semvec/pypi-packages huggingface dataset:
hestia 0.6.0
Polyaxon common utilities.
License: MIT
Keywords: polyaxon,django

[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](LICENSE)
[![Build Status](https://travis-ci.com/polyaxon/hestia.svg?branch=master)](https://travis-ci.com/polyaxon/hestia)
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# hestia

Polyaxon common utilities.

## Installation

```
pip install -U hestia
```

# License

[![FOSSA Status](https://app.fossa.io/api/projects/git%2Bgithub.com%2Fpolyaxon%2Frhea.svg?type=large)](https://app.fossa.io/projects/git%2Bgithub.com%2Fpolyaxon%2Frhea?ref=badge_large)
pyperaptor 0.1.3.1
Easy multithreading pipeline with Python 3
License: MIT
Keywords: pipeline,dinossaurs,threading

PypeRaptor is a library that provides a functional pipeline structure.
    Each execution from the pipeline takes an input item from beginning to end and return the result.
    The Pipeline may be modified by add operator and expects a Node.
    To execute a Pipeline for a single item, user can execute **push** function with item. This execution will pushes the input
    through the pipeline calling every function in the way.
    To execute several items, user can set an Iterable in **process** function.

    A generator can be part of the pipeline, and is recommended to be the first item to when using Pipeline in parallel mode.
    When in parallel mode, PypeRaptor provides a Device as in a way to reserve resources and avoid racing conditions among its threads.

    For examples go to:
    http://github.com/fsan/pyperaptor
v-log 1.0.0
Colored log that also stores a properly formated csv.
License: MIT

# Log
[![Build Status](https://travis-ci.com/villoro/v-log.svg?branch=master)](https://travis-ci.com/villoro/v-log)
[![codecov](https://codecov.io/gh/villoro/v-log/branch/master/graph/badge.svg)](https://codecov.io/gh/villoro/v-log)

Colored log that also stores a properly formated `csv`.

## Installation

You can install it with pip by running:

    pip install v-log

## Usage

It works very similar to the regular `logging` library:

```python
from v_log import VLogger
log = VLogger()

log.critical("critical")
log.error("error")
log.warning("warning")
log.info("info")
log.debug("debug")
```

It can also show execution times and errors:
```python
# Show time
log.info("Test time", time=10)

# Show error
try:
    1 / 0
except Exception as e:
    log.error("Try errors", error=e)
    log.error("Try errors %s", "full", time=10, error=e)
```

This will output the following:

![screnshot](images/screnshot.png)

## Customization

When creating the `VLogger` instance you can define:

| param             | description                                        | default      |
|-------------------|----------------------------------------------------|--------------|
| module_name       | name of the module                                 | "base"       |
| uri_log           | uri of the file where log will be stored           | "log.csv"    |
| file_log_level    | minimum level of log events in order to be writed  | logging.INFO |
| console_log_level | minimum level of log events in order to be printed | logging.INFO |
| csv_separator     | csv separator                                      | ";"          |
| base_path         | name of the root folder of the execution           | "src"        |

for example you could do:

```python
import logging
from v_log import VLogger
log = VLogger(__name__, uri_log="data/log.log", file_log_level=logging.WARNING)
```

## Authors
* [Arnau Villoro](https://villoro.com)

## License
The content of this repository is licensed under a [MIT](https://opensource.org/licenses/MIT).

## Nomenclature
Branches and commits use some prefixes to keep everything better organized.

### Branches
* **f/:** features
* **r/:** releases
* **h/:** hotfixs

### Commits
* **[NEW]** new features
* **[FIX]** fixes
* **[REF]** refactors
* **[PYL]** [pylint](https://www.pylint.org/) improvements
* **[TST]** tests
ocular 0.1.7
A tool for observing Kubernetes pods' statuses in real time.
License: MIT
Keywords: polyaxon,aws,azure,google cloud storage,k8s,kubernetes,docker

[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](LICENSE)
[![Build Status](https://travis-ci.com/polyaxon/ocular.svg?branch=master)](https://travis-ci.com/polyaxon/ocular)
[![PyPI version](https://badge.fury.io/py/ocular.svg)](https://badge.fury.io/py/ocular)
[![Codacy Badge](https://api.codacy.com/project/badge/Grade/a33947d729f94f5da7f7390dfeef7f94)](https://www.codacy.com/app/polyaxon/ocular?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=polyaxon/ocular&amp;utm_campaign=Badge_Grade)
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# ocular
A tool for observing Kubernetes pods' statuses in real time.

