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6ce0e888b9
17 changed files with 0 additions and 738 deletions
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@ -1,8 +1,3 @@
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py_project(
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name = "hydra",
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lib_deps = [
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py_requirement("attrs"),
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py_requirement("click"),
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],
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main = "src/python/hydra/__main__.py",
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)
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|
|
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@ -1,21 +1,12 @@
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#!/usr/bin/env python3.10
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from pathlib import Path
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import click
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from hydra.interpreter import run_script
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@click.group()
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def cli():
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pass
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@cli.command()
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@click.argument("script", type=Path)
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def run(script):
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run_script(script)
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if __name__ == "__main__":
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cli.main(prog_name="hydra")
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|
|
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@ -1,54 +0,0 @@
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#!/usr/bin/env python3
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"""The Hydra interpreter.
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Hydra is an odd implementation of Python interpretation. Control is modeled in
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terms of continuations, each continuation having a classical stack and a control
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pointer. However rather than converting Python ASTs to a bytecode format
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suitable for sequential indexing as in the CPython VM, Hydra simply maintains a
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"cursor" into the AST. This allows for simultaneous implementation of direct AST
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interpretation (for simplicity) and continuations.
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"""
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import ast
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from pathlib import Path
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from typing import Dict, List, Optional
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from hydra.models import Cursor, Continuation, Module, Runtime, Namespace
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from hydra.syntax import validate_mod
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def run_script(
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script: Path,
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pypath: Optional[List[Path]] = None,
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pyenv: Optional[Dict[str, str]] = None,
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):
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"""Given a script, start a thread and run it to 'completion'.
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Mostly a stub designed to get me rolling.
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"""
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pypath = pypath or []
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pyenv = pyenv or {}
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with open(script, "r", encoding="utf-8") as fp:
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mod_ast: ast.Module = ast.parse(fp.read())
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# Locate unsupported syntax, if any
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validate_mod(mod_ast)
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# Create the module object
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mod = Module("__main__", mod_ast)
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# Create the main continuation
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main = Continuation(entrypoint=Cursor(module="__main__", path=[0]), stack=[])
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# Create the runtime
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rt = Runtime(modules=Namespace({"__main__": mod}))
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# Register the main continuation
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rt.conts[rt.main] = main
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for stmt in mod_ast.body:
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print(stmt)
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@ -1,52 +0,0 @@
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#!/usr/bin/env python3
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import ast
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from pathlib import Path
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from typing import Any, Dict, List, Optional
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from attrs import define, field
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from uuid import UUID, uuid4
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@define
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class Cursor:
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module: str
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path: List[int]
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@define
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class Continuation:
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entrypoint: Cursor
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stack: List[Cursor]
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parent: Optional["Continuation"] = None
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@define
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class Namespace:
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"""Namespaces name ... values.
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Modules, classes and other forms of scopes are all Namespaces.
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"""
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d: Dict[str, Any] = field(default=dict)
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@define
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class Module:
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"""A 'module" maps names to code objects such as constants, classes and functions (also classes)."""
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name: str
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ast: ast.Module
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d: Dict[str, Any] = field(default=dict)
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@define
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class Runtime:
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"""A Runtime represents a loaded and potentially runnable"""
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env: Dict[str, str] = field(default=dict)
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path: List[Path] = field(default=list)
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main: UUID = field(default=uuid4)
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conts: Dict[UUID, Continuation] = field(default=dict)
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modules: Namespace = field(default=Namespace)
|
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@ -1,154 +0,0 @@
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#!/usr/bin/env python3
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"""The syntax checker.
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The Python AST module will gladly parse a variety of meaningless statements such
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as top-level `pass` and `return` statements. These are, technically, illegal and
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cannot be evaluated.
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Furthermore, Hydra doesn't support (currently a lot) of Python's syntax. Match
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and async for instance are right out.
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The syntax module exists to provide "validation" that a given AST tree is
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"legitimate".
