A set of data-oriented wrappers around the python API of Blender.
Available on PyPI, install with pip:
pip install databpyThe main use cases are to create objects, store and retrieve attributes
from them. The functions are named around nodes in Geometry Nodes
Store Named Attribute and Named Attribute
import databpy as db
db.store_named_attribute() # store a named attribute on a mesh object
db.named_attribute() # retrieve a named attribute from a mesh objectMostly oriented around creating mesh objects, assigning and getting back
attributes from them. Currently designed around storing and retrieving
numpy data types:
import numpy as np
import databpy as db
# Create a mesh object
random_verts = np.random.rand(10, 3)
obj = db.create_object(random_verts, name="RandomMesh")
obj.name'RandomMesh'
Access attributes from the object’s mesh.
db.named_attribute(obj, 'position')array([[0.33382925, 0.65230972, 0.40697551],
[0.15296361, 0.68834376, 0.87484485],
[0.28670755, 0.69163769, 0.96554619],
[0.37712002, 0.23925965, 0.11042582],
[0.18002324, 0.65962017, 0.91494399],
[0.44024575, 0.27175653, 0.55481952],
[0.68424481, 0.26874498, 0.20417342],
[0.17464781, 0.53077883, 0.99934095],
[0.68674725, 0.33857504, 0.68282163],
[0.40749231, 0.9381994 , 0.18826957]])
This is a convenience class that wraps around the bpy.types.Object,
and provides access to all of the useful functions. We can wrap an
existing Object or return one when creating a new object.
This just gives us access to the named_attribute() and
store_named_attribute() functions on the object class, but also
provides a more intuitive way to access the object’s attributes.
bob = db.BlenderObject(obj) # wraps the existing object
bob = db.create_bob(random_verts) # creates a new object and returns it already wrapped
# these two are identical
bob.named_attribute('position')
bob.positionarray([[0.33382925, 0.65230972, 0.40697551],
[0.15296361, 0.68834376, 0.87484485],
[0.28670755, 0.69163769, 0.96554619],
[0.37712002, 0.23925965, 0.11042582],
[0.18002324, 0.65962017, 0.91494399],
[0.44024575, 0.27175653, 0.55481952],
[0.68424481, 0.26874498, 0.20417342],
[0.17464781, 0.53077883, 0.99934095],
[0.68674725, 0.33857504, 0.68282163],
[0.40749231, 0.9381994 , 0.18826957]])
We can clear all of the data from the object and initialise a new mesh underneath:
bob.new_from_pydata(np.random.randn(5, 3))
bob.positionarray([[ 0.83341789, 0.39877525, -1.19136691],
[ 1.21940732, -2.17261744, 0.5276143 ],
[ 1.18024218, 2.23327231, 0.94101733],
[ 0.60895348, 0.01171492, -1.28239524],
[-0.54698443, -0.6605683 , -1.77002919]])
import polars as pl
import databpy as db
from io import StringIO
json_file = StringIO("""
{
"Dino": [
[55.3846, 97.1795, 0.0],
[51.5385, 96.0256, 0.0]
],
"Star": [
[58.2136, 91.8819, 0.0],
[58.1961, 92.215, 0.0]
]
}
""")
df = pl.read_json(json_file)
columns_to_explode = [col for col in df.columns if df[col].dtype == pl.List(pl.List)]
df = df.explode(columns_to_explode)
vertices = np.zeros((len(df), 3), dtype=np.float32)
bob = db.create_bob(vertices, name="DinoStar")
for col in df.columns:
data = np.vstack(df.get_column(col).to_numpy())
bob.store_named_attribute(data, col)
bob.named_attribute("Dino")array([[55.38460159, 97.17949677, 0. ],
[51.53850174, 96.02559662, 0. ]])
bob.named_attribute("Star")array([[58.21360016, 91.88189697, 0. ],
[58.19609833, 92.21499634, 0. ]])