# Copyright 2016 Google LLC.

#

# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at

#

# http://www.apache.org/licenses/LICENSE-2.0

#

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

# See the License for the specific language governing permissions and

# limitations under the License.

import logging

from flask import Flask

import numpy as np

app = Flask(__name__)

@app.route("/")

def calculate():

"""Performs a dot product on predefined arrays.

Returns:

Returns a formatted message containing the dot product result of

two predefined arrays.

"""

return_str = ""

x = np.array([[1, 2], [3, 4]])

y = np.array([[5, 6], [7, 8]])

return_str += f"x: {str(x)} , y: {str(y)}<br />"

# Multiply matrices

return_str += f"x dot y : {str(np.dot(x, y))}"

return return_str

@app.errorhandler(500)

def server_error(e):

"""Serves a formatted message on-error.

Returns:

The error message and a code 500 status.

"""

logging.exception("An error occurred during a request.")

return (

f"An internal error occurred: <pre>{e}</pre><br>See logs for full stacktrace.",

500,

)

if __name__ == "__main__":

# This is used when running locally. Gunicorn is used to run the

# application on Google App Engine. See entrypoint in app.yaml.

app.run(host="127.0.0.1", port=8080, debug=True)