Numpy-Neuron / app.py
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successfully returning data on how the neural network performed
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from flask import Flask, request, jsonify, make_response
from dataset.random import random_dataset
from opts import options
app = Flask(
__name__,
static_folder="static",
template_folder="templates",
)
def not_valid(params: dict):
"""
is_valid() simply checks if
an incoming response is valid
for this api or not. Key to
avoiding errors
"""
if "algorithm" not in params:
return "User did not specify the algorithm parameter"
if params["algorithm"] not in options:
return f"Invalid algorithm '{params['algorithm']}' is invalid."
return False
@app.route("/", methods=["GET"])
def index():
params = request.json
error_message = not_valid(params=params)
if error_message:
return make_response(error_message, 400)
# parse arguments
algorithm = options[params["algorithm"]]
args = params["arguments"]
# in the future instead of a random data set
# we should do a more real one like palmer penguins
X, y = random_dataset(100, 10)
model = algorithm(X, y, args)
return jsonify(model)
if __name__ == "__main__":
app.run(
debug=True,
)