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# Description
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This PR seeks to add a quality-of-life feature that enables date and
datetime parsing of strings in `polars into-df`, `polars into-lazy`, and
`polars open`, and avoid the more verbose method of casting each column
into date/datetime. Currently, setting the schema to `date` on a `str`
column would silently error as a null column. See a comparison of the
current and proposed implementations.
The proposed implementation assumes a date format "%Y-%m-%d" and a
datetime format of "%Y-%m-%d %H:%M:%S" for naive datetimes and "%Y-%m-%d
%H:%M:%S%:z" for timezone-aware datetimes. Other formats must be
specified via parsing through `polars as-date` and `polars as-datetime`.
```nushell
# Current Implementations
> [[a]; ["2025-04-01"]] | polars into-df --schema {a: date}
╭───┬───╮
│ # │ a │
├───┼───┤
│ 0 │ │
╰───┴───╯
> [[a]; ["2025-04-01 01:00:00"]] | polars into-df --schema {a: "datetime<ns,*>"}
╭───┬───╮
│ # │ a │
├───┼───┤
│ 0 │ │
╰───┴───╯
# Proposed Implementation
> [[a]; ["2025-04-01"]] | polars into-df --schema {a: date}
╭───┬─────────────────────╮
│ # │ a │
├───┼─────────────────────┤
│ 0 │ 04/01/25 12:00:00AM │
╰───┴─────────────────────╯
> [[a]; ["2025-04-01 01:00:00"]] | polars into-df --schema {a: "datetime<ns,*>"}
╭───┬─────────────────────╮
│ # │ a │
├───┼─────────────────────┤
│ 0 │ 04/01/25 01:00:00AM │
╰───┴─────────────────────╯
> [[a]; ["2025-04-01 01:00:00-04:00"]] | polars into-df --schema {a: "datetime<ns,UTC>"}
╭───┬─────────────────────╮
│ # │ a │
├───┼─────────────────────┤
│ 0 │ 04/01/25 05:00:00AM │
╰───┴─────────────────────╯
```
# User-Facing Changes
<!-- List of all changes that impact the user experience here. This
helps us keep track of breaking changes. -->
No breaking changes. Users have the added option to parse string columns
into date/datetimes.
# Tests + Formatting
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The current implementation improperly inverts the conversion from
nanoseconds to the specified time units, resulting in nonsensical
Datetime and Duration parsing and integer overflows when the specified
time unit is not nanoseconds. This PR seeks to correct this conversion
by changing the multiplication to an integer division. Below are
examples highlighting the current and proposed implementations.
## Current Implementation
Specifying a different time unit incorrectly changes the returned value.
```nushell
> [[a]; [2024-04-01]] | polars into-df --schema {a: "datetime<ns,UTC>"}
╭───┬───────────────────────╮
│ # │ a │
├───┼───────────────────────┤
│ 0 │ 04/01/2024 12:00:00AM │
> [[a]; [2024-04-01]] | polars into-df --schema {a: "datetime<ms,UTC>"}
╭───┬───────────────────────╮
│ # │ a │
├───┼───────────────────────┤
│ 0 │ 06/27/2035 11:22:33PM │ <-- changing the time unit should not change the actual value
> [[a]; [1day]] | polars into-df --schema {a: "duration<ns>"}
╭───┬────────────────╮
│ # │ a │
├───┼────────────────┤
│ 0 │ 86400000000000 │
╰───┴────────────────╯
> [[a]; [1day]] | polars into-df --schema {a: "duration<ms>"}
╭───┬──────────────────────╮
│ # │ a │
├───┼──────────────────────┤
│ 0 │ -5833720368547758080 │ <-- i64 overflow
╰───┴──────────────────────╯
```
## Proposed Implementation
```nushell
> [[a]; [2024-04-01]] | polars into-df --schema {a: "datetime<ns,UTC>"}
╭───┬───────────────────────╮
│ # │ a │
├───┼───────────────────────┤
│ 0 │ 04/01/2024 12:00:00AM │
╰───┴───────────────────────╯
> [[a]; [2024-04-01]] | polars into-df --schema {a: "datetime<ms,UTC>"}
╭───┬───────────────────────╮
│ # │ a │
├───┼───────────────────────┤
│ 0 │ 04/01/2024 12:00:00AM │
╰───┴───────────────────────╯
> [[a]; [1day]] | polars into-df --schema {a: "duration<ns>"}
╭───┬────────────────╮
│ # │ a │
├───┼────────────────┤
│ 0 │ 86400000000000 │
╰───┴────────────────╯
> [[a]; [1day]] | polars into-df --schema {a: "duration<ms>"}
╭───┬──────────╮
│ # │ a │
├───┼──────────┤
│ 0 │ 86400000 │
╰───┴──────────╯
```
# User-Facing Changes
<!-- List of all changes that impact the user experience here. This
helps us keep track of breaking changes. -->
No user-facing breaking change.
Developer breaking change: to mitigate the silent overflow in
nanoseconds conversion functions `nanos_from_timeunit` and
`nanos_to_timeunit` (new), the function signatures were changed from
`i64` to `Result<i64, ShellError>`.
# Tests + Formatting
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No additional examples were added, but I'd be happy to add a few if
needed. The covering tests just didn't fit well into any examples.
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# Description
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This PR enables the option to set a column type to `decimal` in the
`--schema` parameter of `polars into-df` and `polars into-lazy`
commands. This option was already available in `polars open`, which used
the underlying polars io commands that already accounted for decimal
types when specified in the schema.
See below for a comparison of the current and proposed implementation.
