PennyQ

from glue.config import importer, settings
from glue.core import Data
from glue.core import DataCollection

from qtpy import QtGui
from qtpy.QtWidgets import QWidget, QInputDialog, QLineEdit

import numpy as np
# TODO: write a test code

PennyQ

import fasttext
import mlflow.pyfunc


class FastTextWrapper(mlflow.pyfunc.PythonModel):
    """
    Class to train and use FastText Models
    """

    def load_context(self, context):

PennyQ

from airflow import DAG
from airflow.operators.python import PythonOperator, PythonVirtualenvOperator, BranchPythonOperator
from airflow.operators.bash import BashOperator 

from datetime import datetime


def choose_stock(ti):
    data = ti.xcom_pull(task_ids="download_yf")
    spy_data = data['Close']['SPY']

PennyQ

# Repo: MySpace/TemplateRepo
# File: azure-pipeline.yml

name: cicd_ci

trigger:
  branches:
    include:
      - master

PennyQ

# Repo: MySpace/TemplateRepo
# File: ci_template.yml

  jobs:
  - job:
    displayName: yamllint_checks
    pool:
      vmImage: 'ubuntu-latest'
    steps:
    - script: |

PennyQ

# Repo: MySpace/UserRepo
# File: azure-pipeline2.yml

name: cicd_ci

trigger:
  branches:
    include:
      - master

PennyQ

# Repo: MySpace/UserRepo
# File: azure-pipeline3.yml

name: cicd_ci

trigger:
  branches:
    include:
      - master

PennyQ

# Repo: MySpace/TemplateRepo
# File: ci_template.yml

parameters:
- name: pylint_threshold
  type: string
  default: 8.0
- name: lint_folder
  type: string
  default: "mockcase-on-test"

PennyQ

# Repo: MySpace/UserRepo
# File: azure-pipeline3.yml

name: cicd_ci

variables:
  - name: PylintThreshold
    value: 8.0
  - name: LintFolder
    value: "folder_dir"

PennyQ

import fasttext
import mlflow
from .fast_text_wrapper import FastTextWrapper

def save_model(
    df: pd.DataFrame,
    model_name: str = "model_name",
    corpus_filename: str = "prepared_corpus",
    prepared_content: str = "prepared_text",
):