71 lines
2.2 KiB
Python
71 lines
2.2 KiB
Python
import logging
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import os
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from typing import Any
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import rapidjson
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from freqtrade.constants import ENV_VAR_PREFIX
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from freqtrade.misc import deep_merge_dicts
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logger = logging.getLogger(__name__)
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def _get_var_typed(val):
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try:
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return int(val)
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except ValueError:
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try:
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return float(val)
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except ValueError:
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if val.lower() in ("t", "true"):
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return True
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elif val.lower() in ("f", "false"):
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return False
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# try to convert from json
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try:
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value = rapidjson.loads(val)
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# Limited to lists for now
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if isinstance(value, list):
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return value
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except rapidjson.JSONDecodeError:
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pass
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# keep as string
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return val
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def _flat_vars_to_nested_dict(env_dict: dict[str, Any], prefix: str) -> dict[str, Any]:
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"""
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Environment variables must be prefixed with FREQTRADE.
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FREQTRADE__{section}__{key}
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:param env_dict: Dictionary to validate - usually os.environ
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:param prefix: Prefix to consider (usually FREQTRADE__)
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:return: Nested dict based on available and relevant variables.
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"""
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no_convert = ["CHAT_ID", "PASSWORD"]
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relevant_vars: dict[str, Any] = {}
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for env_var, val in sorted(env_dict.items()):
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if env_var.startswith(prefix):
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logger.info(f"Loading variable '{env_var}'")
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key = env_var.replace(prefix, "")
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for k in reversed(key.split("__")):
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val = {
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k.lower(): (
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_get_var_typed(val)
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if not isinstance(val, dict) and k not in no_convert
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else val
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)
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}
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relevant_vars = deep_merge_dicts(val, relevant_vars)
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return relevant_vars
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def enironment_vars_to_dict() -> dict[str, Any]:
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"""
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Read environment variables and return a nested dict for relevant variables
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Relevant variables must follow the FREQTRADE__{section}__{key} pattern
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:return: Nested dict based on available and relevant variables.
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"""
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return _flat_vars_to_nested_dict(os.environ.copy(), ENV_VAR_PREFIX)
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