```nushell
# Current Implementation
> [[a b]; [1 1.618]]| polars into-df -s {a: u8, b: 'decimal<4,3>'}
Error: × Error creating dataframe: Unsupported type: Decimal(Some(4), Some(3))
# Proposed Implementation
> [[a b]; [1 1.618]]| polars into-df -s {a: u8, b: 'decimal<4,3>'} | polars schema
╭───┬──────────────╮
│ a │ u8 │
│ b │ decimal<4,3> │
╰───┴──────────────╯
```
# User-Facing Changes
<!-- List of all changes that impact the user experience here. This
helps us keep track of breaking changes. -->
No breaking change. Users has the new option to specify decimal in
`--schema` in `polars into-df` and `polars into-lazy`.
# Tests + Formatting
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An example in `polars into-df` was modified to showcase the decimal
type.
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Contrary to the underlying implementation in polars rust/python, `polars
pivot` throws an error if the user tries to pivot on multiple columns of
different types. This PR seeks to remove this type-check. See comparison
below.
```nushell
# Current implementation: throws error when pivoting on multiple values of different types.
> [[name subject date test_1 test_2 grade_1 grade_2]; [Cady maths 2025-04-01 98 100 A A] [Cady physics 2025-04-01 99 100 A A] [Karen maths 2025-04-02 61 60 D D] [Karen physics 2025-04-02 58 60 D D]] | polars into-df | polars pivot --on [subject] --index [name] --values [test_1 grade_1]
Error: × Merge error
╭─[entry #291:1:271]
1 │ [[name subject date test_1 test_2 grade_1 grade_2]; [Cady maths 2025-04-01 98 100 A A] [Cady physics 2025-04-01 99 100 A A] [Karen maths 2025-04-02 61 60 D D] [Karen physics 2025-04-02 58 60 D D]] | polars into-df | polars pivot --on [subject] --index [name] --values [test_1 grade_1]
· ───────┬──────
· ╰── found different column types in list
╰────
help: datatypes i64 and str are incompatible
# Proposed implementation
> [[name subject date test_1 test_2 grade_1 grade_2]; [Cady maths 2025-04-01 98 100 A A] [Cady physics 2025-04-01 99 100 A A] [Karen maths 2025-04-02 61 60 D D] [Karen physics 2025-04-02 58 60 D D]] | polars into-df | polars pivot --on [subject] --index [name] --values [test_1 grade_1]
╭───┬───────┬──────────────┬────────────────┬───────────────┬─────────────────╮
│ # │ name │ test_1_maths │ test_1_physics │ grade_1_maths │ grade_1_physics │
├───┼───────┼──────────────┼────────────────┼───────────────┼─────────────────┤
│ 0 │ Cady │ 98 │ 99 │ A │ A │
│ 1 │ Karen │ 61 │ 58 │ D │ D │
╰───┴───────┴──────────────┴────────────────┴───────────────┴─────────────────╯
```
Additionally, this PR ports over the `separator` parameter in `pivot`,
which allows the user to specify how to delimit multiple `values` column
names:
```nushell
> [[name subject date test_1 test_2 grade_1 grade_2]; [Cady maths 2025-04-01 98 100 A A] [Cady physics 2025-04-01 99 100 A A] [Karen maths 2025-04-02 61 60 D D] [Karen physics 2025-04-02 58 60 D D]] | polars into-df | polars pivot --on [subject] --index [name] --values [test_1 grade_1] --separator /
╭───┬───────┬──────────────┬────────────────┬───────────────┬─────────────────╮
│ # │ name │ test_1/maths │ test_1/physics │ grade_1/maths │ grade_1/physics │
├───┼───────┼──────────────┼────────────────┼───────────────┼─────────────────┤
│ 0 │ Cady │ 98 │ 99 │ A │ A │
│ 1 │ Karen │ 61 │ 58 │ D │ D │
╰───┴───────┴──────────────┴────────────────┴───────────────┴─────────────────╯
```
# User-Facing Changes
<!-- List of all changes that impact the user experience here. This
helps us keep track of breaking changes. -->
Soft breaking change: where a user may have previously expected an error
(pivoting on multiple columns with different types), no error is thrown.
# Tests + Formatting
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Examples were added to `polars pivot`.
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This PR is a follow-up to the previous PR #15557 and part of a wider
campaign to enable certain polars commands that only operated on the
entire dataframe to also operate on expressions. Here, we enable two
commands `polars as-date` and `polars as-datetime` to receive
expressions as inputs so that they may be used on specific columns in a
dataframe with multiple columns of different types. See examples below.
```nushell
> [[a b]; ["2025-04-01" 1] ["2025-04-02" 2] ["2025-04-03" 3]] | polars into-df | polars select (polars col a | polars as-date %Y-%m-%d) b | polars collect
╭───┬───────────────────────┬───╮
│ # │ a │ b │
├───┼───────────────────────┼───┤
│ 0 │ 04/01/2025 12:00:00AM │ 1 │
│ 1 │ 04/02/2025 12:00:00AM │ 2 │
│ 2 │ 04/03/2025 12:00:00AM │ 3 │
╰───┴───────────────────────┴───╯
> seq date -b 2025-04-01 --periods 4 --increment 25min -o "%Y-%m-%d %H:%M:%S" | polars into-df | polars select (polars col 0 | polars as-datetime "%Y-%m-%d %H:%M:%S") | polars collect
╭───┬───────────────────────╮
│ # │ 0 │
├───┼───────────────────────┤
│ 0 │ 04/01/2025 12:00:00AM │
│ 1 │ 04/01/2025 12:25:00AM │
│ 2 │ 04/01/2025 12:50:00AM │
│ 3 │ 04/01/2025 01:15:00AM │
╰───┴───────────────────────╯
```
# User-Facing Changes
<!-- List of all changes that impact the user experience here. This
helps us keep track of breaking changes. -->
No breaking changes. Users have the additional option to use `polars
as-date` and `polars as-datetime` in expressions that operate on
specific columns.
# Tests + Formatting
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Examples have been added to `polars as-date` and `polars as-datetime`.
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This PR fixes an issue where, for custom values, the `//` operator was
incorrectly mapped to `Math::Divide` instead of `Math::FloorDivide`.
