Saving data
===========

Assuming the data has been succesfully returned from the API server endpoint, and is now loaded in memory, it can be saved. This functionality is handled within the `save_data.py` script. 

Prerequisites
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Given that the main data storage associated with this project is a MariaDB database, the connection to this database must be established first. This is done through the `sqlalchemy` package's `create_engine` function, which is further described in the `database <../database/index.html>`_ section.

Save the data using a single function call
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Once the database engine is available, it can be used in the pandas DataFrame object's method `to_sql` under the `con` argument to directly inject the data into the MariaDB database. For the actual implementation, see `save_data.py::save_df_to_db` method.

What to do when the database connection fails
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If the database connection fails, there is a backup mechanism that automatically saves the data to a local `.csv` file instead. For this, a *BACKUP_FOLDER_PATH* static variable is used to specify the path under which the file should be created.

 .. note::
    Although the `.csv` files are a reliable way to store data locally, their contents will not get displayed in the application. Periodically check the backup path for these backup files, and call the `save_df_to_db` function on these files to save them into the database. Given the simple database structure, this process should be quite reliable and error-proof.