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```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() ```
83 lines
2.7 KiB
Python
83 lines
2.7 KiB
Python
"""Util that calls Google Scholar Search."""
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from typing import Any, Dict, Optional, cast
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from langchain_core.pydantic_v1 import BaseModel, Extra, SecretStr, root_validator
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from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
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class GoogleJobsAPIWrapper(BaseModel):
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"""Wrapper for SerpApi's Google Scholar API
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You can create SerpApi.com key by signing up at: https://serpapi.com/users/sign_up.
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The wrapper uses the SerpApi.com python package:
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https://serpapi.com/integrations/python
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To use, you should have the environment variable ``SERPAPI_API_KEY``
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set with your API key, or pass `serp_api_key` as a named parameter
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to the constructor.
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Example:
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.. code-block:: python
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from langchain_community.utilities import GoogleJobsAPIWrapper
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google_Jobs = GoogleJobsAPIWrapper()
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google_Jobs.run('langchain')
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"""
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serp_search_engine: Any
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serp_api_key: Optional[SecretStr] = None
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class Config:
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"""Configuration for this pydantic object."""
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extra = Extra.forbid
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@root_validator(pre=True)
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def validate_environment(cls, values: Dict) -> Dict:
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"""Validate that api key and python package exists in environment."""
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values["serp_api_key"] = convert_to_secret_str(
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get_from_dict_or_env(values, "serp_api_key", "SERPAPI_API_KEY")
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)
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try:
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from serpapi import SerpApiClient
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except ImportError:
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raise ImportError(
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"google-search-results is not installed. "
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"Please install it with `pip install google-search-results"
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">=2.4.2`"
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)
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serp_search_engine = SerpApiClient
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values["serp_search_engine"] = serp_search_engine
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return values
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def run(self, query: str) -> str:
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"""Run query through Google Trends with Serpapi"""
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# set up query
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serpapi_api_key = cast(SecretStr, self.serp_api_key)
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params = {
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"engine": "google_jobs",
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"api_key": serpapi_api_key.get_secret_value(),
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"q": query,
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}
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total_results = []
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client = self.serp_search_engine(params)
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total_results = client.get_dict()["jobs_results"]
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# extract 1 job info:
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res_str = ""
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for i in range(1):
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job = total_results[i]
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res_str += (
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"\n_______________________________________________"
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+ f"\nJob Title: {job['title']}\n"
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+ f"Company Name: {job['company_name']}\n"
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+ f"Location: {job['location']}\n"
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+ f"Description: {job['description']}"
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+ "\n_______________________________________________\n"
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)
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return res_str + "\n"
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