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Snail programming language interpreter

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Snail

Snail is a programming language that compiles to Python, combining Python's familiarity and extensive libraries with Perl/awk-inspired syntax for quick scripts and one-liners. Its what you get when you shove a snake in a shell.

AI Slop!

Snail is me learning how to devlop code using LLMs. I think its neat, and maybe useful. I don't think this is high quality. I am going to try and LLM my way into something good, but its certainly not there yet.

Installing Snail

pip install snail-lang
-or-
uv tool install snail-lang

That installs the snail CLI for your user; try it with snail "print('hello')" once the install completes.

✨ What Makes Snail Unique

Curly Braces, Not Indentation

Write Python logic without worrying about whitespace:

def process(items) {
    for item in items {
        if item > 0 { print(item) }
        else { continue }
    }
}

Note, since it is jarring to write python with semicolons everywhere, semicolons are optional. You can separate statements with newlines.

Awk Mode

Process files line-by-line with familiar awk semantics:

/hello/ { print("matched:", $0) }
{ print($1, "->", $2) }

Built-in variables:

Variable Description
$0 Current line (with newline stripped)
$1, $2, ... Individual fields (whitespace-split)
$f All fields as a list
$n Global line number (across all files)
$fn Per-file line number
$src Current file path
$m Last regex match object

Setup and teardown code can be supplied via CLI flags (-b/--begin, -e/--end). Begin code runs before the line-processing loop, end code runs after. Awk $ variables are not available in begin/end code (they are outside the awk { } block).

echo -e "5\n4\n3\n2\n1" | snail --awk --begin 'total = 0' --end 'print("Sum:", total)' '/^[0-9]+/ { total = total + int($1) }'

Xargs Mode

Process files one at a time instead of line-by-line:

print("File:", $src)
print("Size:", len($text), "bytes")

Built-in variables:

Variable Description
$src Current file path
$fd Open file handle for the current file
$text Lazy text view of the current file contents

Setup and teardown code can be supplied via CLI flags (-b/--begin, -e/--end). Begin code runs before the file-processing loop, end code runs after. Xargs $ variables are not available in begin/end code (they are outside the xargs { } block).

find . -name "*.txt" | snail --xargs --begin "print('start')" --end "print('done')" "print($src)"

Built-in Variables (All Modes)

Variable Description
$e Exception object in expr:fallback?
$env Environment map (wrapper around os.environ)

Begin/End Flags

The -b/--begin and -e/--end CLI flags prepend and append code around the main program in all modes. In awk mode the code runs outside the awk { } wrapper; in xargs mode it runs outside the xargs { } wrapper.

print("running")

In regular mode, my main use case for this feature is passing unexported variables

my_bashvar=123
snail -b x=$my_bashvar 'int(x) + 1'

This is roughly the same as using $env to access an exported variable.

my_bashvar=123 snail 'int($env.my_bashvar) + 1'

Compact Error Handling

The ? operator makes error handling terse yet expressive:

# Swallow exception, return None
err = risky()?

# Swallow exception, return exception object
err = risky():$e?

# Provide a fallback value (exception available as $e)
value = js("malformed json"):%{"error": "invalid json"}?
details = fetch_url("foo.com"):"default html"?
exception_info = fetch_url("example.com"):$e.http_response_code?

# Access attributes directly
name = risky("")?.__class__.__name__
args = risky("becomes a list"):[1,2,3]?[0]

Destructuring + if let / while let

Unpack tuples and lists directly, including Python-style rest bindings:

x, *xs = [1, 2, 3]

if let [head, *tail] = [1, 2, 3]; head > 0 {
    print(head, tail)
}

if let/while let only enter the block when the destructuring succeeds. A guard after ; lets you add a boolean check that runs after the bindings are created.

Note that this syntax is more powerful than the walrus operator as that does not allow for destructuring.

Pipeline Operator

The | operator enables data pipelining as syntactic sugar for nested function calls. x | y | z becomes z(y(x)). This lets you stay in a shell mindset.

# Pipe data to subprocess stdin
result = "hello\nworld" | $(grep hello)

# Chain multiple transformations
output = "foo\nbar" | $(grep foo) | $(wc -l)

# Custom pipeline handlers
class Doubler {
    def __call__(self, x) { return x * 2 }
}
doubled = 21 | Doubler()  # yields 42

Arbitrary callables make up pipelines, even if they have multiple parameters. Snail supports this via placeholders.

greeting = "World" | greet("Hello ", _)  # greet("Hello ", "World")
excited = "World" | greet(_, "!")        # greet("World", "!")
formal = "World" | greet("Hello ", suffix=_)  # greet("Hello ", "World")

When a pipeline targets a call expression, the left-hand value is passed to the resulting callable. If the call includes a single _ placeholder, Snail substitutes the piped value at that position (including keyword arguments). Only one placeholder is allowed in a piped call. Outside of pipeline calls, _ remains a normal identifier.

