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SUMMARY:Building better data structures\, APIs and configuration systems f
 or scientific software using Pydantic - Nick Langellier\, Axel Donath
DTSTART;TZID=America/Chicago:20230710T080000
DTEND;TZID=America/Chicago:20230710T120000
DTSTAMP:20261007T031245Z
UID:pretalx-2023-VBZ9PN@cfp.scipy.org
DESCRIPTION:This tutorial is an introduction to Pydantic\, a library for d
 ata validation and settings management using Python type annotations. Usin
 g a semi-realistic ML and / or scientific software pipeline scenario we de
 monstrate how Pydantic can be used to support type validations for scienti
 fic data structures\, APIs and configuration systems. We show how the use 
 of Pydantic in scientific and ML software leads to a more pleasant user ex
 perience as well as more robust and easier to maintain code. A minimum kno
 wledge of Python type annotations\, class definitions and data structures 
 will be helpful\nfor beginners but not required.
LOCATION:Classroom 105
URL:https://cfp.scipy.org/2023/talk/VBZ9PN/
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SUMMARY:Gammapy: a Python Package for Gamma-Ray Astronomy Version v1.0 - A
 xel Donath
DTSTART;TZID=America/Chicago:20230712T131500
DTEND;TZID=America/Chicago:20230712T134500
DTSTAMP:20261007T031245Z
UID:pretalx-2023-RSE89M@cfp.scipy.org
DESCRIPTION:In this contribution we will present the first stable version 
 v1.0 of Gammapy\, an openly developed Python package for gamma-ray astrono
 my. Gammapy provides methods for the analysis of astronomical gamma-ray da
 ta\, such as measurement of spectra\, images and light curves. By relying 
 on standardized data formats and a joint likelihood framework\, it allows 
 astronomers to combine data from multiple instruments and constrain underl
 ying astrophysical emission processes across large parts of the electromag
 netic spectrum. Finally we will share lessons learned during the journey t
 owards version v1.0 for an openly developed scientific Python package.
LOCATION:Grand Salon C
URL:https://cfp.scipy.org/2023/talk/RSE89M/
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