Situation

Venezuela's e-commerce sector is expected to grow thanks to increasing internet penetration, an evolving legal framework, and banks that now provide more secure transactions ¹. After the pandemic, business boomed; the law requires invoices in the national currency (Bs.), but most products and transactions are advertised in USD. Let's look at 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 events ².

Its tech stack is an Odoo instance. There's no mobile app and billing happens directly in-store. A quick search indicates there are three extensions and one of them is free, but it might not be open source—I couldn't find a 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 a seamless shopping experience in two states ³.

They appear to use Angular with what looks like an Express backend, although I can't be certain. To stay compliant they need a few things:

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 have 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 Banco Central de Venezuela website.
• 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 published a starter implementation in this repo.

Let me know if you have any questions.

References

Photo by Frederick Medina on Unsplash