Built-in Subprocess

Shell commands are first-class citizens with capturing and non-capturing forms.

# Capture command output with interpolation
greeting = $(echo hello {name})

# Pipe data through commands
result = "foo\nbar\nbaz" | $(grep bar) | $(cat -n)

# Check command status
status = @(make build)?  # returns SnailExitStatus on failure instead of raising
if status { print("build passed") } else { print(status.rc) }

Regex Literals

Snail supports first class patterns. Think of them as an infinte set.

if bad_email in /^[\w.]+@[\w.]+$/ {
    print("Valid email")
}

# Compiled regex for reuse
pattern = /\d{3}-\d{4}/
match = pattern.search(phone)
match2 = "555-1212" in pattern

Snail regexes don't return a match object, rather they return a tuple containing all of the match groups, including group 0. Both search and in return the same tuple (or () when there is no match).

JSON Queries with JMESPath

Parse and query JSON data with the js() function and structured pipeline accessor:

# Parse JSON and query with $[jmespath]

# JSON query with JMESPath
data = js($(curl -s https://api.github.com/repos/sudonym1/snail))
counts = data | $[stargazers_count]

# Inline parsing and querying
result = js('{{"foo": 12}}') | $[foo]

# JSONL parsing returns a list
names = js('{{"name": "Ada"}}\n{{"name": "Lin"}}') | $[[*].name]

Snail rewrites JMESPath queries in $[query] so that double-quoted segments are treated as string literals. This lets you write $[items[?ifname=="eth0"].ifname] inside a single-quoted shell command. If you need JMESPath quoted identifiers (for keys like "foo-bar"), escape the quotes in the query (for example, $[\"foo-bar\"]). JSON literal backticks (`...`) are left unchanged.

Full Python Interoperability

Snail compiles to Python AST—import any Python module, use any library, in any environment. Assuming that you are using Python 3.8 or later.

🚀 Quick Start

# One-liner: arithmetic + interpolation
snail 'name="Snail"; print("{name} says: {6 * 7}")'

# JSON query with JMESPath
snail 'js($(curl -s https://api.github.com/repos/sudonym1/snail)) | $[stargazers_count]'

# Compact error handling with fallback
snail 'result = int("oops"):"bad int {$e}"?; print(result)'

# Regex match and capture
snail 'if let [_, user, domain] = "user@example.com" in /^[\w.]+@([\w.]+)$/ { print(domain) }'

# Awk mode: print line numbers for matches
rg -n "TODO" README.md | snail --awk '/TODO/ { print("{$n}: {$0}") }'

# Environment variables
snail 'print($env.PATH)'

📚 Documentation

Documentation is WIP

🔌 Editor Support

Vim/Neovim plugin with Tree-sitter-based highlighting (Neovim), formatting, and run commands:

Plug 'sudonym1/snail'
-- lazy.nvim
{
  'sudonym1/snail',
  lazy = false, -- optional
}

Open any .snail file and the parser will auto-install if needed. Manual fallback: :TSInstall snail.

See extras/vim/README.md for details. Tree-sitter grammar available in extras/tree-sitter-snail/.

Performance

Section is WIP

Startup performance is benchmarked with ./benchmarks/startup.py. On my machine snail adds 5 ms of overhead above the regular python3 interpreter.

🛠️ Building from Source

Prerequisites

Python 3.8+ (required at runtime)

Snail runs in-process via a Pyo3 extension module, so it uses the active Python environment.

Installation per platform:

  • Ubuntu/Debian: sudo apt install python3 python3-dev
  • Fedora/RHEL: sudo dnf install python3 python3-devel
  • macOS: brew install python@3.12 (or use the system Python 3)
  • Windows: Download from python.org

Build, Test, and Install

# Clone the repository
git clone https://github.com/sudonym1/snail.git
cd snail

make test
make install

Arch Linux (PKGBUILD)

An Arch package build file is available at extras/arch/PKGBUILD.

mkdir -p /tmp/snail-pkg
cp extras/arch/PKGBUILD /tmp/snail-pkg/
cd /tmp/snail-pkg

# Update pkgver and sha256sums as needed, then build and install
makepkg -si

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