semvec/pypi-packages huggingface dataset:
outlooktools 0.1.1
Windows CLI to automate Outlook tasks
Requires Python: >=3.7

# OutlookTools

[![PyPI - Version](https://img.shields.io/pypi/v/outlooktools.svg)](https://pypi.org/project/outlooktools)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/outlooktools.svg)](https://pypi.org/project/outlooktools)

-----

**Table of Contents**

- [Installation](#installation)
- [License](#license)

## Installation

```console
pip install outlooktools
```

## License

`outlooktools` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.

# OutlookTools
 Windows CLI tool to automate some Outlook activities.

 Works via MAPI interface to the user's Outlook session.

 Only works on Windows systems

 Current functions:
 - List mailboxes
 - List folders
 - Save all attachments found in a given folder to a given location
 - Send a plain text email (as the current user) with an attachment as desired.

 When installed should put a "OutlookTools.exe" on your path so can run from the command line

 The MAPI interface can do A LOT.  Basically anything you can do with VBA as described [here:](https://learn.microsoft.com/en-us/office/vba/api/overview/outlook)
 
 Have fun extending
datura 1.0.5
A small pure Python data visualization package

<div align="center">
  <img src="https://raw.githubusercontent.com/ptweir/datura/main/images/datura_196.png"><br>
</div>

# Datura

A simple pure Python data visualization package.

[Documentation](https://datura.readthedocs.io)

[Code](https://github.com/ptweir/datura)
lbaf 1.0.1
Analysis framework for exploring, testing, and comparing load balancing strategies
Requires Python: <=3.10,>=3.8
Keywords: HPC,concurrency,distributed-computing,parallelism,load-balancing

LBAF: Load Balancing Analysis Framework
=======================================

This package provides Python Analysis framework for exploring, testing, and comparing load balancing strategies (website_).

.. _website: https://github.com/DARMA-tasking/LB-analysis-framework


Install
-------

You will need a compatible python interpreter and then just:

.. code-block:: bash

  pip install lbaf
flowsom-clustering 0.0.7
A Python implementation of FlowSOM algorithm with parallelized consensus metaclustering
Requires Python: >=3.7

# FlowSOM

Python implementation of the FlowSOM algorithm based on [minisom](https://github.com/JustGlowing/minisom) and [ConsensusClustering](https://github.com/ZigaSajovic/Consensus_Clustering).

The main advantage over the current implementations is the parallelized nature of the ConsensusClustering.

## Installation

```
    pip install flowsom-clustering

```

## Basic usage:

```python
import numpy as np
import pandas as pd
from FlowSOM import flowsom

# import your data via pandas or numpy

data = pd.DataFrame(data = np.random.rand(250,10),
                    columns = [str(i) for i in range(10)])

cluster_annotations = flowsom(data = data, # input data array
                              x_dim = 50, # x dimension of the self organized map
                              y_dim = 50, # y dimension of the self organized map
                              sigma = 1, # spread of the neighborhood function
                              learning_rate = 0.5, # initial learning rate
                              n_iterations = 100, # trains the map for 100 iterations
                              neighborhood_function = "gaussian", # defines the neighborhood function
                              consensus_cluster_algorithm = "AgglomerativeClustering", # runs Consensus Clustering with Agglomerative Clustering
                              consensus_cluster_min_n = 10, # minimum n_clusters to check for optimal clustering
                              consensus_cluster_max_n = 50, # maximum n_clusters to check for optimal clustering
                              consensus_cluster_resample_proportion = 0.5, # resample proportion for the consensus finding
                              consensus_cluster_n_resamples = 10, # number of resamples for consensus clustering
                              verbose = False, # whether to be verbose
                              n_jobs = None, # number of joblib.Parallel threads
                              random_state = 187 # seed for reproducibility of the results
                              )

data["flowsom_consensus"] = cluster_annotations

```
gradio-foliumtest 0.0.2
Python library for easily interacting with trained machine learning models
Requires Python: >=3.8
Keywords: gradio,gradio custom component,gradio-template-Fallback,machine learning,reproducibility,visualization


# gradio_foliumtest

Create a map with folium and display it on the web with Gradio! 

