[Context on
Discord](https://discord.com/channels/601130461678272522/855947301380947968/1219425984990806207)
# Description
- Rename `CustomValue::value_string()` to `type_name()` to reflect its
usage better.
- Change print behavior to always call `to_base_value()` first, to give
the custom value better control over the output.
- Change `describe --detailed` to show the type name as the subtype,
rather than trying to describe the base value.
- Change custom `Type` to use `type_name()` rather than `typetag_name()`
to make things like `PluginCustomValue` more transparent
One question: should `describe --detailed` still include a description
of the base value somewhere? I'm torn on it, it seems possibly useful
for some things (maybe sqlite databases?), but having `describe -d` not
include the custom type name anywhere felt weird. Another option would
be to add another method to `CustomValue` for info to be displayed in
`describe`, so that it can be more type-specific?
# User-Facing Changes
Everything above has implications for printing and `describe` on custom
values
# Tests + Formatting
- 🟢 `toolkit fmt`
- 🟢 `toolkit clippy`
- 🟢 `toolkit test`
- 🟢 `toolkit test stdlib`
# Description
Adds support for the following operations on plugin custom values, in
addition to `to_base_value` which was already present:
- `follow_path_int()`
- `follow_path_string()`
- `partial_cmp()`
- `operation()`
- `Drop` (notification, if opted into with
`CustomValue::notify_plugin_on_drop`)
There are additionally customizable methods within the `Plugin` and
`StreamingPlugin` traits for implementing these functions in a way that
requires access to the plugin state, as a registered handle model such
as might be used in a dataframes plugin would.
`Value::append` was also changed to handle custom values correctly.
# User-Facing Changes
- Signature of `CustomValue::follow_path_string` and
`CustomValue::follow_path_int` changed to give access to the span of the
custom value itself, useful for some errors.
- Plugins using custom values have to be recompiled because the engine
will try to do custom value operations that aren't supported
- Plugins can do more things 🎉
# Tests + Formatting
Tests were added for all of the new custom values functionality.
- 🟢 `toolkit fmt`
- 🟢 `toolkit clippy`
- 🟢 `toolkit test`
- 🟢 `toolkit test stdlib`
# After Submitting
- [ ] Document protocol reference `CustomValueOp` variants:
- [ ] `FollowPathInt`
- [ ] `FollowPathString`
- [ ] `PartialCmp`
- [ ] `Operation`
- [ ] `Dropped`
- [ ] Document `notify_on_drop` optional field in `PluginCustomValue`
# Description
This PR renames the conversion functions on `Value` to be more consistent.
It follows the Rust [API guidelines](https://rust-lang.github.io/api-guidelines/naming.html#ad-hoc-conversions-follow-as_-to_-into_-conventions-c-conv) for ad-hoc conversions.
The conversion functions on `Value` now come in a few forms:
- `coerce_{type}` takes a `&Value` and attempts to convert the value to
`type` (e.g., `i64` are converted to `f64`). This is the old behavior of
some of the `as_{type}` functions -- these functions have simply been
renamed to better reflect what they do.
- The new `as_{type}` functions take a `&Value` and returns an `Ok`
result only if the value is of `type` (no conversion is attempted). The
returned value will be borrowed if `type` is non-`Copy`, otherwise an
owned value is returned.
- `into_{type}` exists for non-`Copy` types, but otherwise does not
attempt conversion just like `as_type`. It takes an owned `Value` and
always returns an owned result.
- `coerce_into_{type}` has the same relationship with `coerce_{type}` as
`into_{type}` does with `as_{type}`.
- `to_{kind}_string`: conversion to different string formats (debug,
abbreviated, etc.). Only two of the old string conversion functions were
removed, the rest have been renamed only.
- `to_{type}`: other conversion functions. Currently, only `to_path`
exists. (And `to_string` through `Display`.)
This table summaries the above:
| Form | Cost | Input Ownership | Output Ownership | Converts `Value`
case/`type` |
| ---------------------------- | ----- | --------------- |
---------------- | -------- |
| `as_{type}` | Cheap | Borrowed | Borrowed/Owned | No |
| `into_{type}` | Cheap | Owned | Owned | No |
| `coerce_{type}` | Cheap | Borrowed | Borrowed/Owned | Yes |
| `coerce_into_{type}` | Cheap | Owned | Owned | Yes |
| `to_{kind}_string` | Expensive | Borrowed | Owned | Yes |
| `to_{type}` | Expensive | Borrowed | Owned | Yes |
# User-Facing Changes
Breaking API change for `Value` in `nu-protocol` which is exposed as
part of the plugin API.