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"""
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import ast
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from typing import Union
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# 'stmt' from the AST def. (3.11)
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Statement = Union[
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ast.FunctionDef,
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ast.AsyncFunctionDef,
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ast.ClassDef,
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ast.Return,
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ast.Delete,
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ast.Assign,
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ast.AugAssign,
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ast.AnnAssign,
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ast.For,
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ast.AsyncFor,
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ast.While,
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ast.If,
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ast.With,
|
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ast.AsyncWith,
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ast.Match,
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ast.Raise,
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ast.Try,
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ast.Assert,
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ast.Import,
|
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ast.ImportFrom,
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ast.Global,
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ast.Nonlocal,
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ast.Expr,
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ast.Pass,
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ast.Break,
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ast.Continue,
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]
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# 'expr' from the AST def. (3.11)
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Expression = Union[
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ast.BoolOp,
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ast.NamedExpr,
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ast.BinOp,
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ast.UnaryOp,
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ast.Lambda,
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ast.IfExp,
|
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ast.Dict,
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ast.Set,
|
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ast.ListComp,
|
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ast.SetComp,
|
||||
ast.DictComp,
|
||||
ast.GeneratorExp,
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ast.Await,
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ast.Yield,
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ast.YieldFrom,
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ast.Compare,
|
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ast.Call,
|
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ast.FormattedValue,
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ast.JoinedStr,
|
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ast.Constant,
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ast.Attribute,
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ast.Subscript,
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ast.Starred,
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ast.Name,
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ast.List,
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ast.Tuple,
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ast.Slice,
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]
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||||
|
||||
|
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def collect(ctor):
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"""Coerce a generator style function into returning a collection."""
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def decorator(f):
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def helper(*args, **kwargs):
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return ctor(f(*args, **kwargs))
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return helper
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return decorator
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|
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@collect(list)
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def validate_stmt(stmt: Statement, top=False):
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if isinstance(stmt, (ast.AsyncFunctionDef, ast.AsyncFor, ast.AsyncWith, ast.Match)):
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# Stuff we don't support anywhere
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yield stmt
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elif top and isinstance(
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stmt,
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(
|
||||
ast.AsyncFor,
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||||
ast.AsyncWith,
|
||||
ast.Break,
|
||||
ast.Continue,
|
||||
ast.Nonlocal,
|
||||
ast.Pass,
|
||||
ast.Return,
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||||
),
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||||
):
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# Statements that are specifically meaningless at the top level
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yield stmt
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|
||||
elif isinstance(stmt, (ast.FunctionDef, ast.ClassDef)):
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# Recur into function/class definitions
|
||||
for it in stmt.body:
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yield from validate_stmt(it)
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|
||||
elif isinstance(stmt, ast.If):
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for it in stmt.body:
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yield from validate_stmt(it)
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|
||||
for it in stmt.orelse or []:
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yield from validate_stmt(it)
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|
||||
elif isinstance(stmt, ast.Try):
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for it in stmt.body:
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yield from validate_stmt(it)
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|
||||
for handler in stmt.handlers or []:
|
||||
for it in handler.body:
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yield from validate_stmt(it)
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||||
|
||||
for it in stmt.orelse or []:
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yield from validate_stmt(it)
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|
||||
for it in stmt.finalbody or []:
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yield from validate_stmt(it)
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|
||||
elif isinstance(stmt, (ast.With, ast.While, ast.For)):
|
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for it in stmt.body:
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yield from validate_stmt(it)
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|
||||
elif isinstance(stmt, ast.Expression):
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yield from validate_expr(stmt)
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||||
|
||||
|
||||
def validate_mod(mod: ast.Module):
|
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problems = []
|
||||
for stmt in mod.body:
|
||||
if ps := validate_stmt(stmt, top=True):
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problems.extend(ps)
|
|
@ -1,6 +0,0 @@
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|||
py_project(
|
||||
name = "milkshake",
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lib_deps = [
|
||||
py_requirement("lark"),
|
||||
],
|
||||
)
|
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@ -1,45 +0,0 @@
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"""A quick and dirty Lisp reader"""
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|
||||
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from importlib.resources import files
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|
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from lark import Lark, Tree, Token, Transformer, v_args
|
||||
|
||||
|
||||
with files(__package__).joinpath("grammar.lark").open("r", encoding="utf-8") as fp:
|
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GRAMMAR = fp.read()
|
||||
|
||||
|
||||
@v_args(tree=True)
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||||
class T(Transformer):
|
||||
"""A prepackaged transformer that cleans up the quoting details."""
