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
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>
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>
# Description
This is just some cleanup. I moved to_pipeline_data and to_cache_value
to the CustomValueSupport trait, where I should've put them to begin
with.
Co-authored-by: Jack Wright <jack.wright@disqo.com>
# Description
@maxim-uvarov discovered the following error:
```
> [[a b]; [6 2] [1 4] [4 1]] | polars into-lazy | polars sort-by a | polars unique --subset [a]
Error: × Error using as series
╭─[entry #1:1:68]
1 │ [[a b]; [6 2] [1 4] [4 1]] | polars into-lazy | polars sort-by a | polars unique --subset [a]
· ──────┬──────
· ╰── dataframe has more than one column
╰────
```
During investigation, I discovered the root cause was that the lazy frame was incorrectly converted back to a eager dataframe. In order to keep this from happening, I explicitly set that the dataframe did not come from an eager frame. This causes the conversion logic to not attempt to convert the dataframe later in the pipeline.
---------
Co-authored-by: Jack Wright <jack.wright@disqo.com>
# Description
This adds a `SharedCow` type as a transparent copy-on-write pointer that
clones to unique on mutate.
As an initial test, the `Record` within `Value::Record` is shared.
There are some pretty big wins for performance. I'll post benchmark
results in a comment. The biggest winner is nested access, as that would
have cloned the records for each cell path follow before and it doesn't
have to anymore.
The reusability of the `SharedCow` type is nice and I think it could be
used to clean up the previous work I did with `Arc` in `EngineState`.
It's meant to be a mostly transparent clone-on-write that just clones on
`.to_mut()` or `.into_owned()` if there are actually multiple
references, but avoids cloning if the reference is unique.
# User-Facing Changes
- `Value::Record` field is a different type (plugin authors)
# Tests + Formatting
- 🟢 `toolkit fmt`
- 🟢 `toolkit clippy`
- 🟢 `toolkit test`
- 🟢 `toolkit test stdlib`
# After Submitting
- [ ] use for `EngineState`
- [ ] use for `Value::List`
# Description
From @maxim-uvarov's
[post](https://discord.com/channels/601130461678272522/1227612017171501136/1228656319704203375).
When calling `to-lazy` back to back in a pipeline, an error should not
occur:
```
> [[a b]; [6 2] [1 4] [4 1]] | polars into-lazy | polars into-lazy
Error: nu:🐚:cant_convert
× Can't convert to NuDataFrame.
╭─[entry #1:1:30]
1 │ [[a b]; [6 2] [1 4] [4 1]] | polars into-lazy | polars into-lazy
· ────────┬───────
· ╰── can't convert NuLazyFrameCustomValue to NuDataFrame
╰────
```
This pull request ensures that custom value's of NuLazyFrameCustomValue are properly converted when passed in.
Co-authored-by: Jack Wright <jack.wright@disqo.com>
# Description
@maxim-uvarov discovered an issue with the current implementation. When
executing [[index a]; [1 1]] | polars into-df, a plugin_failed_to_decode
error occurs. This happens because a Record is created with two columns
named "index" as an index column is added during conversion. This pull
request addresses the problem by not adding an index column if there is
already a column named "index" in the dataframe.
---------
Co-authored-by: Jack Wright <jack.wright@disqo.com>
# Description
`polars ls` is already different that `dfr ls`. Currently it just shows
the cache key, columns, rows, and type. I have added:
- creation time
- size
- span contents
- span start and end
<img width="1471" alt="Screenshot 2024-04-10 at 17 27 06"
src="https://github.com/nushell/nushell/assets/56345/545918b7-7c96-4c25-bc01-b9e2b659a408">
# Tests + Formatting
Done
Co-authored-by: Jack Wright <jack.wright@disqo.com>