## Description

Often times it's very hard to translate a Kubernetes event to a concrete state, 
and that's the gap that ocular tries fill, i.e. return one of the following statuses:

```
created
building
unschedulable
scheduled
running
succeeded
failed
stopped
unknown
``` 

ocular returns as well a condensed information about the reason of that status.

## Install

```bash
$ pip install -U ocular
```

## Usage

```python
import ocular
from kubernetes import client

api_client = client.api_client.ApiClient(configuration=...)

for pod_state in ocular.monitor(api_client, 
                                namespace='polyaxon', 
                                container_names=('polyaxon-experiment-job',), 
                                label_selector='app in (workers,dashboard),type=runner'):
    print(pod_state)
```

Results

```
...
>> {'status': 'unknown', 'message': 'Unknown pod conditions', 'details': {'event_type': 'ADDED', 'labels': ...
>> {'status': 'building', 'message': None, 'details': {'event_type': 'MODIFIED', 'labels': ...
>> {'status': 'building', 'message': 'PodInitializing', 'details': {'event_type': 'MODIFIED', 'labels': ...
>> {'status': 'building', 'message': 'PodInitializing', 'details': {'event_type': 'MODIFIED', 'labels': ...
>> {'status': 'running', 'message': None, 'details': {'event_type': 'MODIFIED', 'labels': ...
>> {'status': 'running', 'message': None, 'details': {'event_type': 'MODIFIED', 'labels': ...
>> {'status': 'succeeded', 'message': None, 'details': {'event_type': 'MODIFIED', 'labels': ...
...
```


## License

[![FOSSA Status](https://app.fossa.io/api/projects/git%2Bgithub.com%2Fpolyaxon%2Focular.svg?type=large)](https://app.fossa.io/projects/git%2Bgithub.com%2Fpolyaxon%2Focular?ref=badge_large)
polyaxon-dockerizer 0.1.0
Python dockerizer to generate and build docker images.
License: MIT
Keywords: polyaxon,docker,deep-learning,machine-learning,data-science,neural-networks,artificial-intelligence,ai,reinforcement-learning,kubernetes

[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](LICENSE)
[![Build Status](https://travis-ci.com/polyaxon/polyaxon-dockerizer.svg?branch=master)](https://travis-ci.com/polyaxon/polyaxon-dockerizer)
[![PyPI version](https://badge.fury.io/py/polyaxon-dockerizer.svg)](https://badge.fury.io/py/polyaxon-dockerizer)
[![Codacy Badge](https://api.codacy.com/project/badge/Grade/a33947d729f94f5da7f7390dfeef7f94)](https://www.codacy.com/app/polyaxon/polyaxon-dockerizer?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=polyaxon/polyaxon-dockerizer&amp;utm_campaign=Badge_Grade)
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# polyaxon-dockerizer

Python tool to generate dockerfiles compatible with Polyaxon dockerizer and Polyaxon CLI local run.


## Install

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

## Usage

### Generate Dockerfiles

```python
from polyaxon_dockerizer import generate

generate(repo_path,
         from_image,
         build_steps=['apt-get install git', 'pip install tensorflow'],
         env_vars=[['ENV_VAR1', 'VALUE1'], ['ENV_VAR2', 'VALUE2']],
         nvidia_bin=None,
         lang_env='en_US.UTF-8',
         uid=2222,
         gid=2222)
```

### Build images

```python
from polyaxon_dockerizer import build

build(build_context,
      image_tag,
      image_name,
      nocache,
      credstore_env=None,
      registries=None)
```


### Build & Push images

```python
from polyaxon_dockerizer import build_and_push

build_and_push(build_context,
               image_tag,
               image_name,
               nocache,
               credstore_env=None,
               registries=None)
```


## Install polyaxon

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


## Quick start

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