|
||||
|
||||
def un_qq(self, obj):
|
||||
return Tree(
|
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Token(obj.data.type, obj.data.value.replace("qq_", "", 1)), obj.children
|
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)
|
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|
||||
qq_list = un_qq
|
||||
qq_tuple = un_qq
|
||||
qq_vecotor = un_qq
|
||||
qq_map = un_qq
|
||||
qq_set = un_qq
|
||||
qq_atom = un_qq
|
||||
qq_symbol = un_qq
|
||||
|
||||
def qq_quote(self, obj):
|
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return self.quote(self.un_qq(obj))
|
||||
|
||||
def quote(self, obj):
|
||||
return Tree(obj.data, obj.children[1:])
|
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|
||||
quasiquote = quote
|
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unquote = quote
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||||
unquote_splicing = quote
|
||||
|
||||
|
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PARSER = Lark(GRAMMAR, start=["module", "expr"])
|
||||
|
||||
|
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def slurp(text: str, start="module") -> Tree:
|
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return T().transform(PARSER.parse(text, start=start))
|
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@ -1,77 +0,0 @@
|
|||
start: module
|
||||
module: expr+
|
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|
||||
?expr: quote
|
||||
| quasiquote
|
||||
| list
|
||||
| tuple
|
||||
| vector
|
||||
| set
|
||||
| map
|
||||
| atom
|
||||
|
||||
quote: QUOTE expr
|
||||
|
||||
quasiquote: QUASIQUOTE qq_expr
|
||||
unquote: UNQUOTE qq_expr
|
||||
unquote_splicing: UNQUOTE_SPLICING qq_expr
|
||||
qq_quote: QUOTE qq_expr
|
||||
|
||||
?qq_expr: qq_quote
|
||||
| unquote
|
||||
| unquote_splicing
|
||||
| qq_list
|
||||
| qq_tuple
|
||||
| qq_vector
|
||||
| qq_set
|
||||
| qq_map
|
||||
| qq_atom
|
||||
|
||||
list: "(" expr* ")"
|
||||
qq_list: "(" qq_expr* ")"
|
||||
|
||||
tuple: "[" expr "]"
|
||||
qq_tuple: "[" qq_expr "]"
|
||||
|
||||
vector: "#[" expr "]"
|
||||
qq_vector: "#[" qq_expr "]"
|
||||
|
||||
map: "{" (expr expr)* "}"
|
||||
qq_map: "{" (qq_expr qq_expr)* "}"
|
||||
|
||||
set: "#{" expr* "}"
|
||||
qq_set: "#{" qq_expr* "}"
|
||||
|
||||
?atom: string
|
||||
| pattern
|
||||
| number
|
||||
| symbol
|
||||
|
||||
?qq_atom: string
|
||||
| pattern
|
||||
| number
|
||||
| qq_symbol
|
||||
|
||||
string: /"([^"]|\\")+"/
|
||||
|
||||
pattern: /\/([^\/]|\\\/)+\//
|
||||
|
||||
number: /[+-]?(\d+r)?(\d[\d,_\.]*)([\.,][\d,_\.]*)?(e[+-]?\d+)?/
|
||||
|
||||
// Note that we're demoting Symbol from the default parse priority of 0 to -1
|
||||
// This because _anything more specific_ should be chosen over symbol
|
||||
symbol.-1: /[^\d\s'"`()\[\]:]+/
|
||||
|
||||
// Note that qq symbols explicitly forbid leading ~, unlike normal symbols
|
||||
qq_symbol.-1: /[^\d\s'"`()\[\]:~]+/
|
||||
|
||||
QUOTE: /'/
