Metadata-Version: 2.1
Name: alchemy
Version: 20.5
Summary: Alchemy. Experiments logging & visualization.
Home-page: https://github.com/catalyst-team/alchemy
Author: Sergey Kolesnikov
Author-email: scitator@gmail.com
License: Apache License 2.0
Download-URL: https://github.com/catalyst-team/alchemy
Project-URL: Bug Tracker, https://github.com/catalyst-team/alchemy/issues
Project-URL: Documentation, https://catalyst-team.github.io/alchemy
Project-URL: Source Code, https://github.com/catalyst-team/alchemy
Description: 
        <div align="center">
        
        ![Alchemy logo](https://raw.githubusercontent.com/catalyst-team/catalyst-pics/master/pics/alchemy_logo.png)
        
        **Experiments logging & visualization**
        
        ![Build Status](https://github.com/catalyst-team/alchemy/workflows/CI/badge.svg)
        [![CodeFactor](https://www.codefactor.io/repository/github/catalyst-team/alchemy/badge)](https://www.codefactor.io/repository/github/catalyst-team/alchemy)
        [![Pipi version](https://img.shields.io/pypi/v/alchemy.svg)](https://pypi.org/project/alchemy/)
        [![Docs](https://img.shields.io/badge/dynamic/json.svg?label=docs&url=https%3A%2F%2Fpypi.org%2Fpypi%2Fcatalyst%2Fjson&query=%24.info.version&colorB=brightgreen&prefix=v)](https://catalyst-team.github.io/catalyst/index.html)
        [![PyPI Status](https://pepy.tech/badge/alchemy)](https://pepy.tech/project/alchemy)
        
        [![Twitter](https://img.shields.io/badge/news-on%20twitter-499feb)](https://twitter.com/catalyst_core)
        [![Telegram](https://img.shields.io/badge/channel-on%20telegram-blue)](https://t.me/catalyst_team)
        [![Slack](https://img.shields.io/badge/Catalyst-slack-success)](https://join.slack.com/t/catalyst-team-core/shared_invite/zt-d9miirnn-z86oKDzFMKlMG4fgFdZafw)
        [![Github contributors](https://img.shields.io/github/contributors/catalyst-team/alchemy.svg?logo=github&logoColor=white)](https://github.com/catalyst-team/alchemy/graphs/contributors)
        
        </div>
        
        Project [manifest](https://github.com/catalyst-team/catalyst/blob/master/MANIFEST.md). Part of [Catalyst Ecosystem](https://docs.google.com/presentation/d/1D-yhVOg6OXzjo9K_-IS5vSHLPIUxp1PEkFGnpRcNCNU/edit?usp=sharing):
        - [Alchemy](https://github.com/catalyst-team/alchemy) - Experiments logging & visualization
        - [Catalyst](https://github.com/catalyst-team/catalyst) - Accelerated Deep Learning Research and Development
        - [Reaction](https://github.com/catalyst-team/reaction) - Convenient Deep Learning models serving
        
        ---
        
        ## Installation
        
        Common installation:
        ```bash
        pip install -U alchemy
        ```
        
        Previous name `alchemy-catalyst` [![PyPI Status](https://pepy.tech/badge/alchemy-catalyst)](https://pepy.tech/project/alchemy-catalyst)
        
        ## Getting started
        
        1. Goto [Alchemy](https://alchemy.host/) and get your personal token.
        
        2. Run following **example.py**:
            ```python
            import random
            
            from alchemy import Logger
            
            # insert your personal token here
            token = "..."
            project = "default"
            
            for gid in range(1):
                group = f"group_{gid}"
                for eid in range(2):
                    experiment = f"experiment_{eid}"
                    logger = Logger(
                        token=token,
                        experiment=experiment,
                        group=group,
                        project=project,
                    )
                    for mid in range(4):
                        metric = f"metric_{mid}"
                        # let's sample some random data
                        n = 300
                        x = random.randint(-10, 10)
                        for i in range(n):
                            logger.log_scalar(metric, x)
                            x += random.randint(-1, 1)
                    logger.close()
            ```
        3. Now you should see your metrics on [Alchemy](https://alchemy.host/).
        
        
        ## Catalyst.Ecosystem
        
        1. Goto [Alchemy](https://alchemy.host/) and get your personal token.
        
        2. Log your Catalyst experiment with **AlchemyLogger**:
            ```python
            from catalyst.dl import SupervisedRunner, AlchemyLogger
        
            runner = SupervisedRunner()
            runner.train(
                model=model,
                criterion=criterion,
                optimizer=optimizer,
                loaders=loaders,
                logdir=logdir,
                num_epochs=num_epochs,
                verbose=True,
                callbacks={
                    "logger": AlchemyLogger(
                        token="...", # your Alchemy token
                        project="your_project_name",
                        experiment="your_experiment_name",
                        group="your_experiment_group_name",
                    )
                }
            )
            ```
        3. Now you should see your metrics on [Alchemy](https://alchemy.host/).
        
        ## Examples
        
        For mode detailed tutorials, please follow [Catalyst examples](https://github.com/catalyst-team/catalyst/tree/master/examples#tutorials).
        
Keywords: Machine Learning,Deep Learning,PyTorch
Platform: UNKNOWN
Classifier: Environment :: Console
Classifier: Natural Language :: English
Classifier: Development Status :: 4 - Beta
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: System :: Logging
Classifier: Topic :: System :: Monitoring
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: Implementation :: CPython
Requires-Python: >=3.5.0
Description-Content-Type: text/markdown
