Showing entries tagged [metpy]

MetPy Mondays #4 - Units in MetPy

I remember the first class I took in which the professor required that we include units by every quantity in every step of every calculation we did… or it was wrong. I thought this policy was a bit harsh, but after one or two assignments, I was getting the hang of it. By the end of the semester I realized that it was insane to work any other way. In science, we are dealing with physical quantities that represent things in the real world – and things in the real world have units. Keeping track of units throughout a calculation caught many errors I made while solving and rearranging equations. If keeping track of units on paper is a good idea, why is computing any different? In this MetPy Monday, we'll look at how MetPy uses units and how to convert between different units.

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MetPy Mondays #3 - Conda Environments

Have you ever had to manually change your path to switch between Python 2.7 and Python 3? Have you broken your research environment by installing a new package to try? Have you ever wanted to take a snapshot and backup your current Python environment? If so, you'll love Conda environments! This week we show you how to setup your own Python environments and switch between them. We also cover how to create a file defining your environment so others can recreate it. It's another video MetPy Monday!

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MetPy Mondays #2 - Conda Forge

This week we continue setting up our Python environments by learning about Conda channels. We’ll add the Conda Forge channel and see how to install and update packages. We'll round out the screencast by using Conda to install the most recent version of Unidata's MetPy package.

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MetPy Mondays #1 - Conda Installation

Welcome to MetPy Mondays! This week we're going to start off by getting your Python environment up and running. We will install Miniconda, a product of Continuum Analytics. Conda is a Python environment and package manager that makes managing various versions of Python and packages a breeze.

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Exploring Python as an Interface to Unidata Technologies

EDEX SkewT
An example EdexPy interface (click to enlarge)

It is hard to believe my time here at Unidata has come and gone so quickly! Next week, I imagine it will be back to the “harsh” reality of being a student — sitting on a beach somewhere near Monterey or perhaps fly fishing the Sierras over the next twenty days awaiting the start of my first year of graduate school at San Jose State. What a terrible reality that will be!

This experience at Unidata and UCAR has been an incredible opportunity and I am privileged to have been afforded these ten weeks. When I started here, I envisioned an entirely different internship than what previous interns had completed. Rather than developing one particular project, I focused my time on gaining a greater understanding of software engineering as a whole and contributing to existing Unidata projects. I found a comfortable spot working with Unidata Python developers Ryan May and Sean Arms, and within one week I had learned a great deal about unit testing, code health, automated testing, and version control. Later, I would implement these principles in my first Python library, MesoPy.

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A weblog about software development by Unidata developers*
Unidata Developer's Blog
A weblog about software development by Unidata developers*

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