Skip to content
Collection of notebooks and scripts with science use cases
Jupyter Notebook Python
Branch: master
Clone or download
Type Name Latest commit message Commit time
Failed to load latest commit information.
api updated README Jul 19, 2019
example_data Merge branch 'master' of Jun 20, 2019
lib Modified API notebook and wrapper Aug 16, 2019
notebooks Removed requirement of credentials Jun 28, 2019
alercereaduser.json Added read only credentials Jun 20, 2019
requirements.txt Create requirements.txt Jun 20, 2019

See more information about the ALeRCE broker, including its frontend, in

ALeRCE use cases

A collection of jupyter notebooks and scripts on how to access the ALeRCE database, API, etc.

For faster cloning please use: git clone --depth=1


The ALeRCE broker is a Chilean-led initiative to build a community broker for LSST and other large etendue survey telescopes which produce public streams of alerts. ALeRCE is developed by many institutions in Chile and in the U.S., taking advantage of the large network of collaborators which we have established around data science and astronomy during the last decade. The main motivation of ALeRCE is to facilitate the follow-up and the exploration of the LSST and other observatories alert streams.

Scientific aim

ALeRCE aims to facilitate the study of stationary (non--moving) variable and transient objects. We will do this by providing real-time filtered streams of aggregated, annotated and classified alerts, but also by providing alert exploration and analysis tools that can help researchers look for patterns and outliers within large populations of events. We also aim to provide forecasting tools which can help with the optimization of follow--up resources.

This repository

In this repository we show how to access the ALeRCE ZTF database, focused on different science cases. You can find several introductory jupyter notebooks in the notebooks directory, which connect to the database, query some tables and does some processing and visualization of the data. If you would like to beta test this please note that ALeRCE is still under development, with very simple taxonomy and classification models. Please report any problems to francisco dot forster at gmail dot com.

How can I contribute?

The success of ALeRCE depends on being able to build a community of users which can connect LSST with the different follow up resources. Therefore, we are very happy to receive and publish contributed notebooks in this repository showing how your science case can benefit from having a real-time access to an annotated and classified database of ZTF alerts. Please feel free to join this repository and add your science cases!

You can’t perform that action at this time.