mirror of
https://github.com/hwchase17/langchain
synced 2024-11-10 01:10:59 +00:00
a0c2281540
```python
"""python scripts/update_mypy_ruff.py"""
import glob
import tomllib
from pathlib import Path
import toml
import subprocess
import re
ROOT_DIR = Path(__file__).parents[1]
def main():
for path in glob.glob(str(ROOT_DIR / "libs/**/pyproject.toml"), recursive=True):
print(path)
with open(path, "rb") as f:
pyproject = tomllib.load(f)
try:
pyproject["tool"]["poetry"]["group"]["typing"]["dependencies"]["mypy"] = (
"^1.10"
)
pyproject["tool"]["poetry"]["group"]["lint"]["dependencies"]["ruff"] = (
"^0.5"
)
except KeyError:
continue
with open(path, "w") as f:
toml.dump(pyproject, f)
cwd = "/".join(path.split("/")[:-1])
completed = subprocess.run(
"poetry lock --no-update; poetry install --with typing; poetry run mypy . --no-color",
cwd=cwd,
shell=True,
capture_output=True,
text=True,
)
logs = completed.stdout.split("\n")
to_ignore = {}
for l in logs:
if re.match("^(.*)\:(\d+)\: error:.*\[(.*)\]", l):
path, line_no, error_type = re.match(
"^(.*)\:(\d+)\: error:.*\[(.*)\]", l
).groups()
if (path, line_no) in to_ignore:
to_ignore[(path, line_no)].append(error_type)
else:
to_ignore[(path, line_no)] = [error_type]
print(len(to_ignore))
for (error_path, line_no), error_types in to_ignore.items():
all_errors = ", ".join(error_types)
full_path = f"{cwd}/{error_path}"
try:
with open(full_path, "r") as f:
file_lines = f.readlines()
except FileNotFoundError:
continue
file_lines[int(line_no) - 1] = (
file_lines[int(line_no) - 1][:-1] + f" # type: ignore[{all_errors}]\n"
)
with open(full_path, "w") as f:
f.write("".join(file_lines))
subprocess.run(
"poetry run ruff format .; poetry run ruff --select I --fix .",
cwd=cwd,
shell=True,
capture_output=True,
text=True,
)
if __name__ == "__main__":
main()
```
66 lines
1.9 KiB
Python
66 lines
1.9 KiB
Python
"""Logic for converting internal query language to a valid DashVector query."""
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from typing import Tuple, Union
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from langchain_core.structured_query import (
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Comparator,
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Comparison,
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Operation,
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Operator,
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StructuredQuery,
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Visitor,
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)
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class DashvectorTranslator(Visitor):
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"""Logic for converting internal query language elements to valid filters."""
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allowed_operators = [Operator.AND, Operator.OR]
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allowed_comparators = [
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Comparator.EQ,
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Comparator.GT,
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Comparator.GTE,
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Comparator.LT,
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Comparator.LTE,
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Comparator.LIKE,
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]
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map_dict = {
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Operator.AND: " AND ",
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Operator.OR: " OR ",
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Comparator.EQ: " = ",
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Comparator.GT: " > ",
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Comparator.GTE: " >= ",
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Comparator.LT: " < ",
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Comparator.LTE: " <= ",
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Comparator.LIKE: " LIKE ",
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}
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def _format_func(self, func: Union[Operator, Comparator]) -> str:
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self._validate_func(func)
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return self.map_dict[func]
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def visit_operation(self, operation: Operation) -> str:
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args = [arg.accept(self) for arg in operation.arguments]
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return self._format_func(operation.operator).join(args)
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def visit_comparison(self, comparison: Comparison) -> str:
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value = comparison.value
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if isinstance(value, str):
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if comparison.comparator == Comparator.LIKE:
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value = f"'%{value}%'"
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else:
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value = f"'{value}'"
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return (
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f"{comparison.attribute}{self._format_func(comparison.comparator)}{value}"
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)
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def visit_structured_query(
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self, structured_query: StructuredQuery
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) -> Tuple[str, dict]:
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if structured_query.filter is None:
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kwargs = {}
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else:
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kwargs = {"filter": structured_query.filter.accept(self)}
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return structured_query.query, kwargs
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