Spaces:
Sleeping
Sleeping
update
Browse files- .gitignore +1 -0
- main.py +39 -1
- requirements.txt +3 -2
- toolbox/__init__.py +5 -0
- toolbox/os/__init__.py +6 -0
- toolbox/os/command.py +53 -0
- toolbox/os/environment.py +114 -0
- toolbox/os/other.py +9 -0
.gitignore
CHANGED
@@ -6,6 +6,7 @@
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flagged/
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pretrained_models/
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temp/
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**/cache/
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**/__pycache__/
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flagged/
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pretrained_models/
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temp/
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+
trained_models/
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**/cache/
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**/__pycache__/
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main.py
CHANGED
@@ -7,6 +7,8 @@ import argparse
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import json
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import platform
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import fasttext
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from fasttext.FastText import load_model, _FastText
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import gradio as gr
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@@ -14,6 +16,7 @@ from gradio import inputs, outputs
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from langid.langid import LanguageIdentifier, model
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from project_settings import project_path, temp_directory
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def get_args():
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@@ -39,11 +42,34 @@ def get_args():
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lang_id_identifier: LanguageIdentifier = None
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fasttext_model: _FastText = None
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def click_lang_id_button(text: str, ground_true: str, model_name: str):
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global lang_id_identifier
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global fasttext_model
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text = str(text).strip()
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@@ -53,6 +79,16 @@ def click_lang_id_button(text: str, ground_true: str, model_name: str):
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label, prob = fasttext_model.predict(text, k=1)
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label = label[0][9:]
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prob = prob[0]
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else:
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label = "model_name not available."
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prob = -1
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@@ -76,15 +112,17 @@ def main():
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global lang_id_identifier
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global fasttext_model
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lang_id_identifier = LanguageIdentifier.from_modelstring(model, norm_probs=True)
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fasttext_model = fasttext.load_model(args.fasttext_model)
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blocks = gr.Interface(
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click_lang_id_button,
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inputs=[
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inputs.Textbox(lines=3, label="text"),
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inputs.Textbox(label="ground_true"),
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inputs.Dropdown(choices=["langid", "fasttext"], default="langid", label="model_name"),
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],
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outputs=[
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outputs.Textbox(label="label"),
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import json
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import platform
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from allennlp.models.archival import archive_model, load_archive
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from allennlp.predictors.text_classifier import TextClassifierPredictor
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import fasttext
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from fasttext.FastText import load_model, _FastText
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import gradio as gr
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from langid.langid import LanguageIdentifier, model
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from project_settings import project_path, temp_directory
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from toolbox.os.command import Command
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def get_args():
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lang_id_identifier: LanguageIdentifier = None
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fasttext_model: _FastText = None
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qgyd_lang_id_predictor: TextClassifierPredictor = None
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trained_model_dir = project_path / "trained_models/huggingface"
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trained_model_dir.mkdir(parents=True, exist_ok=True)
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def init_qgyd_lang_id_predictor() -> TextClassifierPredictor:
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model_name = "qgyd2021/language_identification"
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model_path = trained_model_dir / model_name
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if not model_path.exists():
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model_path.parent.mkdir(exist_ok=True)
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Command.cd(model_path.parent.as_posix())
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Command.popen("git clone https://huggingface.co/{}".format(model_name))
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archive = load_archive(archive_file=model_path.as_posix())
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predictor = TextClassifierPredictor(
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model=archive.model,
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dataset_reader=archive.dataset_reader,
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)
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return predictor
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def click_lang_id_button(text: str, ground_true: str, model_name: str):
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global lang_id_identifier
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global fasttext_model
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global qgyd_lang_id_predictor
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text = str(text).strip()
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label, prob = fasttext_model.predict(text, k=1)
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label = label[0][9:]
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prob = prob[0]
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elif model_name == "qgyd_lang_id_1":
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json_dict = {
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"sentence": text
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}
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outputs = qgyd_lang_id_predictor.predict_json(
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json_dict
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)
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label = outputs["label"]
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probs = outputs["probs"]
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prob = max(probs)
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else:
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label = "model_name not available."
