chrislit /
abydos
| Conditions | 12 |
| Total Lines | 66 |
| Code Lines | 33 |
| Lines | 0 |
| Ratio | 0 % |
| Tests | 33 |
| CRAP Score | 12 |
| 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.distance._mra.MRA.dist_abs() 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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| 46 | 1 | def dist_abs(self, src, tar): |
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| 47 | """Return the MRA comparison rating of two strings. |
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| 48 | |||
| 49 | Parameters |
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| 50 | ---------- |
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| 51 | src : str |
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| 52 | Source string for comparison |
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| 53 | tar : str |
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| 54 | Target string for comparison |
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| 55 | |||
| 56 | Returns |
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| 57 | ------- |
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| 58 | int |
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| 59 | MRA comparison rating |
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| 60 | |||
| 61 | Examples |
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| 62 | -------- |
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| 63 | >>> cmp = MRA() |
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| 64 | >>> cmp.dist_abs('cat', 'hat') |
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| 65 | 5 |
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| 66 | >>> cmp.dist_abs('Niall', 'Neil') |
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| 67 | 6 |
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| 68 | >>> cmp.dist_abs('aluminum', 'Catalan') |
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| 69 | 0 |
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| 70 | >>> cmp.dist_abs('ATCG', 'TAGC') |
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| 71 | 5 |
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| 72 | |||
| 73 | """ |
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| 74 | 1 | if src == tar: |
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| 75 | 1 | return 6 |
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| 76 | 1 | if src == '' or tar == '': |
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| 77 | 1 | return 0 |
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| 78 | 1 | src = list(mra(src)) |
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| 79 | 1 | tar = list(mra(tar)) |
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| 80 | |||
| 81 | 1 | if abs(len(src) - len(tar)) > 2: |
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| 82 | 1 | return 0 |
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| 83 | |||
| 84 | 1 | length_sum = len(src) + len(tar) |
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| 85 | 1 | if length_sum < 5: |
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| 86 | 1 | min_rating = 5 |
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| 87 | 1 | elif length_sum < 8: |
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| 88 | 1 | min_rating = 4 |
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| 89 | 1 | elif length_sum < 12: |
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| 90 | 1 | min_rating = 3 |
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| 91 | else: |
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| 92 | 1 | min_rating = 2 |
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| 93 | |||
| 94 | 1 | for _ in range(2): |
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| 95 | 1 | new_src = [] |
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| 96 | 1 | new_tar = [] |
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| 97 | 1 | minlen = min(len(src), len(tar)) |
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| 98 | 1 | for i in range(minlen): |
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| 99 | 1 | if src[i] != tar[i]: |
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| 100 | 1 | new_src.append(src[i]) |
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| 101 | 1 | new_tar.append(tar[i]) |
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| 102 | 1 | src = new_src + src[minlen:] |
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| 103 | 1 | tar = new_tar + tar[minlen:] |
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| 104 | 1 | src.reverse() |
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| 105 | 1 | tar.reverse() |
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| 106 | |||
| 107 | 1 | similarity = 6 - max(len(src), len(tar)) |
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| 108 | |||
| 109 | 1 | if similarity >= min_rating: |
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| 110 | 1 | return similarity |
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| 111 | 1 | return 0 |
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| 112 | |||
| 247 |
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