Python query.Q屬性代碼示例

# 需要導入模塊: from elasticsearch_dsl import query [as 別名]
# 或者: from elasticsearch_dsl.query import Q [as 別名]
def filter_permissions(self, search):
        """Filter given query based on permissions of the user in the request.

        :param search: ElasticSearch query object

        """
        user = self.request.user
        if user.is_superuser:
            return search
        if user.is_anonymous:
            user = get_anonymous_user()

        filters = [Q("match", users_with_permissions=user.pk)]
        filters.extend(
            [
                Q("match", groups_with_permissions=group.pk)
                for group in user.groups.all()
            ]
        )
        filters.append(Q("match", public_permission=True))

        # `minimum_should_match` is set to 1 by default
        return search.query("bool", should=filters) 

# 需要導入模塊: from elasticsearch_dsl import query [as 別名]
# 或者: from elasticsearch_dsl.query import Q [as 別名]
def bollinger_band(index='cf_etf_hist_price', start_date='2018-12-26', end_date='2019-03-25', symbol='rfem'):
    ESLowLevelClientByConnection.get_instance()
    search = Search(index=index, using='high_level_client')[0:0]
    search.query = Q(Bool(must=[Range(date={'gte': '2018-12-26', 'lte': '2019-03-25'}), Term(symbol='rfem')]))
    aggs = A(DateHistogram(field='date', interval='1d', format='yyyy-MM-dd', min_doc_count=1))
    aggs_tp = A(ScriptedMetric(init_script='state.totals=[]',
                map_script='state.totals.add((doc.high.value+doc.low.value+doc.close.value)/3)',
                combine_script='double total=0; for (t in state.totals) {total += t} return total',
                reduce_script='double total=0; for (t in states) {total += t} return total'))
    aggs_moving_avg = A(MovingAvg(model='simple', window=20, buckets_path='tp.value'))
    aggs_bbu = A(BucketScript(buckets_path={'SMA':'20_trading_days_moving_avg'}, script='params.SMA + 0.5'))
    aggs_bbl = A(BucketScript(buckets_path={'SMA': '20_trading_days_moving_avg'}, script='params.SMA - 0.5'))
    search.aggs.bucket('Bollinger_band', aggs).metric('tp', aggs_tp).pipeline(
        '20_trading_days_moving_avg', aggs_moving_avg).pipeline('BBU', aggs_bbu).pipeline('BBL', aggs_bbl)
    response = search.execute()
    print(response.to_dict()) 

# 需要導入模塊: from elasticsearch_dsl import query [as 別名]
# 或者: from elasticsearch_dsl.query import Q [as 別名]
def test_inverted_query_with_must_and_must_not():
    q = query.Q('bool',
        must=[query.Q('match', f=3), query.Q('match', f=4)],
        must_not=[query.Q('match', f=1), query.Q('match', f=2)]
    )
    print((~q).to_dict())
    assert ~q == query.Q('bool',
        should=[
            # negation of must
            query.Q('bool', must_not=[query.Q('match', f=3)]),
            query.Q('bool', must_not=[query.Q('match', f=4)]),

            # negation of must_not
            query.Q('match', f=1),
            query.Q('match', f=2),
        ]
    ) 

# 需要導入模塊: from elasticsearch_dsl import query [as 別名]
# 或者: from elasticsearch_dsl.query import Q [as 別名]
def test_function_score_to_dict():
    q = query.Q(
        'function_score',
        query=query.Q('match', title='python'),
        functions=[
            query.SF('random_score'),
            query.SF('field_value_factor', field='comment_count', filter=query.Q('term', tags='python'))
        ]
    )

    d = {
      'function_score': {
        'query': {'match': {'title': 'python'}},
        'functions': [
          {'random_score': {}},
          {
            'filter': {'term': {'tags': 'python'}},
            'field_value_factor': {
              'field': 'comment_count',
            }
          }
        ],
      }
    }
    assert d == q.to_dict() 

# 需要導入模塊: from elasticsearch_dsl import query [as 別名]
# 或者: from elasticsearch_dsl.query import Q [as 別名]
def apply(self, search, field, value):
        """Apply lookup expression to search query."""
        if not isinstance(value, list):
            value = [x for x in value.strip().split(",") if x]

        filters = [Q("match", **{field: item}) for item in value]
        return search.query("bool", should=filters) 

# 需要導入模塊: from elasticsearch_dsl import query [as 別名]
# 或者: from elasticsearch_dsl.query import Q [as 別名]
def default_value_when_missing_filter(field, missing_val):
    """Create a custom exists filter.

    :param field: Field name.
    :missing_val
    :returns: Function that returns the Terms query.
    """
    def inner(values):
        if missing_val in values:
            return Bool(**{'must_not': {'exists': {'field': field}}})
        else:
            return Q('terms', **{field: values})

    return inner 

# 需要導入模塊: from elasticsearch_dsl import query [as 別名]
# 或者: from elasticsearch_dsl.query import Q [as 別名]
def overdue_loans_filter(field):
    """Create a custom filter for ongoing loans.

