j q u e
Query JSON in memory as though it were a Mongo database
Installation
pip3 install jqueUsage
import jquejque accepts a variety of inputs to the constructor.
Pass a list of dicts:
data = jque.jque([
{ "name": "john" },
{ "name": "paul" },
{ "name": "george" },
{ "name": "ringo" }
])Pass a JSON filename:
DATAFILE = "~/my/big/data.json"
data = jque.jque(DATAFILE)Now you can query this dataset using Mongo-like syntax:
>>> data.query({ "name": {"$neq": "paul"} })
[
{ "name": "john" },
{ "name": "george" },
{ "name": "ringo" }
]
Arguments to query:
| Arg | Description |
|---|---|
wrap (boolean : True) |
Whether to wrap the resultant dataset in a new jque object. This allows chaining, like jque.query(...).query(...), if you're the sort of person to do that. Pass False to get back a list instead. |
Another example!
data = jque.jque([{
"_id": "ABC",
"name": "Arthur Dent",
"age": 42,
"current_planet": "earth"
}, {
"_id": "DE2",
"name": "Penny Lane",
"age": 19,
"current_planet": "earth"
}, {
"_id": "123",
"name": "Ford Prefect",
"age": 240,
"current_planet": "Brontitall"
}])teenage_earthlings = data.query({
"current_planet": {"$eq": "earth"},
"age": { "$lte": 20, "$gte": 10 }
})Which returns:
[{
"_id": "DE2",
"name": "Penny Lane",
"age": 19,
"current_planet": "earth"
}]Use Python lambdas as a filter:
>>> libraries = jque.jque([
... {"name": "jque", "language": "Python"},
... {"name": "react", "language": "node"}
... ])
>>> list(libraries.query({
... 'language': lambda x: x[:2] == "Py"
... }))
[{"name": "jque", "language": "Python"}]
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