d7392f1f3b
# Description This PR adds an internal representation language to Nushell, offering an alternative evaluator based on simple instructions, stream-containing registers, and indexed control flow. The number of registers required is determined statically at compile-time, and the fixed size required is allocated upon entering the block. Each instruction is associated with a span, which makes going backwards from IR instructions to source code very easy. Motivations for IR: 1. **Performance.** By simplifying the evaluation path and making it more cache-friendly and branch predictor-friendly, code that does a lot of computation in Nushell itself can be sped up a decent bit. Because the IR is fairly easy to reason about, we can also implement optimization passes in the future to eliminate and simplify code. 2. **Correctness.** The instructions mostly have very simple and easily-specified behavior, so hopefully engine changes are a little bit easier to reason about, and they can be specified in a more formal way at some point. I have made an effort to document each of the instructions in the docs for the enum itself in a reasonably specific way. Some of the errors that would have happened during evaluation before are now moved to the compilation step instead, because they don't make sense to check during evaluation. 3. **As an intermediate target.** This is a good step for us to bring the [`new-nu-parser`](https://github.com/nushell/new-nu-parser) in at some point, as code generated from new AST can be directly compared to code generated from old AST. If the IR code is functionally equivalent, it will behave the exact same way. 4. **Debugging.** With a little bit more work, we can probably give control over advancing the virtual machine that `IrBlock`s run on to some sort of external driver, making things like breakpoints and single stepping possible. Tools like `view ir` and [`explore ir`](https://github.com/devyn/nu_plugin_explore_ir) make it easier than before to see what exactly is going on with your Nushell code. The goal is to eventually replace the AST evaluator entirely, once we're sure it's working just as well. You can help dogfood this by running Nushell with `$env.NU_USE_IR` set to some value. The environment variable is checked when Nushell starts, so config runs with IR, or it can also be set on a line at the REPL to change it dynamically. It is also checked when running `do` in case within a script you want to just run a specific piece of code with or without IR. # Example ```nushell view ir { |data| mut sum = 0 for n in $data { $sum += $n } $sum } ``` ```gas # 3 registers, 19 instructions, 0 bytes of data 0: load-literal %0, int(0) 1: store-variable var 904, %0 # let 2: drain %0 3: drop %0 4: load-variable %1, var 903 5: iterate %0, %1, end 15 # for, label(1), from(14:) 6: store-variable var 905, %0 7: load-variable %0, var 904 8: load-variable %2, var 905 9: binary-op %0, Math(Plus), %2 10: span %0 11: store-variable var 904, %0 12: load-literal %0, nothing 13: drain %0 14: jump 5 15: drop %0 # label(0), from(5:) 16: drain %0 17: load-variable %0, var 904 18: return %0 ``` # Benchmarks All benchmarks run on a base model Mac Mini M1. ## Iterative Fibonacci sequence This is about as best case as possible, making use of the much faster control flow. Most code will not experience a speed improvement nearly this large. ```nushell def fib [n: int] { mut a = 0 mut b = 1 for _ in 2..=$n { let c = $a + $b $a = $b $b = $c } $b } use std bench bench { 0..50 | each { |n| fib $n } } ``` IR disabled: ``` ╭───────┬─────────────────╮ │ mean │ 1ms 924µs 665ns │ │ min │ 1ms 700µs 83ns │ │ max │ 3ms 450µs 125ns │ │ std │ 395µs 759ns │ │ times │ [list 50 items] │ ╰───────┴─────────────────╯ ``` IR enabled: ``` ╭───────┬─────────────────╮ │ mean │ 452µs 820ns │ │ min │ 427µs 417ns │ │ max │ 540µs 167ns │ │ std │ 17µs 158ns │ │ times │ [list 50 items] │ ╰───────┴─────────────────╯ ```  ## [gradient_benchmark_no_check.nu](https://github.com/nushell/nu_scripts/blob/main/benchmarks/gradient_benchmark_no_check.nu) IR disabled: ``` ╭───┬──────────────────╮ │ 0 │ 27ms 929µs 958ns │ │ 1 │ 21ms 153µs 459ns │ │ 2 │ 18ms 639µs 666ns │ │ 3 │ 19ms 554µs 583ns │ │ 4 │ 13ms 383µs 375ns │ │ 5 │ 11ms 328µs 208ns │ │ 6 │ 5ms 659µs 542ns │ ╰───┴──────────────────╯ ``` IR enabled: ``` ╭───┬──────────────────╮ │ 0 │ 22ms 662µs │ │ 1 │ 17ms 221µs 792ns │ │ 2 │ 14ms 786µs 708ns │ │ 3 │ 13ms 876µs 834ns │ │ 4 │ 13ms 52µs 875ns │ │ 5 │ 11ms 269µs 666ns │ │ 6 │ 6ms 942µs 500ns │ ╰───┴──────────────────╯ ``` ## [random-bytes.nu](https://github.com/nushell/nu_scripts/blob/main/benchmarks/random-bytes.nu) I got pretty random results out of this benchmark so I decided not to include it. Not clear why. # User-Facing Changes - IR compilation errors may appear even if the user isn't evaluating with IR. - IR evaluation can be enabled by setting the `NU_USE_IR` environment variable to any value. - New command `view ir` pretty-prints the IR for a block, and `view ir --json` can be piped into an external tool like [`explore ir`](https://github.com/devyn/nu_plugin_explore_ir). # Tests + Formatting All tests are passing with `NU_USE_IR=1`, and I've added some more eval tests to compare the results for some very core operations. I will probably want to add some more so we don't have to always check `NU_USE_IR=1 toolkit test --workspace` on a regular basis. # After Submitting - [ ] release notes - [ ] further documentation of instructions? - [ ] post-release: publish `nu_plugin_explore_ir` |
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|---|---|---|
| .cargo | ||
| .githooks | ||
| .github | ||
| assets | ||
| benches | ||
| crates | ||
| devdocs | ||
| docker | ||
| scripts | ||
| src | ||
| tests | ||
| wix | ||
| .gitattributes | ||
| .gitignore | ||
| Cargo.lock | ||
| Cargo.toml | ||
| CITATION.cff | ||
| CODE_OF_CONDUCT.md | ||
| CONTRIBUTING.md | ||
| Cross.toml | ||
| LICENSE | ||
| README.md | ||
| rust-toolchain.toml | ||
| toolkit.nu | ||
| typos.toml | ||
Nushell
A new type of shell.
Table of Contents
- Status
- Learning About Nu
- Installation
- Configuration
- Philosophy
- Goals
- Officially Supported By
- Contributing
- License
Status
This project has reached a minimum-viable-product level of quality. Many people use it as their daily driver, but it may be unstable for some commands. Nu's design is subject to change as it matures.
Learning About Nu
The Nushell book is the primary source of Nushell documentation. You can find a full list of Nu commands in the book, and we have many examples of using Nu in our cookbook.
We're also active on Discord and Twitter; come and chat with us!
Installation
To quickly install Nu:
# Linux and macOS
brew install nushell
# Windows
winget install nushell
To use Nu in GitHub Action, check setup-nu for more detail.
Detailed installation instructions can be found in the installation chapter of the book. Nu is available via many package managers:
For details about which platforms the Nushell team actively supports, see our platform support policy.
Configuration
The default configurations can be found at sample_config which are the configuration files one gets when they startup Nushell for the first time.
It sets all of the default configuration to run Nushell. From here one can then customize this file for their specific needs.
To see where config.nu is located on your system simply type this command.
$nu.config-path
Please see our book for all of the Nushell documentation.
Philosophy
Nu draws inspiration from projects like PowerShell, functional programming languages, and modern CLI tools. Rather than thinking of files and data as raw streams of text, Nu looks at each input as something with structure. For example, when you list the contents of a directory what you get back is a table of rows, where each row represents an item in that directory. These values can be piped through a series of steps, in a series of commands called a 'pipeline'.
Pipelines
In Unix, it's common to pipe between commands to split up a sophisticated command over multiple steps. Nu takes this a step further and builds heavily on the idea of pipelines. As in the Unix philosophy, Nu allows commands to output to stdout and read from stdin. Additionally, commands can output structured data (you can think of this as a third kind of stream). Commands that work in the pipeline fit into one of three categories:
- Commands that produce a stream (e.g.,
ls) - Commands that filter a stream (e.g.,
where type == "dir") - Commands that consume the output of the pipeline (e.g.,
table)
Commands are separated by the pipe symbol (|) to denote a pipeline flowing left to right.