|
||||
QUASIQUOTE: /`/
|
||||
UNQUOTE: /~/
|
||||
UNQUOTE_SPLICING: /~@/
|
||||
|
||||
COMMENT: /;.*?\n/
|
||||
WHITESPACE: /\s+/
|
||||
|
||||
%ignore COMMENT
|
||||
%ignore WHITESPACE
|
|
@ -1,101 +0,0 @@
|
|||
#!/usr/bin/env python3
|
||||
|
||||
from milkshake import slurp
|
||||
|
||||
from lark import Tree, Token
|
||||
import pytest
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"input, val",
|
||||
[
|
||||
("()", Tree("list", [])),
|
||||
("nil", nil := Tree("symbol", ["nil"])),
|
||||
("(nil nil nil)", Tree("list", [nil, nil, nil])),
|
||||
(
|
||||
"(/ + - * % ^ \\ & # @ ! = |)",
|
||||
Tree(
|
||||
"list",
|
||||
[
|
||||
Tree("symbol", ["/"]),
|
||||
Tree("symbol", ["+"]),
|
||||
Tree("symbol", ["-"]),
|
||||
Tree("symbol", ["*"]),
|
||||
Tree("symbol", ["%"]),
|
||||
Tree("symbol", ["^"]),
|
||||
Tree("symbol", ["\\"]),
|
||||
Tree("symbol", ["&"]),
|
||||
Tree("symbol", ["#"]),
|
||||
Tree("symbol", ["@"]),
|
||||
Tree("symbol", ["!"]),
|
||||
Tree("symbol", ["="]),
|
||||
Tree("symbol", ["|"]),
|
||||
],
|
||||
),
|
||||
),
|
||||
("1.0", Tree("number", ["1.0"])),
|
||||
("+1.0", Tree("number", ["+1.0"])),
|
||||
("-1.0", Tree("number", ["-1.0"])),
|
||||
("-10,000,000.0", Tree("number", ["-10,000,000.0"])),
|
||||
("-10.000.000,0", Tree("number", ["-10.000.000,0"])),
|
||||
("-10_000_000,0", Tree("number", ["-10_000_000,0"])),
|
||||
("-10_000_000.0", Tree("number", ["-10_000_000.0"])),
|
||||
("1e50", Tree("number", ["1e50"])),
|
||||
("-1e-50", Tree("number", ["-1e-50"])),
|
||||
("-1e+50", Tree("number", ["-1e+50"])),
|
||||
(
|
||||
"(+inf -inf inf nan +nan -nan)",
|
||||
Tree(
|
||||
"list",
|
||||
[
|
||||
Tree("symbol", ["+inf"]),
|
||||
Tree("symbol", ["-inf"]),
|
||||
Tree("symbol", ["inf"]),
|
||||
Tree("symbol", ["nan"]),
|
||||
Tree("symbol", ["+nan"]),
|
||||
Tree("symbol", ["-nan"]),
|
||||
],
|
||||
),
|
||||
),
|
||||
("'()", Tree("quote", [Tree("list", [])])),
|
||||
(
|
||||
"`(nil ~'() ~@'())",
|
||||
Tree(
|
||||
"quasiquote",
|
||||
[
|
||||
Tree(
|
||||
"list",
|
||||
[
|
||||
Tree("symbol", ["nil"]),
|
||||
Tree(
|
||||
"unquote",
|
||||
[
|
||||
Tree(
|
||||
"quote",
|
||||
[
|
||||
Tree("list", []),
|
||||
],
|
||||
),
|
||||
],
|
||||
),
|
||||
Tree(
|
||||
"unquote_splicing",
|
||||
[
|
||||
Tree(
|
||||
"quote",
|
||||
[
|
||||
Tree("list", []),
|
||||
],
|
||||
),
|
||||
],
|
||||
),
|
||||
],
|
||||
),
|
||||
],
|
||||
),
|
||||
),
|
||||
(r"/foo\S+/", Tree("pattern", [r"/foo\S+/"])),
|
||||
],
|
||||
)
|
||||
def test_examples(input, val):
|
||||
assert slurp(input, start="expr") == val
|
|
@ -1,7 +0,0 @@
|
|||
py_project(
|
||||
name = "typhon",
|
||||
lib_deps = [
|
||||
"//components/milkshake",
|
||||
py_requirement("attrs"),
|
||||
]
|
||||
)
|
|
@ -1,51 +0,0 @@
|
|||
# Notes
|
||||
|
||||
Natural gradient; interpreter -> semi-VM -> tracing JIT/translator -> optimizing JIT/translator
|
||||
-> abstract interpreter -> static compiler/translator
