udpates

Author: blaylockbk

src/herbie/v2/docs/CHANGELOG.md

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+# New Herbie
+
+New Dependencies
+
+- Polars: I much prefer using this DataFrame library over Pandas.
+- Rich: For printing information for the user in a fancy way.
+
+The default save directory is now `~/herbie-data/`
+
+```python
+from herbie.v2 import Herbie
+```
+
+Herbie is now a namespace, with many model HerbieModel classes for different models.
+
+```python
+H = Herbie.HRRR('2025-01-01')
+```
+
+you may also just import the model you want to use instead
+
+```python
+from herbie.v2 import HRRR
+H = HRRR('2025-01-01')
+```
+
+## `fxx` is now `step`
+
+The forecast lead time is now controlled with the step parameter, and may be a timedelta object (which is converted to integer hours). The following are equivalent:
+
+```python
+from herbie.v2 import Herbie
+from datetime import datetime, timedelta
+
+H = Herbie.HRRR('2025-01-01', step=12)
+
+H = Herbie.HRRR(datetime(2025,1,1), step=timedelta(hours=12))
+```
+
+## Notebook HTML Representor
+
+For convenient user exploration, when displaying a Herbie object in a Jupyter Notebook, there is a new HTML display showing the parameters selected and sources.
+
+## Model Templates
+
+Big change to the model templates. These are subclassed from the base class HerbieModel.
+
+## Inventory
+
+Use Polars as the DataFrame. I'm a big Polars fan, and find it much easier to read and write than Pandas.
+
+Since I'm using Polars for the DataFrame, users can filter the inventory with expressions for each column rather than just the "search_this" column.
+
+The data and index source are now included in the inventory dataframe. This will enable downloading fields from multiple files and "build your own GRIB files."
+
+## Download
+
+Download for subsets are now done with multiple threads, one thread for each subset group.
+
+Use rich progress bars for downloads.
+
+Remote file paths are preserved rather than specifying a custom data path. I wanted to make it possible to use rclone to quickly pre-fill your `herbie-data/` directory, then use Herbie to access those files locally.
+
+## xarray
+
+Multiple hypercubes are returned as a DataTree.
+
+## status
+
+Display the sources and which sources have been checked and if the files exist.
+
+## resolve
+
+Manually check if files exist
+
+```python
+# Find first available file
+H.resolve()
+
+# Check specific source
+H.resolve('google')
+
+# Check all
+H.resolve('all')
+```
+
+## FastHerbie
+
+This behaves _very_ different. Inventory DataFrames are concatted together for many files, then parallel downloads happen and join the fields into a new, custom grib file. It's a "build your own GRIB" feature.
+
+Examples:
+
+- Get all 6-hr `TMP:2 m` forecasts for the day in one file.
+- Get all `GRD:10 m` forecasts initialized at a single time.