semvec/pypi-packages huggingface dataset:
pyFTracks 0.2.8
Fission Track Modelling and Analysis with Python
Keywords: geology thermochronology fission-tracks


.. image:: https://raw.githubusercontent.com/rbeucher/pyFTracks/master/docs/images/logo.png
    :align: center

================================================
Fission Track Modelling and Analysis with python
================================================

.. image:: https://img.shields.io/pypi/v/pyftracks.svg
    :target: https://pypi.python.org/pypi/pyftracks
    :alt: Pip
.. image:: https://www.travis-ci.org/rbeucher/pyFTracks.svg?branch=master
    :alt: Travis
.. image:: https://mybinder.org/badge_logo.svg
    :target: https://mybinder.org/v2/gh/rbeucher/pyFTracks.git/master
    :alt: Logo


pyFTracks is a Python utility which predicts Fission-track ages and track-lengths
distributions for some given thermal-histories and given kinetic parameters.
It is an open source version of programs such as AFTSolve or HeFty developped by
Richard Ketcham and describe in Ketcham, 2000, 2005.

We provide the code in the hope that it will be useful to the community.

We have chosen Python to allow for interaction with the broad range of scientific libraries
available in that language. Python is becoming a language of choice for teaching programming,
it has also many advantages for Research Workflow, such as rapid prototyping and interactivity.


.. image:: https://raw.githubusercontent.com/rbeucher/pyFTracks/master/docs/images/image1.png
    :align: center


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

The code is available on pypi and should work on any Linux distributions, MacOSX and Windows 10.
To install it just run:

.. code:: bash

  pip install pyFTracks

in the console.

You can install the package from the latest github source by doing:

.. code:: bash

  pip install git+https://github.com/rbeucher/pyFTracks.git

------------
Dependencies
------------

The pip install should take care of the dependencies, if not you might want to
check that you have the following packages installed on your system:

- Python >= 3.5.x
- Cython >= 0.29.14
- matplotlib >= 3.1.1
- numpy >= 1.17.4
- scipy >= 1.3.2
- pandas >= 0.25.3
- tables >= 3.6.1

-----------
Recommended
-----------
We recommend using Jupyter:

- jupyter

---------
Licensing
---------

pyFTracks is an open-source project licensed under the MiT License. See LICENSE.md for details.

------------
Contributing
------------

-------
Contact
-------

Dr Romain BEUCHER, 
The Australian National University
romain.beucher@anu.edu.au
python-pangu 0.0.9
ai adapter client for python
Keywords: python pangu,RPC,Remote Procedure Call,Event Driven,Asynchronous,Non-Blocking,Raspberry Pi,ZeroMQ,MessagePack,Arduino

# ai adapter client for python

This is a simple example package. You can use
[Github-flavored Markdown](https://guides.github.com/features/mastering-markdown/)
to write your content.
BankPy 1.0.2
Armazene Seu Dados Sem Perde nada :)
Requires Python: >=3.6

# Jiton Armazen de Dados Versatil
## Muito Simples De Usa

### Muito Pythonic

**VocÃª Pode Cria Um Armazen de Dados Para Sua AplicaÃ§Ã£ Como SÃ© Fosse Um Banco de Dados...**

**Esse Dados SerÃ£o Armazenado Em Um Arquivo Python Onde Ã© Possivel Fazer a ComicaÃ§Ã£o do Sua AplicaÃ§Ã£o Com Arquivo Python de Uma Forma Simples Ã© Util**

* NÃ£o Reque Nada Especial 

```
from Jiton import *

Criando o Path
Create.Path.Pop('testando')
Esta FunÃ§Ã£o Cria Uma Pasta Com um __init__.py
Este Dados Ficaram Salvo Nesse __init__.py

Conectando O Path Criado
var = Connect.Path.Pop('testando')

Armazenando Um Dado Na Variavel 
Write.Variable.Str.Pop(var'Nome_Da_Variavel''Conteudo da Variavel')

```

__Criado Por JosÃ© Alexsandro__




[Desenvolvido Pela Star Comics](https://starcomicstar.weebly.com/)

[Portifolio_Do_Autor](https://alexsandrodev.netlify.app/)
Jiton 1.0.1
Armazene Seu Dados Sem Perde nada :)
Requires Python: >=3.6

# Jiton Armazen de Dados Versatil
## Muito Simples De Usa

### Muito Pythonic

**VocÃª Pode Cria Um Armazen de Dados Para Sua AplicaÃ§Ã£ Como SÃ© Fosse Um Banco de Dados...**

**Esse Dados SerÃ£o Armazenado Em Um Arquivo Python Onde Ã© Possivel Fazer a ComicaÃ§Ã£o do Sua AplicaÃ§Ã£o Com Arquivo Python de Uma Forma Simples Ã© Util**