This PR also fixes the same mis-mapping in the `polars` plugin.
```nushell
> [[a b c]; [x 1 1.1] [y 2 2.2] [z 3 3.3]] | polars into-df | polars select {div: ((polars col c) / (polars col b)), floor_div: ((polars col c) // (polars col b))} | polars collect
╭───┬───────┬───────────╮
│ # │ div │ floor_div │
├───┼───────┼───────────┤
│ 0 │ 1.100 │ 1.000 │
│ 1 │ 1.100 │ 1.000 │
│ 2 │ 1.100 │ 1.000 │
╰───┴───────┴───────────╯
```
**Note:** the number of line changes in this PR is inflated because of
auto-formatting in `nu_plugin_polars/Cargo.toml`. Substantively, I've
only added the `round_series` feature to the polars dependency list.
# User-Facing Changes
<!-- List of all changes that impact the user experience here. This
helps us keep track of breaking changes. -->
Breaking change: users who expected the operator `//` to function the
same as `/` for custom values will not get the expected result.
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No tests were yet added, but let me know if we should put something into
one of the polars examples.
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This PR adds the exponent operator ("**") to polars expressions.
```nushell
> [[a b]; [6 2] [4 2] [2 2]] | polars into-df | polars select a b {c: ((polars col a) ** 2)}
╭───┬───┬───┬────╮
│ # │ a │ b │ c │
├───┼───┼───┼────┤
│ 0 │ 6 │ 2 │ 36 │
│ 1 │ 4 │ 2 │ 16 │
│ 2 │ 2 │ 2 │ 4 │
╰───┴───┴───┴────╯
```
# User-Facing Changes
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helps us keep track of breaking changes. -->
No breaking changes. Users are enabled to use the `**` operator in
polars expressions.
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mode](https://learn.microsoft.com/en-us/windows/apps/get-started/developer-mode-features-and-debugging))
- `cargo run -- -c "use toolkit.nu; toolkit test stdlib"` 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
> ```
-->
An example in `polars select` was modified to showcase the `**`
operator.
# After Submitting
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# Description
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This PR seeks to expand `polars col` functionality to allow selecting
multiple columns and columns by type, which is particularly useful when
piping to subsequent expressions that should be applied to each column
selected (e.g., `polars col int --type | polars sum` as a shorthand for
`[(polars col a | polars sum), (polars col b | polars sum)]`). See
examples below.
```nushell
# Select multiple columns (cannot be used with asterisk wildcard)
> [[a b c]; [x 1 1.1] [y 2 2.2] [z 3 3.3]] | polars into-df
| polars select (polars col b c | polars sum) | polars collect
╭───┬───┬──────╮
│ # │ b │ c │
├───┼───┼──────┤
│ 0 │ 6 │ 6.60 │
╰───┴───┴──────╯
# Select multiple columns by types (cannot be used with asterisk wildcard)
> [[a b c]; [x o 1.1] [y p 2.2] [z q 3.3]] | polars into-df
| polars select (polars col str f64 --type | polars max) | polars collect
╭───┬───┬───┬──────╮
│ # │ a │ b │ c │
├───┼───┼───┼──────┤
│ 0 │ z │ q │ 3.30 │
╰───┴───┴───┴──────╯
```
# User-Facing Changes
<!-- List of all changes that impact the user experience here. This
helps us keep track of breaking changes. -->
No breaking changes. Users have the additional capability to select
multiple columns in `polars col`.
# Tests + Formatting
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Make sure you've run and fixed any issues with these commands:
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Examples have been added to `polars col`.
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# Description
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This PR lifts the constraint that expressions in the `polars group-by`
command must be limited only to the type `Expr::Column` rather than most
`Expr` types, which is what the underlying polars crate allows. This
change enables more complex expressions to group by.
In the example below, we group by even or odd days of column `a`. While
we can reach the same result by creating and grouping by a new column in
two separate steps, integrating these steps in a single group-by allows
for better delegation to the polars optimizer.
```nushell
# Group by an expression and perform an aggregation
> [[a b]; [2025-04-01 1] [2025-04-02 2] [2025-04-03 3] [2025-04-04 4]]
| polars into-lazy
| polars group-by (polars col a | polars get-day | $in mod 2)
| polars agg [
(polars col b | polars min | polars as "b_min")
(polars col b | polars max | polars as "b_max")
(polars col b | polars sum | polars as "b_sum")
]
| polars collect
| polars sort-by a
╭───┬───┬───────┬───────┬───────╮
│ # │ a │ b_min │ b_max │ b_sum │
├───┼───┼───────┼───────┼───────┤
│ 0 │ 0 │ 2 │ 4 │ 6 │
│ 1 │ 1 │ 1 │ 3 │ 4 │
╰───┴───┴───────┴───────┴───────╯
```
# User-Facing Changes
<!-- List of all changes that impact the user experience here. This
helps us keep track of breaking changes. -->
No breaking changes. The user is empowered to use more complex
expressions in `polars group-by`
# Tests + Formatting
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An example is added to `polars group-by`.
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# Description
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This PR directly ports the polars function `polars.Expr.dt.truncate`
(https://docs.pola.rs/api/python/stable/reference/expressions/api/polars.Expr.dt.truncate.html),
which rounds a datetime to an arbitrarily specified period length. This
function is particularly useful when rounding to variable period lengths
such as months or quarters. See below for examples.
