application VS Arraymancer

You could use Budget with Buckets. It's free to use, but you can get a license too. Downside: it doesn't have an app (well, it does, but it's read only and sucks big time).

I use buckets https://www.budgetwithbuckets.com/

I track my balances across various sources, updating once a month. I also set my outgoings.

Funnily enough I don't really use the buckets feature too much, simply the graph over time of savings, and ability to set goals / monthly costs for review is enough.

Right now I'm testing software called Buckets, and I am liking it so far. It's a one-time payment, and the dev seems pretty cool by offering an extremely generous demo. It's kind of a hybrid between manual and automatic, with some macro import options and statement import options that can be helpful. It also has the option to import financial data automatically using SimpleFin for only a fraction of the monthly price of YNAB and Aspire. So far I'm really liking it.

Buckets - I just started to look at this app. It is very basic from what I have seen so far. And while writing this I learned the iOS app is a closed beta. Unlimited FREE trial until you determine it works for you. After that, there is a one-time fee of $49. In September the price is going up to $64.

You might look into budget with buckets

I haven't used it, but the team (person?) that makes [Buckets](https://www.budgetwithbuckets.com) makes [SimpleFIN](https://www.simplefin.org), which seems like it exposes exactly what you want: simple transaction data from arbitrary banks.

Plaid offers [transactions APIs](https://plaid.com/products/transactions/), but I guess to your point these APIs are geared towards fintech companies, not personal use.

I’ve been happy with Budget with Buckets as a YNAB alternative - https://www.budgetwithbuckets.com/

It is a small DSL written using macros at https://github.com/mratsim/Arraymancer/blob/master/src/array....

Nim has pretty great meta-programming capabilities and arraymancer employs some cool features like emitting cuda-kernels on the fly using standard templates depending on backend !

Nim has also a powerful deep learning library called Arraymancer. It's selling point is that you don't have to rewrite your code from research to production. It's used in various machine learning projects, but one recent one that caught my eye was https://github.com/amkrajewski/nimCSO "Composition Space Optimization"

https://github.com/mratsim/Arraymancer

- https://github.com/mratsim/Arraymancer/blob/master/src/array...

It's worth noting that nim async/await transformation is fully implemented as a library in macros.

https://github.com/mratsim/Arraymancer 11. « Premature optimisation is the root of all evil », Donald Knuth, The art of computer Programming It would be quite useful that someone writes one with examples for all these recommendations and more ...

In particular for deep learning as bobsyourunkl already mentioned there is arraymancer on the one hand and also flambeau on the other. The latter is a Nim wrapper around libtorch (i.e. the PyTorch C++ backend). It is missing things (to be wrapped by adding a few lines) and has some rough edges, but if one needs to get stuff done, it's possible.

how are u compiling (optimization, custom compilation flags etc.?) In my case https://github.com/mratsim/Arraymancer big project compile under your 4.2s so or you have like 10k+ lines of codes with macros or you just pass some debug flags to compiler :D

We have both raw wrappers for BLAS:

https://github.com/andreaferretti/nimblas

as well as LAPACK:

https://github.com/andreaferretti/nimlapack

For an example, consider calling the least squares routine `dgelsd` in arraymancer:

https://github.com/mratsim/Arraymancer/blob/master/src/array...

wrapped up in a nicer user facing API.

Feel free to hop onto matrix, if you have more questions!