# Description
Bump polars from 0.36 to 0.37
# User-Facing Changes
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# Tests + Formatting
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# Description
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Fixes https://github.com/nushell/nushell/issues/11716
The problem is in our [record creation
API](0d518bf813/crates/nu-protocol/src/value/record.rs (L33))
which panics if the numbers of columns and values are different. I added
a safe variant that returns a `Result` and used it in the `rotate`
command.
## TODO in another PR:
Go through all `from_raw_cols_vals_unchecked()` (this includes the
`record!` macro which uses the unchecked version) and make sure that
either
a) it is guaranteed the number of cols and vals is the same, or
b) convert the call to `from_raw_cols_vals()`
Reason: Nushell should never panic.
# User-Facing Changes
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# Description
There are times where explicitly specifying a schema for a dataframe is
needed such as:
- Opening CSV and JSON lines files and needing provide more information
to polars to keep it from failing or in a desire to override default
type conversion
- When converting a nushell value to a dataframe and wanting to override
the default conversion behaviors.
This pull requests provides:
- A flag to allow specifying a schema when using dfr into-df
- A flag to allow specifying a schema when using dfr open that works for
CSV and JSON types
- A new command `dfr schema` which displays schema information and will
allow display support schema dtypes
Schema is specified creating a record that has the key value and the
dtype. Examples usages:
```
{a:1, b:{a:2}} | dfr into-df -s {a: u8, b: {a: i32}} | dfr schema
{a: 1, b: {a: [1 2 3]}, c: [a b c]} | dfr into-df -s {a: u8, b: {a: list<u64>}, c: list<str>} | dfr schema
dfr open -s {pid: i32, ppid: i32, name: str, status: str, cpu: f64, mem: i64, virtual: i64} /tmp/ps.jsonl | dfr schema
```
Supported dtypes:
null
bool
u8
u16
u32
u64
i8
i16
i32
i64
f32
f64
str
binary
date
datetime[time_unit: (ms, us, ns) timezone (optional)]
duration[time_unit: (ms, us, ns)]
time
object
unknown
list[dtype]
structs are also supported but are specified via another record:
{a: u8, b: {d: str}}
Another feature with the dfr schema command is that it returns the data
back in a format that can be passed to provide a valid schema that can
be passed in as schema argument:
<img width="638" alt="Screenshot 2024-01-29 at 10 23 58"
src="https://github.com/nushell/nushell/assets/56345/b49c3bff-5cda-4c86-975a-dfd91d991373">
---------
Co-authored-by: Jack Wright <jack.wright@disqo.com>
# Description
* release notes
https://github.com/pola-rs/polars/releases/tag/rs-0.36.2
* dependencies
remove `sysinfo` 0.29.11
add `polars-compute` 0.36.2
# User-Facing Changes
[Change value_counts resulting column name from counts to
count](https://github.com/pola-rs/polars/pull/12506)
# Tests + Formatting
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# Description
Constructing the internals of `Record` without checking the lengths is
bad. (also incompatible with changes to how we store records)
- Use `Record::from_raw_cols_vals` in dataframe code
- Use `record!` macro in dataframe test
- Use `record!` in `nu-color-config` tests
- Stop direct record construction in `nu-command`
- Refactor table construction in `from nuon`
# User-Facing Changes
None
# Tests + Formatting
No new tests, updated tests in equal fashion
Second attempt at polars Struct support. This version avoid using unsafe
checks by cloning the StructArray and utilizing the into_static to
convert to a StructOwned.
---------
Co-authored-by: Jack Wright <jack.wright@disqo.com>
# Description
Replace `.to_string()` used in `GenericError` with `.into()` as
`.into()` seems more popular
Replace `Vec::new()` used in `GenericError` with `vec![]` as `vec![]`
seems more popular
(There are so, so many)
Reverts nushell/nushell#10943
The current implementation of `arr_to_value` is unsound, as it allows
casts of arbitrary data to arbitrary types without being marked
`unsafe`.