```nushell
# Truncate a series of dates by period length
> seq date -b 2025-01-01 --periods 4 --increment 6wk -o "%Y-%m-%d %H:%M:%S" | polars into-df | polars as-datetime "%F %H:%M:%S" --naive | polars select datetime (polars col datetime | polars truncate 5d37m | polars as truncated) | polars collect
╭───┬───────────────────────┬───────────────────────╮
│ # │ datetime │ truncated │
├───┼───────────────────────┼───────────────────────┤
│ 0 │ 01/01/2025 12:00:00AM │ 12/30/2024 04:49:00PM │
│ 1 │ 02/12/2025 12:00:00AM │ 02/08/2025 09:45:00PM │
│ 2 │ 03/26/2025 12:00:00AM │ 03/21/2025 02:41:00AM │
│ 3 │ 05/07/2025 12:00:00AM │ 05/05/2025 08:14:00AM │
╰───┴───────────────────────┴───────────────────────╯
# Truncate based on period length measured in quarters and months
> seq date -b 2025-01-01 --periods 4 --increment 6wk -o "%Y-%m-%d %H:%M:%S" | polars into-df | polars as-datetime "%F %H:%M:%S" --naive | polars select datetime (polars col datetime | polars truncate 1q5mo | polars as truncated) | polars collect
╭───┬───────────────────────┬───────────────────────╮
│ # │ datetime │ truncated │
├───┼───────────────────────┼───────────────────────┤
│ 0 │ 01/01/2025 12:00:00AM │ 09/01/2024 12:00:00AM │
│ 1 │ 02/12/2025 12:00:00AM │ 09/01/2024 12:00:00AM │
│ 2 │ 03/26/2025 12:00:00AM │ 09/01/2024 12:00:00AM │
│ 3 │ 05/07/2025 12:00:00AM │ 05/01/2025 12:00:00AM │
╰───┴───────────────────────┴───────────────────────╯
```
# User-Facing Changes
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helps us keep track of breaking changes. -->
No breaking changes. This PR introduces a new command `polars truncate`
# Tests + Formatting
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> ```
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Example test was added.
# After Submitting
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# Description
Performing a `polars collect` on an eager dataframe should be a no-op
operation. However, when used with a pipeline and not saving to a value
a cache error occurs. This addresses that cache error.
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# Description
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This PR fixes the bug where various commands that cast a column as a
`date` type would return `datetime<ns>` rather than the intended type
`date`. Affected commands include `polars into-df --schema`, `polars
into-lazy --schema`, `polars as-date`, and `polars cast date`.
This bug derives from the fact that Nushell uses the `date` type to
denote a datetime type whereas polars differentiates between `Date` and
`Datetime` types. By default, this PR retains the behavior that a
Nushell `date` type will be mapped to a polars `Datetime<ns>` unless
otherwise specified.
```nushell
# Current (erroneous) implementation
> [[a]; [2025-03-20]] | polars into-df --schema {a: "date"} | polars schema
╭───┬──────────────╮
│ a │ datetime<ns> │
╰───┴──────────────╯
# Fixed implementation
> [[a]; [2025-03-20]] | polars into-df --schema {a: "date"} | polars schema
╭───┬──────╮
│ a │ date │
╰───┴──────╯
# Fixed implementation: by default, Nushell dates map to datetime<ns>
> [[a]; [2025-03-20]] | polars into-df | polars schema
╭───┬───────────────────╮
│ a │ datetime<ns, UTC> │
╰───┴───────────────────╯
```
# User-Facing Changes
<!-- List of all changes that impact the user experience here. This
helps us keep track of breaking changes. -->
Soft breaking change: users previously who wanted to cast a date column
to type `date` can now expect the output to be type `date` instead of
`datetime<ns>`.
# Tests + Formatting
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Example test added to `polars as-date` command.
# After Submitting
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# Description
Output type of `polars schema` signature output type is of dataframe. It
should be of type record.
# User-Facing Changes
- `polars schema` - how has an output type of record
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# Description
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This PR seeks to simplify the syntax for commands that handle a list of
expressions (e.g., `select`, `with-column`, and `agg`) by enabling the
user to replace a list of expressions each aliased with `polars as` to a
single record where the key is the alias for the value. See below for
examples in several contexts.
```nushell
# Select a column from a dataframe using a record
> [[a b]; [6 2] [4 2] [2 2]] | polars into-df | polars select {c: ((polars col a) * 2)}
╭───┬────╮
│ # │ c │
├───┼────┤
│ 0 │ 12 │
│ 1 │ 8 │
│ 2 │ 4 │
╰───┴────╯
# Select a column from a dataframe using a mix of expressions and record of expressions
> [[a b]; [6 2] [4 2] [2 2]] | polars into-df | polars select a b {c: ((polars col a) * 2)}
╭───┬───┬───┬────╮
│ # │ a │ b │ c │
├───┼───┼───┼────┤
│ 0 │ 6 │ 2 │ 12 │
│ 1 │ 4 │ 2 │ 8 │
│ 2 │ 2 │ 2 │ 4 │
╰───┴───┴───┴────╯
# Add series to the dataframe using a record
> [[a b]; [1 2] [3 4]]
| polars into-lazy
| polars with-column {
c: ((polars col a) * 2)
d: ((polars col a) * 3)
}
| polars collect
╭───┬───┬───┬───┬───╮
│ # │ a │ b │ c │ d │
├───┼───┼───┼───┼───┤
│ 0 │ 1 │ 2 │ 2 │ 3 │
│ 1 │ 3 │ 4 │ 6 │ 9 │
╰───┴───┴───┴───┴───╯
# Group by and perform an aggregation using a record
> [[a b]; [1 2] [1 4] [2 6] [2 4]]
| polars into-lazy
| polars group-by a
| polars agg {
b_min: (polars col b | polars min)
b_max: (polars col b | polars max)
b_sum: (polars col b | polars sum)
}
| polars collect
| polars sort-by a
╭───┬───┬───────┬───────┬───────╮
│ # │ a │ b_min │ b_max │ b_sum │
├───┼───┼───────┼───────┼───────┤
│ 0 │ 1 │ 2 │ 4 │ 6 │
│ 1 │ 2 │ 4 │ 6 │ 10 │
╰───┴───┴───────┴───────┴───────╯
```
# User-Facing Changes
<!-- List of all changes that impact the user experience here. This
helps us keep track of breaking changes. -->
No breaking changes. Users now can use a mix of lists of expressions and
records of expressions where previously only lists of expressions were
accepted (e.g., in `select`, `with-column`, and `agg`).
