/etl_economic_indicator

etl_economic_indicator is a a python program that download the economic data indicators in investing.com and upload it to a sql server database

Primary LanguagePython

etl_economic_indicator

Table of Contents

About

etl_economic_indicator is a a python program that download the economic data indicators in investing.com and upload it to a sql server database

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

First, you need to create a conda virtual environment together with python version 3.9.5 and at the same time install the dependencies in the requirements.txt file.

Windows CMD Terminal

conda create --name TypeYourVirtualEnvironmentHere python=3.9.5 --file requirements.txt

Next, activate the virtual environment that you just created now. In the windows terminal, type the following commands.

Windows CMD Terminal

conda activate TypeYourVirtualEnvironmentHere

Installing

Next, after you have created a conda virtual environment with python version 3.9.5 together with the dependencies in the requirements.txt, you need to pip install sqlconnection (the "Module"). In the windows terminal, type the following codes below.

Windows CMD Terminal

pip install version pip install git+https://github.com/Iankfc/etl_economic_indicator.git@master

To use the module in a pythone terminal, import the module just like other python modules such as pandas or numpy.

Python Terminal

from etl_economic_indicator import get_economic_data_from_investing_com as etl
str_date_filter_from = '1/1/1970'
str_date_filter_to = '9/6/2021'

ged = etl.class_get_economic_data_from_investing_com(   str_start_date = str_date_filter_from,
                                                    str_end_date = str_date_filter_to
                                                )

df_economic_data = ged.func_df_get_economic_data(bool_upload_data_to_sqlserver_True_or_False = True,
                                                    bool_sqlserver_upload_append_or_replace = 'append')

Usage

The module can be use to for extract transform and load (ETL) flow of data science.