Using the official exchange rate in Venezuela's e-commerce

Situation

Venezuela’s e-commerce sector is expected to grow due to increasing Internet penetration, development of the legal framework, and improved capabilities of banks to provide secure transactions ¹. After the pandemic business boomed, it’s required by law to have a bill in the national currency (Bs.) but most products and transactions are advertised in USD. let’s see two examples:

Librería La Alegría is a bookstore and stationery store that offers over 15,000 products related to office supplies, school items, art supplies, technical and school books, games, and more. The store also provides a cultural center for the city with workshops for children and events².

It’s tech stack is an Odoo instance. There’s no mobile app. The billing is done directly in a store. A quick search indicates that there are 3 extension and on of them is free. But it might not be open source, I couldn’t find the repo.

Tu Zona Market is an online marketplace that connects local vendors with customers. The platform offers a range of products, including groceries, electronics, and home appliances, and provides customers with a seamless shopping experience in two states ³.

Uses Angular what looks like express backend, I can’t really be sure. So they needed two things for getting the:

1. A web scraper: a program that extracts data from a website by parsing its HTML code.
2. RESTful APIs with minimal code and high performance.
3. Database Storage for historical data (for returns, refunds and the like).

If you use a service like Exchange Rate API you can get the daily exchange rate, but you could get rate limited quickly.

Solution

If you got hardware

Creating a web scraper and using it with crawlab as storage in MongoDB is a great solution.

If you don’t

A simple web scraper built in Python with FastAPI can be useful for a software developer who wants to access and analyze the financial data from the official website of Banco Central de Venezuela.

By using a web scraper built in Python with FastAPI, you can:

• Automate the process of fetching the latest exchange rates, from the website of Banco Central de Venezuela.
• Convert the scraped data into JSON format, which can be stored, transmitted, and processed by various applications and tools.
• Create a custom API that exposes the scraped data as endpoints, which can be accessed by other developers or users who need the data for their own purposes.
• Apply data analysis, visualization, or machine learning techniques to the scraped data, using the rich set of libraries and packages available in Python.

I made a base public in ths repo.

Let me know if you have any questions.

References

Photo by Frederick Medina on Unsplash