我正在使用 Ibm Watson 在 Jupyter Notebook 中为机器学习项目设置一些 python 代码,当我尝试从我的 Postgresql 数据库表中添加数据时,我不断收到 TypeError is not JSON serializable。
为清楚起见,这里是完整的输出:
TypeError: description
0 Lorem ipsum sjvh hcx bftiyf, hufcil, igfgvju...
1 Lorem ajjgvc wiufcfboitf iujcvbnb hjnkjc ivjh...
2 Lorem aiv ibveikb jvk igvcib ok blnb v hb b h...
3 Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb...
4 Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb...
5 Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb...
6 Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb...
7 Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb...
8 Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb...
9 Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb...
10 Lorem sivbnogc hbiuygv bnjiuygv bmkjygv nmjhgv... is not JSON serializable
这是我的 python 代码,它部署了 ML 模型来分析这些数据,如您所见,这些数据是随机句子,但在测试后将成为产品描述:
from watson_developer_cloud import NaturalLanguageClassifierV1
import pandas as pd
import psycopg2
# Connecting to my database.
conn_string = 'host={} port={} dbname={} user={} password={}'.format('159.***.20.***', 5432, 'searchdb', 'lcq09', 'Mys3cr3tPass')
conn_cbedce9523454e8e9fd3fb55d4c1a52e = psycopg2.connect(conn_string)
data_df_1 = pd.read_sql('SELECT description from public."search_product"', con=conn_cbedce2drf563454e8e9fd3fb8776fgh2e)
# Connecting to the ML model.
natural_language_classifier = NaturalLanguageClassifierV1(
iam_apikey='TB97dFv8Dgug6rfi945F3***************'
)
# Apply the ML model to db datas
classes = natural_language_classifier.classify('9841d0z5a1-ncc-9076', data_df_1)
print(json.dumps(classes, indent=2)) # Pretty sure the error is happening here
我该如何解决这个问题?
编辑 1:
我尝试打印此方法:print(data_df_1.to_json())
以查看格式现在是否为 Json,这是我得到的输出:
{"description":{"0":"Lorem ipsum sjvh hcx bftiyf, hufcil, igfgvjuoigv gvj ifcil ,ghn fgbcggtc yfctgg h vgchbvju.","1":"Lorem ajjgvc wiufcfboitf iujcvbnb hjnkjc ivjhn oikgjvn uhn uhn 09iuvhb oiuvh boiuhb mkjhv mkiuhygv m,khbgv mkjhgv mkjhgv。”,“2”:“Lorem aiv ibveikb jvk igvcib ok blnb v hb b hb bnjb bhb bhn bn vf vbgfc vbgv nbhgv bb nb nbh nj mjhbv nmkjhb3”,“:"Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx","4":"Lorem jsvc smc cbd ciecdbbc d vd bcvdvbj obcvb vcibs j dvx","5":"Lorem jsvc smc cbd ciecdbbc d vd bcvdvbcibj obc j dvx"}}
但是当我添加这个方法时我现在得到这个错误:classes = natural_language_classifier.classify('9841d0z5a1-ncc-9076', data_df_1.to_json())
print(json.dumps(classes, indent=2))
到 classes
:
TypeError Traceback (most recent call last)
<ipython-input-16-e72fac39b809> in <module>()
1 classes = natural_language_classifier.classify('998520s521-nlc-1398', data_df_1.to_json())
----> 2 print(json.dumps(classes, indent=2))
/opt/conda/envs/DSX-Python35/lib/python3.5/json/__init__.py in dumps(obj, skipkeys, ensure_ascii, check_circular, allow_nan, cls, indent, separators, default, sort_keys, **kw)
235 check_circular=check_circular, allow_nan=allow_nan, indent=indent,
236 separators=separators, default=default, sort_keys=sort_keys,
--> 237 **kw).encode(obj)
238
239
/opt/conda/envs/DSX-Python35/lib/python3.5/json/encoder.py in encode(self, o)
198 chunks = self.iterencode(o, _one_shot=True)
199 if not isinstance(chunks, (list, tuple)):
--> 200 chunks = list(chunks)
201 return ''.join(chunks)
202
/opt/conda/envs/DSX-Python35/lib/python3.5/json/encoder.py in _iterencode(o, _current_indent_level)
434 raise ValueError("Circular reference detected")
435 markers[markerid] = o
--> 436 o = _default(o)
437 yield from _iterencode(o, _current_indent_level)
438 if markers is not None:
/opt/conda/envs/DSX-Python35/lib/python3.5/json/encoder.py in default(self, o)
177
178 """
--> 179 raise TypeError(repr(o) + " is not JSON serializable")
180
181 def encode(self, o):
TypeError: <watson_developer_cloud.watson_service.DetailedResponse object at 0x7f64ee350240> is not JSON serializable
-
如您在代码中所见,我想将机器学习文本分类器部署到我数据库中的描述表。
我可以用下面的代码对单个句子进行分类,但我想对整个数据库的描述表进行分类:
classes = natural_language_classifier.classify('998260x551-nlc-1018', '今天会有多热?')
打印(json.dumps(classes.result, indent=2))
这就是为什么我用数据框 data_df_1
替换句子的原因。
最佳答案
您需要将表转换为特定的 JSON 格式并使用 classify_collection()
方法,如 official documentation 中的示例所示
import json
from ibm_watson import NaturalLanguageClassifierV1
natural_language_classifier = NaturalLanguageClassifierV1(
iam_apikey='{apikey}',
url='{url}')
classes = natural_language_classifier.classify_collection('10D41B-nlc-1', [{'text':'How hot will it be today?'}, {'text':'Is it hot outside?'}]).get_result()
print(json.dumps(classes, indent=2))
关于python - 数据库表不是 JSON 可序列化的,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/56259311/