Metadata-Version: 2.0
Name: polyaxon-helper
Version: 0.4.2
Summary: A python helper library to report metrics and communicate with Polyaxon.
Home-page: https://github.com/polyaxon/polyaxon-helper
Author: Mourad Mourafiq
Author-email: mourad@polyaxon.com
License: MIT
Description-Content-Type: UNKNOWN
Keywords: polyaxon,tensorFlow,deep-learning,machine-learning,data-science,neural-networks,artificial-intelligence,ai,reinforcement-learning,kubernetes
Platform: any
Classifier: Programming Language :: Python
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Dist: polyaxon-client (==0.4.2)

[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](LICENSE)
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# Polyaxon-helper

Polyaxon helper is a lightweight python library to report metrics and communicate information with Polyaxon.

## Installation

```bash
$ pip install -U polyaxon-helper
```

for python3

```bash
$ pip3 install -U polyaxon-helper
```


## Install polyaxon

Please check [polyaxon installation guide](https://docs.polyaxon.com/installation/introduction)

## Install in polyaxonfile

If you want to delegate the installation to polyaxon during the build process,
add a new step to the `run` section in your polyaxonfile:

```yaml
...
build:
  image: ...
  build_steps:
    - ...
    - pip install -U polyaxon-helper
    - ...

run:
  cmd: ...
```

## Usage

### Getting env variables defined by Polyaxon

```python
from polyaxon_helper import (
    get_cluster_def,
    get_declarations,
    get_experiment_info,
    get_task_info,
    get_tf_config,
    get_job_info,
    get_outputs_path,
    get_outputs_refs_paths,
    get_data_paths,
    get_log_level
)

cluster_def = get_cluster_def()
declarations = get_declarations()
experiment_info = get_experiment_info()
task_info = get_task_info()
job_info = get_job_info()
outputs_path = get_outputs_path()
outputs_refs_paths = get_outputs_refs_paths()
data_paths = get_data_paths()
tf_config = get_tf_config()
log_level = get_log_level()
```

 * `get_cluster_def`: Returns cluster definition created by polyaxon.
    ```json
    {
        "master": ["plxjob-master0-8eefb7a1146f476ca66e3bee9b88c1de:2000"],
        "worker": ["plxjob-worker1-8eefb7a1146f476ca66e3bee9b88c1de:2000",
                   "plxjob-worker2-8eefb7a1146f476ca66e3bee9b88c1de:2000"],
        "ps": ["plxjob-ps3-8eefb7a1146f476ca66e3bee9b88c1de:2000"],
    }
    ```
 * `get_declarations`: Returns all the experiment declarations based on both,

    * declarations section
    * matrix section

 * `get_tf_config`: Returns the TF_CONFIG defining the cluster and the current task.
   if `envvar` is not null, it will set and env variable with `envvar`.

 * `get_experiment_info`: Returns information about the experiment.

    * project_name
    * experiment_group_name
    * experiment_name
    * project_uuid
    * experiment_group_uuid
    * experiment_uuid

 * `get_job_info`: Returns information about the job.

    * project_name
    * job_name
    * project_uuid
    * job_uuid

 * `get_task_info`: Returns the task info: `{"type": str, "index": int}`.

 * `outputs_path`: The outputs path generated by polyaxon based on the hierarchy of the experiment.

        `user/project/group/experiment/files`

 * `data_paths`: The data paths mounted for the job/experiment:

        {
          'data1': '/data/1',
          'data-foo': '/data/foo',
        }

 * `outputs_path`: The references outputs paths requested by the user,
    the order follows the order specified by the user:

        {
            'experiments': [
                `user/project/job12/files`,
            ], 'experiments': [
                `user/project/group/experiment1/files`,
                `user/project/experiment100/files`
            ]
        }

 * `get_log_level`: If set on the polyaxonfile it will return the log level.


### Reporting metrics to Polyaxon

In order to report metrics for an experiment, just add these lines in you program.

```python
from polyaxon_helper import send_metrics

send_metrics(accuracy=0.9, precision=0.95)
```

## Quick start

Please check our [quick start guide](https://docs.polyaxon.com/quick_start) to start training your first experiment.


## License

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