Integrate new large_files
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5 changed files with 67 additions and 26 deletions
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@ -15,9 +15,9 @@ pip install open-large
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### Simple example
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```python
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from open_s3 import LargeFile
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from large_file import LargeFileS3
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LargeFile.configure_credentials({
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LargeFileS3.configure_credentials({
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"aws_region_name": "your_region_like_eu-west-2",
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"aws_access_key_id": "YOUR_ACCESS_KEY_ID",
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"aws_secret_access_key": "YOUR_VERY_SECRET_ACCESS_KEY",
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@ -25,13 +25,13 @@ LargeFile.configure_credentials({
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})
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# Creates a new version and deletes the older version leaving the 3 most recently used intact
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with LargeFile("test.txt", "w", keep_last_n=3) as f:
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with LargeFileS3("test.txt", "w", keep_last_n=3) as f:
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for i in range(100000):
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f.write('test\n')
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# By default the latest version is returned
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# but an optional `version` keyword argument can be provided as well
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with LargeFile("test.txt", "r") as f:
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with LargeFileS3("test.txt", "r") as f:
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print(f.readlines()[0])
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```
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@ -91,13 +91,13 @@ endpoint_url = this is optional, for backblaze, use this: https://s3.us-west-002
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#### Print the expected options
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```sh
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python3 -m open_s3 --help
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python3 -m large_file --help
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```
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#### Upload some files
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```sh
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python3 -m open_s3 --secrets secrets.ini --push my_first_file.json folder/my_second_file my_folder
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python3 -m large_file --backend s3 --secrets secrets.ini --push my_first_file.json folder/my_second_file my_folder
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```
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> Only the filename is used as the S3 name, the rest of the path is ignored.
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@ -107,7 +107,7 @@ python3 -m open_s3 --secrets secrets.ini --push my_first_file.json folder/my_sec
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This can be useful when building a Docker image for example. This way, the files can already reside inside the container and need not be downloaded later.
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```sh
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python3 -m open_s3 --secrets ~/.aws/credentials --cache my_first_file.json:3 my_second_file my_folder:0
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python3 -m large_file --backend s3 -secrets ~/.aws/credentials --cache my_first_file.json:3 my_second_file my_folder:0
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```
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> Versions may be specified by using `:`-s.
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@ -115,5 +115,5 @@ python3 -m open_s3 --secrets ~/.aws/credentials --cache my_first_file.json:3 my_
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#### Delete remote files
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```sh
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python3 -m open_s3 --secrets ~/.aws/credentials --delete my_first_file.json
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python3 -m large_file --backend s3 --secrets ~/.aws/credentials --delete my_first_file.json
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```
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@ -44,6 +44,7 @@ install_requires =
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dash >= 2.4.0
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uvicorn[standard] >= 0.17.0
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watchdog >= 2.1.0
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pymongo >= 4.0.0
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[options.package_data]
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* = *.json, *.yaml, *.yml, *.css
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@ -1,4 +1,14 @@
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from pathlib import Path
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from great_ai.large_file import LargeFileLocal, LargeFileMongo, LargeFileS3
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ENV_VAR_KEY = "ENVIRONMENT"
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PRODUCTION_KEY = "production"
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DEFAULT_TRACING_DB_FILENAME = "tracing_database.json"
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METRICS_PATH = "/metrics"
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DEFAULT_LARGE_FILE_CONFIG_PATHS = {
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LargeFileLocal: None,
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LargeFileMongo: Path("mongodb.ini"),
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LargeFileS3: Path("s3.ini"),
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}
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@ -2,24 +2,29 @@ import os
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import random
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from logging import DEBUG, Logger
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from pathlib import Path
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from typing import Optional
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from typing import Optional, Type
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import great_ai.great_ai.context.context as context
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from great_ai.open_s3 import LargeFile
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from great_ai.large_file import LargeFile, LargeFileLocal
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from great_ai.utilities.logger import get_logger
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from ..constants import DEFAULT_TRACING_DB_FILENAME, ENV_VAR_KEY, PRODUCTION_KEY
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from ..persistence import ParallelTinyDbDriver, PersistenceDriver
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from ..constants import (
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DEFAULT_LARGE_FILE_CONFIG_PATHS,
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DEFAULT_TRACING_DB_FILENAME,
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ENV_VAR_KEY,
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PRODUCTION_KEY,
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)
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from ..tracing.parallel_tinydb_driver import ParallelTinyDbDriver, TracingDatabase
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def configure(
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version: str = "0.0.1",
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log_level: int = DEBUG,
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s3_config: Path = Path("s3.ini"),
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seed: int = 42,
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persistence_driver: PersistenceDriver = ParallelTinyDbDriver(
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tracing_database: TracingDatabase = ParallelTinyDbDriver(
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Path(DEFAULT_TRACING_DB_FILENAME)
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),
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large_file_implementation: Type[LargeFile] = LargeFileLocal,
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should_log_exception_stack: Optional[bool] = None,
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prediction_cache_size: int = 512,
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) -> None:
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@ -28,21 +33,22 @@ def configure(
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if context._context is not None:
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logger.warn(
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"Configuration has been already initialised, overwriting.\n"
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+ 'Make sure to call "configure()" before importing your application code.'
