TypeError: unhashable type: 'list'

Description

When using list as one of the inputs, I got this error

Context

I tried to pass a string and a list to the function, but I cannot. This will prevent me from passing any list as an argument to my function.

Steps to Reproduce

When I run this code

a = 'string'
b = [1,2,3]

def dummy_func(a, b):
   return 'hello'

data_catalog = DataCatalog({'events': MemoryDataSet()})
dummy_func_node =  node(func=dummy_func, inputs=[a, b], outputs='events')
pipeline = Pipeline([dummy_func_node])
runner = SequentialRunner()
print(runner.run(pipeline, data_catalog))

I got

Traceback (most recent call last):
  File "src/get_events.py", line 66, in main
    dummy_func_node =  node(func=dummy_func, inputs=[a, b], outputs='events')
  File "/home/khuyentran/anaconda3/envs/scraping/lib/python3.8/site-packages/kedro/pipeline/node.py", line 665, in node
    return Node(
  File "/home/khuyentran/anaconda3/envs/scraping/lib/python3.8/site-packages/kedro/pipeline/node.py", line 133, in __init__
    self._validate_inputs_dif_than_outputs()
  File "/home/khuyentran/anaconda3/envs/scraping/lib/python3.8/site-packages/kedro/pipeline/node.py", line 570, in _validate_inputs_dif_than_outputs
    common_in_out = set(self.inputs).intersection(set(self.outputs))
TypeError: unhashable type: 'list'

I looked at the source code, and it seems like this error is due to the fact that there will be an error if you take a set of a list of list in common_in_out = set(self.inputs).intersection(set(self.outputs)). I wonder if kedro provides any option when one of the inputs is a list?

Your Environment

Include as many relevant details about the environment in which you experienced the bug:

• Kedro version used: 0.16.4
• Python version used: Python 3.8.3
• Operating system and version: Ubuntu 19.10

[khuyentran1401]

Got it! I think this one provides a good example of how to create modular pipelines. You might want to fix the broken image on this website. This should give me enough information to experiment more with Kedro. Thank you for the help!

[limdauto]

@mzjp2 is correct. The mental model here is: the node(...) function receives a collection of dataset names as inputs and outputs, not the values themselves.