text: # coding: utf-8
  import pandas as pd
  
  from odsclient.utils import create_reading_buffer
  
  
  def ref_dataset_public_platform():
      """Return a reference dataset for the public ODS platform """
  
      dataset_id = "opendatasoft-offices"
  
      ref_csv = """Geo Point;Geo Shape;Office Name;Address
  48.8416126212,2.28492558002;"{""type"": ""Point"", ""coordinates"": [2.2849255800247192, 48.841612621157495]}";Paris HQ;"Opendatasoft
  130, rue de Lourmel
  75015 Paris, France"
  47.2176789432,-1.5440967679;"{""type"": ""Point"", ""coordinates"": [-1.5440967679023743, 47.217678943247684]}";Nantes Office;"Opendatasoft
  4 rue Voltaire
  44000 Nantes"
  42.3568473029,-71.0575962067;"{""type"": ""Point"", ""coordinates"": [-71.05759620666502, 42.356847302874996]}";Boston HQ;"Opendatasoft LLC
  50 Milk St, 16th floor
  Boston MA 02109, U.S.A."
  """ #.replace("\n", "\r\n")
  
      # we keep this hardcoded just in case the ref_df reading does not work as expected
      ref_shape = (3, 3)
  
      ref_df = pd.read_csv(create_reading_buffer(ref_csv, is_literal=True), sep=';')
      ref_df = ref_df.set_index(['Office Name']).sort_index()
  
      return dataset_id, ref_csv, ref_df, ref_shape
  
  
  def ref_dataset_other_platform():
      """ Return a reference dataset for the uat-data.exchange.se.com ODS platform """
  
      # shared info
      # dataset_id = "employment-by-sector-in-france-and-the-united-states-1800-2012"
      # base_url = "https://data.exchange.se.com/"
      dataset_id = "odsclient-reference-dataset"
      base_url = "https://uat-data.exchange.se.com/"
  
      ref_csv = """Transport;Année;Millions de Voyageurs
  SNCF - Trains/RER (y compris T4);;
  RATP - RER;;
  RATP - RER;2011;7575
  RATP - Métro;;
  RATP - RER;2014;7722
  RATP - Métro;2014;5194
  SNCF - Trains/RER (y compris T4);2011;11583
  RATP - RER;2010;7486
  RATP - RER;2013;7605
  SNCF - Trains/RER (y compris T4);2013;12103
  RATP - Métro;2012;5130
  RATP - RER;2012;7675
  SNCF - Trains/RER (y compris T4);2014;12148
  SNCF - Trains/RER (y compris T4);2010;11221
  RATP - Métro;2013;5044
  RATP - Métro;2010;4892
  SNCF - Trains/RER (y compris T4);2012;11816
  RATP - Métro;2011;5022
  """.replace("\n", "\r\n")
      ref_df = pd.read_csv(create_reading_buffer(ref_csv, is_literal=True), sep=';')
      ref_df = ref_df.set_index(['Transport', 'Année']).sort_index()
  
      ref_shape = (18, 1)
  
      return base_url, dataset_id, ref_csv, ref_df, ref_shape
  