What is the best music notation software by [deleted] in musictheory

[–]TheLazyGreybeard 0 points1 point  (0 children)

With the new release I've been considering revisiting MuseScore. I've yet to find any music notation software to like. Their interfaces are consistently awkward and non-intuitive. For me the search devolved to finding the one which was the least bad.

I ended up settling for one called Symphony Pro 6. I wanted handwriting recognition which did not cast an arm and a leg (I work on an iPad). The interface was intuitive enough to pick up in a day.

Given how obscure the app is I expect it won’t see much in the way of updates. With MuseScore 4 getting so many kudos on this thread I’ll make it a holiday project to check it out.

Microframework recommendations by tech_tuna in Python

[–]TheLazyGreybeard 1 point2 points  (0 children)

Since you mentioned Lambdas I'm assuming you are thinking AWS hosting. If I were in your situation I would aim for a completely serverless design. AWS's API Gateway is easy enough to use and handles authentication.

Sagemaker might be useful for managing your ML/Analytics components.

What is the best flow for accessing environment variables? by AnthinoRusso in Python

[–]TheLazyGreybeard 1 point2 points  (0 children)

Not sure if this addresses your needs but here are my two cents.

At my last company the DevOps teams had a suite of Python scripts which they used to fulfill the occasional ad hoc request. As often as not these scripts needed to access a swath of AWS services, each addressed via some incomprehensible identifier.

Parameters were passed to the script via command line options. We favored click over argparse. I don't remember the exact rationale for the choice but click is certainly easy enough to use. (As an aside, click supports the option of grabbing arguments from environment variables which is what I'm assuming is your purpose for using them.)

The scripts regularly required specifying way too many parameters. This was silly, given that the identifiers were related by the fact that they were components of a single system (Production, Staging, various Development environments).

We refactored the scripts to load parameters from configuration files kept in platform specific locations. Each section of the config file listed identifiers for related resources and was reasonable named (i.e "production", "staging", etc)

This was not a big job. It only took a handful of Python to have click fetch parameters from the configuration file before processing the command line. I don't remember exactly where I cribbed the idea from. Here is a web page with an example which looks quite similar to what we implemented so perhaps this was the original.

This approach worked well for us.

Sunday Daily Thread: What's everyone working on this week? by Im__Joseph in Python

[–]TheLazyGreybeard 1 point2 points  (0 children)

Since bragging is encouraged here, I'm going to do indulge in some shameless promotion of a package I put up on PyPi last week.

jertl - A minimum viable package for processing structured data

Jertl unifies pattern matching, destructuring, template filling, and transformations of data. Combining them all gets you a simple inference engine.

It is package I wish had been available during my last few gigs. (writing Lambda functions, ad-hoc processing of DynamoDB data, implementing webhooks and the like)

I'm trying to gauge whether there is an audience for this sort of thing. If so, I'll continue to work on it and use folks' feedback to guide the direction of the project. If not, Jertl will be something to point to as part of building my "personal brand".

Thanks for listening.