Enum - Choices¶
To define a CLI parameter that can take a value from a predefined set of values you can use a standard Python enum.Enum
:
from enum import Enum
import typer
class NeuralNetwork(str, Enum):
simple = "simple"
conv = "conv"
lstm = "lstm"
def main(network: NeuralNetwork = NeuralNetwork.simple):
print(f"Training neural network of type: {network.value}")
if __name__ == "__main__":
typer.run(main)
Tip
Notice that the function parameter network
will be an Enum
, not a str
.
To get the str
value in your function's code use network.value
.
Check it:
$ python main.py --help
// Notice the predefined values [simple|conv|lstm]
Usage: main.py [OPTIONS]
Options:
--network [simple|conv|lstm] [default: simple]
--help Show this message and exit.
// Try it
$ python main.py --network conv
Training neural network of type: conv
// Invalid value
$ python main.py --network capsule
Usage: main.py [OPTIONS]
Try "main.py --help" for help.
Error: Invalid value for '--network': 'capsule' is not one of 'simple', 'conv', 'lstm'.
// Note that enums are case sensitive by default
$ python main.py --network CONV
Usage: main.py [OPTIONS]
Try "main.py --help" for help.
Error: Invalid value for '--network': 'CONV' is not one of 'simple', 'conv', 'lstm'.
Case insensitive Enum choices¶
You can make an Enum
(choice) CLI parameter be case-insensitive with the case_sensitive
parameter:
from enum import Enum
import typer
from typing_extensions import Annotated
class NeuralNetwork(str, Enum):
simple = "simple"
conv = "conv"
lstm = "lstm"
def main(
network: Annotated[
NeuralNetwork, typer.Option(case_sensitive=False)
] = NeuralNetwork.simple,
):
print(f"Training neural network of type: {network.value}")
if __name__ == "__main__":
typer.run(main)
🤓 Other versions and variants
Tip
Prefer to use the Annotated
version if possible.
from enum import Enum
import typer
class NeuralNetwork(str, Enum):
simple = "simple"
conv = "conv"
lstm = "lstm"
def main(
network: NeuralNetwork = typer.Option(NeuralNetwork.simple, case_sensitive=False),
):
print(f"Training neural network of type: {network.value}")
if __name__ == "__main__":
typer.run(main)
And then the values of the Enum
will be checked no matter if lower case, upper case, or a mix:
// Notice the upper case CONV
$ python main.py --network CONV
Training neural network of type: conv
// A mix also works
$ python main.py --network LsTm
Training neural network of type: lstm
List of Enum values¶
A CLI parameter can also take a list of Enum
values:
from enum import Enum
from typing import List
import typer
from typing_extensions import Annotated
class Food(str, Enum):
food_1 = "Eggs"
food_2 = "Bacon"
food_3 = "Cheese"
def main(groceries: Annotated[List[Food], typer.Option()] = [Food.food_1, Food.food_3]):
print(f"Buying groceries: {', '.join([f.value for f in groceries])}")
if __name__ == "__main__":
typer.run(main)
🤓 Other versions and variants
Tip
Prefer to use the Annotated
version if possible.
from enum import Enum
from typing import List
import typer
class Food(str, Enum):
food_1 = "Eggs"
food_2 = "Bacon"
food_3 = "Cheese"
def main(groceries: List[Food] = typer.Option([Food.food_1, Food.food_3])):
print(f"Buying groceries: {', '.join([f.value for f in groceries])}")
if __name__ == "__main__":
typer.run(main)
This works just like any other parameter value taking a list of things:
$ python main.py --help
// Notice the default values being shown
Usage: main.py [OPTIONS]
Options:
--groceries [Eggs|Bacon|Cheese] [default: Eggs, Cheese]
--help Show this message and exit.
// Try it with the default values
$ python main.py
Buying groceries: Eggs, Cheese
// Try it with a single value
$ python main.py --groceries "Eggs"
Buying groceries: Eggs
// Try it with multiple values
$ python main.py --groceries "Eggs" --groceries "Bacon"
Buying groceries: Eggs, Bacon