5vA1GEC6

1#https://gist.github.com/gbaman/b3137e18c739e0cf98539bf4ec4366ad
2import requests
3import pandas as pd
4url = "https://api.pipefy.com/graphql"
5
6payload = """{\"query\":\"{ me { name } }\"}"""
7#TODO:retirar essa key daí pfv!!!!!
8headers = {
9    'authorization': "Bearer SUA_KEY_DO_PIPEFY_AQUI",
10    'content-type': "application/json"
11    }
12def run_query(query): # A simple function to use requests.post to make the API call. Note the json= section.
13    request = requests.post('https://api.pipefy.com/graphql', json={'query': query}, headers=headers)
14    if request.status_code == 200:
15        return request.json()
16    else:
17        raise Exception("Query failed to run by returning code of {}. {}".format(request.status_code, query))
18
19def get_table_record(id):
20  query = """
21  {
22    table_record(id: """+str(id)+""") {
23      assignees {
24        id
25        name
26      }
27      created_at
28      created_by {
29        id
30        name
31      }
32      due_date
33      finished_at
34      id
35      labels {
36        id
37        name
38      }
39      parent_relations {
40        name
41        source_type
42      }
43      record_fields {
44        array_value
45        date_value
46        datetime_value
47        filled_at
48        float_value
49        name
50        required
51        updated_at
52        value
53      }
54      summary {
55        title
56        value
57      }
58      table {
59        id
60      }
61      title
62      updated_at
63      url
64    }
65  }
66  """
67  return run_query(query)
68
69def get_table(id):
70  query = """
71  {
72    table_records( table_id: \""""+str(id)+"""\") {
73      edges {
74        
75        cursor
76        node {
77          id
78          title
79          url
80        
81        }
82      }
83      pageInfo {
84        endCursor
85        hasNextPage
86        hasPreviousPage
87        startCursor
88        
89      }
90    }
91  }
92  """
93  return run_query(query)
94
95#Database Inventário
96inventario_table = get_table("T_WuNkpd")
97print(inventario_table)
98#Coletando os ids
99item_ids = []
100for edge in inventario_table['data']['table_records']['edges']:
101  item_ids.append(edge['node']['id'])
102
103#Coletando as colunas da database
104columns = []
105record_to_extract_column = get_table_record(item_ids[0])
106for record_field in record_to_extract_column['data']['table_record']['record_fields']:
107  columns.append(record_field['name'])
108  #print(i['name'])
109  #print(i['value'])
110
111inventario_df = pd.DataFrame()
112
113#Salvando os Itens dentro do dataframe
114for item_id in item_ids:
115  record_aux = get_table_record(item_id)
116  record_dict_aux = {}
117  for record_field in record_aux['data']['table_record']['record_fields']:
118    if record_field['name'] not in record_dict_aux.keys():
119      record_dict_aux.update({record_field['name']:0})
120    record_dict_aux[record_field['name']] = record_field['value']
121    #print(record_field['name'])
122    #print(record_field['value'])
123  print(record_dict_aux)
124  inventario_df = inventario_df.append(record_dict_aux,ignore_index=True)
125
126inventario_df.to_csv('inventario.csv')
127print(columns)