import os
from pprint import pprint
from typing import Dict, List
import pandas as pd
from typeguard import typechecked
from . import _api, _utils
from ._utils import get_value_from_body, convert_time_formats_in_status
from .settings import ValidStatus
[docs]
@typechecked
def get_user(verbose: bool = False) -> str:
"""Show the username for the twinLab cloud account.
Args:
verbose (bool, optional): Display information about the operation while running.
Returns:
str: User.
Example:
.. code-block:: python
tl.get_user()
.. code-block:: console
'tim@digilab.co.uk'
"""
user = os.getenv("TWINLAB_USER")
if verbose:
print(f"User: {user}")
return user
[docs]
@typechecked
def set_user(username: str, verbose: bool = False) -> None:
"""Set the username for their twinLab cloud account.
Setting this will override the user set in the environment variable ``TWINLAB_USER`` in the ``.env`` file for the current session.
This function can also be used instead of setting a ``TWINLAB_USER`` in a ``.env`` file.
Note that a twinLab username is usually an email address.
Args:
username (str): Username for access to the twinLab cloud.
verbose (bool, optional): Display information about the operation while running.
Example:
.. code-block:: python
tl.set_user("example@digilab.co.uk")
"""
os.environ["TWINLAB_USER"] = username
if verbose:
print(f"User: {username}")
[docs]
@typechecked
def get_api_key(verbose: bool = False) -> str:
"""Show the user API key for their twinLab cloud account.
Args:
verbose (bool, optional): Display information about the operation while running.
Returns:
str: User API key.
Example:
.. code-block:: python
tl.get_api_key()
.. code-block:: console
'secret-12345'
"""
api_key = os.getenv("TWINLAB_API_KEY")
if verbose:
print(f"API key: {api_key}")
return api_key
[docs]
@typechecked
def set_api_key(api_key: str, verbose: bool = False) -> None:
"""Set the user API key for their twinLab cloud account.
Setting this will override the API key set in the environment variable ``TWINLAB_API_KEY`` in the ``.env`` file for the current session.
This function can also be used instead of setting a ``TWINLAB_API_KEY`` in a ``.env`` file.
Args:
api_key (str): API key to use for access to the twinLab cloud.
verbose (bool, optional): Display information about the operation while running.
Example:
.. code-block:: python
tl.set_api_key("12345")
"""
os.environ["TWINLAB_API_KEY"] = api_key
if verbose:
print(f"API key: {api_key}")
[docs]
@typechecked
def get_server_url(verbose: bool = False) -> str:
"""Show the URL from which twinLab is currently being accessed.
Args:
verbose (bool, optional): Display information about the operation while running.
Returns:
str: Server URL.
Example:
.. code-block:: python
tl.get_server_url()
.. code-block:: console
'https://twinlab.digilab.co.uk/v3'
"""
url = os.getenv("TWINLAB_URL")
if verbose:
print(f"Server URL: {url}")
return url
[docs]
@typechecked
def set_server_url(url: str, verbose: bool = False) -> None:
"""Set the server URL for twinLab.
If this is not set the default URL is used: ``https://twinlab.digilab.co.uk/v3``.
This default URL will be correct for most users and should not normally need to be changed.
Setting this will override the URL set in the environment variable ``TWINLAB_URL`` in the ``.env`` file for the current session.
Args:
url (str): URL for the twinLab cloud.
verbose (bool, optional): Display information about the operation while running.
Example:
.. code-block:: python
# Setting the server to test a beta feature
tl.set_server_url("https://twinlab.digilab.co.uk/v3/beta")
"""
os.environ["TWINLAB_URL"] = url
if verbose:
print(f"Server URL: {url}")
[docs]
@typechecked
def versions(verbose: bool = False) -> Dict[str, str]:
"""Get information about the twinLab version being used.
Args:
verbose (bool, optional): Display information about the operation while running.
Returns:
dict: Version information.
Example:
.. code-block:: python
version_info = tl.versions()
print(version_info)
.. code-block:: console
{'cloud': '2.3.0', 'modal': '0.4.0', 'library': '1.7.0', 'image': 'twinlab'}
"""
# TODO: Change function name to get_versions (verb) in the next major release
_, response = _api.get_versions()
version_info = response
if verbose:
print("Version information:")
pprint(version_info, compact=True, sort_dicts=False)
return version_info
[docs]
@typechecked
def list_datasets(verbose: bool = False) -> List[str]:
"""List datasets that have been uploaded to the user's twinLab cloud account.
These datasets can be used for training emulators and for other operations.
New datasets can be uploaded using the ``upload`` method of the ``Dataset`` class.
Args:
verbose (bool, optional): Display information about the operation while running.
Returns:
list: Datasets currently uploaded to the user's `twinLab` cloud account.
