semvec/pypi-packages huggingface dataset:
circe-client-CERTIC 0.0.7
Circe client library
Requires Python: >=3.6

# Circe Python Client Library

This is a client library for the [Circe server](https://git.unicaen.fr/pdn-certic/circe).

## Requirements

The Circe Python client library has been tested with Python versions 3.6 and above.

## Quickstart

### Install

Within a virtual environment:

    pip install circe-client-CERTIC

### Configuration

You may provide the configuration as constructor arguments for the client class as well as 
environment variables:

- CIRCE_ENDPOINT: URL of Circe server
- CIRCE_SECRET: secret key provided by the server
- CIRCE_APP_UUID: id of current client app

### Basic usage

    from circe_client import Client
    
    client = Client(api_endpoint="http://localhost:8000/", secret_key="test", application_uuid="test")
    job = client.new_job()
    job.add_file("mydocument.docx")
    job.add_transformation("mytransformation_id")
    client.send(job, wait=True)
    for file_name, file_pointer in job.result.files:
        pass  # do something with result files
lumpyrem 0.1.3
This package reads, writes and runs LUMPREM2 and associated utility programs
Requires Python: >=3.6

# Lumpyrem
Python package to interact with the LUMPREM software suite. Lumpyrem is very much a work in progress. User beware.

If you find a bug or think the software is not working as intended, please [submit an issue](https://github.com/rhugman/lumpyrem/issues).

### Contributors 
Rui Hugman https://github.com/rhugman<br>
Kevin Hayley https://github.com/khayley<br>

[![DOI](https://zenodo.org/badge/294125928.svg)](https://zenodo.org/badge/latestdoi/294125928)

# Introduction
Lumpyrem is a Python package that facilitates interaction with the [LUMPREM lumped-parameter recharge model](https://s3.amazonaws.com/docs.pesthomepage.org/software/lumprem.zip) and its ancillary programs that assist in setup, and provide a linkage between LUMPREM and MODFLOW 6.
It is intended to make setting up and running LUMPREM models easier, in particular if integrated into [Flopy](https://github.com/modflowpy/flopy) workflows. 

LUMPREM requires daily inputs of rainfall and potential ET. Nonlinear relationships based on stored soil moisture are used to calculate recharge, runoff and actual ET. The parameters which govern these relationships can be adjusted by PEST. Numerous quantities of interest are recorded on LUMPREM’s output file. These include residual daily ET (which can be reformatted for input to the EVT package of MODFLOW), irrigation demand, and boundary condition head. The latter is calculated using a parameterizable, nonlinear relationship between head and stored soil moisture. Heads calculated in this way can be assigned to MODFLOW boundary conditions after appropriate re-formatting.

# Installation
Lumpyrem requires LUMPREM, LUMPREP and LR2SERIES. Executables can be downloaded from the [PESTHomepage.org](https://pesthomepage.org/software-0). It is recomended these be placed in a folder in the environment path on your local machine. Alternatively, the executables may be placed within the workspace folder.

You can install Lumpyem from PyPi:
   
    pip install lumpyrem
   
Installing from the git-hub repository is recommended; the PyPi version lags behind updates in the git-repo.


# Documentation
Documentation is a work in progress. [Jupyter Notebooks are provided with simple examples of code functionality](https://github.com/rhugman/lumpyrem/tree/master/examples). 

LUMPREM and utilities are extensively documented by their developer.

# To do
* deploy documentation to readthedocs
* utility to read lumprem output and convert to Feflow timeseries/.pow files
* utility to write PEST template files **DONE**
* make OS independent

# Funding
Development of Lumpyrem has been supported in part by the Groundwater Modelling Decision Support Initiative (GMDSI). https://gmdsi.org/
wakamaro 0.0.4
A package for visualizing the number of waka poetry composed by poets in Nijuichidaishu
Requires Python: >=3.8

# wakamaro

## Abstract
wakamaro is a package for visualizing the number of waka poetry composed by poets in Nijuichidaishu (21 waka poetry anthologies)

Using a Nijuichidaishu dataset, Visualize the number of waka poetry per waka poet.

The Nijuichidaishu dataset is downloadable from:
http://codh.rois.ac.jp/pmjt/


## Overview of Data
- the Center for Open Data in the Humanities
- “The Dataset of Pre-Modern Japanese Text (the National Institute of Japanese Literature)
- http://codh.rois.ac.jp/index.html.en

Link to download data
- http://codh.rois.ac.jp/pmjt/package/text.zip


## How to run wakamaro
$ pip install wakamaro


## How to run wakamaro
$ wakamaro <number of Nijuichidaishu> <number of appearances>

The first argument: number of Nijuichidaishu (1 to 21)
The second argument: minimum number of appearances of the waka poets to be displayed

Example of Running: waka poets that appeared more than 5 times in kokin wakashu
$ wakamaro 1 5

<img src="https://drive.google.com/uc?export=view&id=1WIl8yS4Z3wwaJ7TlgTCwW34I4nQBtGXw" alt="result">

The vertical axis shows number of appearances in waka poetry.
The horizontal axis show appearance of waka poets in waka poetry.