use schala_repl::{ ComputationRequest, ComputationResponse, GlobalOutputStats, LangMetaRequest, LangMetaResponse, ProgrammingLanguageInterface, }; use stopwatch::Stopwatch; use crate::{ error::SchalaError, parsing, reduced_ir, symbol_table, tokenizing, tree_walk_eval, type_inference, }; /// All the state necessary to parse and execute a Schala program are stored in this struct. pub struct Schala<'a> { /// Holds a reference to the original source code, parsed into line and character source_reference: SourceReference, //state: eval::State<'static>, /// Keeps track of symbols and scopes symbol_table: symbol_table::SymbolTable, /// Contains information for type-checking type_context: type_inference::TypeContext, /// Schala Parser active_parser: parsing::Parser, /// Execution state for AST-walking interpreter eval_state: tree_walk_eval::State<'a>, timings: Vec<(&'static str, std::time::Duration)>, } /* impl Schala { //TODO implement documentation for language items /* fn handle_docs(&self, source: String) -> LangMetaResponse { LangMetaResponse::Docs { doc_string: format!("Schala item `{}` : <>", source) } } */ } */ impl<'a> Schala<'a> { /// Creates a new Schala environment *without* any prelude. fn new_blank_env() -> Schala<'a> { Schala { source_reference: SourceReference::new(), symbol_table: symbol_table::SymbolTable::new(), type_context: type_inference::TypeContext::new(), active_parser: parsing::Parser::new(), eval_state: tree_walk_eval::State::new(), timings: Vec::new(), } } /// Creates a new Schala environment with the standard prelude, which is defined as ordinary /// Schala code in the file `prelude.schala` #[allow(clippy::new_without_default)] pub fn new() -> Schala<'a> { let prelude = include_str!("../source-files/prelude.schala"); let mut env = Schala::new_blank_env(); let response = env.run_pipeline(prelude, SchalaConfig::default()); if let Err(err) = response { panic!("Error in prelude, panicking: {}", err.display()); } env } /// This is where the actual action of interpreting/compilation happens. /// Note: this should eventually use a query-based system for parallelization, cf. /// https://rustc-dev-guide.rust-lang.org/overview.html fn run_pipeline(&mut self, source: &str, config: SchalaConfig) -> Result { self.timings = vec![]; let sw = Stopwatch::start_new(); // 1st stage - tokenization // TODO tokenize should return its own error type let tokens = tokenizing::tokenize(source); if let Some(err) = SchalaError::from_tokens(&tokens) { return Err(err); } //2nd stage - parsing self.active_parser.add_new_tokens(tokens); let ast = self .active_parser .parse() .map_err(|err| SchalaError::from_parse_error(err, &self.source_reference))?; self.timings.push(("parsing", sw.elapsed())); let sw = Stopwatch::start_new(); //Perform all symbol table work self.symbol_table .process_ast(&ast, &mut self.type_context) .map_err(SchalaError::from_symbol_table)?; self.timings.push(("symbol_table", sw.elapsed())); // Typechecking // TODO typechecking not working //let _overall_type = self.type_context.typecheck(&ast).map_err(SchalaError::from_type_error); let sw = Stopwatch::start_new(); let reduced_ir = reduced_ir::reduce(&ast, &self.symbol_table, &self.type_context); self.timings.push(("reduced_ir", sw.elapsed())); let sw = Stopwatch::start_new(); let evaluation_outputs = self.eval_state.evaluate(reduced_ir, &self.type_context, config.repl); self.timings.push(("tree-walking-evaluation", sw.elapsed())); let text_output: Result, String> = evaluation_outputs.into_iter().collect(); let text_output: Result, SchalaError> = text_output.map_err(|err| SchalaError::from_string(err, Stage::Evaluation)); let eval_output: String = text_output.map(|v| Iterator::intersperse(v.into_iter(), "\n".to_owned()).collect())?; Ok(eval_output) } } /// Represents lines of source code pub(crate) struct SourceReference { lines: Option>, } impl SourceReference { fn new() -> SourceReference { SourceReference { lines: None } } fn load_new_source(&mut self, source: &str) { //TODO this is a lot of heap allocations - maybe there's a way to make it more efficient? self.lines = Some(source.lines().map(|s| s.to_string()).collect()); } pub fn get_line(&self, line: usize) -> String { self.lines .as_ref() .and_then(|x| x.get(line).map(|s| s.to_string())) .unwrap_or_else(|| "NO LINE FOUND".to_string()) } } #[allow(dead_code)] #[derive(Clone, Copy, Debug)] pub(crate) enum Stage { Tokenizing, Parsing, Symbols, ScopeResolution, Typechecking, AstReduction, Evaluation, } fn stage_names() -> Vec<&'static str> { vec!["tokenizing", "parsing", "symbol-table", "typechecking", "ast-reduction", "ast-walking-evaluation"] } #[derive(Default, Clone)] pub struct SchalaConfig { pub repl: bool, } impl<'a> ProgrammingLanguageInterface for Schala<'a> { //TODO flesh out Config type Config = SchalaConfig; fn language_name() -> String { "Schala".to_owned() } fn source_file_suffix() -> String { "schala".to_owned() } fn run_computation(&mut self, request: ComputationRequest) -> ComputationResponse { let ComputationRequest { source, debug_requests: _, config: _ } = request; self.source_reference.load_new_source(source); let sw = Stopwatch::start_new(); let main_output = self.run_pipeline(source, request.config).map_err(|schala_err| schala_err.display()); let total_duration = sw.elapsed(); let stage_durations: Vec<_> = std::mem::replace(&mut self.timings, vec![]) .into_iter() .map(|(label, duration)| (label.to_string(), duration)) .collect(); let global_output_stats = GlobalOutputStats { total_duration, stage_durations }; ComputationResponse { main_output, global_output_stats, debug_responses: vec![] } } fn request_meta(&mut self, request: LangMetaRequest) -> LangMetaResponse { match request { LangMetaRequest::StageNames => LangMetaResponse::StageNames(stage_names().iter().map(|s| s.to_string()).collect()), _ => LangMetaResponse::Custom { kind: "not-implemented".to_string(), value: "".to_string() }, } } }