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+ "Make sure to call `configure()` before importing your application code."
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)
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is_production = _is_in_production_mode(logger=logger)
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_initialize_large_file(s3_config, logger=logger)
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_initialize_large_file(large_file_implementation, logger=logger)
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_set_seed(seed)
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if not persistence_driver.is_threadsafe:
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if not tracing_database.is_threadsafe:
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logger.warning(
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f"The selected persistence driver ({type(persistence_driver).__name__}) is not threadsafe"
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f"The selected persistence driver ({type(tracing_database).__name__}) is not threadsafe"
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)
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context._context = context.Context(
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version=version,
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persistence=persistence_driver,
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tracing_database=tracing_database,
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large_file_implementation=large_file_implementation,
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is_production=is_production,
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logger=logger,
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should_log_exception_stack=not is_production
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@ -77,12 +83,23 @@ def _is_in_production_mode(logger: Optional[Logger]) -> bool:
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return is_production
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def _initialize_large_file(s3_config: Path, logger: Logger) -> None:
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if s3_config.exists():
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LargeFile.configure_credentials_from_file(s3_config)
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def _initialize_large_file(large_file: Type[LargeFile], logger: Logger) -> None:
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path = DEFAULT_LARGE_FILE_CONFIG_PATHS[large_file]
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if path is None:
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return
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if large_file.initialized:
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logger.warning(
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f"{large_file.__name__} has been already configured: skipping initialisation"
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)
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return
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if path.exists():
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large_file.configure_credentials_from_file(path)
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logger.info(f"{large_file.__name__} initialised with config ({path.resolve()})")
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else:
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logger.warning(
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f"Provided S3 config ({s3_config.resolve()}) not found, skipping LargeFile initialisation"
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f"Default {large_file.__name__} config ({path.resolve()}) not found, skipping {large_file.__name__} initialisation"
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)
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@ -1,14 +1,17 @@
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from logging import Logger
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from typing import Optional
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from typing import Any, Dict, Optional, Type
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from pydantic import BaseModel
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from ..persistence import PersistenceDriver
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from great_ai.large_file.large_file.large_file import LargeFile
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from ..tracing.tracing_database import TracingDatabase
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class Context(BaseModel):
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version: str
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persistence: PersistenceDriver
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tracing_database: TracingDatabase
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large_file_implementation: Type[LargeFile]
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is_production: bool
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logger: Logger
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should_log_exception_stack: bool
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@ -17,5 +20,15 @@ class Context(BaseModel):
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class Config:
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arbitrary_types_allowed = True
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def to_flat_dict(self) -> Dict[str, Any]:
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return {
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"version": self.version,
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"tracing_database": type(self.tracing_database).__name__,
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"large_file_implementation": self.large_file_implementation.__name__,
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"is_production": self.is_production,
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"logger": type(self.logger).__name__,
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"should_log_exception_stack": self.should_log_exception_stack,
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}
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_context: Optional[Context] = None
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