Conditions | 16 |
Total Lines | 114 |
Lines | 0 |
Ratio | 0 % |
Tests | 1 |
CRAP Score | 255.6934 |
Changes | 4 | ||
Bugs | 0 | Features | 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 _generate_triggers() 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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42 | 1 | def _generate_triggers(osmalchemy, maxage=60*60*24): |
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43 | """ Generates the triggers for online functionality. |
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44 | |||
45 | osmalchemy - reference to the OSMAlchemy instance to be configured |
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46 | maxage - maximum age of objects before they are updated online, in seconds |
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47 | """ |
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48 | |||
49 | _visited_queries = WeakSet() |
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50 | |||
51 | @listens_for(Query, "before_compile") |
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52 | def _query_compiling(query): |
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53 | # Get the session associated with the query: |
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54 | session = query.session |
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55 | |||
56 | # Prevent recursion by skipping already-seen queries |
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57 | if query in _visited_queries: |
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58 | return |
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59 | else: |
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60 | _visited_queries.add(query) |
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61 | |||
62 | # Check whether this query affects our model |
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63 | affected_models = set([c["type"] for c in query.column_descriptions]) |
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64 | our_models = set([osmalchemy.Node, osmalchemy.Way, osmalchemy.Relation, |
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65 | osmalchemy.Element]) |
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66 | if affected_models.isdisjoint(our_models): |
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67 | # None of our models is affected |
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68 | return |
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69 | |||
70 | # Check whether this query filters elements |
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71 | # Online update will only run on a specified set, not all data |
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72 | if query.whereclause is None: |
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73 | # No filters |
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74 | return |
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75 | |||
76 | # Define operator to string mapping |
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77 | _ops = {operator.eq: "==", |
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78 | operator.ne: "!=", |
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79 | operator.lt: "<", |
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80 | operator.gt: ">", |
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81 | operator.le: "<=", |
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82 | operator.ge: ">=", |
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83 | operator.and_: "&&", |
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84 | operator.or_: "||"} |
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85 | |||
86 | # Traverse whereclause recursively |
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87 | def _analyse_clause(clause): |
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88 | if type(clause) is BinaryExpression: |
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89 | # This is something like "latitude >= 51.0" |
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90 | left = clause.left |
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91 | right = clause.right |
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92 | op = clause.operator |
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93 | |||
94 | # Left part should be a column |
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95 | if type(left) is AnnotatedColumn: |
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96 | # Get table class and field |
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97 | model = left._annotations["parentmapper"].class_ |
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98 | field = left |
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99 | |||
100 | # Double-check this model belongs to us |
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101 | if model in our_models: |
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102 | # Convert model class and field to string names |
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103 | left = (model.__name__, field.name) |
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104 | else: |
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105 | return None |
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106 | else: |
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107 | # Right now, we cannot cope with anything but a column on the left |
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108 | return None |
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109 | |||
110 | # Right part should be a literal value |
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111 | if type(right) is BindParameter: |
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112 | # Extract literal value |
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113 | right = right.value |
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114 | else: |
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115 | # Right now, we cannot cope with something else here |
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116 | return None |
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117 | |||
118 | # Look for a known operator |
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119 | if op in _ops.keys(): |
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120 | # Get string representation |
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121 | op = _ops[op] |
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122 | else: |
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123 | # Right now, we cannot cope with other operators |
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124 | return None |
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125 | |||
126 | # Return polish notation tuple of this clause |
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127 | return (op, left, right) |
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128 | elif type(clause) is BooleanClauseList: |
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129 | # This is an AND or OR operation |
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130 | op = clause.operator |
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131 | clauses = [] |
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132 | |||
133 | # Iterate over all the clauses in this operation |
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134 | for clause in clause.clauses: |
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135 | # Recursively analyse clauses |
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136 | res = _analyse_clause(clause) |
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137 | # None is returned for unsupported clauses or operations |
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138 | if res is not None: |
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139 | # Append polish notation result to clauses list |
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140 | clauses.append(res) |
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141 | |||
142 | # Look for a known operator |
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143 | if op in _ops.keys(): |
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144 | # Get string representation |
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145 | op = _ops[op] |
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146 | else: |
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147 | # Right now, we cannot cope with anything else |
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148 | return None |
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149 | |||
150 | # Return polish notation tuple of this clause |
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151 | return (op, clauses) |
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152 | else: |
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153 | # We hit an unsupported type of clause |
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154 | return None |
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155 | tree = _analyse_clause(query.whereclause) |
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156 |