# Description
This resurrects the work from #12866 and fixes#12732.
Polars panics for a plethora or reasons. While handling panics is
generally frowned upon, in cases like with `polars collect` a panic
cause a lot of work to be lost. Often you might have multiple dataframes
in memory and you are trying one operation and lose all state.
While it possible the panic can leave things a strange state, it is
pretty unlikely as part of a polars pipeline. Most of the time polars
objects are not manipulating dataframes in memory mutability, but rather
creating a new dataframe the operations being applied. This is always
the case with a lazy pipeline. After the collect call, the original
dataframes are intact still and I haven't observed any side effects.
# Description
In order to be more consistent with it's nu counterpart, `polars save`
now returns an empty pipeline instead of a message of the saved file.
# User-Facing Changes
- `polars save` no longer displays a save message, making it consistent
with `save` behavior.
# Description
This PR:
- Removes the lazy_command, expr_command macros and migrates the
commands that were utilizing them.
- Removes the custom logic in DataFrameValues::is_equals to use the
polars DataFrame version of PartialEq
- Adds examples to commands that previously did not have examples or had
inadequate ones.
NOTE: A lot of examples now have a `polars sort` at the end. This is
needed due to the comparison in the result. The new polars version of
equals cares about the ordering. I removed the custom equals logic as it
causes comparisons to lock up when comparing dataframes that contain a
row that contains a list. I discovered this issue when adding examples
to `polars implode`
# Description
Previously there were no examples or explanations that you can use '*'
to select all columns. Updated description and added a new example.
# Description
In order to be more consistent with the nushell terminology and with
polars expression terminology `polars concatenate` is now `polars
str-join`. `polars str-join` can also be used as expression.
<img width="857" alt="Screenshot 2024-09-04 at 12 41 25"
src="https://github.com/user-attachments/assets/8cc5a0c2-194c-49ec-9fe1-65ec4825414d">
# User-Facing Changes
- `polars concatenate` is now `polars str-join`
- `polars str-join` can be used as an expression
# Description
Allows `polars str-lengths` to be used as an expression:
<img width="826" alt="Screenshot 2024-09-04 at 13 57 45"
src="https://github.com/user-attachments/assets/b74139e0-e8ba-4910-84c2-cf4be4a084b6">
# User-Facing Changes
- `polars str-lengths` can be used as an expression.
- char length is now the default. Use the --bytes flag to get bytes
length.
# Description
Adds the ability for `polars replace` and `polars replace-all` to work
as expressions.
# User-Facing Changes
- `polars replace` can be used with polars expressions
- `polars replace-all` can be used with polars expressions
# Description
The meaning of the word usage is specific to describing how a command
function is *used* and not a synonym for general description. Usage can
be used to describe the SYNOPSIS or EXAMPLES sections of a man page
where the permitted argument combinations are shown or example *uses*
are given.
Let's not confuse people and call it what it is a description.
Our `help` command already creates its own *Usage* section based on the
available arguments and doesn't refer to the description with usage.
# User-Facing Changes
`help commands` and `scope commands` will now use `description` or
`extra_description`
`usage`-> `description`
`extra_usage` -> `extra_description`
Breaking change in the plugin protocol:
In the signature record communicated with the engine.
`usage`-> `description`
`extra_usage` -> `extra_description`
The same rename also takes place for the methods on
`SimplePluginCommand` and `PluginCommand`
# Tests + Formatting
- Updated plugin protocol specific changes
# After Submitting
- [ ] update plugin protocol doc
# Description
Fixes issue [12828](https://github.com/nushell/nushell/issues/12828).
When attempting a `polars collect` on an eager dataframe, we return
dataframe as is. However, before this fix I failed to increment the
internal cache reference count. This caused the value to be dropped from
the internal cache when the references were decremented again.
This fix adds a call to cache.get to increment the value before
returning.
# Description
This pull request merges `polars sink` and `polars to-*` into one
command `polars save`.
