在Jupyter Notebook上获取JsonDecodeError

Question

I'm setting up a Jupyter Notebook that apply a Machine learning model from the Ibm watson studio API to some datas that are coming from my Postgresql database.

While reshaping the data to be readable by the API, a JSONDecodeError: Expecting property name enclosed in double quotes: line 1 column 2 (char 1) appeared and I can't solve it.

This is the full traceback:

---------------------------------------------------------------------------
JSONDecodeError                           Traceback (most recent call last)
<ipython-input-114-9d8e7cf98a41> in <module>()
      1 import json
      2 
----> 3 classes = natural_language_classifier.classify_collection('7818d2s519-nlc-1311', reshaped).get_result()
      4 
      5 print(json.dumps(classes, indent=2))

/opt/conda/envs/DSX-Python35/lib/python3.5/site-packages/watson_developer_cloud/natural_language_classifier_v1.py in classify_collection(self, classifier_id, collection, **kwargs)
    152         if collection is None:
    153             raise ValueError('collection must be provided')
--> 154         collection = [self._convert_model(x, ClassifyInput) for x in collection]
    155 
    156         headers = {}

/opt/conda/envs/DSX-Python35/lib/python3.5/site-packages/watson_developer_cloud/natural_language_classifier_v1.py in <listcomp>(.0)
    152         if collection is None:
    153             raise ValueError('collection must be provided')
--> 154         collection = [self._convert_model(x, ClassifyInput) for x in collection]
    155 
    156         headers = {}

/opt/conda/envs/DSX-Python35/lib/python3.5/site-packages/watson_developer_cloud/watson_service.py in _convert_model(val, classname)
    461         if classname is not None and not hasattr(val, "_from_dict"):
    462             if isinstance(val, str):
--> 463                 val = json_import.loads(val)
    464             val = classname._from_dict(dict(val))
    465         if hasattr(val, "_to_dict"):

/opt/conda/envs/DSX-Python35/lib/python3.5/json/__init__.py in loads(s, encoding, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, **kw)
    317             parse_int is None and parse_float is None and
    318             parse_constant is None and object_pairs_hook is None and not kw):
--> 319         return _default_decoder.decode(s)
    320     if cls is None:
    321         cls = JSONDecoder

/opt/conda/envs/DSX-Python35/lib/python3.5/json/decoder.py in decode(self, s, _w)
    337 
    338         """
--> 339         obj, end = self.raw_decode(s, idx=_w(s, 0).end())
    340         end = _w(s, end).end()
    341         if end != len(s):

/opt/conda/envs/DSX-Python35/lib/python3.5/json/decoder.py in raw_decode(self, s, idx)
    353         """
    354         try:
--> 355             obj, end = self.scan_once(s, idx)
    356         except StopIteration as err:
    357             raise JSONDecodeError("Expecting value", s, err.value) from None

JSONDecodeError: Expecting property name enclosed in double quotes: line 1 column 2 (char 1)

Here's the code in my Notebook:

from watson_developer_cloud import NaturalLanguageClassifierV1
import pandas as pd
import psycopg2
import json

# connect to the database
conn_string = 'host={} port={}  dbname={}  user={}  password={}'.format('119.203.10.242', 5432, 'mydb', 'locq', 'Mypass***')
conn_cbedce9523454e8e9fd3fb55d4c1a52e = psycopg2.connect(conn_string)

# select the description column
data_df_1 = pd.read_sql('SELECT description from public."search_product"', con=conn_cbedce9523454e8e9fd3fb55d4c1a52e)

# package phrases into format required by Watson
reshaped = json.dumps({'collection': [{'text' : t} for t in data_df_1['description']]})

# connect to the Watson Studio API
natural_language_classifier = NaturalLanguageClassifierV1(
    iam_apikey='F76ugy8hv1s3sr87buhb7564vb7************'
)

# apply the model to the datas
classes = natural_language_classifier.classify_collection('7818d2s519-nlc-1311', reshaped).get_result()

# print the results
print(classes)

When I comment the classes line and I just do print(reshaped) , this is the response I'm getting which is the correct format for Watson studio:

{
  "collection": [
    {
      "text": "Lorem ipsum sjvh  hcx bftiyf,  hufcil, igfgvjuoigv gvj ifcil ,ghn fgbcggtc   yfctgg h vgchbvju."
    },
    {
      "text": "Lorem ajjgvc wiufcfboitf iujcvbnb hjnkjc  ivjhn oikgjvn uhnhgv 09iuvhb  oiuvh boiuhb mkjhv mkiuhygv m,khbgv mkjhgv mkjhgv."
    },
    {
      "text": "Lorem aiv ibveikb jvk igvcib ok blnb v  hb b hb bnjb bhb bhn bn vf vbgfc vbgv nbhgv bb nb nbh nj mjhbv mkjhbv nmjhgbv nmkn"
    },
    {
      "text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"
    },
    {
      "text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"
    },
    {
      "text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"
    },
    {
      "text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"
    }
  ]
}

Please help.