## Example usage

```python
import gradio as gr
from gradio_foliumtest import FoliumTest
from typing import Literal
from folium import Map


LAT_LONG_MAP = {
    "New York City": (40.7128, -74.0060),
    "London": (51.5074, -0.1278),
    "San Francisco": (37.7749, -122.4194),
    "Tokyo": (35.6762, 139.6503),
    "Miami": (25.7617, -80.1918),
}

def get_city(city: Literal["New York City", "London", "San Francisco", "Tokyo", "Miami"]):
    city = city or "Miami"
    return Map(location=LAT_LONG_MAP[city], zoom_start=12)

with gr.Blocks() as demo:
    with gr.Row():
        with gr.Column():
            city = gr.Radio(choices=["New York City", "London", "San Francisco", "Tokyo", "Miami"],
                            label="City")
        with gr.Column():
            map_ = FoliumTest(label="Foo")
        city.change(get_city, city, map_)

demo.launch()
```
szh_toolbox 0.0.18
我自己的工具箱
Requires Python: >=3.7

# 写在前面
我自己写的工具箱，没有api文档的，想看函数功能就直接看函数定义时的注释吧，还挺详细的
# python代码功能
```python
# 示例1，读取WRF变量计算天顶角
from szh_toolbox import get_zenith_angle
WRFfile = 'wrfout_d01_2021-07-22_04:00:00'
Longitude = getwrfvar(WRFfile, 'XLONG')
Latitude = getwrfvar(WRFfile, 'XLAT')
z2 = get_zenith_angle(123,0,35786,Longitude, Latitude)
```
```python
# 示例2，实现namelist文件和python对象的相互转化
import szh_toolbox.namelist as nl
# config是python字典对象
config = nl.load("data/namelist.input")
print(nl.dump(config))
```
```python
# 示例3，实现shell脚本中变量定义赋值的替换
from szh_toolbox import ShellScriptVariable
# 类功能展示
ssv = ShellScriptVariable('data/myshell.sh')
ssv.show()
ssv.update('a', '这是A', 0)
ssv.update('d', '"这是 D"')
ssv.show()
ssv.save('data/myshell2.sh')
# 一行代码替换变量
ShellScriptVariable.modify('data/myshell.sh', 'a', '这是A', 'data/myshell3.sh')
```
# 命令行工具
也就是可以直接在命令行里执行的代码
```bash
# 直接打印namelist.wps文件定义的区域的范围
st-wps
st-wps namelist.wps
```
```bash
# 下载noaa的数据比如ATMS L1
st-noaa -h
st-noaa orderId -o savepath
```
djangocms-filer-display-pages-where-files-are-used-before-removing-them 0.3.0
Show locations of images & other files before deleting them.

Name of the module is self-explanatory.

Lists all CMS pages that contain a plugin linked to the file you are trying to delete.

----

## Install

* Install the package
   ```bash
   python3 -m pip install djangocms-filer-display-pages-where-files-are-used-before-removing-them
   ```

* Add it ***just before `filer`*** in your `INSTALLED_APPS`:
   ```python
       'djangocms_filer_display_pages_where_files_are_used_before_removing_them',
    ```

* ![that's all folks!](https://gitlab.com/kapt/open-source/djangocms-filer-display-pages-where-files-are-used-before-removing-them/uploads/ce92945bf31ba742cbe1de93ead4b503/image.png)

----

## Old screenshots/video, the current look has slightly changed

| Remove multiple files | Remove folder | Video |
| ---- | ---- | ---- |
| [![1](https://gitlab.com/kapt/open-source/djangocms-filer-display-pages-where-files-are-used-before-removing-them/uploads/eb52070954358881bc73b0bc51fa9b11/image.png)](https://gitlab.com/kapt/open-source/djangocms-filer-display-pages-where-files-are-used-before-removing-them/uploads/cae9ab7299f5eb9d0e93cb446e06bb7f/image.png) | [![2](https://gitlab.com/kapt/open-source/djangocms-filer-display-pages-where-files-are-used-before-removing-them/uploads/ca576f3d4de9ba63b8f9268c052baefe/image.png)](https://gitlab.com/kapt/open-source/djangocms-filer-display-pages-where-files-are-used-before-removing-them/uploads/0bd2e1cf2d850336a0e04f9aa3744700/image.png) | ![django-filer-this-module-name-is-too-long-damn](https://gitlab.com/kapt/open-source/djangocms-filer-display-pages-where-files-are-used-before-removing-them/uploads/e5cbf76772455532df6f49a5bc97ee72/django-filer-this-module-name-is-too-long-damn.webm)