111–120 of 418 posts
Matlab: Great for prototyping and tinkering.
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I think Jira is among the better in the enterprise software class. Compared with ServiceNow (different use case but also enterprice-y) I much much prefer Jira. For example, the URL structure is sane.
Wait, service now is 3rd party software? It's so bad I assumed it was internal, by a team of 2-3 utterly incompetent web developers. This is paid for? Oh my god...
And we all get crushed under that weight.
I so much prefer Jira.
Phabricator
Only GitHub
Node.js
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That is the first time I hear someone praise Outlook. For an application that gets billions in billing, there are no valid excuses for it to be the same thing as it was 15 years ago.
I think there's a solid argument that getting billions in billing while being stagnant is self evidently a valid excuse to be stagnant.
yes.
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The only reason I keep paying for the “All Products” pack is because I like to use CLion for Rust and come light C and C++ work. Goland is also different enough to justify paying for at least CLion and Goland, but at that point, the “All Products” pack still makes sense.
Yeah, I use CLion as well for C work. Good to know it's useful for Rust as well, I hope to take that dive at some point. I feel slightly better about my purchase now, thanks!
Every time I want to be dismissive of the product, it's exceeded what I believed to be an extremely unlikely to meet set of expectations.
They've clearly got some pretty competent people. I'd love to draft them somehow
Beyond that, the services of namecheap Ava digital ocean. They clearly have developers who rely on the product. All the elements are there and they work well.
Azure's python libraries I find way easier than AWS's boto3, which for some reason always reminds me of dbus programming. I keep meaning to try Google's bud I haven't yet.
I also have been meaning to write one that somehow transparently uses things like rsync/scp with some partitioning strategy so you can migrate say a personal project costing you $50/month, generating you $0 and used by only a few dozen people to potentially a lot less.
(I've got numerous large scale efforts that almost nobody uses...)
Things that we pay for. SQL Server : it's not cheap, but it's genuinely good. Live query plans, clustered columnstore indices, linked servers, rich SQL features. Tableau : more than a dashboarding tool, it's actually a really good multivariate exploratory data analysis (EDA) tool. You can use it to visualize multidimensional data easily. I do use Jupyter (seaborn, plotly) and R (ggplot2) which are good, but Tableau l…
I definitely am on the opposite side when it comes to Tableau. After you get over the initial learning curve you start to realize that everything in Tableau when working with calculated fields is a workaround. If your data doesn't already look amazing going into Tableau you're in for a bad time.
The most common workarounds are for folks coming in with an Excel mindset (where operations are cell-level) who want to accomplish something that is easy in Excel but hard in Tableau. For instance, almost everything in Tableau is an aggregation, so displaying a simple unaggregated table is actually really hard (you have to make certain fields Dimensions, others Values, etc).
In Tableau, almost every operation maps to some SQL operation (in fact, you can peek at the underlying SQL query if you run the profiler), so mastery of Tableau almost always entails mastery of deep SQL concepts.
Why doesn't Tableau make easy things easy, say like Excel does? The trouble is Excel’s reactive cell level operations don't scale. Tableau lets you connect to massive backend databases to compute and display multifaceted viz's with relatively high performance, and the only way it can accomplish this is to restrict itself to SQL-friendly operations.
This difference is philosophically analogous to using for loops vs vectorized operations - the latter requires a mindset shift, and is less flexible/granular than the former but you gain a tremendous performance boost.