Graphistry

Latest version: v0.33.8

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0.27.3

Changed

* Infra: Remove heavy AI dependencies from `pip install graphistry[dev]`

Added

* igraph: Optional `use_vids` parameter (default `False`) for `to_igraph()` and its callers (`layout_igraph`, `compute_graph`)
* igraph: add `coreness` and `harmonic_centrality` to `compute_igraph`

Fixed

* igraph: CI errors around igraph
* igraph: Tolerate deprecation warning of `clustering`
* Docs: Typos and updates - thanks gadde5300 + szhorvat !

0.27.2

Changed

* Speed up `import graphistry` 10X+ by lazily importing AI dependencies. Use of `pygraphistry[ai]` features will still trigger slow upstream dependency initialization times upon first use.

Fixed

* Docs: Update Labs references to Hub

0.27.1

Fixed

* `group_in_a_box_layout()`: Remove verbose output
* `group_in_a_box_layout()`: Remove synthesized edge weight

0.27.0

Breaking 🔥

* Types: Switch `materialize_nodes` engine param to explicitly using`Engine` typing (no change to untyped user code)

Added

* `g.keep_nodes(List or Series)`
* `g.group_in_a_box_layout(...)`: Both CPU (pandas/igraph) and (cudf/cugraph) versions, and various partitioning/layout/styling settings
* Internal clientside Brewer palettes helper for categorical point coloring

Changed

* Infra: CI early fail on deeper lint
* Infra: Move Python 3.6 from core to minimal tests due to sklearn 1.0 incompatibility

Fixed

* lint
* suppress known dgl bindings test type bug

0.26.1

Breaking 🔥

* `_table_to_arrow()` for `cudf`: Updated for RAPIDS 2022.02+ to handle deprecation of `cudf.DataFrame.hash_columns()` in favor of new `cudf.DataFrame.hash_values()`

Added

* `materialize_nodes()`: Supports `cudf`, materializing a `cudf.DataFrame` nodes table when `._edges` is an instance of `cudf.DataFrame`
* `to_cugraph()`, `from_cugraph()`, `compute_cugraph()`, `layout_cugraph()`
* docs: [cugraph demo notebook](demos/demos_databases_apis/gpu_rapids/cugraph.ipynb)

Changed

* Infra: Update GPU test env settings
* `materialize_nodes`: Return regular index

Fixed

* `hypergraph()` in dask handles failing metadata type inference
* tests: gpu env tweaks
* tests: umap logging was throwing warnings

0.26.0

Added
* `g.transform()`
* `g.transform_umap()`
* `g.scale()`
* Memoization on UMAP and Featurize calls
* Adds **kwargs and propagates them through to different function calls (featurize, umap, scale, etc)

Breaking 🔥

* Final deprecation of `register(api=2)` protobuf/vgraph mode - also works around need for protobuf test upgrades

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