Subsequence parttern matching for time series
The real state of the art here is the Matrix Profile suite, developed by Eamonn Keogh and his team in University of California at Riverside (UCR). Here are some links to get you started:

Matrix Profile Foundation homepage
The UCR Matrix Profile Page
MPA: a novel cross-language API for time series analysis paper (2020) with links to Python, R, and Go implementations
Introducing matrixprofile-ts, a Python Library for Detecting Patterns and Anomalies in Massive Datasets
Towards a Near Universal Time Series Data Mining Tool: Introducing the Matrix Profile (PhD thesis)
100 Time Series Data Mining Questions (with answers!) (highly recommended high-level view)

You'll find links to implementations in the above stuff.
Apart from the team at UCR, there is another (and possibly more efficient) implementation of the relevant algorithms in the STUMPY Python package:

STUMPY documentation &amp; Github repo
STUMPY: A Powerful and Scalable Python Library for Time Series Data Mining paper (2019)