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arrakis-python

Arrakis Python client library

ci documentation

Installation

pip install git+https://git.ligo.org/ngdd/arrakis-python.git

Features

  • Query live and historical timeseries data
  • Describe channel metadata
  • Search for channels matching a set of conditions
  • Publish timeseries data

Quickstart

Stream timeseries

1. Live data
import arrakis

channels = [
    "H1:CAL-DELTAL_EXTERNAL_DQ",
    "H1:LSC-POP_A_LF_OUT_DQ",
]

for block in arrakis.stream(channels):
    print(block)
2. Historical data
import arrakis

start = 1187000000
end = 1187001000
channels = [
    "H1:CAL-DELTAL_EXTERNAL_DQ",
    "H1:LSC-POP_A_LF_OUT_DQ",
]

for block in arrakis.stream(channels, start, end):
    print(block)

Fetch timeseries

import arrakis

start = 1187000000
end = 1187001000
channels = [
    "H1:CAL-DELTAL_EXTERNAL_DQ",
    "H1:LSC-POP_A_LF_OUT_DQ",
]

block = arrakis.fetch(channels, start, end)

Describe metadata

import arrakis

channels = [
    "H1:CAL-DELTAL_EXTERNAL_DQ",
    "H1:LSC-POP_A_LF_OUT_DQ",
]

metadata = arrakis.describe(channels)

Find channels

import arrakis

channels = arrakis.find("H1:LSC-*")

Count channels

import arrakis

count = arrakis.count("H1:LSC-*")

Publish timeseries

import arrakis
from arrakis import SeriesBlock, Time
import numpy

series = {
    "H1:FKE-TEST_CHANNEL1": numpy.array([0.1, 0.2, 0.3, 0.4], dtype=numpy.float64),
    "H1:FKE-TEST_CHANNEL2": numpy.array([1.1, 1.2, 1.3, 1.4], dtype=numpy.float64),
}
block = SeriesBlock(1234567890 * Time.SECONDS, series)

with arrakis.connect("kafka://localhost:9092") as client:
    client.publish(block)