EDIT

This is what I just did:

reshape = json.dumps([{'text' : t} for t in data_df_1['description']])


print(reshape)

This is the result I'm getting:

[{"text": "Lorem ipsum sjvh  hcx bftiyf,  hufcil, igfgvjuoigv gvj ifcil ,ghn fgbcggtc   yfctgg h vgchbvju."}, {"text": "Lorem ajjgvc wiufcfboitf iujcvbnb hjnkjc  ivjhn oikgjvn uhnhgv 09iuvhb  oiuvh boiuhb mkjhv mkiuhygv m,khbgv mkjhgv mkjhgv."}, {"text": "Lorem aiv ibveikb jvk igvcib ok blnb v  hb b hb bnjb bhb bhn bn vf vbgfc vbgv nbhgv bb nb nbh nj mjhbv mkjhbv nmjhgbv nmkn"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "lorem sivbnogc hbiuygv bnjiuygv bmkjygv nmjhgv"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "lore  juhgv bnmkiuhygv nmkiuhb mkjiuhb mkjgv mkjhygv nmkjuytfrdc mjhygtfvc mkijuytfc vbnmkjuhygtfv bnmkjuhygtfvc mjhygv mjhgv nmjhuygv bnjhb mnhgv mjhgv njhgv bnjhb njhygvbnjkiuhbhjihbv mjhgbv nmkjhbhnjb njhgv njmkjhbvbh nhgv mbhhnb hjbhu njbhn njb n  jjijh bb jiji bi jiijib bkiijij b hggg."}, {"text": "Lorem uhygfv bniuhgv nmkjuhgv nmkijuhygv mkihv bjijnb bnjib bjinb bnjub vgvg bhgfc nhgytredxc ngtfv mkjuygfcv bnmjuygv mjhgv bnmkjhgv njhgv njgfvc."}]

I copied the results and replace the reshape with these datas:

#reshape = json.dumps([{'text' : t} for t in data_df_1['description']])

reshape = [{"text": "Lorem ipsum sjvh  hcx bftiyf,  hufcil, igfgvjuoigv gvj ifcil ,ghn fgbcggtc   yfctgg h vgchbvju."}, {"text": "Lorem ajjgvc wiufcfboitf iujcvbnb hjnkjc  ivjhn oikgjvn uhnhgv 09iuvhb  oiuvh boiuhb mkjhv mkiuhygv m,khbgv mkjhgv mkjhgv."}, {"text": "Lorem aiv ibveikb jvk igvcib ok blnb v  hb b hb bnjb bhb bhn bn vf vbgfc vbgv nbhgv bb nb nbh nj mjhbv mkjhbv nmjhgbv nmkn"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "lorem sivbnogc hbiuygv bnjiuygv bmkjygv nmjhgv"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx"}, {"text": "lore  juhgv bnmkiuhygv nmkiuhb mkjiuhb mkjgv mkjhygv nmkjuytfrdc mjhygtfvc mkijuytfc vbnmkjuhygtfv bnmkjuhygtfvc mjhygv mjhgv nmjhuygv bnjhb mnhgv mjhgv njhgv bnjhb njhygvbnjkiuhbhjihbv mjhgbv nmkjhbhnjb njhgv njmkjhbvbh nhgv mbhhnb hjbhu njbhn njb n  jjijh bb jiji bi jiijib bkiijij b hggg."}, {"text": "Lorem uhygfv bniuhgv nmkjuhgv nmkijuhygv mkihv bjijnb bnjib bjinb bnjub vgvg bhgfc nhgytredxc ngtfv mkjuygfcv bnmjuygv mjhgv bnmkjhgv njhgv njgfvc."}]


classes = natural_language_classifier.classify_collection('7818d2s519-nlc-1311', reshape).get_result()

print(classes)

And I got a successful response this way.. but that's not very a good way to do it. Any solution?

Answer 1

The problem was that json.dumps() was returning <class 'str'> (json representation) and the input to the classify_collections() required <class 'list'> . Hence we don't use json.dumps() here and simply replace to double quotes(") for the keys and pass <class 'list'> to the function.

reshape = [{"text" : t} for t in data_df_1["description"]]