Getting Started#

Installation#

Pip install

twinLab can be installed via pip from PyPI.

pip install twinlab

Note

See our installation guide for more detailed installation instructions.

Import#

To start using twinLab, enter the following line of Python.

import twinlab as tl

Tip

If you’re using Google Colab, you don’t have to install twinLab on your machine. You can just install and import at the top of the .ipynb file:

!pip install twinlab
import twinlab as tl

Configure API Key#

Need an API key?

If you still need an API key get in touch and let our solution engineers set you up with a free trial.

There are two options for configuring your API key. One involves setting a .env file on your computer which contains your API key:

.env file

Once this .env file has been set, this will enable your API key to be read from any script run in the subsequent directory tree.

Windows

Powershell

echo "TWINLAB_API_KEY=<your_api_key>" > .env

Command Line

echo TWINLAB_API_KEY=<your_api_key> > .env

Linux

echo "TWINLAB_API_KEY=<your_api_key>" > .env

MacOS

echo "TWINLAB_API_KEY=<your_api_key>" > .env

set_api_key()

Setting this function will enable you not to have to store your API key on your computer’s operating system.

import twinlab as tl

API_KEY = '<your_api_key>'

tl.set_api_key(API_KEY)

Warning

While we offer the flexibility to utilize the set_api_key() functionality, this should be used with care not to publicly expose your API key when sharing files.

It should return something like this:

====== TwinLab Client Initialisation ======
Version     : 2.0.0
Server      : https://twinlab.digilab.co.uk
Environment : <my_project_directory>/.env

Run an example#

You’re all set! Here’s an example script to get you started:

# Import pandas as well
import pandas as pd

# Create a dataset and upload to twinLab cloud
df = pd.DataFrame({"X": [1, 2, 3, 4], "y": [1, 4, 9, 16]})
dataset = tl.Dataset("test-data")
dataset.upload(df)

# Train a machine-learning emulator for the data
emulator = tl.Emulator("test-emulator")
emulator.train(dataset=dataset, inputs=["X"], outputs=["y"])

# Evaluate the emulator on some unseen data
sample_points = pd.DataFrame({"X": [1.5, 2.5, 3.5]})
df_mean, df_std = emulator.predict(df=sample_points)

# Explore the results
print(df_mean)
print(df_std)

Having Problems?#

If twinLab is unable to locate your .env file, you may receive the following error:

{message: 'Unable to find user with API key: `None`'}

Error: permission denied

This could be for a few reasons: - the .env file does not exist (see the steps above) - the .env file does not have the correct information (see the steps above) - the .env file does not exist in the current working directory or above - your windows user account doesn’t have read permissions on the .env file and the directory where the python code is being executed - your windows user account doesn’t have execute permissions on the directory where the python code is being executed - the .env file doesn’t exist on the same drive as the directory where the python code is being executed

Anything else?#

If you have any questions or concerns you can email us at twinlab@digilab.co.uk or find out more on our website.