Example:
.. code-block:: python
datasets = tl.list_datasets()
print(datasets)
.. code-block:: console
['biscuits', 'gardening', 'force-energy', 'combusion']
"""
_, response = _api.get_datasets()
datasets = get_value_from_body("datasets", response)
if verbose:
print("Datasets:")
pprint(datasets, compact=True, sort_dicts=False)
return datasets
[docs]
@typechecked
def list_emulators(
verbose: bool = False,
) -> List[str]:
"""List trained emulators that exist in the user's twinLab cloud account.
These trained emulators can be used for a variety of inference operations (see methods of the Emulator class).
Args:
verbose (bool, optional): Display information about the operation while running.
Returns:
list: Currently trained and training emulators.
Example:
.. code-block:: python
emulators = tl.list_emulators()
print(emulators)
.. code-block:: console
['biscuits', 'gardening', 'new-emulator', 'my-emulator']
"""
_, response = _api.get_emulators()
emulators = _utils.get_value_from_body("emulators", response)
if verbose:
print("Emulators:")
pprint(emulators, compact=True, sort_dicts=False)
return emulators
[docs]
@typechecked
def list_emulators_statuses(
verbose: bool = False,
) -> List[dict]:
"""List the status of training and trained emulators, as well as those that have failed to train.
This includes the start and end times of training, the status of the emulator, and any error messages if the emulator failed to train.
Args:
verbose (bool, optional): Display information about the operation while running.
Returns:
list: Statuses of emulators on the twinLab cloud.
Example:
.. code-block:: python
statuses = tl.list_emulators_statuses()
print(statuses)
.. code-block:: console
[
{
"status": "success",
"start_time": "2024-08-20 12:28:05",
"end_time": "2024-08-20 12:28:07",
"emulator_name": "biscuits",
},
{
"status": "processing",
"start_time": "2024-08-20 12:19:16",
"emulator_name": "gardening",
},
{
"status": "failure",
"start_time": "2024-08-06 13:07:06",
"end_time": "2024-08-06 13:07:07",
"error": "KeyError: DataFrame must contain columns: ['X,y']",
"emulator_name": "new-emulator",
},
]
"""
_, response = _api.get_emulators_statuses()
emulator_statuses = _utils.get_value_from_body("emulators_statuses", response)
# Print detailed emulator information to screen
if verbose:
# Create dictionary of cuddly status messages
status_messages = {
ValidStatus.PROCESSING.value: "Emulators currently training:",
ValidStatus.SUCCESS.value: "Successfully trained emulators:",
ValidStatus.FAILURE.value: "Emulators that failed to train:",
None: "Emulators with unknown status:",
}
if emulator_statuses:
for nice_status in status_messages.keys():
print("\033[1m" + status_messages[nice_status]) # Bold text
print("\033[0m") # Reset text formatting
status_count = 0
for status_dict in emulator_statuses:
status_dict = convert_time_formats_in_status(status_dict)
status = status_dict.get("status", None)
if status == nice_status:
status_count += 1
pprint(status_dict, compact=True, sort_dicts=False)
print()
if status_count == 0:
print(f"No {status_messages[nice_status].lower()[:-1]}")
print()
else:
print("No emulators found.")
return emulator_statuses
[docs]
@typechecked
def list_example_datasets(verbose: bool = False) -> list:
"""List example datasets that are available on the twinLab cloud.
These datasets can be downloaded and used for training emulators and other operations and are used in many of the examples in the documentation.
Datasets can be loaded using the ``load_example_dataset`` function.
Args:
verbose (bool, optional): Display information about the operation while running.
Returns:
list: Example datasets available for loading.
Example:
.. code-block:: python
example_datasets = tl.list_example_datasets()
print(example_datasets)
.. code-block:: console
['biscuits', 'gardening', 'quickstart', 'tritium-desorption']
"""
_, response = _api.get_example_datasets()
datasets = get_value_from_body("datasets", response)
if verbose:
print("Example datasets:")
pprint(datasets, compact=True, sort_dicts=False)
return datasets
[docs]
def load_example_dataset(dataset_id: str, verbose: bool = False) -> pd.DataFrame:
"""Load an example dataset from the twinLab cloud into the current session.
Args:
dataset_id (str): The name of the dataset to load.
verbose (bool, optional): Display information about the operation while running.
Returns:
pandas.DataFrame: The example dataset.
Example:
.. code-block:: python
tl.load_example_dataset("quickstart")
.. code-block:: console
x y
0 0.696469 -0.817374
1 0.286139 0.887656
2 0.226851 0.921553
3 0.551315 -0.326334
4 0.719469 -0.832518
5 0.423106 0.400669
6 0.980764 -0.164966
7 0.684830 -0.960764
8 0.480932 0.340115
9 0.392118 0.845795
"""
_, response = _api.get_example_dataset(dataset_id)
df = _utils.process_dataset_response(response)
if verbose:
print("Example dataset:")
print(df)
print("Dataframe downloaded successfully.")
return df
