semvec/pypi-packages huggingface dataset:
deathdaily 0.1.7
A package for predicting the number of daily deaths
Requires Python: >=3.8

# COVID-19 daily death prediction 
[![Open in Code Ocean](https://codeocean.com/codeocean-assets/badge/open-in-code-ocean.svg)](https://codeocean.com/capsule/3aa3e186-03f3-43b4-85d1-fe86f43bedd9/tree)

DOI: https://doi.org/10.24433/CO.1663204.v1

The paper was published:
Takefuji, Y. Deathdaily: A Python Package Index for predicting the number of daily COVID-19 deaths. Netw Model Anal Health Inform Bioinforma 11, 14 (2022). https://doi.org/10.1007/s13721-022-00359-1

Verification for computational reproducibility & quality is doned by codeocean:
https://codeocean.com/capsule/3aa3e186-03f3-43b4-85d1-fe86f43bedd9/tree

deathdaily is a Python program using new_deaths.csv for predicting daily deaths due to COVID-19 in the next seven days. The prediction is based on the Xthe degree polynomial curve-fitting.

According to PyPI Stats at https://pepy.tech/, deathdaily has been downloaded by 30105 times worldwide as of Feb.22, 2023, one of the most popular COVID-19 tools of its kind.

deathdaily takes three parameters: country, days, the xth degree of a polynomial.
Days shows the number of days used for calculating the curve-fiting function with xth
degree of a polynomial for curve-fitting function.

The maximum days range is available from Jan.22 2020 to the day you have downloaded in new_deaths.csv file. 

Y-axis depicts the number of daily deaths in the country.

# new_deaths.csv

deathdaily needs a new_deaths.csv file for predicting the daily deaths of the next seven days.

The new_deaths.csv file is automatically downloaded by deathdaily from the following site:

https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/jhu/new_deaths.csv


# How to install deathdaily

$ pip install deathdaily

or

$ pip install deathdaily --force-reinstall --no-cache-dir --no-binary :all:

# How to run deathdaily 

"country" shows which country you would like to predict the daily deaths of the next seven days.

"days" indicates how many days are used for Xth degree polynomial curve-fitting.

"degree" determines the degree of polynomial curve-fitting.

$ deathdaily Japan days degree

$ deathdaily Japan 200 11

country="Japan", days=200, degree=11

<img src="https://github.com/y-takefuji/covid-19_daily_death_prediction/raw/main/Japan.png" width=320 height=240 >


$ deathdaily 'United States' 200 11

<img src="https://github.com/y-takefuji/covid-19_daily_death_prediction/raw/main/United States.png" width=320 height=240 >

$ deathdaily Israel 200 9

<img src="https://github.com/y-takefuji/covid-19_daily_death_prediction/raw/main/Israel.png" width=320 height=240 >

$ deathdaily 'United Kingdom' 100 11

<img src="https://github.com/y-takefuji/covid-19_daily_death_prediction/raw/main/United Kingdom.png" width=320 height=240 >
mosqito 1.2.1
Modular Sound Quality Integrated Toolbox
Requires Python: >=3.5

<div align="center">
    <img src="https://raw.githubusercontent.com/Eomys/MoSQITo/master/logo.png">
</div>

## What is MOSQITO ?

The objective of MOSQITO is to provide a unified and modular development framework of key sound quality tools (including key SQ metrics), favoring reproducible science and efficient shared scripting among engineers, teachers and researchers community. The development roadmap of the project is presented in more details in the Scope of the project.

It is written in Python, one of the most popular free programming language in the scientific computing community. It is meant to be highly documented and validated with reference sound samples and scientific publications.

## Documentation

Full documentation available on the [ReadTheDocs website](https://mosqito.readthedocs.io/en/latest/) !
trevorproxy-serverless 0.0.2
TREVORproxy wrapper that integrates with aws fargate based proxy cluster
Requires Python: >=3.6

TREVORproxy_serverless
==

<br/>

Sets up an autoscaling cluster of SOCKS proxies to use along with [TREVORproxy](https://github.com/blacklanternsecurity/TREVORproxy).

- `trevorproxy_serverless` uses an SQS queue to control the autoscaling of the proxy cluster
- as long as there is a `proxy-intent` message in the queue the cluster will stay up.
- when running the cli it adds a message to the queue to signal it needs a running cluster of proxies
- when the cli terminates gracefully it removes the message from the queue
- if the cli is terminated non gracefully, the message will remain in the queue until the message retention period of the queue passes
- while the cli is running it is using a sliding window approach to ensure the proxy intent message will not expire while the cli is running.

the proxy count can be adjusted trough [terraform variables](https://github.com/aristosMiliaressis/TREVORproxy_serverless/blob/master/infra/variables.tf).

