Verdin

Verdin is a tiny bird, and also a Tinybird SDK for Python .

Install

pip install verdin

Requirements

Python 3.8+

Usage

Run an SQL Query

# the tinybird module exposes all important tinybird concepts
from verdin import tinybird

client = tinybird.Client("p.mytoken")
query = client.sql("select * from my_datasource__v0")

# run the query with `FORMAT JSON` and receive a QueryJsonResult
response: tinybird.QueryJsonResult = query.json()

# print records returned from the pipe
print(response.data)

You can also run, e.g., query.get(format=OutputFormat.CSV) to get the raw response with CSV data.

Query a Pipe

from verdin import tinybird

client = tinybird.Client("p.mytoken")
pipe = client.pipe("my_pipe")

# query the pipe using dynamic parameters
response: tinybird.PipeJsonResponse = pipe.query({"key": "val"})

# print records returned from the pipe
print(response.data)

Append to a DataSource

from verdin import tinybird

client = tinybird.Client("p.mytoken")

# will access my_datasource__v0
datasource = client.datasource("my_datasource", version=0)

# query the pipe using dynamic parameters
datasource.append([
    ("col1-row1", "col2-row1"),
    ("col1-row2", "col2-row2"),
])

Queue and batch records into a DataSource

Verdin provides a way to queue and batch data continuously:

from queue import Queue
from threading import Thread

from verdin import tinybird
from verdin.worker import QueuingDatasourceAppender

client = 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"))

Develop

Create the virtual environment, install dependencies, and run tests

make venv
make test

Run the code formatter

make format

Upload the pypi package using twine

make upload

localstack/verdin