14d1c67863
<!-- if this PR closes one or more issues, you can automatically link the PR with them by using one of the [*linking keywords*](https://docs.github.com/en/issues/tracking-your-work-with-issues/linking-a-pull-request-to-an-issue#linking-a-pull-request-to-an-issue-using-a-keyword), e.g. - this PR should close #xxxx - fixes #xxxx you can also mention related issues, PRs or discussions! --> # Description <!-- Thank you for improving Nushell. Please, check our [contributing guide](../CONTRIBUTING.md) and talk to the core team before making major changes. Description of your pull request goes here. **Provide examples and/or screenshots** if your changes affect the user experience. --> This PR adds a new evaluator path with callbacks to a mutable trait object implementing a Debugger trait. The trait object can do anything, e.g., profiling, code coverage, step debugging. Currently, entering/leaving a block and a pipeline element is marked with callbacks, but more callbacks can be added as necessary. Not all callbacks need to be used by all debuggers; unused ones are simply empty calls. A simple profiler is implemented as a proof of concept. The debugging support is implementing by making `eval_xxx()` functions generic depending on whether we're debugging or not. This has zero computational overhead, but makes the binary slightly larger (see benchmarks below). `eval_xxx()` variants called from commands (like `eval_block_with_early_return()` in `each`) are chosen with a dynamic dispatch for two reasons: to not grow the binary size due to duplicating the code of many commands, and for the fact that it isn't possible because it would make Command trait objects object-unsafe. In the future, I hope it will be possible to allow plugin callbacks such that users would be able to implement their profiler plugins instead of having to recompile Nushell. [DAP](https://microsoft.github.io/debug-adapter-protocol/) would also be interesting to explore. Try `help debug profile`. ## Screenshots Basic output:  To profile with more granularity, increase the profiler depth (you'll see that repeated `is-windows` calls take a large chunk of total time, making it a good candidate for optimizing):  ## Benchmarks ### Binary size Binary size increase vs. main: **+40360 bytes**. _(Both built with `--release --features=extra,dataframe`.)_ ### Time ```nushell # bench_debug.nu use std bench let test = { 1..100 | each { ls | each {|row| $row.name | str length } } | flatten | math avg } print 'debug:' let res2 = bench { debug profile $test } --pretty print $res2 ``` ```nushell # bench_nodebug.nu use std bench let test = { 1..100 | each { ls | each {|row| $row.name | str length } } | flatten | math avg } print 'no debug:' let res1 = bench { do $test } --pretty print $res1 ``` `cargo run --release -- bench_debug.nu` is consistently 1--2 ms slower than `cargo run --release -- bench_nodebug.nu` due to the collection overhead + gathering the report. This is expected. When gathering more stuff, the overhead is obviously higher. `cargo run --release -- bench_nodebug.nu` vs. `nu bench_nodebug.nu` I didn't measure any difference. Both benchmarks report times between 97 and 103 ms randomly, without one being consistently higher than the other. This suggests that at least in this particular case, when not running any debugger, there is no runtime overhead. ## API changes This PR adds a generic parameter to all `eval_xxx` functions that forces you to specify whether you use the debugger. You can resolve it in two ways: * Use a provided helper that will figure it out for you. If you wanted to use `eval_block(&engine_state, ...)`, call `let eval_block = get_eval_block(&engine_state); eval_block(&engine_state, ...)` * If you know you're in an evaluation path that doesn't need debugger support, call `eval_block::<WithoutDebug>(&engine_state, ...)` (this is the case of hooks, for example). I tried to add more explanation in the docstring of `debugger_trait.rs`. ## TODO - [x] Better profiler output to reduce spam of iterative commands like `each` - [x] Resolve `TODO: DEBUG` comments - [x] Resolve unwraps - [x] Add doc comments - [x] Add usage and extra usage for `debug profile`, explaining all columns # User-Facing Changes <!-- List of all changes that impact the user experience here. This helps us keep track of breaking changes. --> Hopefully none. # Tests + Formatting <!-- Don't forget to add tests that cover your changes. Make sure you've run and fixed any issues with these commands: - `cargo fmt --all -- --check` to check standard code formatting (`cargo fmt --all` applies these changes) - `cargo clippy --workspace -- -D warnings -D clippy::unwrap_used` to check that you're using the standard code style - `cargo test --workspace` to check that all tests pass (on Windows make sure to [enable developer mode](https://learn.microsoft.com/en-us/windows/apps/get-started/developer-mode-features-and-debugging)) - `cargo run -- -c "use std testing; testing run-tests --path crates/nu-std"` to run the tests for the standard library > **Note** > from `nushell` you can also use the `toolkit` as follows > ```bash > use toolkit.nu # or use an `env_change` hook to activate it automatically > toolkit check pr > ``` --> # After Submitting <!-- If your PR had any user-facing changes, update [the documentation](https://github.com/nushell/nushell.github.io) after the PR is merged, if necessary. This will help us keep the docs up to date. --> |
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| .cargo | ||
| .githooks | ||
| .github | ||
| assets | ||
| benches | ||
| crates | ||
| devdocs | ||
| docker | ||
| scripts | ||
| src | ||
| tests | ||
| wix | ||
| .gitattributes | ||
| .gitignore | ||
| Cargo.lock | ||
| Cargo.toml | ||
| 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.