semvec/pypi-packages huggingface dataset:
monitor-memory 0.0.2
Tools for working with container types, command data operations, and concise exception handling
License: MIT

Monitor Memory
==============

This package creates a command-line utility that will run a command
and also run a daemon monitoring memory use as the command runs. The
daemon uses the `ps` command to check memory use, so this will only
work on `UNIX`-like systems.

I've found this functionality to be particularly useful in batch
processing jobs that run in docker containers, because the output
of `ps aux` isolates only processes running in-container. So by
recording max memory use, you can track how large of containers you
need.


Usage::
  pip install monitor_memory
  monitor_memory <some command>

All arguments after the command are forwarded to the command, as is standard
input. So, for example, to run an arbitrary bash script you can use a
here-document::
  monitor_memory bash << \EOF_
  NAME="me"
  echo ${NAME}
  EOF_
djzen 17.12.5
Tools to streamline and simplify using Django.
License: MIT

Zen of Django
=============

Tools to streamline and simplify using Django.

Why the Zen of Django?
----------------------

| After teaching Django I found several aspects of the framework which
  could be
| streamlined and simplified to help those learning the framework. So I
  curated
| some best practices, pre-configured popular libraries, and simplified
  parts of
| Django. Both beginners and seasoned veterans can use Zen of Django to
  simplify
| and start faster. Each piece can be easily exchanged or removed once
  you out
| grow any of them.

Features
--------

-  **Production Ready Deployment:** Pre-built with
   `uWSGI <https://uwsgi-docs.readthedocs.io/en/latest/index.html>`__ or
   `Gunicorn <http://gunicorn.org/>`__ support for deployment. Both have
   become the high performance standard for Django deployments thus we
   baked it in by default.
-  **Production Ready Static File Serving:** Static file serving is
   configured out of the box using
   `WhiteNoise <http://whitenoise.evans.io/en/stable/>`__. WhiteNoise
   provides simple static file serving with performance in mind.
-  **Settings Management:** Settings are split into development and
   production. Debug is turned off in production by default. It is also
   easy to add more environments.
-  **SECRET\_KEY Management:** The secret key is setup using
   environmental variables so you don't commit it to your repository by
   accident. A dot env file is also added and ignored in git for added
   safety.
-  **Git Ignore Setup:** Adds your secrets and db.sqlite3 to your
   ``.gitingore`` automatically.

Installation
------------

``pipenv install djzen[uwsgi]``

or

``pipenv install djzen[gunicorn]``

Quick Start
-----------

::

    pipenv install djzen[uwsgi]
    djzen startproject <projectname>
    Install to:
      [1] Current directory (recommended)
      [2] testproj
    Directory? [1]: <enter>
    Setup .gitignore? [Y/n]: <enter>

    pipenv run python manage.py devserver
    # or 
    pipenv run python manage.py collectstatic
    pipenv run python manage.py prodserver

Usage
-----

Starting a ``djzen`` project
~~~~~~~~~~~~~~~~~~~~~~~~~~~~

``pipenv run djzen startproject [projectname] [directory]``

*directory is optional*

Development Server
~~~~~~~~~~~~~~~~~~

``pipenv run python manage.py devserver``

Does the same thing as
`runserver <https://docs.djangoproject.com/en/1.11/ref/django-admin/#runserver>`__
just gives you a better indication of which environment you're running.

Production Server
~~~~~~~~~~~~~~~~~

``pipenv run python manage.py prodserver``

Does the same thing as
`runuwsgi <http://django-uwsgi.readthedocs.io/en/master/command.html>`__
just gives you a better indication of which environment you're running.

Static Files
~~~~~~~~~~~~

Static files will be served automatically with the production server.
You only need to run the ``collectstatic`` command on deployment.

``pipenv run python manage.py collectstatic``

Secrets
~~~~~~~

Secrets are stored in ``.env`` which use the DotEnv format. Using pipenv
the values are loaded into environment automatically if a ``.env``
exists.
modulemd 1.3.3
A python library for manipulation of the proposed module metadata format.
License: MIT
Keywords: modularization modularity module metadata

Module metadata definitions and the modulemd library
====================================================

This repository contains simple module metadata template and the corresponding
library for the manipulation thereof.

`spec.yaml <https://pagure.io/modulemd/blob/master/f/spec.yaml>`_:
        This file serves two roles -- it is the input for tools generating the
        actual module (such as pungi-modularization) and it is also present in
        the resulting repository, available to its consumers (such as
        fm-metadata-service).  For practical reasons, it is written in YAML.
        See comments in the template for details.

modulemd:
        A python library for manipulation of the proposed module metadata format.
        API documentation is available at http://modulemd.readthedocs.org/.