The full safety requirements to perform both the cast and the following
unchecked access are not as clear that a simple change of `fn
arr_to_value` to `unsafe fn arr_to_value` could be blessed without
further investigation.
cc @ayax79
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# Description
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Clippy fixes for rust 1.76.0-nightly
# User-Facing Changes
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helps us keep track of breaking changes. -->
N/A
# Tests + Formatting
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crates/nu-std"` to run the tests for the standard library
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Provides support for reading Polars structs. This allows opening of
supported files (jsonl, parquet, etc) that contain rows with structured
data.
The following attached json lines
file([receipts.jsonl.gz](https://github.com/nushell/nushell/files/13311476/receipts.jsonl.gz))
contains a customer column with structured data. This json lines file
can now be loaded via `dfr open` and will render as follows:
<img width="525" alt="Screenshot 2023-11-09 at 10 09 18"
src="https://github.com/nushell/nushell/assets/56345/4b26ccdc-c230-43ae-a8d5-8af88a1b72de">
This also addresses some cleanup of date handling and utilizing
timezones where provided.
This pull request only addresses reading data from polars structs. I
will address converting nushell data to polars structs in a future
request as this change is large enough as it is.
---------
Co-authored-by: Jack Wright <jack.wright@disqo.com>
# Description
This is easy to do with rust-analyzer, but I didn't want to just pump
these all out without feedback.
Part of #10700
# User-Facing Changes
None
# Tests + Formatting
- 🟢 `toolkit fmt`
- 🟢 `toolkit clippy`
- 🟢 `toolkit test`
- 🟢 `toolkit test stdlib`
# After Submitting
N/A
---------
Co-authored-by: Stefan Holderbach <sholderbach@users.noreply.github.com>
# Description
This PR cleans up some warnings on the latest chrono dependency.
# User-Facing Changes
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# Tests + Formatting
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# Description
We made the decision that our floating point type should be referred to
as `float` over `decimal`.
Commands were updated by #9979 and #10320
Now make the internal codebase consistent in referring to this data type
as `float`.
Work for #10332
# User-Facing Changes
`decimal` has been removed as a type name/symbol.
Instead of
```nushell
def foo [bar: decimal] decimal -> decimal {}
```
use
```nushell
def foo [bar: float] float -> float {}
```
Potential effect of `SyntaxShape`'s `Display` implementation now also
referring to `float` instead of `decimal`
# Details
- Rename `SyntaxShape::Decimal` to `Float`
- Update `Display for SyntaxShape` to `float`
- Update error message + fn name in dataframe code
- Fix docs in command examples
- Rename tests that are float specific
- Update doccomment on `SyntaxShape`
- Update comment in script
# Tests + Formatting
Updates the names of some tests
# Description
As part of the refactor to split spans off of Value, this moves to using
helper functions to create values, and using `.span()` instead of
matching span out of Value directly.
Hoping to get a few more helping hands to finish this, as there are a
lot of commands to update :)
# User-Facing Changes
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# Tests + Formatting
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---------
Co-authored-by: Darren Schroeder <343840+fdncred@users.noreply.github.com>
Co-authored-by: WindSoilder <windsoilder@outlook.com>
This addresses the warnings generated from using DateTime::from_utc.
DateTime::from_utc was deprecated as of chrono 0.4.27
Co-authored-by: Jack Wright <jack.wright@disqo.com>
# Description
This doesn't really do much that the user could see, but it helps get us
ready to do the steps of the refactor to split the span off of Value, so
that values can be spanless. This allows us to have top-level values
that can hold both a Value and a Span, without requiring that all values
have them.
We expect to see significant memory reduction by removing so many
unnecessary spans from values. For example, a table of 100,000 rows and
5 columns would have a savings of ~8megs in just spans that are almost
always duplicated.
# User-Facing Changes
Nothing yet
# Tests + Formatting
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# Description
This PR creates a new `Record` type to reduce duplicate code and
possibly bugs as well. (This is an edited version of #9648.)
- `Record` implements `FromIterator` and `IntoIterator` and so can be
iterated over or collected into. For example, this helps with
conversions to and from (hash)maps. (Also, no more
`cols.iter().zip(vals)`!)
- `Record` has a `push(col, val)` function to help insure that the
number of columns is equal to the number of values. I caught a few
potential bugs thanks to this (e.g. in the `ls` command).