# Tests + Formatting
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Example tests were added to `select`, `with-column`, and `agg`.
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# Description
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Introducing a basic implementation of the polars expression for window
functions: `over`
(https://docs.pola.rs/api/python/stable/reference/expressions/api/polars.Expr.over.html).
Note that this PR only implements the default values for the sorting and
`mapping_strategy` parameters. Implementations for other values for
these parameters may be added in a future PR, as the demand arises.
```nushell
# Compute expression over an aggregation window
> [[a b]; [x 2] [x 4] [y 6] [y 4]]
| polars into-lazy
| polars select a (polars col b | polars cumulative sum | polars over a | polars as cum_b)
| polars collect
╭───┬───┬───────╮
│ # │ a │ cum_b │
├───┼───┼───────┤
│ 0 │ x │ 2 │
│ 1 │ x │ 6 │
│ 2 │ y │ 6 │
│ 3 │ y │ 10 │
╰───┴───┴───────╯
# Compute expression over an aggregation window where partitions are defined by expressions
> [[a b]; [x 2] [X 4] [Y 6] [y 4]]
| polars into-lazy
| polars select a (polars col b | polars cumulative sum | polars over (polars col a | polars lowercase) | polars as cum_b)
| polars collect
╭───┬───┬───────╮
│ # │ a │ cum_b │
├───┼───┼───────┤
│ 0 │ x │ 2 │
│ 1 │ X │ 6 │
│ 2 │ Y │ 6 │
│ 3 │ y │ 10 │
╰───┴───┴───────╯
```
# User-Facing Changes
<!-- List of all changes that impact the user experience here. This
helps us keep track of breaking changes. -->
No breaking changes. This PR seeks to add a new command only.
# Tests + Formatting
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Example tests are included.
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# Description
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This PR updates the following functions so they may also be used in a
polars expression:
- `polars get-day`
- `polars get-hour`
- `polars get-minute`
- `polars get-month`
- `polars get-nanosecond`
- `polars get-ordinal`
- `polars get-second`
- `polars get-week`
- `polars get-weekday`
- `polars get-year`
Below examples provide a comparison of the two contexts in which each of
these commands may be used:
```nushell
# Returns day from a date (current use case)
> let dt = ('2020-08-04T16:39:18+00:00' | into datetime --timezone 'UTC');
let df = ([$dt $dt] | polars into-df);
$df | polars get-day
╭───┬───╮
│ # │ 0 │
├───┼───┤
│ 0 │ 4 │
│ 1 │ 4 │
╰───┴───╯
# Returns day from a date in an expression (additional use case provided by this PR)
> let dt = ('2020-08-04T16:39:18+00:00' | into datetime --timezone 'UTC');
let df = ([$dt $dt] | polars into-df);
$df | polars select (polars col 0 | polars get-day)
╭───┬───╮
│ # │ 0 │
├───┼───┤
│ 0 │ 4 │
│ 1 │ 4 │
╰───┴───╯
```
# User-Facing Changes
<!-- List of all changes that impact the user experience here. This
helps us keep track of breaking changes. -->
No breaking changes. Each of these functions retains its current
behavior and gains the benefit that they can now be used in an
expression as well.
# Tests + Formatting
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- `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 toolkit.nu; toolkit test stdlib"` 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
> ```
-->
Tests have been added to each of the examples.
# After Submitting
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documentation](https://github.com/nushell/nushell.github.io) after the
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# Description
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guide](../CONTRIBUTING.md) and talk to the core team before making major
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This PR seeks to expand `polars lit` to handle additional nushell types:
Value::Date and Value::Duration. This change is especially relevant to
the `polars filter` command, where expressions would then directly
incorporate Value::Date and Value::Duration types as literals. See one
such example below.
```nushell
# Filter dataframe for rows where dt is within the last 2 days of the maximum dt value
> [[dt val]; [2025-04-01 1] [2025-04-02 2] [2025-04-03 3] [2025-04-04 4]] | polars into-df | polars filter ((polars col dt) > ((polars col dt | polars max | $in - 2day)))
╭───┬─────────────────────┬─────╮
│ # │ dt │ val │
├───┼─────────────────────┼─────┤
│ 0 │ 04/03/25 12:00:00AM │ 3 │
│ 1 │ 04/04/25 12:00:00AM │ 4 │
╰───┴─────────────────────┴─────╯
```
# User-Facing Changes
<!-- List of all changes that impact the user experience here. This
helps us keep track of breaking changes. -->
No breaking changes. Users now can directly access Value::Date and
Value::Duration types as literals in polars expressions.
# Tests + Formatting
<!--
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Make sure you've run and fixed any issues with these commands:
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- `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))
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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
> ```
-->
Several additional examples added to `polars lit` and `polars filter`
# After Submitting
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# Description
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This is a direct port of the python polars command `convert_time_zone`
(https://docs.pola.rs/api/python/stable/reference/series/api/polars.Series.dt.convert_time_zone.html).
Consistent with the rust/python implementation, naive datetimes are
treated as if they are in UTC time.
