update README.md

README.md

@@ -11,7 +11,7 @@
        supports loading multiple partitions (use `dict[str, pl.DataFrame]` type annotation), ...
    - Implemented serialization formats:
      - `PolarsParquetIOManager` - for reading and writing files in Apache Parquet format. Supports reading partitioned Parquet datasets (for example, often produced by Spark). All read/write options can be set via metadata values.
-     - `PolarsDeltaIOManager` - for reading and writing Delta Lake. All read/write options can be set via metadata values. `"partition_by"` metadata value can be set to use native Delta Lake partitioning (it's passed to `delta_write_options` of `write_delta`). In this case, all the asset partitions will be stored in the same Delta Table directory. You are responsible for filtering correct partitions when reading the data in the downstream assets.
+     - `PolarsDeltaIOManager` - for reading and writing Delta Lake. All read/write options can be set via metadata values. `"partition_by"` metadata value can be set to use native Delta Lake partitioning (it's passed to `delta_write_options` of `write_delta`). In this case, all the asset partitions will be stored in the same Delta Table directory. You are responsible for filtering correct partitions when reading the data in the downstream assets. Extra dependencies can be installed with `pip install 'dagster-polars[deltalake]'`.
  - `BigQueryPolarsIOManager` - for reading and writing data from/to [BigQuery](https://cloud.google.com/bigquery). Supports writing partitioned tables (`"partition_expr"` input metadata key must be specified). Extra dependencies can be installed with `pip install 'dagster-polars[gcp]'`.
 
 ## Quickstart
@@ -68,7 +68,6 @@ poetry run pre-commit install
 poetry run pytest
 ```
 
-## TODO
- - [ ] Add `PolarsDeltaIOManager`
- - [ ] Data validation like in [dagster-pandas](https://docs.dagster.io/integrations/pandas#validating-pandas-dataframes-with-dagster-types)
- - [ ] Maybe use `DagsterTypeLoader` ?
+## Ideas
+ - Data validation like in [dagster-pandas](https://docs.dagster.io/integrations/pandas#validating-pandas-dataframes-with-dagster-types)
+ - Maybe use `DagsterTypeLoader` ?