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A python wrapper for the KSQL REST API.
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bryanyang0528/ksql-python
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A python wrapper for the KSQL REST API. Easily interact with the KSQL REST API using this library.
Supported KSQLDB version: 0.10.1+Supported Python version: 3.5+
pip install ksql
Or
git clone https://github.com/bryanyang0528/ksql-pythoncd ksql-pythonpython setup.py installThis is the GITHUB page of KSQL.https://github.com/confluentinc/ksql
If you have installed open source Confluent CLI (e.g. by installing Confluent Open Source or Enterprise Platform), you can start KSQL and its dependencies with one single command:
confluent start ksql-server
- Setup for the KSQL API:
fromksqlimportKSQLAPIclient=KSQLAPI('http://ksql-server:8088')
- Setup for KSQl API with logging enabled:
importloggingfromksqlimportKSQLAPIlogging.basicConfig(level=logging.DEBUG)client=KSQLAPI('http://ksql-server:8088')
- Setup for KSQL API with Basic Authentication
fromksqlimportKSQLAPIclient=KSQLAPI('http://ksql-server:8088',api_key="your_key",secret="your_secret")
| Option | Type | Required | Description |
|---|---|---|---|
url | string | yes | Your ksql-server url. Example:http://ksql-server:8080 |
timeout | integer | no | Timout for Requests. Default:5 |
api_key | string | no | API Key to use on the requests |
secret | string | no | Secret to use on the requests |
This method can be used for some KSQL features which are not supported via other specific methods likequery,create_stream orcreate_stream_as.The following example shows how to execute theshow tables statement:
client.ksql('show tables')
- Example Response
[{'tables': {'statementText': 'show tables;', 'tables': []}}]
It will execute sql query and keep listening streaming data.
client.query('select * from table1')
This command returns a generator. It can be printed e.g. by reading its values via next(query) or a for loop. Here is a complete example:
fromksqlimportKSQLAPIclient=KSQLAPI('http://localhost:8088')query=client.query('select * from table1')foriteminquery:print(item)
Example Response
{"row":{"columns":[1512787743388,"key1",1,2,3]},"errorMessage":null}{"row":{"columns":[1512787753200,"key1",1,2,3]},"errorMessage":null}{"row":{"columns":[1512787753488,"key1",1,2,3]},"errorMessage":null}{"row":{"columns":[1512787753888,"key1",1,2,3]},"errorMessage":null}
Execute queries with the new/query-stream endpoint. Documentedhere
To execute a sql query use the same syntax as the regular query, with the additionaluse_http2=True parameter.
client.query('select * from table1',use_http2=True)
A generator is returned with the following example response
{"queryId":"44d8413c-0018-423d-b58f-3f2064b9a312","columnNames":["ORDER_ID","TOTAL_AMOUNT","CUSTOMER_NAME"],"columnTypes":["INTEGER","DOUBLE","STRING"]}[3,43.0,"Palo Alto"][3,43.0,"Palo Alto"][3,43.0,"Palo Alto"]To terminate the query above use theclose_query call.Provide thequeryId returned from thequery call.
client.close_query("44d8413c-0018-423d-b58f-3f2064b9a312")
Uses the new/inserts-stream endpoint. Seedocumentation
rows= [ {"ORDER_ID":1,"TOTAL_AMOUNT":23.5,"CUSTOMER_NAME":"abc"}, {"ORDER_ID":2,"TOTAL_AMOUNT":3.7,"CUSTOMER_NAME":"xyz"} ]results=self.api_client.inserts_stream("my_stream_name",rows)
An array of object will be returned on success, with the status of each row inserted.
client.create_stream(table_name=table_name,columns_type=columns_type,topic=topic,value_format=value_format)
| Option | Type | Required | Description |
|---|---|---|---|
table_name | string | yes | name of stream/table |
columns_type | list | yes | ex:['viewtime bigint','userid varchar','pageid varchar'] |
topic | string | yes | Kafka topic |
value_format | string | no | JSON (Default) orDELIMITED orAVRO |
key | string | for Table | Key (used for JOINs) |
- Responses
| If create table/stream succeed: | return True |
|---|---|
| If failed: | raise a CreateError(respose_from_ksql_server) |
a simplified api for creating stream as select
client.create_stream_as(table_name=table_name,select_columns=select_columns,src_table=src_table,kafka_topic=kafka_topic,value_format=value_format,conditions=conditions,partition_by=partition_by,**kwargs)
CREATE STREAM<table_name>[WITH ( kafka_topic=<kafka_topic>, value_format=<value_format>, property_name=expression ... )]ASSELECT<select_columns>FROM<src_table>[WHERE<conditions>]PARTITION BY<partition_by>];
| Option | Type | Required | Description |
|---|---|---|---|
table_name | string | yes | name of stream/table |
select_columns | list | yes | you can select[*] or['columnA', 'columnB'] |
src_table | string | yes | name of source table |
kafka_topic | string | no | The name of the Kafka topic of this new stream(table). |
value_format | string | no | DELIMITED,JSON``(Default) or ``AVRO |
conditions | string | no | The conditions in the where clause. |
partition_by | string | no | Data will be distributed across partitions by this column. |
kwargs | pair | no | please providekey=value pairs. Please see more options. |
KSQL JOINs between Streams and Tables are not supported yet via explicit methods, but you can use theksql method for this like the following:
client.ksql("CREATE STREAM join_per_user WITH (VALUE_FORMAT='AVRO', KAFKA_TOPIC='join_per_user') AS SELECT Time, Amount FROM source c INNER JOIN users u on c.user = u.userid WHERE u.USERID = 1")
Run commands from a .ksql file. Can only support ksql commands and not streaming queries.
fromksql.uploadimportFileUploadpointer=FileUpload('http://ksql-server:8080')pointer.upload('rules.ksql')
| Option | Type | Required | Description |
|---|---|---|---|
ksqlfile | string | yes | name of file containing the rules |
- Responses
| If ksql-commands succesfully executed: | return (List of server response for all commands) |
|---|---|
| If failed: | raise the appropriate error |
There are more properties (partitions, replicas, etc...) in the official document.
- Responses
| If create table/stream succeed: | return True |
|---|---|
| If failed: | raise a CreatError(respose_from_ksql_server) |
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A python wrapper for the KSQL REST API.
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