def notifyLabguru(content, members_ids, flow_title):
  url = f'{base()}/api/v1/web_notifications/notify'
  data = {
      "item": {
          "title":f"Labguru Automation - {flow_title}",
          "content": content
      },
      "recipients": members_ids,
      "token": token()
  }
  response = requests.post(url, json=data)
  print ("notifyLabguru response status_code", response.status_code)
  
### member_ids should be sent as an array

# Update the "name" field of the trigger_bacterium item using a PUT request

# Get the value of the "trigger_bacterium" variable
new_bac = variable("trigger_bacterium")

res = requests.put(f"{base()}/api/v1/bacteria/{new_bac['id']}", json={"token":token(), "item":{"name":new_item_name}})
print("request code is ", res.status_code)
if res.status_code // 100 == 2:
  print("created new item with name ", new_item_name)

# Get the value of the "trigger_bacterium" variable
new_bac = variable("trigger_bacterium")

# Initialize page count for pagination
page_count = 1

# Initialize a variable to store the last item in the list
last_item = ""

# Start a loop until the last_item is found
while not last_item:

  # Prepare the request body for the API call
  kendo_body = {
    "token": token(),
    "kendo": True,
    "page": page_count,
    "sort": {"0": {"field": "name", "dir": "desc"}},
    "filter":{
      "logic":"or",
      "filters":
          {"0":
           {
               "field":"name",
               "operator":"startswith",
               "value": "b"
           },
          }
      }
  }
  
  # Send a GET request to the API to retrieve page items and parse the response as JSON
  items_in_page = requests.get(f"{base()}/api/v1/bacteria", json=kendo_body).json()

#Adds a sample to sample element, provide sample element and item objects
def add_sample_to_sample_element(item, sample_element_id):
  # reset sample element data, necessary for update element
  reset = requests.put(f'{base()}/api/v1/elements/{sample_element_id}', json={
    'token': token(),
    'element': {
      'data': None
    }
  })


  # Add sample to sample element
  response = requests.post(f'{base()}/api/v1/samples', json={
    'token': token(),
    'item': { 
      "name": item['name'],
          "item_type": item['class_name'],
          "item_id": item['id'],
          "container_id": sample_element_id,
          "container_type": "Element",
    }
  })
  return response
#Examples

se = requests.get(f"{base()}/api/v1/elements/559", json={"token": token()}).json() #get a sample element
cell_line = requests.get(f"{base()}/api/v1/cell_lines/21", json={"token": token()}).json() #get an item

sample = add_sample_to_sample_element(cell_line, se)

#get elements from an experiment. must write exp. id. If all parameters left blank, return all elements in an experiment
def get_elements_from_experiment(exp_id, element_type='', element_name=''):
    if element_type:
        elements = requests.get(f'{base()}/api/v1/experiments/{exp_id}/elements', json={'token': token(), 'element_type':element_type}).json()
    elif element_name:
        elements = requests.get(f'{base()}/api/v1/experiments/{exp_id}/elements', json={'token': token(), 'name': element_name}).json()
    else:
        elements = requests.get(f'{base()}/api/v1/experiments/{exp_id}/elements', json={'token': token()}).json()
    return elements

#Example
get_elements_from_experiment(33, element_type='samples', element_name='')

#For entity, put only string with either "experiments" or "reports"
def copy_section(entity ,destination_id, section_id):
    if entity == "experiments" or entity == "reports":
      body = {'item':
                  {'item_id': f"{destination_id}",
                   'section_id': f"{section_id}"},
              "token": token()}
      res = requests.post(f'{base()}/api/v1/{entity}/copy_section', json=body)
      return res
    else:
      return "INVALID ENTITY"

# Retrieve data from dataset
data_list =[]
dataset = requests.get (f'{base()}/api/v1/datasets/nnn', json = {'token': token()})
# print ("get dataset", dataset.status_code)
dataset = variable ("dataset_1")
for vector in dataset["vectors"]:
  data_list.append(vector["vector"]["data"])
  print (vector["vector"]["data"])

# Create a DataFrame from the data
df = pd.DataFrame(data_list)