|
||||
|
||||
A semi-VM which demand translates AST nodes into a stack of demanded evaluation
|
||||
terms and then walks the evaluation stack as if it were a bytecode or
|
||||
semi-bytecode evaluator. The advantage of this strategy is that the demanded
|
||||
operation / control stack and paired data stack eliminate the need to leverage
|
||||
the system control stack. This gets you serializable stacks for Flowmetal. But
|
||||
you write two half interpreters.
|
||||
|
||||
Now the natural question is why write a hosted VM to get serializable stacks
|
||||
when Python has a perfectly good bytecode VM already? Sticking one VM atop
|
||||
another is ... a bit silly especially since the goal of doing so is to be able
|
||||
to "drop down" from the one to the other to ensure compatibility.
|
||||
|
||||
Is there a lens through which the serialization requirements of Flowmental can
|
||||
be satisfied from "normal" Python using the "normal" Python bytecode
|
||||
interpreter?
|
||||
|
||||
Consider - function call points and function return points are in a sense
|
||||
language safe points. Rather than trying to capture the entire evaluation
|
||||
"image" at some point, one could instead track the call/return evaluation log
|
||||
for replay. Such a scheme would allow Flowmetal to be implemented using static
|
||||
rewrites of Python ASTs. Any function call becomes a checkpoint as does
|
||||
receiving the return result.
|
||||
|
||||
Any `__call__` invocation needs to be evaluated as something like
|
||||
|
||||
x = runtime.call(const_gen_call_id, instance, args)
|
||||
|
||||
This tactic specifically leans on `yield` being a statement _with a return
|
||||
value_. This pattern would let the "runtime" as the root evaluation routine
|
||||
'continue' any given call site with the return result. `runtime.call` would be
|
||||
some incantation for producing a sentinel value to the runtime noting that a
|
||||
function call had been requested - and that its result should either be computed
|
||||
or replayed from a log.
|
||||
|
||||
There are a lot of opportunities for optimization here. Not every function call
|
||||
needs its value persisted into the log. Most function calls depend only on the
|
||||
direct live state of the program. Exceptions are things like interacting with
|
||||
file descriptors/sockets and clocks. But strictly data-dependent operations like
|
||||
dictionary mutations are entirely safe under replay. They're only path
|
||||
dependent. So really we only need to "de-optimize" or spy on "key" function
|
||||
calls which occur against _unsafe_ operations. Or which occur against captured
|
||||
function/method instances which cannot be statically identified.
|
||||
|
||||
There may be games to be played with yield/coroutines here, but that could play
|
||||
heck with normal generators. Intercepting "normal" calls with "normal" calls is
|
||||
probably the easy strategy.