> ls | where type == "dir" | table
╭────┬──────────┬──────┬─────────┬───────────────╮
│ # │ name │ type │ size │ modified │
├────┼──────────┼──────┼─────────┼───────────────┤
│ 0 │ .cargo │ dir │ 0 B │ 9 minutes ago │
│ 1 │ assets │ dir │ 0 B │ 2 weeks ago │
│ 2 │ crates │ dir │ 4.0 KiB │ 2 weeks ago │
│ 3 │ docker │ dir │ 0 B │ 2 weeks ago │
│ 4 │ docs │ dir │ 0 B │ 2 weeks ago │
│ 5 │ images │ dir │ 0 B │ 2 weeks ago │
│ 6 │ pkg_mgrs │ dir │ 0 B │ 2 weeks ago │
│ 7 │ samples │ dir │ 0 B │ 2 weeks ago │
│ 8 │ src │ dir │ 4.0 KiB │ 2 weeks ago │
│ 9 │ target │ dir │ 0 B │ a day ago │
│ 10 │ tests │ dir │ 4.0 KiB │ 2 weeks ago │
│ 11 │ wix │ dir │ 0 B │ 2 weeks ago │
╰────┴──────────┴──────┴─────────┴───────────────╯
Because most of the time you'll want to see the output of a pipeline, table is assumed.
We could have also written the above:
> ls | where type == "dir"
Being able to use the same commands and compose them differently is an important philosophy in Nu.
For example, we could use the built-in ps command to get a list of the running processes, using the same where as above.
> ps | where cpu > 0
╭───┬───────┬───────────┬───────┬───────────┬───────────╮
│ # │ pid │ name │ cpu │ mem │ virtual │
├───┼───────┼───────────┼───────┼───────────┼───────────┤
│ 0 │ 2240 │ Slack.exe │ 16.40 │ 178.3 MiB │ 232.6 MiB │
│ 1 │ 16948 │ Slack.exe │ 16.32 │ 205.0 MiB │ 197.9 MiB │
│ 2 │ 17700 │ nu.exe │ 3.77 │ 26.1 MiB │ 8.8 MiB │
╰───┴───────┴───────────┴───────┴───────────┴───────────╯
Opening files
Nu can load file and URL contents as raw text or structured data (if it recognizes the format). For example, you can load a .toml file as structured data and explore it:
> open Cargo.toml
╭──────────────────┬────────────────────╮
│ bin │ [table 1 row] │
│ dependencies │ {record 25 fields} │
│ dev-dependencies │ {record 8 fields} │
│ features │ {record 10 fields} │
│ package │ {record 13 fields} │
│ patch │ {record 1 field} │
│ profile │ {record 3 fields} │
│ target │ {record 3 fields} │
│ workspace │ {record 1 field} │
╰──────────────────┴────────────────────╯
We can pipe this into a command that gets the contents of one of the columns:
> open Cargo.toml | get package
╭───────────────┬────────────────────────────────────╮
│ authors │ [list 1 item] │
│ default-run │ nu │
│ description │ A new type of shell │
│ documentation │ https://www.nushell.sh/book/ │
│ edition │ 2018 │
│ exclude │ [list 1 item] │
│ homepage │ https://www.nushell.sh │
│ license │ MIT │
│ metadata │ {record 1 field} │
│ name │ nu │
│ repository │ https://github.com/nushell/nushell │
│ rust-version │ 1.60 │
│ version │ 0.72.0 │
╰───────────────┴────────────────────────────────────╯
And if needed we can drill down further:
> open Cargo.toml | get package.version
0.72.0
Plugins
Nu supports plugins that offer additional functionality to the shell and follow the same structured data model that built-in commands use. There are a few examples in the crates/nu_plugins_* directories.
Plugins are binaries that are available in your path and follow a nu_plugin_* naming convention.
These binaries interact with nu via a simple JSON-RPC protocol where the command identifies itself and passes along its configuration, making it available for use.
If the plugin is a filter, data streams to it one element at a time, and it can stream data back in return via stdin/stdout.
If the plugin is a sink, it is given the full vector of final data and is given free reign over stdin/stdout to use as it pleases.
The awesome-nu repo lists a variety of nu-plugins while the showcase repo shows off informative blog posts that have been written about Nushell along with videos that highlight technical topics that have been presented.
Goals
Nu adheres closely to a set of goals that make up its design philosophy. As features are added, they are checked against these goals.
-
First and foremost, Nu is cross-platform. Commands and techniques should work across platforms and Nu has first-class support for Windows, macOS, and Linux.
-
Nu ensures compatibility with existing platform-specific executables.
-
Nu's workflow and tools should have the usability expected of modern software in 2022 (and beyond).
-
Nu views data as either structured or unstructured. It is a structured shell like PowerShell.
-
Finally, Nu views data functionally. Rather than using mutation, pipelines act as a means to load, change, and save data without mutable state.
Officially Supported By
Please submit an issue or PR to be added to this list.
Contributing
See Contributing for details. Thanks to all the people who already contributed!
License
The project is made available under the MIT license. See the LICENSE file for more information.