Documentation and report.

README.md

@@ -1,2 +1,55 @@
 # lisp-interpreter
 
+This project is a simple Lisp interpreter written in Python, to the spec of New Mexico Tech's 2026 CSE3024 Project 2 assignment.
+
+## Running the Interpreter
+
+You may run the interpreter with the commands `make`, `make run`, or `python repl.py`. To supply an alternative location for the output file, specify it as a command-line argument. By default, the output file is `output.txt`.
+
+## Completeness
+
+The interpreter's support and completeness is outlined below:
+
+| Lisp Construct         | Status |
+|------------------------|--------|
+| Variable reference     | Done   |
+| Constant literal       | Done   |
+| Quotation              | Done   |
+| Conditional            | Done   |
+| Variable definition    | Done   |
+| Function call          | Done   |
+| Assignment             | Done   |
+| Function definition    | Done   |
+| Arithmetic operators   | Done   |
+| Integer type           | Done   |
+| `car` and `cdr`        | Done   |
+| `cons` support         | Done   |
+| sqrt, pow              | Done   |
+| Comparison expressions | Done   |
+| Logical operations     | Done   |
+| `mapcar` function      | Done   |
+| Lambda support         | Not    |
+
+## Implementation Notes
+
+### Data Types
+
+Data types were straightforward to implement, as I opted for a Python-native approach to data representation, with the actual back-end values being simple heterogeneous lists of lists, `int`s, `str`s, `float`s, and `bool`s.
+
+### Mathematical Operators
+
+All the built-in functions follow a similar principle, sifting through a match case of built-ins before checking for user defined functions. The mathematical operations, as well as the logical expressions, all simply check for correct parameters, then return the result of the native Python operation on the arguments.
+
+### Environment Management
+
+Variables and function definitions make use of the `Lisp` class's `env` property, a simple hashmap relating a symbol name to a value, for variables, or for a simple `Function` struct, for functions. When the function is executed, the `Lisp` instance recursively creates a new interpreter instance so as to offer the passed parameters to the expression within the function.
+
+### List Manipulation
+
+List manipulation was simple in this implementation, largely due to Python's loose typing and highly dynamic lists. `car`, `cdr`, and `cons` only needed simple list appending and concatenation.
+
+## References
+
+> [Make-a-Lisp](https://github.com/kanaka/mal/blob/master/process/guide.md) by `kanaka` on GitHub
+
+This resource proved to be less applicable than I had originally hoped, and in practice I only benefitted from the birds-eye understanding given by the REPL data-flow diagrams, and a starting point for the tokenization regex. The rest of the project was much more thorough than was useful to me, and the rest was through trial-and-error.