semvec/pypi-packages huggingface dataset:
meteo-utils 2.1.3
Python methods for the automatic download and processing of ECMWF data relevant for evapotranspiration modelling.
Requires Python: >=3.6
Keywords: SEN-ET, Evapotranspiration, Landsat, Sentinel-3, SLSTR, Copernicus, ERA5, CAMS, ECMWF, Remote Sensing

# Meteo Utils
This Python repository contains methods that allow the automatic download and processing of ECMWF data relevant for evapotranspiration modelling.

## Installation
With `conda`, you can create a complete environment with all the required librarie typing
```
conda env create -f environment.yml
```
or update a current environment:
```
conda env update -n <environment> -f environment.yml
```

## Requirements
### Registration at the Copernicus climate and atmoshperic data stores
This plugin allows the automatic download and preprocessing of ERA5 meteorological data, provided by ECMWF.
In order to properly work you should first register to get an ECWMF account [here](https://accounts.ecmwf.int/auth/realms/ecmwf/login-actions/registration?client_id=cds&tab_id=uP8OQT6ER-E).
Once registered, follow the next steps to configure the credentials for the processor:

1. Go to your *HOME* or *user* folder. 
  > In Linux/MacOS this folder is at `/home/your_user_name`. In windows it is usually at `C:\Users\your_user_name`.

2. Login to the [Climate Data Store](https://cds.climate.copernicus.eu/) with your ECMWF username and password, 
then type the next URL address [https://cds.climate.copernicus.eu/how-to-api](https://cds.climate.copernicus.eu/how-to-api)

3. Create a blank ASCII file in your *HOME* folder named `.cdsapirc` (please note the dot `.` at the beginning of the string),
and paste the two lines that appear in the black box of the webpage.

![](./figures/cds_key.png)

  > These two lines have the following format:
  ```
  url: https://cds.climate.copernicus.eu/api
  key: UID:API-KEY
  ```
  where *UID* and *API-KEY* are your Copernicus Climate Data Store credentials.

4. Login to the [Atmospheric Data Store](https://ads.atmosphere.copernicus.eu/) with your ECMWF username and password, 
then type the next URL address [https://ads.atmosphere.copernicus.eu/how-to-api](https://ads.atmosphere.copernicus.eu/how-to-api)

5. Create a blank ASCII file in your *HOME* folder named `.adsapirc` (please note the dot `.` at the beginning of the string),
and paste the two lines that appear in the black box of the webpage.

  > These two lines have the following format:
  ```
   url: https://ads.atmosphere.copernicus.eu/api
   key: UID:API-KEY
  ```
  where *UID* and *API-KEY* are your Copernicus Atmospheric Climate Data Store credentials.

## Usage
An example for using the package can be found in the script `process_era5.py`
maxframe 2.5.0
MaxFrame operator-based data analyze framework

MaxCompute MaxFrame Client
==========================

MaxFrame is a computational framework created by Alibaba Cloud to
provide a way for Python developers to parallelize their code with
MaxCompute. It creates a runnable computation graph locally, submits it
to MaxCompute to execute and obtains results from MaxCompute.

MaxFrame client is the client of MaxFrame. Currently it provides a
DataFrame-based SDK with compatible APIs for pandas. In future, other
common Python libraries like numpy and scikit-learn will be added as
well. Python 3.7 is recommended for MaxFrame client to enable all
functionalities while supports for higher Python versions are on the
way.

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

You may install MaxFrame client through PIP:

.. code:: bash

   pip install maxframe

Latest beta version can be installed with ``--pre`` argument:

.. code:: bash

   pip install --pre maxframe

You can also install MaxFrame client from source code:

.. code:: bash

   pip install git+https://github.com/aliyun/alibabacloud-odps-maxframe-client.git

Getting started
---------------

We show a simple code example of MaxFrame client which read data from a
MaxCompute table, performs some simple data transform and writes back
into MaxCompute.

.. code:: python

   import maxframe.dataframe as md
   import os
   from maxframe import new_session
   from odps import ODPS

   o = ODPS(
       os.getenv('ALIBABA_CLOUD_ACCESS_KEY_ID'),
       os.getenv('ALIBABA_CLOUD_ACCESS_KEY_SECRET'),
       project='your-default-project',
       endpoint='your-end-point',
   )
   session = new_session(o)

   df = md.read_odps_table("source_table")
   df["A"] = "prefix_" + df["A"]
   md.to_odps_table(df, "prefix_source_table")

Documentation
-------------

Detailed documentations can be found
`here <https://maxframe.readthedocs.io>`__.

License
-------

Licensed under the `Apache License
2.0 <https://www.apache.org/licenses/LICENSE-2.0.html>`__.