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()
```
59 lines
1.9 KiB
Python
59 lines
1.9 KiB
Python
"""Loads RST files."""
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from pathlib import Path
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from typing import Any, List, Union
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from langchain_community.document_loaders.unstructured import (
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UnstructuredFileLoader,
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validate_unstructured_version,
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)
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class UnstructuredRSTLoader(UnstructuredFileLoader):
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"""Load `RST` files using `Unstructured`.
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You can run the loader in one of two modes: "single" and "elements".
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If you use "single" mode, the document will be returned as a single
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langchain Document object. If you use "elements" mode, the unstructured
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library will split the document into elements such as Title and NarrativeText.
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You can pass in additional unstructured kwargs after mode to apply
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different unstructured settings.
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Examples
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--------
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from langchain_community.document_loaders import UnstructuredRSTLoader
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loader = UnstructuredRSTLoader(
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"example.rst", mode="elements", strategy="fast",
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)
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docs = loader.load()
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References
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----------
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https://unstructured-io.github.io/unstructured/bricks.html#partition-rst
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"""
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def __init__(
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self,
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file_path: Union[str, Path],
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mode: str = "single",
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**unstructured_kwargs: Any,
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):
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"""
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Initialize with a file path.
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Args:
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file_path: The path to the file to load.
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mode: The mode to use for partitioning. See unstructured for details.
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Defaults to "single".
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**unstructured_kwargs: Additional keyword arguments to pass
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to unstructured.
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"""
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validate_unstructured_version(min_unstructured_version="0.7.5")
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super().__init__(file_path=file_path, mode=mode, **unstructured_kwargs)
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def _get_elements(self) -> List:
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from unstructured.partition.rst import partition_rst
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return partition_rst(filename=self.file_path, **self.unstructured_kwargs)
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