[英]How to setup a request.py for this machine learning models?
我正在关注这个在线教程并使用Python部署机器学习模型。 我按照指示完成了所有部分,包括创建了model.py和request.py文件,并在Terminal中运行它们。
但是,我无法创建request.py文件来生成预测。 我的server.py是:
# Import libraries
import numpy as np
import flask
import pickle
app = flask.Flask(__name__)
model = pickle.load(open("model.pkl","rb"))
@app.route('/predict', methods=['POST'])
def predict():
feature_array = request.get_json()['feature_array']
#our model rates the wine based on the input array
prediction = model.predict([feature_array]).tolist()
#preparing a response object and storing the model's predictions
response = {}
response['predictions'] = prediction
#sending our response object back as json
return flask.jsonify(response)
而我的request.py:
import requests
# URL
url = 'http://localhost:5000/request'
r = requests.post(url,json=[7.4,0.66,0,1.8,0.075,13,40,0.9978,3.51,0.56,9.4])
print(r.json())
from flask import request
是否缺少server.py文件,如教程第2行所示?
在server.py文件中导入:
from flask import request
在server.py
文件的末尾添加它(用于在端口5000运行服务器, debug=True
以调试并解决错误,如果有的话):
if __name__ == '__main__':
app.run(port=5000, debug=True)
更新了request.py
文件(您的代码缺少在server.py
文件中引用的feature_array
键):
import requests, json
# URL
url = 'http://localhost:5000/predict'
r = requests.post(url, json={"feature_array":[7.4,0.66,0,1.8,0.075,13,40,0.9978,3.51,0.56,9.4]})
print(r.json())
在运行request.py
文件之前运行server.py
。
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