code: """
  This file contains some utilities from Neurowatch for visualizing local files of neurons and meshes in FlyBrainLab.
  """
  
  import json
  import pandas as pd
  
  def loadJSON(client, file_name, uname=None, mesh_class = 'Neuropil'):
      """Loads a mesh stored in the .json format.
      # Arguments
          client (FlyBrainLab Client): A FlyBrainLab Client.
          file_name (str): Database ID of the neuron or node.
          scale_factor (float): A scale factor to scale the neuron's dimensions with. Defaults to 1.
          uname (str): Unique name to use in the frontend. Defaults to the file_name.
          mesh_class (str): Mesh class to use. Can be "Neuropil" or "MorphologyData". Defaults to "Neuropil".
      # Examples:
          loadJSON(client, 'cloud.json', uname = 'my_neuropil')
  
      """
      with open(file_name) as f:
          data = json.load(f)
      if uname == None:
          uname = file_name.split('.')[0]
      rid = '#'+uname
      mesh_data = {'data': {'data': {rid: {'name': uname,
                      'uname': uname,
                      'morph_type': 'mesh',
                      'faces': data['faces'],
                      'vertices': data['vertices'],
                      'class': mesh_class}},
                    'queryID': '0-0'},
                   'messageType': 'Data',
                   'widget': 'NLP'}
      client.tryComms(mesh_data)
      
  def loadSWC(client, file_name, scale_factor=1., uname=None):
      """Loads a neuron skeleton stored in the .swc format.
      # Arguments
          client (FlyBrainLab Client): A FlyBrainLab Client.
          file_name (str): Database ID of the neuron or node.
          scale_factor (float): A scale factor to scale the neuron's dimensions with. Defaults to 1.
          uname (str): Unique name to use in the frontend. Defaults to the file_name.
      """
      neuron_pd = pd.read_csv(file_name,
                      names=['sample','identifier','x','y','z','r','parent'],
                      comment='#',
                      delim_whitespace=True)
      if uname == None:
          uname = file_name.split('.')[0]
      rid = '#'+file_name
      neuron_data = {'data': {'data': {rid: {'name': file_name,
              'uname': uname,
              'morph_type': 'mesh',
              'faces': list(scale_factor * neuron_pd['x']),
              'vertices': list(scale_factor * neuron_pd['y']),
              'class': 'MorphologyData'}},
            'queryID': '0-0'},
           'messageType': 'Data',
           'widget': 'NLP'}
      client.tryComms(neuron_data)
  
      return True
apis: pandas.read_csv