# User-Facing Changes
- `polars to-*` commands have all been replaced with `polars save`. When
saving a lazy frame to a type that supports a polars sink operation, a
sink operation will be performed. Sink operations are much more
performant, performing a collect while streaming to the file system.
# Description
This exposes the `LazyFrame::sink_*` functionality to allow a streaming
collect directly to the filesystem. This useful when working with data
that is too large to fit into memory.
# User-Facing Changes
- Introduction of the `polars sink` command
# Description
Prior this pull request `polars first` and `polars last` would collect a
lazy frame into an eager frame before performing operations. Now `polars
first` will to a `LazyFrame::limit` and `polars last` will perform a
`LazyFrame::tail`. This is really useful in working with very large
datasets.
# Description
When opening a dataframe the default operation will be to create a lazy
frame if possible. This works much better with large datasets and
supports hive format.
# User-Facing Changes
- `--lazy` is nolonger a valid option. `--eager` must be used to
explicitly open an eager dataframe.
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Per discussion on
[Discord](https://discord.com/channels/601130461678272522/864228801851949077/1265718178927870045)
# Description
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To facilitate column-oriented dataframe construction, this PR added a
`--as-columns` flag to `polars into-df` command so that when specified,
and when input shape is record of lists, each list will be treated as a
column rather than a cell value, i.e. `{a: [1 3], b: [2 4]} | polars
into-df --as-columns` returns the same dataframe as `[[a b];[1 2] [3 4]]
| polars into-df`
# User-Facing Changes
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helps us keep track of breaking changes. -->
A new flag `--as-columns`, no change of semantics if this flag is
unspecified.
# Tests + Formatting
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automatically
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# After Submitting
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---------
Co-authored-by: Ben Yang <ben@ya.ng>
# Description
Makes `polars unpivot` use the same arguments as `polars pivot` and
makes it consistent with the polars' rust api. Additionally, support for
the polar's streaming engine has been exposed on eager dataframes.
Previously, it would only work with lazy dataframes.
# User-Facing Changes
* `polars unpivot` argument `--columns`|`-c` has been renamed to
`--index`|`-i`
* `polars unpivot` argument `--values`|`-v` has been renamed to
`--on`|`-o`
* `polars unpivot` short argument for `--streamable` is now `-t` to make
it consistent with `polars pivot`. It was made `-t` for `polars pivot`
because `-s` is short for `--short`
There was a bug where anytime the plugin cache remove was called, the
plugin gc was turned back on. This probably happened when I added the
reference counter logic.
# Description
Upgrading to Polars 0.41
# User-Facing Changes
* `polars melt` has been renamed to `polars unpivot` to match the change
in the polars API. Additionally, it now supports lazy dataframes.
Introduced a `--streamable` option to use the polars streaming engine
for lazy frames.
* The parameter `outer` has been replaced with `full` in `polars join`
to match polars change.
* `polars value-count` now supports the column (rename count column),
parallelize (multithread), sort, and normalize options.
The list of polars changes can be found
[here](https://github.com/pola-rs/polars/releases/tag/rs-0.41.2)
In this pull request, I converted the `perf` function within `nu_utils`
to a macro. This change facilitates easier usage within plugins by
allowing the use of `env_logger` and setting `RUST_LOG=nu_plugin_polars`
(or another plugin). Without this conversion, the `RUST_LOG` variable
would need to be set to `RUST_LOG=nu_utils::utils`, which is less
intuitive and impossible to narrow the perf results to one plugin.
Addresses performance issues that @maxim-uvarov found with CSV and JSON
lines.
This ensures that the schema inference follows the polars defaults of
100 lines. Recent changes caused the default values to be override and
caused the entire file to be scanned when inferring the schema.
# Description
This allows plugins to report their version (and potentially other
metadata in the future). The version is shown in `plugin list` and in
`version`.
The metadata is stored in the registry file, and reflects whatever was
retrieved on `plugin add`, not necessarily the running binary. This can
help you to diagnose if there's some kind of mismatch with what you
expect. We could potentially use this functionality to show a warning or
error if a plugin being run does not have the same version as what was
in the cache file, suggesting `plugin add` be run again, but I haven't
done that at this point.
