I have a list of dictionaries:
friends = [
{'name': 'Sam', 'gender': 'male', 'sport': 'Basketball'},
{'name': 'Emily', 'gender': 'female', 'sport': 'volleyball'},
]
I need to create functions query
, select
, and field_filter
to work with similar lists. These functions have to provide a possibility to select necessary columns and make filtering by these columns.
Example:
result = query(friends,
select('name', 'gender', 'sport'),
field_filter('sport', *('Basketball', 'volleyball')),
field_filter('gender', *('male',)))`
[{'gender': 'male', 'name': 'Sam', 'sport': 'Basketball'}]
I need to use predefined code:
from typing import Dict, Any, Callable, Iterable
DataType = Iterable[Dict[str, Any]]
ModifierFunc = Callable[[DataType], DataType]
def query(data: DataType, selector: ModifierFunc,
*filters: ModifierFunc) -> DataType:
"""Query data with column selection and filters
:param data: List of dictionaries with columns and values
:param selector: result of `select` function call
:param filters: Any number of results of `field_filter` function calls
:return: Filtered data"""
pass
def select(*columns: str) -> ModifierFunc:
"""Return function that selects only specific columns from dataset"""
pass
def field_filter(column: str, *values: Any) -> ModifierFunc:
"""Return function that filters specific column to be one of `values`"""
pass
CodePudding user response:
Although the question implies that select
and field_filter
might want to be classes, I don't think that's necessary here; I'd just make them return regular old tuples:
select = field_filter = lambda *args: args
and then query
is just a list and dict comprehension where you iterate over the list of dicts and return the select
ed fields from the dicts that match the field_filter
s:
def query(data, keys, *filters):
return [
{k: d[k] for k in keys}
for d in data
if all(d[k] in v for k, *v in filters)
]
friends = [
{'name': 'Sam', 'gender': 'male', 'sport': 'Basketball'},
{'name': 'Emily', 'gender': 'female', 'sport': 'volleyball'},
]
result = query(
friends,
select('name', 'gender', 'sport'),
field_filter('sport', *('Basketball', 'volleyball')),
field_filter('gender', *('male',))
)
print(result) # [{'name': 'Sam', 'gender': 'male', 'sport': 'Basketball'}]