semvec/pypi-packages huggingface dataset:
litho1pt0 1.5.0
Python interface to Litho 1.0 dataset - based on stripy

# Litho1pt0


`litho1pt0` is a python interface to the _crust 1.0_ dataset and the lithospheric part of the _litho 1.0_ dataset (Laske et al, 2013 and Pasyanos et al, 2014) which both requires and demonstrates the triangulation / searching and interpolation on the sphere that is provided by `stripy`.


## Navigation / Notebooks



```bash
   python -c 'import litho1pt0; litho1pt0.documentation.install_documentation(path="Notebooks")'
```

The first three notebooks are an introduction to `litho1pt0` 
the next two worked examples show how to search, interpolate and plot with the help of `stripy` routines.
`stripy is a dependency`

  - [Ex1-Litho1Layers.ipynb](litho1pt0-src/litho1pt0/Notebooks/litho1pt0/Ex1-Litho1Layers.ipynb)
  - [Ex2-Litho1Properties.ipynb](litho1pt0-src/litho1pt0/Notebooks/litho1pt0/Ex2-Litho1Properties.ipynb)
  - [Ex3-CrustalRegionalisation.ipynb](litho1pt0-src/litho1pt0/Notebooks/litho1pt0/Ex3-CrustalRegionalisation.ipynb)
  - [WorkEx1-CratonAverageProperties.ipynb](litho1pt0-src/litho1pt0/Notebooks/litho1pt0/WorkEx1-CratonAverageProperties.ipynb)
  - [WorkEx2-OceanDepthAge.ipynb](litho1pt0-src/litho1pt0/Notebooks/litho1pt0/WorkEx2-OceanDepthAge.ipynb)


## Installation

### Dependencies

You will need **Python 3.5 or greater**.
Also, the following packages are required:

 - [`stripy`]()
 - [`gfortran`](https://www.fatiando.org/verde/latest/install.html) (or any Fortran compiler)
 - [`numpy`](http://numpy.org)

### Installing using pip

You can install `litho1pt0` and the `stripy` dependency using the
[`pip package manager`](https://pypi.org/project/pip/):

```bash
pip install [--user] litho1pt0 stripy
```

The dependencies will be automatically installed by `pip`, except for `gfortran`
(or any Fortran compiler). It must be installed in your system before installing
`stripy` with `pip`.

### Documentation

Automatically populated to [underworldcode.github.io/litho1pt0](https://underworldcode.github.io/litho1pt0)
kodexa-platform 2.0.13
Kodexa Platform

# Kodexa Deployer

[![Build Status](https://dev.azure.com/kodexa/Dharma/_apis/build/status/kodexa-ai.kodexa?branchName=master)](https://dev.azure.com/kodexa/Dharma/_build/latest?definitionId=36&branchName=master)
[![Slack](https://slack.kodexa.com/badge.svg?version)](https://slack.kodexa.com/)


The Kodexa Deployer is used when you want to deploy a local pipeline to an instance of the Kodexa Platform.

## Documentation & Examples

For more information on how to use Kodexa Deployer see https://developer.kodexa.com/

## Set-up

Ensure you have Anaconda 3 or greater installed, then run:

    conda env create -f environment.yml 
    
Activate the conda environment with the command:

    conda activate kodexa
    pip install -r requirements.txt

## License

GPL v3.0
python-aliyun-api-gateway 0.0.2
aliyun api gateway
Keywords: command,line,tool

阿里云网关API-Python包使用规范
-------------------------------------------------


::

    from aliyun.api.gateway.sdk import client
    from aliyun.api.gateway.sdk.http import request
    from aliyun.api.gateway.sdk.common import constant

    host = "http://xxxx"
    url = "/api/vrp/express/areas"

    cli = client.DefaultClient(app_key="key", app_secret="secret")

    req_post = request.Request(host=host, protocol=constant.HTTP, url=url, method="GET", time_out=30000)

    data = cli.execute(req_post)

    print(data)