It is optional, and it requires the plugin author to make some code
changes if they want to provide it, since I can't automatically
determine the version of the calling crate or anything tricky like that
to do it.
Example:
```
> plugin list | select name version is_running pid
╭───┬────────────────┬─────────┬────────────┬─────╮
│ # │ name │ version │ is_running │ pid │
├───┼────────────────┼─────────┼────────────┼─────┤
│ 0 │ example │ 0.93.1 │ false │ │
│ 1 │ gstat │ 0.93.1 │ false │ │
│ 2 │ inc │ 0.93.1 │ false │ │
│ 3 │ python_example │ 0.1.0 │ false │ │
╰───┴────────────────┴─────────┴────────────┴─────╯
```
cc @maxim-uvarov (he asked for it)
# User-Facing Changes
- `plugin list` gets a `version` column
- `version` shows plugin versions when available
- plugin authors *should* add `fn metadata()` to their `impl Plugin`,
but don't have to
# Tests + Formatting
Tested the low level stuff and also the `plugin list` column.
# After Submitting
- [ ] update plugin guide docs
- [ ] update plugin protocol docs (`Metadata` call & response)
- [ ] update plugin template (`fn metadata()` should be easy)
- [ ] release notes
This allows performance debugging to be turned on by setting:
```nushell
$env.POLARS_PLUGIN_PERF = "true"
```
Furthermore, this improves the other plugin debugging by allowing the
env variable for debugging to be set at any time versus having to be
available when nushell is launched:
```nushell
$env.POLARS_PLUGIN_DEBUG = "true"
```
This plugin introduces a `perf` function that will output timing
results. This works very similar to the perf function available in
nu_utils::utils::perf. This version prints everything to std error to
not break the plugin stream and uses the engine interface to see if the
env variable is configured.
This pull requests uses this `perf` function when:
* opening csv files as dataframes
* opening json lines files as dataframes
This will hopefully help provide some more fine grained information on
how long it takes polars to open different dataframes. The `perf` can
also be utilized later for other dataframes use cases.
Per discussion on discord dataframes channel with @maxim-uvarov and pyz.
When converting a dataframe to an nushell value via `polars into-nu`,
the index column should not be added by default and should only be added
when specifying `--index`
As reported by @maxim-uvarov and pyz in the dataframes discord channel:
```nushell
[[a b]; [1 1] [1 2] [2 1] [2 2] [3 1] [3 2]] | polars into-df | polars with-column ((polars col a) / (polars col b)) --name c
× Type mismatch.
╭─[entry #45:1:102]
1 │ [[a b]; [1 1] [1 2] [2 1] [2 2] [3 1] [3 2]] | polars into-df | polars with-column ((polars col a) / (polars col b)) --name c
· ───────┬──────
· ╰── Right hand side not a dataframe expression
╰────
```
This pull request corrects the type casting on the right hand side and
allows more than just polars literal expressions.
# Description
@maxim-uvarov did a ton of research and work with the dply-rs author and
ritchie from polars and found out that the allocator matters on macos
and it seems to be what was messing up the performance of polars plugin.
ritchie suggested to use jemalloc but i switched it to mimalloc to match
nushell and it seems to run better.
## Before (default allocator)
note - using 1..10 vs 1..100 since it takes so long. also notice how
high the `max` timings are compared to mimalloc below.
