Boosting The Productivity of Machine Learning Engineers
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Installation
From PyPi:
pip install kxy -U
From GitHub:
git clone https://github.com/kxytechnologies/kxy-python.git & cd ./kxy-python & pip install .
Authentication
All heavy-duty computations are run on our serverless infrastructure and require an API key. To configure the package with your API key, run
kxy configure
and follow the instructions. To get your own API key you need an account; you can sign up here. You'll then be automatically given an API key which you can find here.
Docker
The Docker image kxytechnologies/kxy has been built for your convenience, and comes with anaconda, auto-sklearn, and the kxy package.
To start a Jupyter Notebook server from a sandboxed Docker environment, run
docker run -i -t -p 5555:8888 kxytechnologies/kxy:latest /bin/bash -c "kxy configure <YOUR API KEY> && /opt/conda/bin/jupyter notebook --notebook-dir=/opt/notebooks --ip='*' --port=8888 --no-browser --allow-root --NotebookApp.token=''"
where you should replace <YOUR API KEY> with your API key and navigate to http://localhost:5555 in your browser. This docker environment comes with all examples available on the documentation website.
To start a Jupyter Notebook server from an existing directory of notebooks, run
docker run -i -t --mount src=</path/to/your/local/dir>,target=/opt/notebooks,type=bind -p 5555:8888 kxytechnologies/kxy:latest /bin/bash -c "kxy configure <YOUR API KEY> && /opt/conda/bin/jupyter notebook --notebook-dir=/opt/notebooks --ip='*' --port=8888 --no-browser --allow-root --NotebookApp.token=''"
where you should replace </path/to/your/local/dir> with the path to your local notebook folder and navigate to http://localhost:5555 in your browser.
You can also get the same Docker image from GitHub here.
Other Programming Language
We plan to release friendly API client in more programming language.
In the meantime, you can directly issue requests to our RESTFul API using your favorite programming language.
Pricing
All API keys are given a free quota (a few dozen backend tasks) that should be enough to try out the package and see if you love it. Beyond the free quota you will be billed a small fee per task.
KXY is free for academic use; simply signup with your university email.
KXY is also free for Kaggle competitions; sign up and email kaggle@kxy.ai to get a promotional code.
Release files for kxy 1.4.11
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| kxy-1.4.11.tar.gz | 65.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| kxy-1.4.11-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 167.5 kB
Release files / kxy-1.4.11.tar.gz
| Download URL | kxy-1.4.11.tar.gz |
|---|---|
| Size | 65.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
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BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.7.10
|
Release files / kxy-1.4.11-py3-none-any.whl
| Download URL | kxy-1.4.11-py3-none-any.whl |
|---|---|
| Size | 102.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.7.10
|
