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README.md
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README.md
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# banner
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A discord bot for executing queries & searches on the Ellucian Banner instance hosting all of UTSA's class data.
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A complex multi-service system providing a Discord bot and browser-based interface to UTSA's course data.
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## Feature Wishlist
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## Services
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- Commands
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- ICS Download (get a ICS download of your classes with location & timing perfectly - set for every class you're in)
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- Classes Now (find classes happening)
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- Autocomplete
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- Class Title
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- Course Number
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- Term/Part of Term
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- Professor
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- Attribute
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- Component Pagination
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- RateMyProfessor Integration (Linked/Embedded)
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- Smart term selection (i.e. Summer 2024 will be selected automatically when opened)
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- Rate Limiting (bursting with global/user limits)
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- DMs Integration (allow usage of the bot in DMs)
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- Class Change Notifications (get notified when details about a class change)
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- Multi-term Querying (currently the backend for searching is kinda weird)
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- Full Autocomplete for Every Search Option
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- Metrics, Log Query, Privileged Error Feedback
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- Search for Classes
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- Major, Professor, Location, Name, Time of Day
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- Subscribe to Classes
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- Availability (seat, pre-seat)
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- Waitlist Movement
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- Detail Changes (meta, time, location, seats, professor)
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- `time` Start, End, Days of Week
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- `seats` Any change in seat/waitlist data
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- `meta`
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- Lookup via Course Reference Number (CRN)
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- Smart Time of Day Handling
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- "2 PM" -> Start within 2:00 PM to 2:59 PM
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- "2-3 PM" -> Start within 2:00 PM to 3:59 PM
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- "ends by 2 PM" -> Ends within 12:00 AM to 2:00 PM
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- "after 2 PM" -> Start within 2:01 PM to 11:59 PM
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- "before 2 PM" -> Ends within 12:00 AM to 1:59 PM
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- Get By Section Command
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- CS 4393 001 =>
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- Will require SQL to be able to search for a class by its section number
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The application consists of three modular services that can be run independently or together:
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## Analysis Required
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- Discord Bot ([`bot`][src-bot])
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Some of the features and architecture of Ellucian's Banner system are not clear.
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The follow features, JSON, and more require validation & analysis:
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- Primary interface for course monitoring and data queries
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- Built with [Serenity][serenity] and [Poise][poise] frameworks for robust command handling
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- Uses slash commands with comprehensive error handling and logging
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- Struct Nullability
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- Much of the responses provided by Ellucian contain nulls, and most of them are uncertain as to when and why they're null.
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- Analysis must be conducted to be sure of when to use a string and when it should nillable (pointer).
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- Multiple Professors / Primary Indicator
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- Multiple Meeting Times
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- Meeting Schedule Types
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- AFF vs AIN vs AHB etc.
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- Do CRNs repeat between years?
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- Check whether partOfTerm is always filled in, and it's meaning for various class results.
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- Check which API calls are affected by change in term/sessionID term select
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- SessionIDs
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- How long does a session ID work?
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- Do I really require a separate one per term?
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- How many can I activate, are there any restrictions?
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- How should session IDs be checked as 'invalid'?
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- What action(s) keep a session ID 'active', if any?
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- Are there any courses with multiple meeting times?
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- Google Calendar link generation, as an alternative to ICS file generation
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- Web Server ([`web`][src-web])
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## Change Identification
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- [Axum][axum]-based server with Vite/React-based frontend
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- [Embeds static assets][rust-embed] at compile time with E-Tags & Cache-Control headers
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- Important attributes of a class will be parsed on both the old and new data.
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- These attributes will be compared and given identifiers that can be subscribed to.
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- When a user subscribes to one of these identifiers, any changes identified will be sent to the user.
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- Scraper ([`scraper`][src-scraper])
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## Real-time Suggestions
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- Intelligent data collection system with priority-based queuing inside PostgreSQL via [`sqlx`][sqlx]
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- Rate-limited scraping with burst handling to respect UTSA's systems
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- Handles course data updates, availability changes, and metadata synchronization
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Various commands arguments have the ability to have suggestions appear.
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## Quick Start
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- They must be fast. As ephemeral suggestions that are only relevant for seconds or less, they need to be delivered in less than a second.
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- They need to be easy to acquire. With as many commands & arguments to search as I do, it is paramount that the API be easy to understand & use.
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- It cannot be complicated. I only have so much time to develop this.
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- It does not need to be persistent. Since the data is scraped and rolled periodically from the Banner system, the data used will be deleted and re-requested occasionally.
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```bash
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pnpm install -C web # Install frontend dependencies
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cargo build # Build the backend
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For these reasons, I believe SQLite to be the ideal place for this data to be stored.
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It is exceptionally fast, works well in-memory, and is less complicated compared to most other solutions.
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just dev # Runs auto-reloading dev build
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just dev bot,web # Runs auto-reloading dev build, running only the bot and web services
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just dev-build # Development build with release characteristics (frontend is embedded, non-auto-reloading)
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- Only required data about the class will be stored, along with the JSON-encoded string.
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- For now, this would only be the CRN (and possibly the Term).
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- Potentially, a binary encoding could be used for performance, but it is unlikely to be better.
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- Database dumping into R2 would be good to ensure that over-scraping of the Banner system does not occur.
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- Upon a safe close requested
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- Must be done quickly (<8 seconds)
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- Every 30 minutes, if any scraping ocurred.
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- May cause locking of commands.
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just build # Production build that embeds assets
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```
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## Scraping
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## Documentation
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In order to keep the in-memory database of the bot up-to-date with the Banner system, the API must be scraped.
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Scraping will be separated by major to allow for priority majors (namely, Computer Science) to be scraped more often compared to others.
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This will lower the overall load on the Banner system while ensuring that data presented by the app is still relevant.
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Comprehensive documentation is available in the [`docs/`][documentation] folder.
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For now, all majors will be scraped fully every 4 hours with at least 5 minutes between each one.
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- On startup, priority majors will be scraped first (if required).
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- Other majors will be scraped in arbitrary order (if required).
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- Scrape timing will be stored in Redis.
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- CRNs will be the Primary Key within SQLite
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- If CRNs are duplicated between terms, then the primary key will be (CRN, Term)
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Considerations
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- Change in metadata should decrease the interval
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- The number of courses scraped should change the interval (2 hours per 500 courses involved)
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## Rate Limiting, Costs & Bursting
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Ideally, this application would implement dynamic rate limiting to ensure overload on the server does not occur.
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Better, it would also ensure that priority requests (commands) are dispatched faster than background processes (scraping), while making sure different requests are weighted differently.
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For example, a recent scrape of 350 classes should be weighted 5x more than a search for 8 classes by a user.
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Still, even if the cap does not normally allow for this request to be processed immediately, the small user search should proceed with a small bursting cap.
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The requirements to this hypothetical system would be:
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- Conditional Bursting: background processes or other requests deemed "low priority" are not allowed to use bursting.
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- Arbitrary Costs: rate limiting is considered in the form of the request size/speed more or less, such that small simple requests can be made more frequently, unlike large requests.
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[documentation]: docs/README.md
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[src-bot]: src/bot
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[src-web]: src/web
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[src-scraper]: src/scraper
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[serenity]: https://github.com/serenity-rs/serenity
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[poise]: https://github.com/serenity-rs/poise
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[axum]: https://github.com/tokio-rs/axum
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[rust-embed]: https://lib.rs/crates/rust-embed
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[sqlx]: https://github.com/launchbadge/sqlx
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