|
|
@ -1,147 +0,0 @@
|
|||
#!/usr/bin/env python3
|
||||
|
||||
"""
|
||||
A prototype 'flat' interpreter for a continuation based Lisp.
|
||||
|
||||
Not intended to be anything real, just intended to serve as a prototype for how
|
||||
to implement a flat, stackless, serializable interpreter.
|
||||
"""
|
||||
|
||||
import operator
|
||||
import typing as t
|
||||
|
||||
import attrs
|
||||
|
||||
|
||||
@attrs.define()
|
||||
class Vm:
|
||||
"""
|
||||
:field log: All evaluated expressions, in order
|
||||
:field mod_ns: A map from symbols to currently bound expressions
|
||||
:field continuations: A list of coroutines/continuations of control
|
||||
"""
|
||||
|
||||
log: t.List[list]
|
||||
mod_ns: t.Dict[str, t.Any] = attrs.field(factory=dict)
|
||||
continuations: t.List["Cont"] = attrs.field(factory=list)
|
||||
|
||||
|
||||
@attrs.define()
|
||||
class Cont:
|
||||
"""
|
||||
Continuations represent sequences of evaluation.
|
||||
|
||||
:field frames: A list of call frames
|
||||
"""
|
||||
|
||||
frames: t.List["Frame"] = attrs.field(factory=list)
|
||||
|
||||
|
||||
@attrs.define()
|
||||
class Frame:
|
||||
"""
|
||||
Frames represent function call boundaries.
|
||||
|
||||
:field pc: Program points within the AST being interpreted
|
||||
:field frame_ns: Frame-local bindings
|
||||
"""
|
||||
|
||||
pc: list = attrs.field(factory=lambda: [0])
|
||||
frame_ns: dict = attrs.field(factory=dict)
|
||||
op_stack: list = attrs.field(factory=list)
|
||||
data_stack: list = attrs.field(factory=list)
|
||||
|
||||
|
||||
def chain(its):
|
||||
for it in its:
|
||||
yield from it
|
||||
|
||||
|
||||
def get_in(idxable, idxs):
|
||||
for idx in idxs:
|
||||
idxable = idxable[idx]
|
||||
return idxable
|
||||
|
||||
|
||||
class Operator:
|
||||
"""Stack operators."""
|
||||
|
||||
|
||||
class Task:
|
||||
@attrs.define()
|
||||
class Complete:
|
||||
"""Signals program termination."""
|
||||
|
||||
pass
|
||||
|
||||
@attrs.define()
|
||||
class Eval:
|
||||
"""Evaluate the current term."""
|
||||
|
||||
pass
|
||||
|
||||
@attrs.define()
|
||||
class Apply:
|
||||
"""Apply an operator to the stack."""
|
||||
|
||||
operator: "Operator" = attrs.field()
|
||||
|
||||
@attrs.define()
|
||||
class Next:
|
||||
"""Advance the program counter to the 'next' statement."""
|
||||
|
||||
pc: list
|
||||
|
||||
|
||||
def step(vm: Vm, cont: Cont, frame: Frame):
|
||||
"""Step moves the VM forwards one "cycle".
|
||||
|
||||
This VM is built as a semi-VM.
|
||||
|
||||
Interpretation occurs at two levels - the first over a direct syntax tree.
|
||||
This allows the interpreter to forego a formal VM or any compilation step.
|
||||
|
||||
This model however poses a challenge for AST nodes with data dependencies.
|
||||
Sub-expressions are the most obivous example. For these, we need semi-VM
|
||||
behavior where the AST node is translated into a sequence of concrete
|
||||
sub-step demanded operations which can actually be executed. Note that this
|
||||
provides a neat natural definition of a tracing JIT or optimizing compiler.
|
||||
|
||||
This makes the execution mode well bimodal.
|
||||
|
||||
- On the one hand if we have demanded operations on the stack (`op_stack`)
|
||||
then we want to execute the "top" demanded operation.
