Plugins#
PyGraphistry is frequently used with a variety of external tools such as data providers, compute engines, layout engines, and more.
Users typically prefer to go through PyGraphistry’s native dataframe support (Apache Arrow, Pandas, cuDF, …). That is often an efficient, safe, and easy starting point.
Occasionally, native PyGraphistry plugins streamline common operations, such as with graph databases. We link to the native API integrations below as appropriate.
For more examples, see also the notebook catalog.
Databases#
Graph#
Document, Key-Value, Log, Text, and SIEM#
SQL#
Typically accessed via dataframe bindings
When available, we recommend exploring for accelerated bindings via ADBC
Compute engines#
Natively supported in methods such as .nodes()
and .edges()
:
Partial native support:
Accelerated interop via Apache Arrow or Parquet:
Graph layout and analytics#
Tools#
We are constantly experimenting, feel free to add:
OWASP Amass
Storage engines and file formats#
GPU-accelerated readers via cuDF (in-memory single-GPU) and Dask-cuDF (bigger-than-memory, multi-GPU):
Arrow
CSV
JSON
JSONL
LOG
ORC
Parquet
TXT
Others, often via fsspec:
Azure blobstore
GML
S3
XLS(X)