![]() ![]() Navigate to to the notebooks folder and run these notebooks:.Open a Jupyter Notebook within the environment from the repo.To regenerate the gradebook database, you need to: The databases already exist in the rep and the flask app can be run immediately.Make sure for this task and all future tasks that you activate your environment each time.After cloning the repository, you will need to access a terminal within the repo's root directory.Generate project environment using venv: python -m venv venv.Create conda environment for Python version 3.9.9 but 3.6+ should be fine.With studentCTE(student_id, person_id,sCTEcohort_id) ASĪND DATE() = bin) AND (next_bin IS NULL OR days_from_due_date < next_bin) Here is an example of a query that bins student homework submission status into bins like "very late", "late", "early", "very early", etc: Examples of the queries can be found in the queries folder. DBeaver can be used to interact with multiple RDBMS. This software works as an interface program similar to what pgAdmin is to PostgreSQL. Queries using the SQLite database were developed using DBeaver. Sample queries can be found in the db_query.ipynb notebook. The data is added through the db_insert.ipynb notebook in the same folder. The schema model can be found in the notebook folder within the db_setup.ipynb notebook. The data is also contained in the form of CSV files. SQLite files are generated using SQLAlchemy and the ORM. The modals are connected to the page through the myModal.js reference.Ĭharts are added through flask macros in coordination with javascript functions.įig 6.Functions for plotting are connected to each page through the m圜hart.js reference. ![]() Currently, data is connected to each page through the data.js referce but the unit.html page uses only flask API data.Repeated page elements are found in the base template page: layouts.html There are currently five pages including: The flask webpages can be found in the templates folder. This will aid with future modifications and site consistency. In in a similar manner, javascript functions were made that generate the plot based on the plot type. Since many parts of the website are repeated, flask templates and flask template parts were used so page element were modular. The user interace for the application is made with the Bootstrap5 framework with Plotly charts. The choices mimic the type of data that is typically found in the Microsoft SQLExpress sample database which is also about school enrollments and my person experiences working in education. ![]() The data files (CSV files and SQLite files) in this repo are fake and designed based on a schema that I made. The next step will also involve developing scripts that will update a database as part of Phase 7.Ī strategy has been developed to create a utility.db database that will contain settings for the application and create a way of introducing and updating monitoring guidelines and tools. Some additional graphics will need to be developed to have the student-centered effect the project mission was to serve. Phase 5 is only partially complete and additional routes need to be developed to replace the placeholder data found in the webpages. The remaining steps have not been started. Phases 6 is also complete but contains priveleged information and will not be added to a public repository. This means that Phases 1,2,3,4,and 5 are approaching completion with most of those steps being completely done. This repo holds the content of the database schema, fake data, and Flask server with HTML interface.
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