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prob = -1
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global lang_id_identifier
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global fasttext_model
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global qgyd_lang_id_predictor
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lang_id_identifier = LanguageIdentifier.from_modelstring(model, norm_probs=True)
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fasttext_model = fasttext.load_model(args.fasttext_model)
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qgyd_lang_id_predictor = init_qgyd_lang_id_predictor()
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blocks = gr.Interface(
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click_lang_id_button,
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inputs=[
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inputs.Textbox(lines=3, label="text"),
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inputs.Textbox(label="ground_true"),
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inputs.Dropdown(choices=["langid", "fasttext", "qgyd_lang_id_1"], default="langid", label="model_name"),
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],
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outputs=[
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outputs.Textbox(label="label"),
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requirements.txt
CHANGED
@@ -1,3 +1,4 @@
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gradio==2.1.1
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langid==1.1.6
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fasttext==0.9.2
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fasttext==0.9.2
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langid==1.1.6
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gradio==2.3.0
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allennlp
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toolbox/__init__.py
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#!/usr/bin/python3
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# -*- coding: utf-8 -*-
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if __name__ == "__main__":
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pass
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toolbox/os/__init__.py
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#!/usr/bin/python3
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# -*- coding: utf-8 -*-
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if __name__ == '__main__':
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pass
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toolbox/os/command.py
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import os
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class Command(object):
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custom_command = [
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'cd'
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]
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@staticmethod
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def _get_cmd(command):
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command = str(command).strip()
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if command == '':
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return None
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cmd_and_args = command.split(sep=' ')
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cmd = cmd_and_args[0]
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args = ' '.join(cmd_and_args[1:])
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return cmd, args
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@classmethod
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def popen(cls, command):
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cmd, args = cls._get_cmd(command)
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if cmd in cls.custom_command:
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method = getattr(cls, cmd)
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return method(args)
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else:
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resp = os.popen(command)
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result = resp.read()
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resp.close()
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return result
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@classmethod
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def cd(cls, args):
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if args.startswith('/'):
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os.chdir(args)
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else:
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pwd = os.getcwd()
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path = os.path.join(pwd, args)
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os.chdir(path)
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@classmethod
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def system(cls, command):
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return os.system(command)
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def __init__(self):
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pass
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def ps_ef_grep(keyword: str):
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cmd = 'ps -ef | grep {}'.format(keyword)
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rows = Command.popen(cmd)
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rows = str(rows).split('\n')
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rows = [row for row in rows if row.__contains__(keyword) and not row.__contains__('grep')]
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return rows
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toolbox/os/environment.py
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@@ -0,0 +1,114 @@
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#!/usr/bin/python3
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# -*- coding: utf-8 -*-
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import json
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import os
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from dotenv import load_dotenv
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from dotenv.main import DotEnv
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from smart.json.misc import traverse
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class EnvironmentManager(object):
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def __init__(self, path, env, override=False):
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filename = os.path.join(path, '{}.env'.format(env))
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self.filename = filename
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load_dotenv(
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dotenv_path=filename,
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override=override
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)
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self._environ = dict()
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def open_dotenv(self, filename: str = None):
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filename = filename or self.filename
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dotenv = DotEnv(
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dotenv_path=filename,
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stream=None,
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verbose=False,
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interpolate=False,
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override=False,
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encoding="utf-8",
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)
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result = dotenv.dict()
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return result
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def get(self, key, default=None, dtype=str):
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result = os.environ.get(key)
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if result is None:
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if default is None:
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result = None
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else:
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result = default
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else:
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result = dtype(result)
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self._environ[key] = result
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return result
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_DEFAULT_DTYPE_MAP = {
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'int': int,
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'float': float,
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'str': str,
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'json.loads': json.loads
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}
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class JsonConfig(object):
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"""
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将 json 中, 形如 `$float:threshold` 的值, 处理为:
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从环境变量中查到 threshold, 再将其转换为 float 类型.
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"""
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def __init__(self, dtype_map: dict = None, environment: EnvironmentManager = None):
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self.dtype_map = dtype_map or _DEFAULT_DTYPE_MAP
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self.environment = environment or os.environ
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def sanitize_by_filename(self, filename: str):
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with open(filename, 'r', encoding='utf-8') as f:
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js = json.load(f)
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return self.sanitize_by_json(js)
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def sanitize_by_json(self, js):
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js = traverse(
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js,
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callback=self.sanitize,
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environment=self.environment
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)
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return js
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def sanitize(self, string, environment):
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"""支持 $ 符开始的, 环境变量配置"""
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if isinstance(string, str) and string.startswith('$'):
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dtype, key = string[1:].split(':')
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dtype = self.dtype_map[dtype]
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value = environment.get(key)
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if value is None:
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raise AssertionError('environment not exist. key: {}'.format(key))
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value = dtype(value)
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result = value
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else:
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result = string
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return result
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def demo1():
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import json
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from project_settings import project_path
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environment = EnvironmentManager(
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path=os.path.join(project_path, 'server/callbot_server/dotenv'),
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env='dev',
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)
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init_scenes = environment.get(key='init_scenes', dtype=json.loads)
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print(init_scenes)
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print(environment._environ)
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return
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if __name__ == '__main__':
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demo1()
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toolbox/os/other.py
ADDED
@@ -0,0 +1,9 @@
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import os
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import inspect
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def pwd():
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"""你在哪个文件调用此函数, 它就会返回那个文件所在的 dir 目标"""
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frame = inspect.stack()[1]
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module = inspect.getmodule(frame[0])
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return os.path.dirname(os.path.abspath(module.__file__))
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