def find(self, filter={}, fields=None, skip=0, limit=None, sort=None):
"""
@param:query(dict), specify the WHERE clause
{"name": "...", "id": ...}
@param: fields, specify what fields are needed
skip, limit: both integers, skip without defining limit is meaningless
@return a QuerySet object
"""
if not fields:
self.__ensure_columns()
fields = self.columns
query_obj = Query(source=self.name, filter=filter, fields=fields, skip=skip, limit=limit, sort=sort)
return QuerySet(cursor=self.cursor, query=query_obj)
def find(self, filter={}, fields=None, skip=0, limit=None, sort=None):
"""
Searches the table using the filters provided.
:Examples:
>>> users = user_table.find({'id': {'$in': [10, 20]}, 'age': {'$gt': 20}}) # Complex query
>>> user_count = len(users)
>>> for user in users:
>>> # Do something...
>>> print user.id
>>>
>>> users = user_table.find({}, sort=[('age', monsql.ASCENDING)]) # sort by age
Also support complex operators:
>>> {a: 1} # a == 1
>>> {a: {$gt: 1}} # a > 1
>>> {a: {$gte: 1}} # a >= 1
>>> {a: {$lt: 1}} # a < 1
>>> {a: {$lte: 1}} # a <= 1
>>> {a: {$eq: 1}} # a == 1
>>> {a: {$in: [1, 2]}} # a == 1 or a == 2
>>> {a: {$contains: '123'}} # a like %123%
>>> {$not: condition} # !(condition)
>>> {$and: [condition1, condition2, ...]} # condition1 and condition2
>>> {$or: [condition1, condition2, ...]} # condition1 or condition2
:Parameters:
- query(dict): specify the WHERE clause. One example is {"name": "...", "id": ...}
- fields: specify what fields are needed
- skip, limit: both integers, skip without defining limit is meaningless
- sort: A list, each element is a two-item tuple, with the first item be the column name
and the second item be either monsql.ASCENDING or monsql.DESCENDING
:Return: a QuerySet object
"""
if not fields:
self.__ensure_columns()
fields = self.columns
query_obj = Query(source=self.name,
filter=filter,
fields=fields,
skip=skip,
limit=limit,
sort=sort)
return QuerySet(cursor=self.cursor, query=query_obj)
def test_queryset():
lut = FunctionTrigger()
ledger1 = pd.DataFrame({"Key1": ["A1", "B1"], "Key2": ["A2", "B2"]})
ledger2 = pd.DataFrame({
"Key1": ["A1", "D1", "E1"],
"Key2": ["A2", "D2", "E2"]
})
cls1 = ConstantLedgerSource(ledger1)
cls2 = ConstantLedgerSource(ledger2)
led1 = Ledger(lut, cls1)
led2 = Ledger(lut, cls2)
lut.invoke()
qs = QuerySet([led1, led2],
pd.DataFrame({
"Source": ["S0", "S0"],
"Query": ["Q0", "Q2"]
}))
result_iterator = qs.join(3)
results = result_iterator.as_list()
target = pd.DataFrame({
"Key1": ["A1", "B1", "D1", "A1", "B1", "D1", "E1", "E1"],
"Key2": ["A2", "B2", "D2", "A2", "B2", "D2", "E2", "E2"],
"Source": ["S0"] * 8,
"Query": ["Q0", "Q2"] * 4
})
c = 0
for result in results:
row = target.loc[[c]]
query = Query(**row.to_dict(orient="index")[c])
assert query == result
c += 1
def get_query_set(self):
return QuerySet(model=self.model, db=self.db)
