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Sprints 0-8: Types, schema, KSEI parser, entity resolution, DB CRUD, Bing API client, import pipeline, query commands, graph traversal, changes diff, entity resolution CLI, FTS5 search. - KSEI PDF parser (mutool stext + quick-xml, 99.2% accuracy) - 7 query commands: ticker, entity, search, cross-holders, concentration, flow, releases - Ownership graph with recursive CTE (ASCII tree + Graphviz DOT) - Release diff/changes between KSEI snapshots - Entity resolution CLI: unresolved, map, merge - FTS5 trigram search on entity names - Feature-gated under 'ownership' (default-on) - 82 tests passing
127 lines
4.1 KiB
Markdown
127 lines
4.1 KiB
Markdown
# Conventions
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## Design Philosophy
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### Schema-Driven Development
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Define data types FIRST, then build logic around them. Types are the spec.
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```rust
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// ✅ Good: rich type with documented fields, integer precision
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct KseiHolding {
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/// Ownership percentage in basis points: 41.10% → 4110.
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pub percentage_bps: i64,
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/// Total shares held (absolute count).
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pub total_shares: i64,
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}
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// ❌ Bad: stringly-typed, float precision
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pub struct Holding {
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pub percentage: f64, // what unit? what precision?
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pub shares: String, // why string?
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}
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```
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### Functional Approach
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Parse/transform functions are **pure**: take input, return `Result<T, IdxError>`, no side effects.
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```rust
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// ✅ Good: pure function, testable in isolation
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pub fn parse_id_number(s: &str) -> Result<i64, IdxError> { ... }
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pub fn normalize_name(raw: &str) -> String { ... }
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pub fn parse_quote_from_str(symbol: &str, raw: &str) -> Result<Quote, IdxError> { ... }
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// ❌ Bad: function with side effects, hard to test
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pub fn fetch_and_save_quote(symbol: &str) -> Result<(), IdxError> { ... }
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```
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### Types Over Primitives
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Use newtypes, enums, and rich structs. Avoid `String` where a domain type exists.
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```rust
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// ✅ Good
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pub struct InvestorTypeCode(pub String);
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pub enum Locality { Local, Foreign }
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pub enum FlowSignal { Holder, Buyer, Seller, NewPosition, Exited }
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// ❌ Bad
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pub type InvestorType = String;
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pub type Locality = String;
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```
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## Naming
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### Files
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- `types.rs` — domain data types for a module
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- `mod.rs` — module declarations and re-exports
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- `client.rs` — HTTP client code
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- `map.rs` / `parse.rs` — response mapping / parsing functions
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- `raw_types.rs` — raw API response shapes (before normalization)
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### Functions
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- `parse_*` — deserialize raw data into domain types
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- `normalize_*` — clean/transform data (names, numbers, dates)
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- `resolve_*` — lookup/match entities
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- `query_*` — read from database
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- `fetch_*` — HTTP requests to external APIs
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- `render_*` — output formatting (tables, JSON)
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- `handle` — CLI command dispatch entry point
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### Types
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- `*Raw` / `*RawRow` — pre-normalization data (strings from API/PDF)
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- `*Holding` — ownership fact row
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- `*Metrics` — computed analytics
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- `*Row` — display-ready composite type
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- `*Args` — clap command arguments
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## Patterns
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### Provider Trait Pattern
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```rust
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pub trait QuoteProvider {
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fn quote(&self, symbol: &str) -> Result<Quote, IdxError>;
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}
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// Factory function, not direct construction
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pub fn default_provider(kind: ProviderKind) -> Box<dyn MarketDataProvider> { ... }
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```
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### Parse Pipeline Pattern
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```rust
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// Raw API response → domain type, always via parse function
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let raw: &str = &response_body;
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let quote = yahoo::parse_quote_from_str("BBCA.JK", raw)?;
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```
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### DB Function Pattern
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```rust
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// Take &Connection, caller manages lifetime. Use transactions for bulk.
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pub fn insert_ksei_holdings(conn: &Connection, holdings: &[KseiHolding]) -> Result<usize, IdxError> { ... }
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pub fn query_ticker_holdings(conn: &Connection, code: &str) -> Result<TickerOwnership, IdxError> { ... }
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```
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### Error Propagation
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```rust
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// Map external errors to IdxError variants
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let conn = Connection::open(path)
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.map_err(|e| IdxError::DatabaseError(e.to_string()))?;
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```
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## Integer Precision
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- **Percentages:** basis points (i64). `41.10%` → `4110`
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- **Shares:** absolute count (i64). No floats.
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- **Prices:** whole IDR (i64). Rounded from float at parse boundary.
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- **Money (USD):** whole dollars (i64) for Bing data.
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## Testing
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- **Unit tests:** pure functions (parsers, normalizers, signals)
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- **Integration tests:** in-memory SQLite (`Connection::open_in_memory()`), mock providers
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- **Fixtures:** `tests/fixtures/*.json` — real API responses, sanitized
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- **No live API calls in CI** — `IDX_USE_MOCK_PROVIDER=1`
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- **Test naming:** `test_<function>_<scenario>` (e.g., `test_parse_id_number_with_dots`)
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## Git / VCS
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- **jj (Jujutsu)** as local workflow, colocated with git
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- Push via `nix develop --command git push` (for prek hooks)
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- Branch naming: `feat/<name>`, `fix/<name>`
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- Commit messages: conventional commits (`feat:`, `fix:`, `refactor:`, `docs:`)
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