<p align="center">
  <img src="https://github.com/aristosMiliaressis/TREVORproxy_serverless/blob/master/img/demo.png?raw=true">
</p>

<br/>

**Dependencies for infra.sh**
- aws cli (configured with enough permissions)
- terraform
- docker
- jq

<br/>

**trevorproxy_serverless Installation**
```bash
$ pip install trevorproxy_serverless
```

<br/>

**Notes**

Cost of one proxy instance running for an hour is 0,012$.

PS: Fargate bills per minute spent so if you spin up 100 servers for 30 minutes it will cost 0,012 * 100 / 2 = 0,60$

PS: Spin up time can take a few minutes because SQS pushes metrics to cloudwatch on an interval of 1 or 5 minues, the following aws regions support [1 minute metrics](https://aws.amazon.com/about-aws/whats-new/2019/12/amazon-sqs-now-supports-1-minute-cloudwatch-metrics/), so they are recommended:
US East (Ohio), 
EU (Ireland), 
EU (Stockholm), 
Asia Pacific (Tokyo)

<p align="center">
  <img src="https://github.com/aristosMiliaressis/TREVORproxy_serverless/blob/master/img/cost_calc.png?raw=true">
</p>
php-ast 1.5
A Python package for php_ast

<h1 align="center">Python Get PHP-AST </h1>

<div align="center">

[![PHP-AST](https://img.shields.io/badge/php-ast-blue)](https://github.com/php-ast/php_ast)
[![PHP](https://img.shields.io/badge/python_module-blue)](https://github.com/php-ast/php_ast)
[![version](https://img.shields.io/github/v/release/php-ast/php_ast.svg?color=blue)](https://github.com/php-ast/php_ast)
[![social](https://img.shields.io/github/stars/php-ast/php_ast?style=social)](https://github.com/php-ast/php_ast)
</div>
<p align="center">
</p>

## Install 
```bash
pip install  php-ast
```


## exapme 
```Python
# get bytes php code ast
from php_ast import php_ast
php_ast=php_ast()
php_ast.get_ast(b"<?php phpinfo();?>")
{'status': 'successed', 'ast': {'kind': 'AST_STMT_LIST', 'flags': 0, 'lineno': 1, 'children': [{'kind': 'AST_CALL', 'flags': 0, 'lineno': 1, 'children': {'expr': {'kind': 'AST_NAME', 'flags': 1, 'lineno': 1, 'children': {'name': 'phpinfo'}}, 'args': {'kind': 'AST_ARG_LIST', 'flags': 0, 'lineno': 1, 'children': []}}}]}}



# get php file ast
from php_ast import php_ast
php_ast=php_ast()
php_ast.get_file_ast("/home/11.php")
{'status': 'successed', 'ast': {'kind': 'AST_STMT_LIST', 'flags': 0, 'lineno': 1, 'children': [{'kind': 'AST_CALL', 'flags': 0, 'lineno': 1, 'children': {'expr': {'kind': 'AST_NAME', 'flags': 1, 'lineno': 1, 'children': {'name': 'phpinfo'}}, 'args': {'kind': 'AST_ARG_LIST', 'flags': 0, 'lineno': 1, 'children': []}}}]}}

```

## 说明
- 本项目是基于php-ast扩展的python模块，用于获取php代码的ast树
- 暂时只支持Linux 系统 


## 参考:
- [php-ast](https://github.com/nikic/php-ast)
dndlprof 0.10.0
A simple tool for profiling and tracing PyTorch programs on NVIDIA GPUs

# DND: Dnd's Not Dlprof!

[![PyPI version](https://badge.fury.io/py/dndlprof.svg)](https://badge.fury.io/py/dndlprof)

DND is a simple tool for profiling and tracing PyTorch programs on NVIDIA GPUs.
If uses NVIDIA's NSIGHT Systems and NSIGHT Compute along-side PyTorch 2.0's
Dynamo graph capturing system to provide framework operator and CUDA kernel
level breakdowns of a Deep Learning application. Check out the
[Sample App](./dnd/sample_app.py) for an example of an instrumented application.


## Install
```bash
$ pip install dndlprof
```

## Quick Start
```bash
$ dnd -- python -m dnd.sample_app
```