def _save_df(cls, df: pd.DataFrame) -> DPTmpFile:
fn = DPTmpFile(ArrowFormat.ext)
df = to_df(df)
process_df(df)
ArrowFormat.save_file(fn.name, df)
log.debug(f"Saved df to {fn} ({os.path.getsize(fn.file)} bytes)")
return fn
def _save_obj(cls, data: t.Any, as_json: bool) -> DPTmpFile:
# import here as a very slow module due to nested imports
from ..files import save
fn = save(data, default_to_json=as_json)
log.debug(f"Saved object to {fn} ({os.path.getsize(fn.file)} bytes)")
return fn
def is_analytics_disabled() -> bool:
"""Determine the initial state for analytics if not already set"""
# disable if globally disabled or in certain envs
if _NO_ANALYTICS_FILE.exists() or ON_DATAPANE or _IN_PYTEST or _IN_DPSERVER:
log.debug("Analytics disabled")
return True
return False
def init(config_env: str = "default", config: t.Optional[Config] = None):
"""Init an API config - this MUST handle being called multiple times"""
if get_config() is not None:
log.debug("Reinitialising client config")
if config:
set_config(config)
else:
config_f = load_from_envfile(config_env)
log.debug(f"Loaded client environment from {config_f}")
def save_df(df: pd.DataFrame) -> DPTmpFile:
"""Export a df for uploading"""
fn = DPTmpFile(ArrowFormat.ext)
# create a copy of the df to process
df = to_df(df)
# process_df called in Arrow.save_file
# process_df(df)
ArrowFormat.save_file(fn.name, df)
log.debug(f"Saved df to {fn} ({os.path.getsize(fn.file)} bytes)")
return fn
def init(config_env: str = "default",
config: t.Optional[Config] = None) -> Config:
"""
Init an API config
- this MUST handle being called multiple times and only from the main-thread
"""
if get_config() is not None:
log.debug("Reinitialising client config")
if config:
set_config(config)
else:
config = Config.load(config_env)
return config
def load(cls, env: str = "default") -> "Config":
"""Load config for an environment and set globally"""
config_f = cls.get_config_file(env)
if not config_f.exists():
cls.create_default(env, config_f)
with config_f.open("r") as f:
c_yaml = yaml.safe_load(f)
# load config obj from file
config = dacite.from_dict(Config, c_yaml)
config._env = env
config._path = config_f
log.debug(f"Loaded client environment from {config._path}")
# check if stored file is out of date
config.upgrade_config_format()
# set to the global state
set_config(config)
return config
def get_config_file(env: str = DEFAULT_ENV) -> Path:
config_f = APP_DIR / f"{env}.yaml"
if not config_f.exists():
config_f.write_text(get_default_config())
log.debug(f"Creating default config file at {config_f}")
return config_f
def update(self, **kwargs):
# filter None values
kwargs = {k: v for (k, v) in kwargs.items() if v is not None}
self.res.patch(**kwargs)
self.refresh()
log.debug(f"Updated object {self.url}")
def delete(self):
"""Delete the object on the server"""
self.res.delete()
log.debug(f"Deleted object {self.url}")
def refresh(self):
"""Refresh the object with the latest data from the Datapane Server"""
self.dto = self.res.get()
log.debug(f"Refreshed {self.url}")
def __getattr__(self, attr):
if self.has_dto and not attr.startswith("__"):
log.debug(f"Proxying '{attr}' lookup to DTO")
return getattr(self._dto, attr)
# Default behaviour
return self.__getattribute__(attr)
def refresh(self):
"""Refresh the object with the latest data from the Datapane Server
- override to pull updated fields from dto to top-level
"""
self.dto = self.res.get()
log.debug(f"Refreshed {self.url}")