    :param field: Field to filter.
    :param range_query: Dictionary with available keys and their range options.
    """
    def inner(values):
        range_query = {
            "Overdue": {"lt": str(arrow.utcnow().date())},
            "Upcoming return": {
                "lte": str(
                    current_app.config["CIRCULATION_POLICIES"][
                        "upcoming_return_range"]().date()),
                "gte": str(arrow.utcnow().date())}
        }

        args = {}
        for range_key, mappings in range_query.items():
            if range_key in values:
                for key, value in mappings.items():
                    args[key] = value

        return Range(**{field: args}) & Q('terms', **{
            'state': current_app.config["CIRCULATION_STATES_LOAN_ACTIVE"]})

    return inner 

# 需要導入模塊: from elasticsearch_dsl import query [as 別名]
# 或者: from elasticsearch_dsl.query import Q [as 別名]
def test_match_phrase_query_via_connection(self):
        ESLowLevelClientByConnection.get_instance()
        search = Search(index='cf_etf', using='high_level_client')
        # call the Q method
        search.query = Q('match_phrase', fund_name='iShares MSCI ACWI ETF')
        response = search.execute()
        self.assertEqual(response['hits']['total']['value'], 1) 

# 需要導入模塊: from elasticsearch_dsl import query [as 別名]
# 或者: from elasticsearch_dsl.query import Q [as 別名]
def test_filter_can_be_instantiated_using_positional_args():
    a = aggs.Filter(query.Q('term', f=42))

    assert {
        'filter': {
            'term': {'f': 42}
        }
    } == a.to_dict()

    assert a == aggs.A('filter', query.Q('term', f=42)) 

# 需要導入模塊: from elasticsearch_dsl import query [as 別名]
# 或者: from elasticsearch_dsl.query import Q [as 別名]
def test_filter_aggregation_as_nested_agg():
    a = aggs.Terms(field='tags')
    a.bucket('filtered', 'filter', query.Q('term', f=42))

    assert {
        'terms': {'field': 'tags'},
        'aggs': {
            'filtered': {
                'filter': {
                    'term': {'f': 42}
                },
            }
        }
    } == a.to_dict() 

# 需要導入模塊: from elasticsearch_dsl import query [as 別名]
# 或者: from elasticsearch_dsl.query import Q [as 別名]
def test_filter_aggregation_with_nested_aggs():
    a = aggs.Filter(query.Q('term', f=42))
    a.bucket('testing', 'terms', field='tags')

    assert {
        'filter': {
            'term': {'f': 42}
        },
        'aggs': {
            'testing': {'terms': {'field': 'tags'}}
        }
    } == a.to_dict() 

# 需要導入模塊: from elasticsearch_dsl import query [as 別名]
# 或者: from elasticsearch_dsl.query import Q [as 別名]
def test_filters_correctly_identifies_the_hash():
    a = aggs.A('filters', filters={'group_a': {'term': {'group': 'a'}}, 'group_b': {'term': {'group': 'b'}}})

    assert {
        'filters': {
            'filters': {
                'group_a': {'term': {'group': 'a'}},
                'group_b': {'term': {'group': 'b'}}
            }
        }
    } == a.to_dict()
    assert a.filters.group_a == query.Q('term', group='a') 

# 需要導入模塊: from elasticsearch_dsl import query [as 別名]
# 或者: from elasticsearch_dsl.query import Q [as 別名]
def test_empty_Q_is_match_all():
    q = query.Q()

    assert isinstance(q, query.MatchAll)
    assert query.MatchAll() == q 

# 需要導入模塊: from elasticsearch_dsl import query [as 別名]
# 或者: from elasticsearch_dsl.query import Q [as 別名]
def test_bool_and_other_sets_min_should_match_if_needed():
    q1 = query.Q('term', category=1)
    q2 = query.Q('bool', should=[
        query.Q('term', name='aaa'),
        query.Q('term', name='bbb')]
    )

    q = q1 & q2
    assert q == query.Bool(
        must=[q1],
        should=[query.Q('term', name='aaa'), query.Q('term', name='bbb')],
        minimum_should_match=1
    ) 

# 需要導入模塊: from elasticsearch_dsl import query [as 別名]
# 或者: from elasticsearch_dsl.query import Q [as 別名]
def test_bool_with_different_minimum_should_match_should_not_be_combined():
    q1 = query.Q('bool', minimum_should_match=2, should=[query.Q('term', field='aa1'), query.Q('term', field='aa2'), query.Q('term', field='aa3'), query.Q('term', field='aa4')])
    q2 = query.Q('bool', minimum_should_match=3, should=[query.Q('term', field='bb1'), query.Q('term', field='bb2'), query.Q('term', field='bb3'), query.Q('term', field='bb4')])
    q3 = query.Q('bool', minimum_should_match=4, should=[query.Q('term', field='cc1'), query.Q('term', field='cc2'), query.Q('term', field='cc3'), query.Q('term', field='cc4')])

    q4 = q1 | q2
    assert q4 == query.Bool(
        should=[q1, q2]
    )

    q5 = q1 | q2 | q3
    assert q5 == query.Bool(
        should=[q1, q2, q3]
    )