```nushell
❯ 1..10 | each {timeit {polars open Data7602DescendingYearOrder.csv | polars group-by year | polars agg (polars col geo_count | polars sum) | polars collect | null}} | | {mean: ($in | math avg), min: ($in | math min), max: ($in | math max), stddev: ($in | into int | into float | math stddev | into int | $'($in)ns' | into duration)}
╭────────┬─────────────────────────╮
│ mean │ 4sec 999ms 605µs 995ns │
│ min │ 983ms 627µs 42ns │
│ max │ 13sec 398ms 135µs 791ns │
│ stddev │ 3sec 476ms 479µs 939ns │
╰────────┴─────────────────────────╯
❯ use std bench
❯ bench { polars open Data7602DescendingYearOrder.csv | polars group-by year | polars agg (polars col geo_count | polars sum) | polars collect | null } -n 10
╭───────┬────────────────────────╮
│ mean │ 6sec 220ms 783µs 983ns │
│ min │ 1sec 184ms 997µs 708ns │
│ max │ 18sec 882ms 81µs 708ns │
│ std │ 5sec 350ms 375µs 697ns │
│ times │ [list 10 items] │
╰───────┴────────────────────────╯
```
## After (using mimalloc)
```nushell
❯ 1..100 | each {timeit {polars open Data7602DescendingYearOrder.csv | polars group-by year | polars agg (polars col geo_count | polars sum) | polars collect | null}} | | {mean: ($in | math avg), min: ($in | math min), max: ($in | math max), stddev: ($in | into int | into float | math stddev | into int | $'($in)ns' | into duration)}
╭────────┬───────────────────╮
│ mean │ 103ms 728µs 902ns │
│ min │ 97ms 107µs 42ns │
│ max │ 149ms 430µs 84ns │
│ stddev │ 5ms 690µs 664ns │
╰────────┴───────────────────╯
❯ use std bench
❯ bench { polars open Data7602DescendingYearOrder.csv | polars group-by year | polars agg (polars col geo_count | polars sum) | polars collect | null } -n 100
╭───────┬───────────────────╮
│ mean │ 103ms 620µs 195ns │
│ min │ 97ms 541µs 166ns │
│ max │ 130ms 262µs 166ns │
│ std │ 4ms 948µs 654ns │
│ times │ [list 100 items] │
╰───────┴───────────────────╯
```
## After (using jemalloc - just for comparison)
```nushell
❯ 1..100 | each {timeit {polars open Data7602DescendingYearOrder.csv | polars group-by year | polars agg (polars col geo_count | polars sum) | polars collect | null}} | | {mean: ($in | math avg), min: ($in | math min), max: ($in | math max), stddev: ($in | into int | into float | math stddev | into int | $'($in)ns' | into duration)}
╭────────┬───────────────────╮
│ mean │ 113ms 939µs 777ns │
│ min │ 108ms 337µs 333ns │
│ max │ 166ms 467µs 458ns │
│ stddev │ 6ms 175µs 618ns │
╰────────┴───────────────────╯
❯ use std bench
❯ bench { polars open Data7602DescendingYearOrder.csv | polars group-by year | polars agg (polars col geo_count | polars sum) | polars collect | null } -n 100
╭───────┬───────────────────╮
│ mean │ 114ms 363µs 530ns │
│ min │ 108ms 804µs 833ns │
│ max │ 143ms 521µs 459ns │
│ std │ 5ms 88µs 56ns │
│ times │ [list 100 items] │
╰───────┴───────────────────╯
```
## After (using parquet + mimalloc)
```nushell
❯ 1..100 | each {timeit {polars open data.parquet | polars group-by year | polars agg (polars col geo_count | polars sum) | polars collect | null}} | | {mean: ($in | math avg), min: ($in | math min), max: ($in | math max), stddev: ($in | into int | into float | math stddev | into int | $'($in)ns' | into duration)}
╭────────┬──────────────────╮
│ mean │ 34ms 255µs 492ns │
│ min │ 31ms 787µs 250ns │
│ max │ 76ms 408µs 416ns │
│ stddev │ 4ms 472µs 916ns │
╰────────┴──────────────────╯
❯ use std bench
❯ bench { polars open data.parquet | polars group-by year | polars agg (polars col geo_count | polars sum) | polars collect | null } -n 100
╭───────┬──────────────────╮
│ mean │ 34ms 897µs 562ns │
│ min │ 31ms 518µs 542ns │
│ max │ 65ms 943µs 625ns │
│ std │ 3ms 450µs 741ns │
│ times │ [list 100 items] │
╰───────┴──────────────────╯
```
# User-Facing Changes
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helps us keep track of breaking changes. -->
# Tests + Formatting
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This reverts commit 68adc4657f.
