Best Python code snippet using selene_python
dataset.py
Source:dataset.py
1from .models import DrugsApproved2from django.db.models.functions import ExtractYear3from django.db.models import Count, Max, Min4from django.db.models.query import EmptyQuerySet5from copy import deepcopy6class DrugDataset(object):7 """generate dataset for creating echarts"""8 MAX_KEYWORD_NUM = 39 TOO_LARGE_QSET = 5000010 EXCEPT_KEYWORDS = ['å½è¯ååZ2','å½è¯ååH2','å½è¯ååS2','æéå
¬å¸','199','200','201', '02', '03', '04']11 colnames = ['drug_name_zh', 'production_unit__production_unit_name', 'drug_name_en', 'drug_approval_num']12 view_colnames = ['drug_index', 'drug_approval_num', 'drug_name_zh', 'drug_name_en', 'drug_form','drug_spec', 'production_unit__production_unit_name','production_unit__province', 'approval_date']13 date_columns = ['approval_date']14 one_ending = '_one'15 many_ending = '_many'16 charts_by_column = {17 'default':['approval_date', 'production_unit__province'],18 'drug_name_zh'+one_ending:['approval_date', 'production_unit__province'],19 'drug_name_zh'+many_ending:['approval_date', 'production_unit__province', 'drug_form'],20 # 'drug_name_zh'+one_ending:['drug_spec', 'production_unit__production_unit_name', 'approval_date'],21 # 'drug_name_zh'+many_ending:['drug_name_zh', 'category', 'drug_spec', 'production_unit__production_unit_name', 'approval_date'],22 'production_unit__production_unit_name'+one_ending:['approval_date','drug_form'],23 'production_unit__production_unit_name'+many_ending:['approval_date', 'drug_form', 'production_unit__province'],24 'drug_approval_num'+one_ending:['approval_date','drug_form'],25 'drug_approval_num'+many_ending:['approval_date', 'drug_form', 'production_unit__production_unit_name'],26 'drug_name_en'+one_ending:['approval_date','drug_form'],27 'drug_name_en'+many_ending:['approval_date', 'drug_form', 'production_unit__province'],28 }29 chartbyids = {30 'drug_name_zh':'æè¯åå称',31 'drug_form':'æåå',32 'drug_spec':'æè§æ ¼',33 'production_unit__production_unit_name':'æä¼ä¸å称',34 'production_unit__province':'æç份',35 'approval_date':'ææ¹å年份',36 }37 x = 'axisX'38 y = 'axisY'39 is_by_and = True40 default_qsets = {}41 model = DrugsApproved42 querys_dict = {}43 def __init__(self):44 super(DrugDataset, self).__init__()45 def _parse_keyword(self, keyword, splitchars=[' ', '+', ',', 'ï¼']):46 # split keyword to a list47 keyword = keyword.strip()48 for c in splitchars:49 kwords = keyword.split(c)50 if len(kwords) > 1: 51 if c in [',', 'ï¼']:52 self.is_by_and = False53 else:54 self.is_by_and = True55 break56 def except_word(kword):57 if kword == '': return False58 kword = kword.upper()59 for ewords in DrugDataset.EXCEPT_KEYWORDS:60 if kword in ewords:61 return False62 return True63 #drop the space char of list64 kwords = list(filter(except_word, kwords))65 return kwords or []66 def _get_query_columns(self, kwords):67 # find out the relative columns of kwords68 columns = []69 qwords = []70 for keyword in kwords:71 column = self._get_query_column_by_one(keyword)72 if column :73 columns.append(column)74 qwords.append(keyword)75 print('query kwords:{}, columns:{}'.format(qwords, columns))76 return qwords, columns77 def _get_query_column_by_one(self, keyword):78 # find out the first correct column of a keyword79 for col in self.colnames:80 obj = self.model.objects\81 .filter(**{col+'__icontains' : keyword})\82 .first()83 if obj: return col84 def _get_query_names_by_cols(self, objs, qwords, columns):85 # collect all the different column values of every qword by column86 querys_dict = {}87 cur_words = []88 for i in range(len(columns)):89 dnames = objs.values_list(columns[i], flat = True)90 dnames = list(set(dnames))91 dnames.sort()92 if qwords[i] in dnames:93 cur_words.append(qwords[i])94 j = dnames.index(qwords[i])95 dnames[i], dnames[j] = dnames[j], dnames[i]96 else:97 cur_words.append(dnames[0])98 querys = {'kwords' : dnames, 'column': columns[i], 'active':''}99 # print('querys = {}'.format(querys))100 querys_dict[qwords[i]] = querys101 102 querys_dict = self._collect_same_column(querys_dict)103 return querys_dict, cur_words104 def _collect_same_column(self, querys_dict):105 # collect and group by the same column, space char join keys by same columns106 d = {}107 for k, v in querys_dict.items():108 col = v['column']109 if col in d.keys():110 d[col] = d[col] + ' ' + k111 else:112 d[col] = k113 