How to load a pickle file containing machine learning in c? - c

Question

I need to load the sklearn model via pickle file in C. But I do not find how to do that. This is my code and my model:
import pandas
from sklearn import model_selection
from sklearn.linear_model import LogisticRegression
import pickle
url = "https://raw.githubusercontent.com/jbrownlee/Datasets/master/pima-indians-diabetes.data.csv"
names = ['preg', 'plas', 'pres', 'skin', 'test', 'mass', 'pedi', 'age', 'class']
dataframe = pandas.read_csv(url, names=names)
array = dataframe.values
X = array[:, 0:8]
Y = array[:, 8]
test_size = 0.33
seed = 7
X_train, X_test, Y_train, Y_test = model_selection.train_test_split(X, Y, test_size=test_size, random_state=seed)
# Fit the model on 33%
model = LogisticRegression()
model.fit(X_train, Y_train)
print(model.score(X_test, Y_test))
# save the model to disk
filename = 'finalized_model.sav'
pickle.dump(model, open(filename, 'wb'))
I do not know how to do that. I would be grateful if you could help me, please.

Answer 1

There are always workarounds, One such way could be
Write a python flask based API/microservice over your python code & call it in c using the LibCurl library. I've made an asumption that your test_data will be a single column csv file, All flask apps runs on localhost:5000 by default. I will suggest you to write your own app with proper requests for arguments if your data doesnt't look like this. This piece of code is for reference only.
#python flask code
from flask import Flask
app = Flask(__name__)
#app.route('/')
def your_model():
test_data = pandas.read_csv('test_data.csv')
model = pickle.load("your_model.pkl")
pred_result = model.predict(test_data)
return(pred_result)
app.run()
/* c code*/
CURL *hnd = curl_easy_init();
curl_easy_setopt(hnd, CURLOPT_CUSTOMREQUEST, "POST");
curl_easy_setopt(hnd, CURLOPT_URL, "http://localhost:5000/your_API_name");
struct curl_slist *headers = NULL;
test_data_as_json_string = {""};
headers = curl_slist_append(headers, "any_parameter: value");
headers = curl_slist_append(headers, "content-type: application/json");
curl_easy_setopt(hnd, CURLOPT_HTTPHEADER, headers);
curl_easy_setopt(hnd, CURLOPT_POSTFIELDS, test_data_as_json_string);
CURLcode ret = curl_easy_perform(hnd);
This code too is for reference write your own c code or you can copy paste similar kind of code from Postman's code section while running the flask api.