```nushell
# Convert timezone for timezone-aware datetime
> ["2025-04-10 09:30:00 -0400" "2025-04-10 10:30:00 -0400"] | polars into-df
| polars as-datetime "%Y-%m-%d %H:%M:%S %z"
| polars select (polars col datetime | polars convert-time-zone "Europe/Lisbon")
╭───┬───────────────────────╮
│ # │ datetime │
├───┼───────────────────────┤
│ 0 │ 04/10/2025 02:30:00PM │
│ 1 │ 04/10/2025 03:30:00PM │
╰───┴───────────────────────╯
# Timezone conversions for timezone-naive datetime will assume the original timezone is UTC
> ["2025-04-10 09:30:00" "2025-04-10 10:30:00"] | polars into-df
| polars as-datetime "%Y-%m-%d %H:%M:%S" --naive
| polars select (polars col datetime | polars convert-time-zone "America/New_York")
╭───┬───────────────────────╮
│ # │ datetime │
├───┼───────────────────────┤
│ 0 │ 04/10/2025 05:30:00AM │
│ 1 │ 04/10/2025 06:30:00AM │
╰───┴───────────────────────╯
```
# User-Facing Changes
<!-- List of all changes that impact the user experience here. This
helps us keep track of breaking changes. -->
No breaking changes. Users have access to a new command `polars
convert-time-zone`
# Tests + Formatting
<!--
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Make sure you've run and fixed any issues with these commands:
- `cargo fmt --all -- --check` to check standard code formatting (`cargo
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- `cargo test --workspace` to check that all tests pass (on Windows make
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mode](https://learn.microsoft.com/en-us/windows/apps/get-started/developer-mode-features-and-debugging))
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tests for the standard library
> **Note**
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> ```bash
> use toolkit.nu # or use an `env_change` hook to activate it
automatically
> toolkit check pr
> ```
-->
Example tests have been added.
# After Submitting
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# Description
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This PR seeks to add a direct port of the python polars
`replace_time_zone` command in the `dt` namespace
(https://docs.pola.rs/api/python/stable/reference/series/api/polars.Series.dt.replace_time_zone.html).
Please note: I opted for two keywords "dt" and "replace-time-zone" to
map directly with the implementation in both the rust and python
packages, but I'm open to simplifying it to just one keyword, or `polars
replace-time-zone`
```nushell
# Apply timezone to a naive datetime
> ["2021-12-30 00:00:00" "2021-12-31 00:00:00"] | polars into-df
| polars as-datetime "%Y-%m-%d %H:%M:%S" --naive
| polars select (polars col datetime | polars dt replace-time-zone "America/New_York")
╭───┬─────────────────────╮
│ # │ datetime │
├───┼─────────────────────┤
│ 0 │ 12/30/21 12:00:00AM │
│ 1 │ 12/31/21 12:00:00AM │
╰───┴─────────────────────╯
# Apply timezone with ambiguous datetime
> ["2025-11-02 00:00:00", "2025-11-02 01:00:00", "2025-11-02 02:00:00", "2025-11-02 03:00:00"]
| polars into-df
| polars as-datetime "%Y-%m-%d %H:%M:%S" --naive
| polars select (polars col datetime | polars dt replace-time-zone "America/New_York" --ambiguous null)
╭───┬─────────────────────╮
│ # │ datetime │
├───┼─────────────────────┤
│ 0 │ 11/02/25 12:00:00AM │
│ 1 │ │
│ 2 │ 11/02/25 02:00:00AM │
│ 3 │ 11/02/25 03:00:00AM │
╰───┴─────────────────────╯
# Apply timezone with nonexistent datetime
> ["2025-03-09 01:00:00", "2025-03-09 02:00:00", "2025-03-09 03:00:00", "2025-03-09 04:00:00"]
| polars into-df
| polars as-datetime "%Y-%m-%d %H:%M:%S" --naive
| polars select (polars col datetime | polars dt replace-time-zone "America/New_York" --nonexistent null)
╭───┬─────────────────────╮
│ # │ datetime │
├───┼─────────────────────┤
│ 0 │ 03/09/25 01:00:00AM │
│ 1 │ │
│ 2 │ 03/09/25 03:00:00AM │
│ 3 │ 03/09/25 04:00:00AM │
╰───┴─────────────────────╯
```
# User-Facing Changes
No breaking changes. The user will be able to access the new command.
# Tests + Formatting
See example tests.
# After Submitting
# Description
Introduces `polars into-schema` which allows converting Values such as
records to a schema. This implicitly happens when when passing records
into commands like `polars into-df` today. This allows you to convert to
a schema object ahead of time and reuse the schema object. This can be
useful for guaranteeing your schema object is correct.
```nu
> ❯ : let schema = ({name: str, type: str} | polars into-schema)
> ❯ : ls | select name type | polars into-lazy -s $schema | polars schema
╭──────┬─────╮
│ name │ str │
│ type │ str │
╰──────┴─────╯
```
# User-Facing Changes
- Introduces `polars into-schema` allowing records to be converted to
schema objects.
# Description
This pull request does a lot of the heavy lifting needed to supported
more complex dtypes like categorical dtypes. It introduces a new
CustomValue, NuDataType and makes NuSchema a full CustomValue. Further
more it introduces a new command `polars into-dtype` that allows a dtype
to be created. This can then be passed into schemas when they are
created.
```nu
> ❯ : let dt = ("str" | polars to-dtype)
> ❯ : [[a b]; ["one" "two"]] | polars into-df -s {a: $dt, b: str} | polars schema
╭───┬─────╮
│ a │ str │
│ b │ str │
╰───┴─────╯
```
# User-Facing Changes
- Introduces new command `polars into-dtype`, allows dtype variables to
be passed in during schema creation.
Bumps [indexmap](https://github.com/indexmap-rs/indexmap) from 2.8.0 to
2.9.0.
