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A Tinybird SDK for Python 🐦
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localstack/verdin
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Verdin is atiny bird, and also aTinybird SDK for Python.
pip install verdinPython 3.10+
# the tinybird module exposes all important tinybird conceptsfromverdinimporttinybirdclient=tinybird.Client("p.mytoken")query=client.sql("select * from my_datasource__v0")# run the query with `FORMAT JSON` and receive a QueryJsonResultresponse:tinybird.QueryJsonResult=query.json()# print records returned from the pipeprint(response.data)
You can also run, e.g.,query.get(format=OutputFormat.CSV) to get the raw response with CSV data.
fromverdinimporttinybirdclient=tinybird.Client("p.mytoken")pipe=client.pipe("my_pipe")# query the pipe using dynamic parametersresponse:tinybird.PipeJsonResponse=pipe.query({"key":"val"})# print records returned from the pipeprint(response.data)
fromverdinimporttinybirdclient=tinybird.Client("p.mytoken")# will access my_datasource__v0datasource=client.datasource("my_datasource",version=0)# query the pipe using dynamic parametersdatasource.append([ ("col1-row1","col2-row1"), ("col1-row2","col2-row2"),])
Verdin provides a way to queue and batch data continuously:
fromqueueimportQueuefromthreadingimportThreadfromverdinimporttinybirdfromverdin.workerimportQueuingDatasourceAppenderclient=tinybird.Client("p.mytoken")records=Queue()appender=QueuingDatasourceAppender(records,client.datasource("my_datasource"))Thread(target=appender.run).start()# appender will regularly read batches of data from the queue and append them# to the datasource. the appender respects rate limiting.records.put(("col1-row1","col2-row1"))records.put(("col1-row2","col2-row2"))
Create the virtual environment, install dependencies, and run tests
make venvmake testRun the code formatter
make formatUpload the pypi package using twine
make uploadAbout
A Tinybird SDK for Python 🐦
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