title: Numba, Jitclass w/ nopython mode and dictionaries
body: <p>trying to figure out how to skip a class method while using jitclass.</p>
  
  <p>Have a pretty big recursive model (pretty much, a massive for-loop), which - given path-dependent calculations, cannot be vectorized with straight Numpy.</p>
  
  <p>The class runs through a series of numpy arrays, with generally numba-friendly syntax, however I have one section which calls a few of the methods in an ordered fashion:</p>
  
  <pre><code>def operations(self, i, ops_order_config):
  
      ops_dict = self.ops_dict
  
      for index in range(len(waterfall_config)):
          try:
              if isinstance(ops_config[index], tuple):
                  ops_dict[ops_config[index][0]](i, ops_config[index][1])
              else:
                  ops_dict[ops_config[index]](i)
          except KeyError:
              pass
  </code></pre>
  
  <p>This part of the model is pretty crucial for flexibility - the "config" is an ordered list of tuples which contain the appropriate method to call, and the respective parameters. The ops_dict holds the actual self. that is called from the config, with proper parameters.</p>
  
  <p>If I'm making a jitclass, is there any way to just skip over jitting this dictionary aspect?</p>