Deploy and Publish your Corporate Finance Web App : Python Coding for Quantitative Finance

Опубликовано: 01 Январь 1970
на канале: QuantFinance

#QuantFinance #PythonCoding #FinanceWebApp #DeployApp #CorporateFinance #QuantitativeFinance #WebAppDeployment #PythonProgramming

Welcome to @QuantFinance! In this video, we’re diving into the crucial steps needed to deploy and publish your corporate finance web app using Python. This tutorial is part of our 'Python Coding for Quantitative Finance' series, where we cover everything you need to know to leverage Python in the realm of finance. Today’s focus is on taking your Shiny for Python app and making it accessible online for others to use and benefit from.

Video Title: Deploy and Publish your Corporate Finance Web App: Python Coding for Quantitative Finance

Overview:
In this comprehensive guide, we will walk you through the steps to deploy and publish your Shiny for Python app. Deploying a web app allows you to share your application with a broader audience, providing valuable insights and tools in the field of corporate finance. This video will cover the essential steps, from installing the necessary packages to deploying your app on a server. Whether you’re a finance professional, a data scientist, or a coding enthusiast, this tutorial will equip you with the skills needed to make your finance apps publicly accessible.

Steps Covered:

Step 1: Install rsconnect-python
To deploy your Shiny for Python app, you first need to install the rsconnect-python package. This package is essential for connecting your local app to the server where it will be deployed.
pip install rsconnect-python
This command installs the necessary package to facilitate the deployment process. Make sure your environment is set up correctly and that you have an internet connection to download the package.

Step 2: Add Your Account to rsconnect
Next, you need to add your account to rsconnect using your account details. Replace XXXXXXXXXXXXX and YYYYYYYYYYYYYYYYYYYYYYY with your actual token and secret.
rsconnect add --account NAME --name NAME --token XXXXXXXXXXXXX --secret YYYYYYYYYYYYYYYYYYYYYYYY python
This command connects your local development environment with your rsconnect account, allowing you to deploy apps directly from your local machine.

Step 3: Prepare Your Project Directory
Navigate to your project directory and prepare the environment requirements. The pip freeze command captures all the dependencies your app needs in a requirements.txt file.
cd 15PBPscenario
pip freeze requirements.txt

This step ensures that all necessary packages are listed and will be installed on the server where your app is deployed.

Step 4: Create a runtime.txt File
Create a runtime.txt file in your project directory. This file specifies the Python version your app uses. For instance, if your app uses Python 3.8.7, you would add the following line to the runtime.txt file:
python-3.8.7
Then, deploy your app for the first time using the --new flag. This command specifies the app name and title for the deployment .
rsconnect deploy shiny --new . --name NAME --title 15PBPscenario
This command initializes a new deployment, setting up the app on the server with the specified parameters.

Step 5: Deploy or Update Your App
Finally, deploy your app to the server. If you are deploying for the first time or creating a new deployment, use the following command.
rsconnect deploy shiny . --name NAME --title 15PBPscenario
To update an existing deployment, use:
rsconnect deploy shiny --new . --name NAME --title 15PBPscenario
This step publishes your app online, making it accessible to anyone with the link. The server will use the information in requirements.txt and runtime.txt to set up the environment correctly.

Key Features of the Video:

Interactive Deployment: Learn how to deploy a Shiny for Python app step-by-step.
Real-World Application: Focus on a corporate finance scenario, providing practical insights.
Comprehensive Guide: From package installation to final deployment, all steps are covered in detail.
Hands-On Example: See the entire process in action with clear, easy-to-follow instructions.
Why Subscribe to @QuantFinance?

Expert Guidance: Gain insights from an experienced professional in quantitative finance and Python programming.
Comprehensive Tutorials: Step-by-step guides that cover both fundamental and advanced topics in finance.
Interactive Learning: Learn how to create practical, real-world applications that you can use in your own projects.
Engaging Content: High-quality videos designed to keep you engaged and motivated throughout your learning journey.
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