# Description
Reverts the lazyframe refactor (#12669) for the next release, since
there are still a few lingering issues. This temporarily solves #12863
and #12828. After the release, the lazyframes can be added back and
cleaned up.
# Description
This PR adds a few functions to `Span` for merging spans together:
- `Span::append`: merges two spans that are known to be in order.
- `Span::concat`: returns a span that encompasses all the spans in a
slice. The spans must be in order.
- `Span::merge`: merges two spans (no order necessary).
- `Span::merge_many`: merges an iterator of spans into a single span (no
order necessary).
These are meant to replace the free-standing `nu_protocol::span`
function.
The spans in a `LiteCommand` (the `parts`) should always be in order
based on the lite parser and lexer. So, the parser code sees the most
usage of `Span::append` and `Span::concat` where the order is known. In
other code areas, `Span::merge` and `Span::merge_many` are used since
the order between spans is often not known.
# Description
This PR introduces a `ByteStream` type which is a `Read`-able stream of
bytes. Internally, it has an enum over three different byte stream
sources:
```rust
pub enum ByteStreamSource {
Read(Box<dyn Read + Send + 'static>),
File(File),
Child(ChildProcess),
}
```
This is in comparison to the current `RawStream` type, which is an
`Iterator<Item = Vec<u8>>` and has to allocate for each read chunk.
Currently, `PipelineData::ExternalStream` serves a weird dual role where
it is either external command output or a wrapper around `RawStream`.
`ByteStream` makes this distinction more clear (via `ByteStreamSource`)
and replaces `PipelineData::ExternalStream` in this PR:
```rust
pub enum PipelineData {
Empty,
Value(Value, Option<PipelineMetadata>),
ListStream(ListStream, Option<PipelineMetadata>),
ByteStream(ByteStream, Option<PipelineMetadata>),
}
```
The PR is relatively large, but a decent amount of it is just repetitive
changes.
This PR fixes#7017, fixes#10763, and fixes#12369.
This PR also improves performance when piping external commands. Nushell
should, in most cases, have competitive pipeline throughput compared to,
e.g., bash.
| Command | Before (MB/s) | After (MB/s) | Bash (MB/s) |
| -------------------------------------------------- | -------------:|
------------:| -----------:|
| `throughput \| rg 'x'` | 3059 | 3744 | 3739 |
| `throughput \| nu --testbin relay o> /dev/null` | 3508 | 8087 | 8136 |
# User-Facing Changes
- This is a breaking change for the plugin communication protocol,
because the `ExternalStreamInfo` was replaced with `ByteStreamInfo`.
Plugins now only have to deal with a single input stream, as opposed to
the previous three streams: stdout, stderr, and exit code.
- The output of `describe` has been changed for external/byte streams.
- Temporary breaking change: `bytes starts-with` no longer works with
byte streams. This is to keep the PR smaller, and `bytes ends-with`
already does not work on byte streams.
- If a process core dumped, then instead of having a `Value::Error` in
the `exit_code` column of the output returned from `complete`, it now is
a `Value::Int` with the negation of the signal number.
# After Submitting
- Update docs and book as necessary
- Release notes (e.g., plugin protocol changes)
- Adapt/convert commands to work with byte streams (high priority is
`str length`, `bytes starts-with`, and maybe `bytes ends-with`).
- Refactor the `tee` code, Devyn has already done some work on this.
---------
Co-authored-by: Devyn Cairns <devyn.cairns@gmail.com>
Fix for #12730
All of the code expected a list of floats, but the syntax shape expected
a table. Resolved by changing the syntax shape to list of floats.
cc: @maxim-uvarov
This moves to predominantly supporting only lazy dataframes for most
operations. It removes a lot of the type conversion between lazy and
eager dataframes based on what was inputted into the command.
