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Merge pull request #1077 from redis/DOC-4345-python-home-json
DOC-4345 added testable JSON index/query examples for Python
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‎content/develop/clients/dotnet/queryjson.md

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description: Learn how to use the Redis query engine with JSON
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linkTitle: JSON query example
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linkTitle: Index and query JSON
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title: Example - Index and query JSON documents
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weight: 2
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---

‎content/develop/clients/go/queryjson.md

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description: Learn how to use the Redis query engine with JSON
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linkTitle: JSON query example
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linkTitle: Index and query JSON
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title: Example - Index and query JSON documents
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weight: 2
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‎content/develop/clients/jedis/queryjson.md

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description: Learn how to use the Redis query engine with JSON
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linkTitle: JSON query example
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linkTitle: Index and query JSON
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title: Example - Index and query JSON documents
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weight: 2
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‎content/develop/clients/php/queryjson.md

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description: Learn how to use the Redis query engine with JSON
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linkTitle: JSON query example
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linkTitle: Index and query JSON
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title: Example - Index and query JSON documents
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‎content/develop/clients/redis-py/queryjson.md

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description: Learn how to use the Redis query engine with JSON
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linkTitle: JSON query example
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linkTitle: Index and query JSON
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title: Example - Index and query JSON documents
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weight: 2
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---
@@ -24,98 +24,51 @@ Make sure that you have Redis Stack and `redis-py` installed.
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Import dependencies:
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```python
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import redis
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from redis.commands.json.path import Path
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import redis.commands.search.aggregation as aggregations
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import redis.commands.search.reducers as reducers
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from redis.commands.search.field import TextField, NumericField, TagField
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from redis.commands.search.indexDefinition import IndexDefinition, IndexType
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from redis.commands.search.query import NumericFilter, Query
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```
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{{< clients-example py_home_json import >}}
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{{< /clients-example >}}
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Connect to your Redis database.
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```python
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r = redis.Redis(host='localhost', port=6379)
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```
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Let's create some test data to add to your database.
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```python
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user1 = {
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"name": "Paul John",
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"email": "paul.john@example.com",
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"age": 42,
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"city": "London"
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}
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user2 = {
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"name": "Eden Zamir",
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"email": "eden.zamir@example.com",
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"age": 29,
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"city": "Tel Aviv"
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}
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user3 = {
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"name": "Paul Zamir",
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"email": "paul.zamir@example.com",
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"age": 35,
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"city": "Tel Aviv"
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}
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```
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Define indexed fields and their data types using `schema`. Use JSON path expressions to map specific JSON elements to the schema fields.
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```python
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schema = (
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TextField("$.name", as_name="name"),
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TagField("$.city", as_name="city"),
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NumericField("$.age", as_name="age")
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)
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```
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Create an index. In this example, all JSON documents with the key prefix `user:` will be indexed. For more information, see [Query syntax]({{< relref "/develop/interact/search-and-query/query/" >}}).
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```python
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rs = r.ft("idx:users")
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rs.create_index(
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schema,
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definition=IndexDefinition(
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prefix=["user:"], index_type=IndexType.JSON
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)
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)
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# b'OK'
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```
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Use [`JSON.SET`]({{< baseurl >}}/commands/json.set/) to set each user value at the specified path.
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```python
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r.json().set("user:1", Path.root_path(), user1)
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r.json().set("user:2", Path.root_path(), user2)
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r.json().set("user:3", Path.root_path(), user3)
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```
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Let's find user `Paul` and filter the results by age.
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```python
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res = rs.search(
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Query("Paul @age:[30 40]")
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)
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# Result{1 total, docs: [Document {'id': 'user:3', 'payload': None, 'json': '{"name":"Paul Zamir","email":"paul.zamir@example.com","age":35,"city":"Tel Aviv"}'}]}
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```
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Query using JSON Path expressions.
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```python
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rs.search(
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Query("Paul").return_field("$.city", as_field="city")
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).docs
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# [Document {'id': 'user:1', 'payload': None, 'city': 'London'}, Document {'id': 'user:3', 'payload': None, 'city': 'Tel Aviv'}]
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```
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Aggregate your results using [`FT.AGGREGATE`]({{< baseurl >}}/commands/ft.aggregate/).
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```python
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req = aggregations.AggregateRequest("*").group_by('@city', reducers.count().alias('count'))
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print(rs.aggregate(req).rows)
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# [[b'city', b'Tel Aviv', b'count', b'2'], [b'city', b'London', b'count', b'1']]
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```
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{{< clients-example py_home_json connect >}}
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{{< /clients-example >}}
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Create some test data to add to your database.
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{{< clients-example py_home_json create_data >}}
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{{< /clients-example >}}
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Create an index. In this example, only JSON documents with the key prefix `user:` are indexed. For more information, see [Query syntax]({{< relref "/develop/interact/search-and-query/query/" >}}).
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{{< clients-example py_home_json make_index >}}
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{{< /clients-example >}}
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Add the three sets of user data to the database as
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[JSON]({{< relref "/develop/data-types/json" >}}) objects.
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If you use keys with the `user:` prefix then Redis will index the
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objects automatically as you add them:
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{{< clients-example py_home_json add_data >}}
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{{< /clients-example >}}
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You can now use the index to search the JSON objects. The
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[query]({{< relref "/develop/interact/search-and-query/query" >}})
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below searches for objects that have the text "Paul" in any field
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and have an `age` value in the range 30 to 40:
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{{< clients-example py_home_json query1 >}}
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{{< /clients-example >}}
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Specify query options to return only the `city` field:
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{{< clients-example py_home_json query2 >}}
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{{< /clients-example >}}
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Use an
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[aggregation query]({{< relref "/develop/interact/search-and-query/query/aggregation" >}})
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to count all users in each city.
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{{< clients-example py_home_json query3 >}}
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{{< /clients-example >}}
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See the [Redis query engine]({{< relref "/develop/interact/search-and-query" >}}) docs
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for a full description of all query features with examples.

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