semvec/pypi-packages huggingface dataset:
snimar-pycsw 2.1.2
pycsw implementation for the SNIMar project
License: MIT

snimar_pycsw README
===================

snimar_pycsw is a fork of the original pycsw application. This piece of software was developed
with the requirements of the SNIMar project in mind and, as such, shall not be used outside the
local catalogue environment of the SNIMar network.

Below is a copy of the original pycsw README.
---------------------------------------------

pycsw is an OGC CSW server implementation written in Python.

pycsw fully implements the OpenGIS Catalogue Service Implementation Specification (Catalogue Service for the Web). Initial development started in 2010 (more formally announced in 2011). The project is certified OGC Compliant, and is an OGC Reference Implementation.  Since 2015, pycsw is an official OSGeo Project.

pycsw allows for the publishing and discovery of geospatial metadata via numerous APIs (CSW 2/CSW 3, OpenSearch, OAI-PMH, SRU). Existing repositories of geospatial metadata can also be exposed, providing a standards-based metadata and catalogue component of spatial data infrastructures.

pycsw is Open Source, released under an MIT license, and runs on all major platforms (Windows, Linux, Mac OS X).

Please read the docs at http://pycsw.org/docs for more information.
shared-ndarray 1.1.1
A pickleable wrapper for sharing NumPy ndarrays between processes using POSIX shared memory.
License: MIT
Keywords: numpy ndarray array shared memory shm

shared\_ndarray
===============

A pickleable wrapper for sharing NumPy ndarrays between processes using POSIX
shared memory.

SharedNDArrays are designed to be sent over multiprocessing.Pipe and Queue
without serializing or transmitting the underlying ndarray or buffer. While the
associated file descriptor is closed when the SharedNDArray is garbage
collected, the underlying buffer is not released when the process ends: you
must manually call the ``unlink()`` method from the last process to use it.

Usage
-----

.. code:: python

    from __future__ import print_function

    import multiprocessing as mp

    import numpy as np
    from shared_ndarray import SharedNDArray

    try:
        shm = SharedNDArray((4, 4))
        shm.array[0, 0] = 1
        p = mp.Process(target=lambda shm: print(shm.array), args=(shm,))
        p.start()
        p.join()
    finally:
        shm.unlink()

This should print::

    [[ 1.  0.  0.  0.]
     [ 0.  0.  0.  0.]
     [ 0.  0.  0.  0.]
     [ 0.  0.  0.  0.]]

There are also convenience methods to create a new SharedNDArray from an
existing NumPy array:

.. code:: python

    arr = np.array([0, 0])
    shm1 = SharedNDArray.copy(arr)
    shm2 = SharedNDArray.zeros_like(arr)
    shm1.unlink()
    shm2.unlink()

Dependencies
------------

- `numpy <http://www.numpy.org>`_
- `posix_ipc <http://semanchuk.com/philip/posix_ipc/>`_
fabrik 3.3.0
A simple to use deployment toolkit built on top of Fabric
License: MIT

[![Build Status](https://travis-ci.org/Frojd/Fabrik.svg?branch=master)](https://travis-ci.org/Frojd/Fabrik)
[![PyPI version](https://badge.fury.io/py/fabrik.svg)](http://badge.fury.io/py/fabrik)

![Fabrik](https://raw.githubusercontent.com/frojd/fabrik/develop/img/frojd-fabrik.png)

# Fabrik

A deployment toolkit built on top of Fabric.

The purpose of this library is to provide a stable python based deploy tool that covers a wide range a use cases,
Those cases include Wordpress, Node.js and Django. We favor composition and customization by code before configuration.

## Supports

- Git
- Rollbacks
- A full Django deploy script with migrations
- ClI for scaffolding
- Virtualenv creation and activation
- NPM management
- Nginx
- Uwsgi
- Forever
- Envfile handling
- Celeryd
- Wordpress with bedrock
- Composer
- Scp


## Requirements

To install Fabrik you need Python 2.7, virtualenv and pip.


## Installation

Fabrik can be installed through pip.

### Stable

`pip install fabrik`

### "Unstable"

- `pip install git+git://github.com/Frojd/Fabrik.git@develop`

### For development

- `git clone git@github.com:Frojd/Fabrik.git`
- `virtualenv venv`
- `source venv/bin/activate`
- `pip install --editable .`


## Quickstart

To create setup deployment for django, run the following:
`fabrik_start --stages=stage,prod --recipe=django`

This command will create the following files.

```
/fabfile.py
/stages/
    __init__.py
    stage.py
    prod.py
```

This script will create the necessary files and add git repro setting (if present) and recipe import. Once generated, you'll need to add SSH settings and recipe unique settings by editing the files.


## Quickstart

To create setup deployment for django, run the following:
`fabrik_start --stages=stage,prod --recipe=django`

This command will create the following files.

```
/fabfile.py
/stages/
    __init__.py
    stage.py
    prod.py
```

This script will create the necessary files and add git repro setting (if present) and recipe import. Once generated, you'll need to add SSH settings and recipe unique settings by editing the files.


## Examples

This project ships with examples for Django and Wordpress (just check `examples/*`)


## Tests

Tests can be run with `python runtests.py`, this will run the entire suite. Just make sure you run `pip install -r requirements/tests.txt` first.

It also possible to run a specific case:  `python runtests.py tests.test_api.TestApi`

... or a specific unittest:
`test_deploy_rollback python runtests.py tests.test_api.TestApi.test_deploy_rollback`

### Writing tests

All tests should reside in the `tests` directory and prefixed `test_*`, to include a test in the main suite add the test path in `runtests.py`.


## Documentation

The documentation can be found [here](documentation/README.md).


## Contributing

Want to contribute? Awesome. Just send a pull request.


## License

Fabrik is released under the [MIT License](http://www.opensource.org/licenses/MIT).