class_docstr: Organises data transformations into a pipeline.
  
  Example
  -------
  >>> pipeline = DataPipeline(
  ...     static_data_keys=["text"],
  ...     dynamic_items=[
  ...     {"func": lambda x: x.lower(), "takes": "text", "provides": "foo"},
  ...     {"func": lambda x: x[::-1], "takes": "foo", "provides": "bar"},
  ...     ],
  ...     output_keys=["bar"],
  ... )
  >>> pipeline({"text": "Test"})
  {'bar': 'tset'}
class_docstr_tok: ["Organises","data","transformations","into","a","pipeline",".","Example","--","--","--","-",">",">",">","pipeline","=","DataPipeline","(","...","static_data_keys=","[","``","text","''","]",",","...","dynamic_items=","[","...","{","``","func","''",":","lambda","x",":","x.lower","(",")",",","``","takes","''",":","``","text","''",",","``","provides","''",":","``","foo","''","}",",","...","{","``","func","''",":","lambda","x",":","x","[",":",":-1","]",",","``","takes","''",":","``","foo","''",",","``","provides","''",":","``","bar","''","}",",","...","]",",","...","output_keys=","[","``","bar","''","]",",","...",")",">",">",">","pipeline","(","{","``","text","''",":","``","Test","''","}",")","{","'bar","'",":","'tset","'","}"]
docstr: Informs the pipeline about static items.
  
  Static items are the ones provided to __call__ as data.
docstr_tok: ["Informs","the","pipeline","about","static","items",".","Static","items","are","the","ones","provided","to","__call__","as","data","."]
code: def add_static_keys(self, static_keys):
      """Informs the pipeline about static items.
  
      Static items are the ones provided to __call__ as data.
      """
      for key in static_keys:
          node_id = self.dg.add_node(data=StaticItem(key=key))
          self.key_to_node[key] = node_id
  
imports: import inspect
  from dataclasses import dataclass
  from speechbrain.utils.depgraph import DependencyGraph
label_desc: Use image node_id 2 for calling the DataPipeline obj's underlying member method code with example usage: obj.add_static_keys(static_keys) without return types