rust-analyzer VS lila

go build 3.62s user 0.76s system 171% cpu 2.545 total

I was looking forward to parallel front-end[4], but I have not seen any improvement for these small changes.

[1]: https://github.com/rust-lang/rust-analyzer

For example, intelephense can show diagnostics in real time, there is no need to save the file to get new diagnostics. But rust-analyzer, the language server for rust, can only update diagnostics after saving the file.

6. Rust Analyzer

The rust-analyzer readme suggests you go here for support request. But even there, you'll need to provide more details to get useful help.

For example: https://github.com/rust-lang/rust-analyzer/blob/master/docs/...

> If you create an LSP, it will work best in VS Code.

Any editor can work just as well as (or even better than) VS Code.

So, apparently the reason why rust-analyzer, the LSP server for Rust does not have persistent caching is because it would make "optimizing initial passes less important".

All I want to know is: Will it have a build configuration pulldown?

I am not a Rust dev. It surely looks great.

However, from what I understand it seems to supply just a parser separate from the Rust compiler (https://github.com/rust-lang/rust-analyzer/tree/master/crate...) trying to keep up with Rust‘s development. So, in principle, it could have been just another treesitter parser plugin, too.

So, again, the LSP framework does not directly provide any magical benefit over a static parsing framework. All the semantic analysis capabilities stem from a good parser.

rust-analyzer > manual > helix > binary > rustup component add rust-analyzer

Once you’re finished, we’re going to set up a lichess bot account. Head over to https://lichess.org/ and create a new account.

Lichess - Online Chess Server. Scala, TypeScript

> the player who committed more blunders lost 86% of the time

In some sense this is almost tautological. While finding an exact definition for a chess blunder isn't straightforward, here is one example from the Lichess UI:

https://github.com/lichess-org/lila/blob/b527746b179cdde6438...

Basically, if you make a move which decreases your winning probability more than 14% over the best move, that's a blunder. But winning probability is a nonlinear function of stockfish centipawns. A drop in 100 centipawns when you're up 15 points isn't a blunder. When the game was equal, it is.

Point is, by the time you know it's a blunder you already know something about the outcome of that move, that it swung the winning probability by more than 14%. So the analysis is kind of just measuring some function of winning probability and saying that it is highly correlated with winning probability.

If you want to improve make it your goal to play the best chess you can, not increase an arbitrary number. Watch YouTube series like John Bartholomew's "Climb the Rating Ladder" for some general insight into what you might be doing wrong. Read Irving Chernev's "Logical Chess: Move By Move" to see the thinking process of high level players. Do lots of puzzles (I like lichess.org for puzzles). And always analyze your games. When you analyze make it your goal to find at least two things you could have improved.

The easiest way to play against Stockfish is perhaps on https://lichess.org/, but it's not the only chess engine that evaluates positions with a neural network.

Lichess.com

if you actually like chess, try lichess.org, the free and open-source, no ads ever, premium alternative