<details>
<summary>Changelog</summary>
<p><em>Sourced from <a
href="https://github.com/indexmap-rs/indexmap/blob/main/RELEASES.md">indexmap's
changelog</a>.</em></p>
<blockquote>
<h2>2.9.0 (2025-04-04)</h2>
<ul>
<li>Added a <code>get_disjoint_mut</code> method to
<code>IndexMap</code>, matching Rust 1.86's
<code>HashMap</code> method.</li>
<li>Added a <code>get_disjoint_indices_mut</code> method to
<code>IndexMap</code> and <code>map::Slice</code>,
matching Rust 1.86's <code>get_disjoint_mut</code> method on
slices.</li>
<li>Deprecated the <code>borsh</code> feature in favor of their own
<code>indexmap</code> feature,
solving a cyclic dependency that occured via
<code>borsh-derive</code>.</li>
</ul>
</blockquote>
</details>
<details>
<summary>Commits</summary>
<ul>
<li><a
href="1818d4140d"><code>1818d41</code></a>
Merge pull request <a
href="https://redirect.github.com/indexmap-rs/indexmap/issues/387">#387</a>
from cuviper/release-2.9.0</li>
<li><a
href="9f4998341b"><code>9f49983</code></a>
Release 2.9.0</li>
<li><a
href="582a90fda3"><code>582a90f</code></a>
Merge pull request <a
href="https://redirect.github.com/indexmap-rs/indexmap/issues/386">#386</a>
from cuviper/de-borsh</li>
<li><a
href="90117397b6"><code>9011739</code></a>
Deprecate the "borsh" feature</li>
<li><a
href="0a836e8648"><code>0a836e8</code></a>
Merge pull request <a
href="https://redirect.github.com/indexmap-rs/indexmap/issues/238">#238</a>
from NiklasJonsson/get_many_mut</li>
<li><a
href="434d7ac6d1"><code>434d7ac</code></a>
Avoid let-else for MSRV's sake</li>
<li><a
href="5be552d557"><code>5be552d</code></a>
Implement additional suggestions from review</li>
<li><a
href="4e1d8cef47"><code>4e1d8ce</code></a>
Address review feedback</li>
<li><a
href="5aec9ec674"><code>5aec9ec</code></a>
Implement get_disjoint_mut for arrays of keys</li>
<li><a
href="d10de30e74"><code>d10de30</code></a>
Merge pull request <a
href="https://redirect.github.com/indexmap-rs/indexmap/issues/385">#385</a>
from iajoiner/docs/macros</li>
<li>Additional commits viewable in <a
href="https://github.com/indexmap-rs/indexmap/compare/2.8.0...2.9.0">compare
view</a></li>
</ul>
</details>
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# Description
The current implementation of `polars into-df` and `polars into-lazy`
will throw an error if `--schema` is provided but not all columns are
defined. This PR seeks to remove this requirement so that when a partial
`--schema` is provided, the types on the defined columns are overridden
while the remaining columns take on their default types.
**Current Implementation**
```
$ [[a b]; [1 "foo"] [2 "bar"]] | polars into-df -s {a: str} | polars schema
Error: × Schema does not contain column: b
╭─[entry #88:1:12]
1 │ [[a b]; [1 "foo"] [2 "bar"]] | polars into-df -s {a: str} | polars schema
· ─────
╰────
```
**New Implementation (no error thrown on partial schema definition)**
Column b is not defined in `--schema`
```
$ [[a b]; [1 "foo"] [2 "bar"]] | polars into-df --schema {a: str} | polars schema
╭───┬─────╮
│ a │ str │
│ b │ str │
╰───┴─────╯
```
# User-Facing Changes
Soft breaking change: The user's previous (erroneous) code that would
have thrown an error would no longer throw an error. The user's previous
working code will still work.
# Tests + Formatting
# After Submitting
# Description
There are some clippy(version 0.1.86) errors on nushell repo. This pr is
trying to fix it.
# User-Facing Changes
Hopefully none.
# Tests + Formatting
NaN
# After Submitting
NaN
# Description
This PR seeks to fix an error in `polars as-datetime` where timezone
information is entirely ignored. This behavior raises a host of silent
errors when dealing with datetime conversions (see example below).
## Current Implementation
Timezones are entirely ignored and datetimes with different timezones
are converted to the same naive datetimes even when the user
specifically indicates that the timezone should be parsed. For example,
"2021-12-30 00:00:00 +0000" and "2021-12-30 00:00:00 -0400" will both be
parsed to "2021-12-30 00:00:00" even when the format string specifically
includes "%z".
```
$ ["2021-12-30 00:00:00 +0000" "2021-12-30 00:00:00 -0400"] | polars into-df | polars as-datetime "%Y-%m-%d %H:%M:%S %z"
╭───┬───────────────────────╮
│ # │ datetime │
├───┼───────────────────────┤
│ 0 │ 12/30/2021 12:00:00AM │
│ 1 │ 12/30/2021 12:00:00AM │ <-- Same datetime even though the first is +0000 and second is -0400
╰───┴───────────────────────╯
$ ["2021-12-30 00:00:00 +0000" "2021-12-30 00:00:00 -0400"] | polars into-df | polars as-datetime "%Y-%m-%d %H:%M:%S %z" | polars schema
╭──────────┬──────────────╮
│ datetime │ datetime<ns> │
╰──────────┴──────────────╯
```
## New Implementation
Datetimes are converted to UTC and timezone information is retained.
```
$ "2021-12-30 00:00:00 +0000" "2021-12-30 00:00:00 -0400"] | polars into-df | polars as-datetime "%Y-%m-%d %H:%M:%S %z"
╭───┬───────────────────────╮
│ # │ datetime │
├───┼───────────────────────┤
│ 0 │ 12/30/2021 12:00:00AM │
│ 1 │ 12/30/2021 04:00:00AM │ <-- Converted to UTC
╰───┴───────────────────────╯
$ ["2021-12-30 00:00:00 +0000" "2021-12-30 00:00:00 -0400"] | polars into-df | polars as-datetime "%Y-%m-%d %H:%M:%S %z" | polars schema
╭──────────┬───────────────────╮
│ datetime │ datetime<ns, UTC> │
╰──────────┴───────────────────╯
```
The user may intentionally ignore timezone information by setting the
`--naive` flag.
