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Time Series with Python - QuestDB official Python client just released
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Time-series data is everywhere, and python is the choice of many developers and data scientist to deal with time-series analytics. You can use the Postgres wire protocol to query data using, for example, psycopg2. But when it comes to ingesting data, it is better to use the ILP protocol. Until now, using ILP from Python would imply dealing with sockets, which is not ideal. We are excited to announce the official release of our Python client, so ingesting data at HIGH speeds is as easy and convenient as possible. In this video, I show you how to use it in different scenarios. Give it a try and let us know what you think.
00:00 Intro
00:15 Postgres and ILP protocols on QuestDB
01:15 Ingesting data using InfluxDB ILP protocol before this release
02:14 Introducing the Python client
02:47 The basics of ingesting data
03:30 Flushing data to send rows over to QuestDB
04:18 Clearing data after flushing and auto-flush
05:35 Python code example showing basic ingestion
09:00 Verifying data was correctly committed
09:25 Python example: Explicit buffers for more control and to send data to multiple QuestDB instances
10:35 ILP Authentication in QuestDB
11:11 Python example: ILP Authentication and TLS
12:41 Acknowledgements, summary, and closing
00:00 Intro
00:15 Postgres and ILP protocols on QuestDB
01:15 Ingesting data using InfluxDB ILP protocol before this release
02:14 Introducing the Python client
02:47 The basics of ingesting data
03:30 Flushing data to send rows over to QuestDB
04:18 Clearing data after flushing and auto-flush
05:35 Python code example showing basic ingestion
09:00 Verifying data was correctly committed
09:25 Python example: Explicit buffers for more control and to send data to multiple QuestDB instances
10:35 ILP Authentication in QuestDB
11:11 Python example: ILP Authentication and TLS
12:41 Acknowledgements, summary, and closing
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