MarwanDebbiche

MarwanDebbiche

MarwanDebbiche

from flask import Flask
from flask import request
import joblib
import pandas as pd
import json


with open("iris_classifier.joblib", "rb") as f:
    iris_classifier = joblib.load(f)

MarwanDebbiche

@app.route('/predict-species-proba', methods=['POST'])
def predict_species_proba():
    flower = {}
    for feature in iris_classifier_features:
        flower[feature] = [request.form[feature]]

    flower = pd.DataFrame(flower)

    probas = iris_classifier.predict_proba(flower[iris_classifier_features])[0, :].tolist()

MarwanDebbiche

[tool.poetry]
name = "tsgen"
version = "0.1.0"
description = "Time Series Generator"
authors = ["Marwan Debbiche <marwan.debbiche@example.com>"]
license = "MIT"

[tool.poetry.dependencies]
python = "^3.8"
pandas = "^1.1.3"

MarwanDebbiche

import pandas as pd
import numpy as np


class TimeSerie:
    def __init__(self, index, y):
        if not isinstance(index, pd.DatetimeIndex):
            raise TypeError("index should be a pandas.DatetimeIndex")
        self.index = index
        self.y = np.array(y)

MarwanDebbiche

import math

import numpy as np
import pandas as pd


from tsgen.time_serie import TimeSerie


def affine(start, end, freq, start_y, end_y):

MarwanDebbiche

from tsgen.time_serie import TimeSerie
import tsgen.generators as generators


__all__ = ["TimeSerie", "generators"]

MarwanDebbiche

import pandas as pd
import numpy as np
import pytest

from tsgen import TimeSerie


@pytest.fixture
def ts_monthly_constant():
    start = "2020"

MarwanDebbiche

repos:
  - repo: https://github.com/pre-commit/pre-commit-hooks
    rev: v3.2.0
    hooks:
      - id: check-yaml
      - id: debug-statements
      - id: end-of-file-fixer
      - id: trailing-whitespace
  - repo: local
    hooks: