# **[rustlr](https://docs.rs/rustlr/latest/rustlr/index.html)**
**LR(1) and LALR(1) parser generator by Chuck Liang.**
**A [Tutorial](https://cs.hofstra.edu/~cscccl/rustlr_project/) is being prepared.**
The project grew out of the author's compiler construction and
programming languages classes over the years. It has been used for
implmentating modestly scaled, experimental programming languages. It
will be become more robust, with enhanced features, in future
releases.
#### Version 0.1.1:
The ability to train the parser has been added: the [Runtime::parse_train][1]
function will ask for user input to improve error reporting by augmenting
the basic generated LR state machine with Error entries.
#### Version 0.1.2:
Fixed problem with Accept state; added LBox smartpointer for encapsulating
lexical information into abstract syntax.
The parse function has been decomposed into a parse_core, which takes a
functional argument that handles error reporting. This allows a custom
parser interface to be created if one does not wish to be restricted to
the supplied [RuntimeParser::parse][2] function, which uses stdio.
#### Version 0.1.3:
Training the parser now modifies the same parser file that it reads from.
The ability to use LBox and LRc for non-intrusively encapsulating lexical
(line/column/source) information into abstract syntax has been expanded.
Fixes an error where a non-terminal symbol is declared without any rules
defined for it.
parse_core has been retained but a new parse_base function is
introduced that takes as input the error handler as a trait object.
This should allow better flexibility in building custom parser
interfaces while still using the basic state machine generated.
Constructing a parser that gives helpful error messages can be tricky,
especially after a grammar has been modified and the parser is re-generated,
which changes the state transition table. Interactive training with
the parse_train function now produces, in addition to an augmented parser,
a training-script that records each error encountered along with the line,
column numbers and the unexpected token. It's the user's responsibility to
keep track of the sample input used during interactive training and
the script that was created from it. A parser can be retrained from the
script, given the identical input (and tokenizer) using the
[RuntimeParser::train_from_script][3] function.
Future releases of rustlr will further enhance the training feature.
We also hope to identify a robust, generic lexical tokenizer tool
for Rust so that the parser generator can also automatically
generate a lexical analyzer from additional specifications in the grammar.
Another potential feature to be explored is the ability to generate an
abstract syntax type structure from the grammar itself.
#### Version 0.1.4:
This version's main enhancements are pattern labels. In a grammar production,
the value attached to nonterminal and terminal symbols can be extracted by
specifying a pattern, which will cause an if-let statement to be automatically
generated. For abstract syntax with many layers of enums and structs, but
which shares a single "absyntype" for the grammar. For example, if *Exp* and
*Expl* are variants of a common enum, one can now write rules such as
```
Exprlist --> { Expl(Vec::new()) }
Exprlist --> Exprlist:@Expl(mut ev)@ , Expr:@Exp(e)@ {ev.push(e); Expl(ev)}
```
This capability was used to construct a parser for a scaled-down version of
Java and is included in the examples directory of the repository.
Abilities for using LBox were also extended, which allows *`LBox<dyn Any>`* to
be used as the abstract syntax type, with functions and macros for
up/downcasting.
[1]:https://docs.rs/rustlr/latest/rustlr/runtime_parser/struct.RuntimeParser.html#method.parse_train
[2]:https://docs.rs/rustlr/latest/rustlr/runtime_parser/struct.RuntimeParser.html#method.parse
[3]:https://docs.rs/rustlr/latest/rustlr/runtime_parser/struct.RuntimeParser.html#method.train_from_script