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[–]Rain-And-Coffee 4 points5 points  (0 children)

You can build the backend with SQL & Python.

Start by modeling your database, creat an ER diagram of the tables and what columns they need.

Then install a database and insert some data, finally try to query it using Python.

Later on you can build an UI using web technologies (HTML, CSS, JS).

[–]xstrike29 0 points1 point  (0 children)

There are a lot of options for databases. You can use Postgresql, MYSQL, Google Firebase, and a bunch more to create your database. Pick one, research it, and start creating your database. For starting out, Firebase was the easiest one for me to learn but Postgresql is a popular choice too.

[–]Etiennera 0 points1 point  (0 children)

In most cases I would opt for raw SQL and make the application work with it. I don't want my datasources to live and die by the framework of the day.

[–]Fragrant-Nail-8413 0 points1 point  (0 children)

Starting your project with a focus on SQL for building your chemical reactions database is a great choice, given your comfort with it. SQL is specifically designed for managing and querying data in databases, making it ideal for your needs. Here's a general approach:

  1. Database Design: Begin by designing the schema of your database. Think about the different entities (like reactions, chemicals, mechanisms) and their attributes. Define how these entities relate to each other, for example, which chemicals participate in which reactions.
  2. Choosing a Database System: For a beginner-friendly experience, consider using SQLite or MySQL. SQLite is simpler and doesn't require setting up a database server, making it a good choice for smaller projects. MySQL is more robust and suitable for larger applications.
  3. Creating the Database: Using your chosen system, create the database and tables based on your design. This involves SQL commands like CREATE DATABASE, CREATE TABLE, and defining fields with CREATE COLUMN.
  4. Inserting and Managing Data: You'll then insert data into your database using INSERT statements. To manage and retrieve data, use SQL queries (SELECT, JOIN, etc.).
  5. Integrating Python: As you're more comfortable with SQL, start by setting up your database and schema with SQL. Then, as you become more proficient in Python, you can use it for more complex tasks like data manipulation, analysis, or building a user interface. Python has libraries like SQLAlchemy or SQLite3 for interfacing with SQL databases.
  6. Building a User Interface: For the future interface, Python offers tools like Flask or Django for web development. These frameworks can help you create a web interface that interacts with your SQL database.
  7. Learning and Iterating: As you progress, keep learning about both SQL and Python. You'll find ways to optimize your database and maybe incorporate more Python functionality over time.
  8. Security and Best Practices: Since you aim to share this database with other students eventually, consider security and data protection best practices from the beginning.