dd = {}114 for col, keys in d.items():115 for value in querys_dict.values():116 if value['column'] == col:117 dd[keys] = value118 break119 return dd120 def _get_queryset_by_list(self, objs, kwords, columns, by_exact = True, by_and = True):121 # filter with all the kwords by columns from objs of db122 if len(kwords) != len(columns): return []123 if not by_exact:124 cols_methods = [col+'__icontains' for col in columns]125 else:126 cols_methods = [col+'__iexact' for col in columns]127 filter_kw = dict(zip(kwords, cols_methods))128 print('kwords = {}, columns = {}, kw={}'.format(kwords, columns, filter_kw))129 colset = set(filter_kw.values())130 return self._get_queryset_by_recursion(objs, filter_kw, colset, by_and = by_and)131 def _get_queryset_by_recursion(self, objs, filter_kw, colset, by_and = True):132 cur_col = colset.pop()133 qset = objs.none()134 for value, col in filter_kw.items():135 if col == cur_col: 136 print('col = {}, value = {}'.format(col, value))137 if isinstance(qset, EmptyQuerySet):138 qset = objs.filter(**{col: value})139 else:140 qs = objs.filter(**{col: value})141 # QuerySet & QuerySet one by one, intersection142 if by_and:143 qset = qset & qs144 else:145 qset = qset | qs146 # print('queryset by list len:{}'.format(len(qset)))147 # print('qset by list kwords:{} = {}, qset ={}'.format(col, value, qset))148 if len(colset) == 0:149 return qset150 else:151 return self._get_queryset_by_recursion(qset, filter_kw, colset, by_and = by_and)152 def _get_queryset_by_one(self, objs, name, column, is_exact = False):153 # filter withe one kword by column from objs of db154 if is_exact:155 qset = objs.filter(**{column+'__iexact': name})156 else:157 qset = objs.filter(**{column+'__icontains': name})158 print('queryset by one len:{}'.format(len(qset)))159 return qset160 def get_queryset(self, keyword, is_exact = False):161 # get queryset by keyword162 self.keyword = keyword163 kwords = self._parse_keyword(keyword)164 if kwords == []: return [], kwords, []165 qwords, columns = self._get_query_columns(kwords)166 if qwords == []: return [], kwords, []167 kn = len(qwords)168 if kn == 1:169 qset = self._get_queryset_by_one(self.model.objects, qwords[0], columns[0], is_exact = is_exact)170 elif kn > 1:171 qset = self._get_queryset_by_list(self.model.objects, qwords, columns, by_exact = is_exact, by_and = self.is_by_and)172 # print('qset = {}'.format(qset))173 return qset, qwords, columns174 def get_queryset_by_dict(self, **keys_cols):175 # get queryset by dict, to ready for request ajax176 kwords = list(keys_cols.keys())177 columns = list(keys_cols.values())178 qset = self._get_queryset_by_list(self.model.objects, kwords, columns, by_and = False)179 print('qset by dict len:', len(qset))180 return qset181 def get_datasets_by_dict(self, cur_keyword = '', **keys_cols):182 # get datasets by dict, to ready for request ajax183 if cur_keyword != '':184 qset = DrugDataset.default_qsets[cur_keyword]185 chartbycols = self.charts_by_column['default']186 kwords = []187 columns = []188 else:189 kwords = list(keys_cols.keys())190 columns = list(keys_cols.values())191 qset = self._get_queryset_by_list(self.model.objects, kwords, columns, by_and = False)192 if len(columns) > 1:193 chartbycols = self.charts_by_column[columns[0]+self.many_ending]194 else:195 chartbycols = self.charts_by_column[columns[0]+self.one_ending] 196 chartdatas = {}197 # get every chart by specified columns198 for chartbycol in chartbycols:199 # create a dict with zero values of every different chartbycol's key value200 print('chartbycol = ', chartbycol)201 chartdata = {}202 zdataset, new_col = self._init_dataset(qset, chartbycol)203 # count the item data of chartbycol filted by each filter_col and key204 if len(keys_cols) == 0:205 data = self._get_data_count_by(chartbycol, qset, zdataset, new_col)206 chartdata['Catgory with All Results'] = data207 else:208 for key, filter_col in keys_cols.items():209 print('*'*100)210 data = self._get_data_count_by(chartbycol, qset, zdataset, new_col, filter_by_col = filter_col, filter_keyword = key)211 chartdata[key] = data212 chartdatas[self.chartbyids[chartbycol]] = chartdata213 # self._save_dataset_to_db(qset, '', datasets)214 return chartdatas, kwords, columns215 # def _get_dataset_from_cache(self, keyword):216 # return [], [], [], [], ''217 def get_query_names(self, keyword, is_exact = False):218 # get