 | word[-2:] in {'er', 'en'} |
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| 100 | or (word[-2:] == 'st' and word[-3] in self._st_ending) |
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| 101 | ): |
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| 102 | 1 | word = word[:-2] |
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| 103 | |||
| 104 | 1 | return word |
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| 105 | |||
| 140 |
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