For the most part the changes will mean:
* You will need to run `polars collect` after performing operations
* The into-lazy command has been removed as it is redundant.
* When opening files a lazy frame will be outputted by default if the
reader supports lazy frames
A list of individual command changes can be found
[here](https://hackmd.io/@nucore/Bk-3V-hW0)
---------
Co-authored-by: Ian Manske <ian.manske@pm.me>
# Description
I added some more tests to our mighty `polars` ~~, yet I don't know how
to add expected results in some of them. I would like to ask for help.~~
~~My experiments are in the last commit: [polars:
experiments](f7e5e72019).
Without those experiments `cargo test` goes well.~~
UPD. I moved out my unsuccessful test experiments into a separate
[branch](https://github.com/maxim-uvarov/nushell/blob/polars-tests-broken2/).
So, this branch seems ready for a merge.
@ayax79, maybe you'll find time for me please? It's not urgent for sure.
P.S. I'm very new to git. Please feel free to give me any suggestions on
how I should use it better
# Description
I would like to help with `polars` plugin development and add tests to
all the `polars` command's existing params.
Since I have never written any lines of Rust, even though the task of
creating tests is relatively simple, I would like to ask for feedback to
ensure I did everything correctly here.
# Description
Continuing from #12568, this PR further reduces the size of `Expr` from
64 to 40 bytes. It also reduces `Expression` from 128 to 96 bytes and
`Type` from 32 to 24 bytes.
This was accomplished by:
- for `Expr` with multiple fields (e.g., `Expr::Thing(A, B, C)`),
merging the fields into new AST struct types and then boxing this struct
(e.g. `Expr::Thing(Box<ABC>)`).
- replacing `Vec<T>` with `Box<[T]>` in multiple places. `Expr`s and
`Expression`s should rarely be mutated, if at all, so this optimization
makes sense.
By reducing the size of these types, I didn't notice a large performance
improvement (at least compared to #12568). But this PR does reduce the
memory usage of nushell. My config is somewhat light so I only noticed a
difference of 1.4MiB (38.9MiB vs 37.5MiB).
---------
Co-authored-by: Stefan Holderbach <sholderbach@users.noreply.github.com>
# Description
This pull request provides three new commands:
`polars store-ls` - moved from `polars ls`. It provides the list of all
object stored in the plugin cache
`polars store-rm` - deletes a cached object
`polars store-get` - gets an object from the cache.
The addition of `polars store-get` required adding a reference_count to
cached entries. `polars get` is the only command that will increment
this value. `polars rm` will remove the value despite it's count. Calls
to PolarsPlugin::custom_value_dropped will decrement the value.
The prefix store- was chosen due to there already being a `polars cache`
command. These commands were not made sub-commands as there isn't a way
to display help for sub commands in plugins (e.g. `polars store`
displaying help) and I felt the store- seemed fine anyways.
The output of `polars store-ls` now shows the reference count for each
object.
# User-Facing Changes
polars ls has now moved to polars store-ls
---------
Co-authored-by: Jack Wright <jack.wright@disqo.com>
# Description
The polars dtype command is largerly redundant since the introduction of
the schema command. The schema command also has the added benefit that
it's output can be used as a parameter to other schema commands:
```nushell
[[a b]; [5 6] [5 7]] | polars into-df -s ($df | polars schema
```
# User-Facing Changes
`polars dtypes` has been removed. Users should use `polars schema`
instead.
Co-authored-by: Jack Wright <jack.wright@disqo.com>
I had previously changed NuLazyFrame::collect to set the NuDataFrame's
from_lazy field to false to prevent conversion back to a lazy frame. It
appears there are cases where this should happen. Instead, I am only
setting from_lazy=false inside the `polars collect` command.
[Related discord
message](https://discord.com/channels/601130461678272522/1227612017171501136/1230600465159421993)
Co-authored-by: Jack Wright <jack.wright@disqo.com>