query names219 qset, qwords, columns = self.get_queryset(keyword, is_exact)220 print('qset type:{}'.format(type(qset)))221 if len(qset) == 0: return {}, keyword, []222 if len(qset) > DrugDataset.TOO_LARGE_QSET: return {}, keyword, DrugDataset.TOO_LARGE_QSET223 DrugDataset.default_qsets[self.keyword] = qset224 querys_dict, cur_words = self._get_query_names_by_cols(qset, qwords, columns)225 return querys_dict, cur_words, qset226 def _get_data_count_by(self, count_by_col, qset, zdataset, new_col, filter_by_col = None, filter_keyword = None ):227 # count a column by group by itself228 if filter_by_col:229 qset = qset.filter(**{filter_by_col+'__iexact': filter_keyword})230 if count_by_col in self.date_columns:231 # print('-----------annotate date by year-------------')232 qset = qset.annotate(**{new_col : ExtractYear(count_by_col)}).values(new_col)233 data_count = qset.values(new_col).annotate(**{self.y : Count(new_col)}).values(new_col, self.y).order_by(new_col)234 print('data_count = {}'.format(data_count))235 #union the result dataset with zdataset236 zdataset = deepcopy(zdataset)237 # print('zdataset = {}'.format(zdataset))238 for d in zdataset:239 for cy in data_count:240 if d[new_col] == cy[new_col]: d[self.y] = cy[self.y]241 data_count = [tuple(d.values()) for d in zdataset]242 print('data_count tuple = {}'.format(data_count))243 return data_count or []244 def _init_dataset(self, qset, col):245 # init zero dataset246 if col in self.date_columns:247 qset = qset.annotate(**{self.x : ExtractYear(col)})248 col = self.x249 dset = qset.values_list(col, flat = True).order_by(col)250 dset = list(set(dset))251 dset.sort()252 # print('dset = {}'.format(dset))253 return [{col : i, self.y : 0 } for i in dset], col254 def _save_dataset_to_db(self, qset, query_dict, datasets):...
condition.py
Source:condition.py
...5E = TypeVar('E')6R = TypeVar('R')7class Condition(Callable[[E], None]):8 @classmethod9 def by_and(cls, *conditions):10 def fn(entity):11 for condition in conditions:12 condition.call(entity)13 return cls(' and '.join(map(str, conditions)), fn)14 @classmethod15 def by_or(cls, *conditions):16 def fn(entity):17 errors: List[Exception] = []18 for condition in conditions:19 try:20 condition.call(entity)21 return22 except Exception as e:23 errors.append(e)24 raise AssertionError('; '.join(map(str, errors)))25 return cls(' or '.join(map(str, conditions)), fn)26 @classmethod27 def as_not(28 cls, condition: Condition[E], description: str = None29 ) -> Condition[E]:30 condition_words = str(condition).split(' ')31 is_or_have = condition_words[0]32 name = ' '.join(condition_words[1:])33 no_or_not = 'not' if is_or_have == 'is' else 'no'34 new_description = description or f'{is_or_have} {no_or_not} {name}'35 def fn(entity):36 try:37 condition.call(entity)38 except Exception:39 return40 raise ConditionNotMatchedError()41 return cls(new_description, fn)42 @classmethod43 def raise_if_not(44 cls, description: str, predicate: Predicate[E]45 ) -> Condition[E]:46 def fn(entity: E) -> None:47 if not predicate(entity):48 raise ConditionNotMatchedError()49 return cls(description, fn)50 @classmethod51 def raise_if_not_actual(52 cls, description: str, query: Lambda[E, R], predicate: Predicate[R]53 ) -> Condition[E]:54 def fn(entity: E) -> None:55 query_to_str = str(query)56 result = (57 query.__name__58 if query_to_str.startswith('<function')59 else query_to_str60 )61 actual = query(entity)62 if not predicate(actual):63 raise AssertionError(f'actual {result}: {actual}')64 return cls(description, fn)65 def __init__(self, description: str, fn: Lambda[E, None]):66 self._description = description67 self._fn = fn68 def call(self, entity: E) -> None:69 self._fn(entity)70 @property71 def predicate(self) -> Lambda[E, bool]:72 def fn(entity):73 try:74 self.call(entity)75 return True76 except Exception as e:77 return False78 return fn79 @property80 def not_(self) -> Condition[E]:81 return self.__class__.as_not(self)82 def __call__(self, *args, **kwargs):83 return self._fn(*args, **kwargs)84 def __str__(self):85 return self._description86 def and_(self, condition: Condition[E]) -> Condition[E]:87 return Condition.by_and(self, condition)88 def or_(self, condition: Condition[E]) -> Condition[E]:89 return Condition.by_or(self, condition)90def not_(condition_to_be_inverted: Condition):...
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