|
||||
|
||||
- On the other, if we have no demanded operations we want to
|
||||
|
||||
"""
|
||||
|
||||
match expr:
|
||||
case ["native", native_fn, arg_exprs, vararg_expr]:
|
||||
pass
|
||||
|
||||
case ["invoke", fn_expr, arg_exprs, vararg_expr]:
|
||||
pass
|
||||
|
||||
case ["var", name]:
|
||||
pass
|
||||
|
||||
case int() | float() | str() | bool():
|
||||
pass
|
||||
|
||||
|
||||
def run(program, state=None):
|
||||
vm = state or Vm([], {}, [])
|
||||
replc = Cont([Frame([0], {})])
|
||||
vm.continuations.append(replc)
|
||||
|
||||
for form in program:
|
||||
# Enter the form into the log
|
||||
vm.log.append(form)
|
||||
# Set the REPL continuation's point to the new form
|
||||
replc.frames = [Frame([len(vm.log) - 1])]
|
||||
# Evaluate the continuation to completion (or something)
|
||||
while True:
|
||||
match (state := step(vm, replc, replc.frames[-1])):
|
||||
case _:
|
||||
pass
|
|
@ -1 +0,0 @@
|
|||
#!/usr/bin/env python3
|
|
@ -1,20 +0,0 @@
|
|||
; -*- mode: scheme -*-
|
||||
|
||||
(define +
|
||||
(lambda (x y)
|
||||
(py "lambda x, y: x + y" [x y] [])))
|
||||
|
||||
(define format
|
||||
(lambda (&args)
|
||||
(py "lambda fmt, *args: fmt % args" [fmt] &args)))
|
||||
|
||||
(define print
|
||||
(lambda (&args)
|
||||
(py "print" [] &args)))
|
||||
|
||||
(define add2
|
||||
(lambda (x)
|
||||
(+ (2 x))))
|
||||
|
||||
(print
|
||||
(format "%d" (add2 2)))
|
|
@ -43,7 +43,6 @@ def py_pytest(name, srcs, deps, main=None, python_version=None, args=None, **kwa
|
|||
py_requirement("pytest-pudb"),
|
||||
py_requirement("pytest-cov"),
|
||||
py_requirement("pytest-timeout"),
|
||||
py_requirement("pytest-clarity"),
|
||||
] + deps))
|
||||
|
||||
srcs = [f] + srcs
|
||||
|
|
|
@ -2,10 +2,8 @@ attrs
|
|||
black
|
||||
cattrs
|
||||
hypothesis
|
||||
lark
|
||||
pudb
|
||||
pytest
|
||||
pytest-clarity
|
||||
pytest-cov
|
||||
pytest-pudb
|
||||
pytest-timeout
|
||||
|
|
|
@ -9,25 +9,19 @@ hypothesis==6.68.2
|
|||
iniconfig==2.0.0
|
||||
isort==5.12.0
|
||||
jedi==0.18.2
|
||||
lark==1.1.5
|
||||
markdown-it-py==2.2.0
|
||||
mdurl==0.1.2
|
||||
mypy-extensions==1.0.0
|
||||
packaging==23.0
|
||||
parso==0.8.3
|
||||
pathspec==0.11.0
|
||||
platformdirs==3.1.0
|
||||
pluggy==1.0.0
|
||||
pprintpp==0.4.0
|
||||
pudb==2022.1.3
|
||||
pyflakes==3.0.1
|
||||
Pygments==2.14.0
|
||||
pytest==7.2.2
|
||||
pytest-clarity==1.0.1
|
||||
pytest-cov==4.0.0
|
||||
pytest-pudb==0.7.0
|
||||
pytest-timeout==2.1.0
|
||||
rich==13.3.5
|
||||
sortedcontainers==2.4.0
|
||||
tomli==2.0.1
|
||||
urwid==2.1.2
|
||||
|
|
Loading…
Reference in a new issue