```
$ ["2021-12-30 00:00:00 +0000" "2021-12-30 00:00:00 -0400"] | polars into-df | polars as-datetime "%Y-%m-%d %H:%M:%S %z" --naive
╭───┬───────────────────────╮
│ # │ datetime │
├───┼───────────────────────┤
│ 0 │ 12/30/2021 12:00:00AM │
│ 1 │ 12/30/2021 12:00:00AM │ <-- the -0400 offset is ignored when --naive is set
╰───┴───────────────────────╯
$ ["2021-12-30 00:00:00 +0000" "2021-12-30 00:00:00 -0400"] | polars into-df | polars as-datetime "%Y-%m-%d %H:%M:%S %z" --naive | polars schema
╭──────────┬──────────────╮
│ datetime │ datetime<ns> │
╰──────────┴──────────────╯
```
# User-Facing Changes
<!-- List of all changes that impact the user experience here. This
helps us keep track of breaking changes. -->
`polars as-datetime` will now account for timezone information and
return type `datetime<ns,UTC>` rather than `datetime<ns>` by default.
The user can replicate the previous behavior by setting `--naive`.
# 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))
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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
> ```
-->
Tests that incorporated `polars as-datetime` had to be tweaked to
include `--naive` flag to replicate previous behavior.
# 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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- this PR should close #xxxx
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# Description
This PR expands the `dtype` parameter of the `polars cast` command to
include `decimal<precision, scale>` type. Setting precision to "*" will
compel inferring the value. Note, however, setting scale to a
non-integer value will throw an explicit error (the underlying polars
crate assigns scale = 0 in such a case, but I opted for throwing an
error instead). .
```
$ [[a b]; [1 2] [3 4]] | polars into-df | polars cast decimal<4,2> a | polars schema
╭───┬──────────────╮
│ a │ decimal<4,2> │
│ b │ i64 │
╰───┴──────────────╯
$ [[a b]; [10.5 2] [3.1 4]] | polars into-df | polars cast decimal<*,2> a | polars schema
╭───┬──────────────╮
│ a │ decimal<*,2> │
│ b │ i64 │
╰───┴──────────────╯
$ [[a b]; [10.05 2] [3.1 4]] | polars into-df | polars cast decimal<5,*> a | polars schema
rror: × Invalid polars data type
╭─[entry #25:1:47]
1 │ [[a b]; [10.05 2] [3.1 4]] | polars into-df | polars cast decimal<5,*> a | polars schema
· ─────┬─────
· ╰── `*` is not a permitted value for scale
╰────
```
# User-Facing Changes
<!-- List of all changes that impact the user experience here. This
helps us keep track of breaking changes. -->
There are no breaking changes. The user has the additional option to
`polars cast` to a decimal type
# Tests + Formatting
Tests have been added to
`nu_plugin_polars/src/dataframe/values/nu_schema.rs`
# Description
This PR removes the mimalloc allocator due to run-away memory leaks
recently found.
closes#15311
# User-Facing Changes
<!-- List of all changes that impact the user experience here. This
helps us keep track of breaking changes. -->
# 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 toolkit.nu; toolkit test stdlib"` 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.
-->
# fixes https://github.com/nushell/nushell/issues/15281
# Description
Provides the ability read dataframes with Categorical and Enum data
The ability to write Categorical and Enum data will provided in a future
PR
This PR (based on #15249 and #15248 because it mentions them) adds extra
documentation to the main polars command outlining the main datatypes
that are used by the plugin. The lack of a description of the types
involved in `polars xxx` commands was quite confusing to me when I
started using the plugin and this is a first try improving it.
I didn't find a better place but please let me know what you think.
# Description
This PR adds `polars str-strip-chars-end`
# User-Facing Changes
New function that can be used as follows:
```
~/Projects/nushell> [[text]; [hello!!!] [world!!!]] | polars into-df | polars select (polars col text | polars str-strip-chars-end "!") | polars collect
╭───┬───────╮
│ # │ text │
├───┼───────┤
│ 0 │ hello │
│ 1 │ world │
╰───┴───────╯
```
# Tests + Formatting
tests ran locally.
I ran the formatter.
# 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.
-->
# Description
This PR adds two new `ParseError` and `ShellError` cases for type errors
relating to operators.
- `OperatorUnsupportedType` is used when a type is not supported by an
operator in any way, shape, or form. E.g., `+` does not support `bool`.
- `OperatorIncompatibleTypes` is used when a operator is used with types
it supports, but the combination of types provided cannot be used
together. E.g., `filesize + duration` is not a valid combination.
The other preexisting error cases related to operators have been removed
and replaced with the new ones above. Namely:
- `ShellError::OperatorMismatch`
- `ShellError::UnsupportedOperator`
- `ParseError::UnsupportedOperationLHS`
- `ParseError::UnsupportedOperationRHS`
- `ParseError::UnsupportedOperationTernary`
# User-Facing Changes
- `help operators` now lists the precedence of `not` as 55 instead of 0
(above the other boolean operators). Fixes#13675.
- `math median` and `math mode` now ignore NaN values so that `[NaN NaN]
| math median` and `[NaN NaN] | math mode` no longer trigger a type
error. Instead, it's now an empty input error. Fixing this in earnest
can be left for a future PR.
- Comparisons with `nan` now return false instead of causing an error.
E.g., `1 == nan` is now `false`.
- All the operator type errors have been standardized and reworked. In
particular, they can now have a help message, which is currently used
for types errors relating to `++`.
```nu
[1] ++ 2
```
```
Error: nu::parser::operator_unsupported_type
× The '++' operator does not work on values of type 'int'.
╭─[entry #1:1:5]
1 │ [1] ++ 2
· ─┬ ┬
· │ ╰── int
· ╰── does not support 'int'
╰────
help: if you meant to append a value to a list or a record to a table, use the `append` command or wrap the value in a list. For example: `$list ++ $value` should be
`$list ++ [$value]` or `$list | append $value`.
```
# Description
Parquet, CSV, NDJSON, and Arrow files can be written to AWS S3 via
`polars save`. This mirrors the s3 functionality provided by `polars
open`.
```nushell
ls | polars into-df | polars save s3://my-bucket/test.parquet
```
# User-Facing Changes
- S3 urls are now supported by `polars save`
