Skip to main content

A package for auto quantum machine learning-izing your experiments!

Project description

AQMLator

A package for auto (quantum machine learning)-izing your experiments!

Requirements

Python version 3.11 is required. Necessary packages are provided in the respective requirements*.txt files.

Database

The Postgres database is used to store the Optuna trials data. It has to be installed prior to running the package, so that the psycopg2 package can be installed properly.

Documentation

The documentation is built using Sphinx. Building PDF version of the documentation requires latex distribution (we used miktex) and perl (we used strawberry perl). To generate the pdf version of documentation, run

make latexpdf

and to generate the html version of documentation, run

make html

Both command should be run from the docs directory.

Installation

The package is available on pip, and can be installed using

pip install aqmlator

To install the package from the sources, run

pip install .

To develop the package, run

pip install -e .

To install the packages required for development, run

pip install -r requirements -r requirements-dev.txt

Setup

To fully set up the package, one has to add the database url to the aqmlator_database_url environment variable. The example of the database url is

postgresql://user:password@localhost/mydb

where user is the database user, password is the database password, localhost is the database host, and mydb is the database name.

Access

To access the Optuna trials data use optuna-dashboard application. By default, it can be run using the following command

optuna-dashboard postgresql://user:password@localhost/mydb

while the (PostgreSQL) database is running.

Alternatively, one can use aqmlator.database.export_data_to_sqlite_database to export the data to the SQLite database, and handle it as one pleases.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

aqmlator-0.1.2.tar.gz (39.7 kB view details)

Uploaded Source

Built Distribution

AQMLator-0.1.2-py3-none-any.whl (36.8 kB view details)

Uploaded Python 3

File details

Details for the file aqmlator-0.1.2.tar.gz.

File metadata

  • Download URL: aqmlator-0.1.2.tar.gz
  • Upload date:
  • Size: 39.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.0

File hashes

Hashes for aqmlator-0.1.2.tar.gz
Algorithm Hash digest
SHA256 1f5669f9484ed35244219f82d2f0477550859fa747650671865cbf517c97657c
MD5 50889c3cd6602144e7b725187f508d44
BLAKE2b-256 2fc0657c62590e1fe910c028e6b5a318d27db34427989e7b9df32b49775df475

See more details on using hashes here.

File details

Details for the file AQMLator-0.1.2-py3-none-any.whl.

File metadata

  • Download URL: AQMLator-0.1.2-py3-none-any.whl
  • Upload date:
  • Size: 36.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.0

File hashes

Hashes for AQMLator-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 8d1ef8b34792896823d3dff16e4e19197058afe521d1c4b84711a3d17bacb7b5
MD5 141f6db8cd7a0c539a337e45820b82be
BLAKE2b-256 304f8e47023f1dca1522fd7ed6d039d9c550871abe9a9285754e3720c02c8c7e

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page