- Finally, this PR also adds a `record!` macro that helps simplify
record creation. It is used like so:
```rust
record! {
"key1" => some_value,
"key2" => Value::string("text", span),
"key3" => Value::int(optional_int.unwrap_or(0), span),
"key4" => Value::bool(config.setting, span),
}
```
Since macros hinder formatting, etc., the right hand side values should
be relatively short and sweet like the examples above.
Where possible, prefer `record!` or `.collect()` on an iterator instead
of multiple `Record::push`s, since the first two automatically set the
record capacity and do less work overall.
# User-Facing Changes
Besides the changes in `nu-protocol` the only other breaking changes are
to `nu-table::{ExpandedTable::build_map, JustTable::kv_table}`.
# Description
- Adds support for conversion between nushell lists and polars lists
instead of treating them as a polars object.
- Fixed explode and flatten to work both as expressions or lazy
dataframe commands. The previous item was required to make this work.
---------
Co-authored-by: Jack Wright <jack.wright@disqo.com>
Co-authored-by: Darren Schroeder <343840+fdncred@users.noreply.github.com>
# Description
Today the only way to extract date parts from a dfr series is the dfr
get-* set of commands. These create a new dataframe with just the
datepart in it, which is almost entirely useless. As far as I can tell
there's no way to append it as a series in the original dataframe. In
discussion with fdncred on Discord we decided the best route was to add
an expression for modifying columns created in dfr with-column. These
are the way you manipulate series within a data frame.
I'd like feedback on this approach - I think it's a fair way to handle
things. An example to test it would be:
```[[ record_time]; [ (date now)]] | dfr into-df | dfr with-column [ ((dfr col record_time) | dfr datepart nanosecond | dfr as "ns" ), (dfr col record_time | dfr datepart second | dfr as "s"), (dfr col record_time | dfr datepart minute | dfr as "m"), (dfr col record_time | dfr datepart hour | dfr as "h") ]```
I'm also proposing we deprecate the dfr get-* commands. I've not been able to figure out any meaningful way they could ever be useful, and this approach makes more sense by attaching the extracted date part to the row in the original dataframe as a new column.
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# User-Facing Changes
add in dfr datepart as an expression
<!-- List of all changes that impact the user experience here. This helps us keep track of breaking changes. -->
# Tests + Formatting
Need to add some better assertive tests. I'm also not sure how to properly write the test_dataframe at the bottom, but will revisit as part of this PR. Wanted to get feedback early.
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---------
Co-authored-by: Robert Waugh <robert@waugh.io>
# Description
Fixes the clippy warnings we're about to get hit with next time we
upgrade Rust.
The big one was shrinking ShellError and related under 128 bytes.
# User-Facing Changes
Shouldn't notice much difference. In theory, we could see a tiny perf
improvement, but I didn't notice one.
# Tests + Formatting
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# After Submitting
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All of the dataframe commands ported over with no issues...
### 11 tests are commented out (for now)
So 100 of the original 111 tests are passing with only 11 tests being
ignored for now..
As per our conversation in the core team meeting on Wednesday
I took @jntrnr suggestion and just commented out the tests dealing
with
[IntoDatetime](https://github.com/nushell/nushell/blob/main/crates/nu-command/src/conversions/into/mod.rs)
Later on we can move this functionality out of nu-command if we decide
it makes sense...
### The following tests were ignored...
```rust
modified: crates/nu-cmd-dataframe/src/dataframe/series/date/get_day.rs
modified: crates/nu-cmd-dataframe/src/dataframe/series/date/get_hour.rs
modified: crates/nu-cmd-dataframe/src/dataframe/series/date/get_minute.rs
modified: crates/nu-cmd-dataframe/src/dataframe/series/date/get_month.rs
modified: crates/nu-cmd-dataframe/src/dataframe/series/date/get_nanosecond.rs
modified: crates/nu-cmd-dataframe/src/dataframe/series/date/get_ordinal.rs
modified: crates/nu-cmd-dataframe/src/dataframe/series/date/get_second.rs
modified: crates/nu-cmd-dataframe/src/dataframe/series/date/get_week.rs
modified: crates/nu-cmd-dataframe/src/dataframe/series/date/get_weekday.rs
modified: crates/nu-cmd-dataframe/src/dataframe/series/date/get_year.rs
modified: crates/nu-cmd-dataframe/src/dataframe/series/string/strftime.rs
```