* NÃ£o Reque Nada Especial 

```
from Jiton import *

Criando o Path
Create.Path.Pop('testando')
Esta FunÃ§Ã£o Cria Uma Pasta Com um __init__.py
Este Dados Ficaram Salvo Nesse __init__.py

Conectando O Path Criado
var = Connect.Path.Pop('testando')

Armazenando Um Dado Na Variavel 
Write.Variable.Str.Pop(var'Nome_Da_Variavel''Conteudo da Variavel')

```

__Criado Por JosÃ© Alexsandro__




[Desenvolvido Pela Star Comics](https://starcomicstar.weebly.com/)

[Portifolio_Do_Autor](https://alexsandrodev.netlify.app/)
jit-jiton 1.0.0
Armazene Seu Dados Sem Perde nada :)
Requires Python: >=3.6

# JIT Armazen de Dados Versatil
## Muito Simples De Usa

### Muito Pythonico

**VocÃª Pode Cria Um Armazen de Dados Para Sua AplicaÃ§Ã£ Como SÃ© Fosse Um Banco de Dados...**


__Criado Por JosÃ© Alexsandro__


[Desenvolvido Pela Star Comics](https://starcomicstar.weebly.com/)

[Portifolio_Do_Autor](https://alexsandrodev.netlify.app/)
aws-cdk.zip-asset-code 1.0.1
AWS CDK extension for aws-cdk.aws-lambda
Requires Python: >=3.8

```python
from aws_cdk import aws_lambda as lambda_
from aws_cdk.zip_asset_code import ZipAssetCode

lambda_.Function(stack, 'ExampleLambdaFunction',
                 code=ZipAssetCode('example-lambda/'),
                 handler='handler.handler',
                 runtime=lambda_.Runtime.PYTHON_3_8)
```
(snippet from [example-cdk-lambda.py](examples/example-cdk-lambda.py))
searchoffer 0.0.3
Python library suggestqueries google api

# searchoffer

searchoffer is a Python library for suggestqueries google api.

## Installation

Use the package manager [pip](https://pypi.org/project/searchoffer/) to install searchoffer.

```bash
pip install searchoffer
```

## Usage

```python
from searchoffer import SearchOffer

keyword = "ماهکان"
language = "fa"
SearchOffer(keyword,language).offer() # Default offer
SearchOffer(keyword,language).google() # Offer from Google
```
amazontrends 0.0.6
amazontrends
Requires Python: >=3.5

# amazontrends
![python_version](https://img.shields.io/static/v1?label=Python&message=3.5%20|%203.6%20|%203.7&color=blue) [![PyPI downloads/month](https://img.shields.io/pypi/dm/amazontrends?logo=pypi&logoColor=white)](https://pypi.python.org/pypi/amazontrends)

## Description
amazontrends

## Install
~~~~bash
pip install amazontrends
# or
pip3 install amazontrends
~~~~
vault-client 0.3.4
This library implements wrapper for ...

# vault-client

Клиент предназанчен для унифицированного доступа к переменным  окружения размещённым в конфигурационном
файле (или переменных окружения) или в хранилище Vault, в зависимости от параметров инициализации.

## Установка клиента

> pip install vault-client

## Интерфейс клиента

### Инициализация клиента:

> client = VaultClient(environ="LOCAL")

При таком способе инициализации источником данных является файл ***.deploy/.envs/local.env***.

При отсутствии параметра ***environ*** 
> client = VaultClient()

или ***environ=None*** 

> client = VaultClient(environ=None)

Данные получаются из Vault, параметры сервера Vault должны быть заданы в переменных окружения. 

Для получения параметров из хранилища Vault в переменных окружения задаются следующие данные;
- адрес хоста и порт Vault (*host*, *port*);
- токен доступа к Vault (*token*);
- точка монтирования (*mount_point*);
- стадия разработки (PROD, STAGE, DEV и т.д.) (*environ*)

Перечисленные параметры должны быть установлены в переменных окружения:

* VAULT_TOKEN
* VAULT_PORT
* VAULT_HOST
* VAULT_MOUNT_POINT 
* VAULT_ENV

  
**Внимание:** при записи параметров в Vault, наименование параметра должно указываться строчными символами. 

### Пример структуры данных в файле local.env или в Vault

    STORAGE_HOST=127.0.0.1
    STORAGE_PORT=50001
    PARSER_HOST=127.0.0.2
    PARSER_PORT=50002
    
Данные определяется таким образом:
  
  <Сервис>_<Параметр> - при размещении данных в файле local.env;
 
  <Сервис>/STAGE/<Параметр> - при  размещении данных в Vault; 
  
#### Пример получения параметра
 
>client = VaultClient(environ="LOCAL")
>
>result = client.get("storage", "host")

При иницализации клиента с параметром ***environ = LOCAL***, значение параметра будет получаться из переменной
окружения **STORAGE_HOST**, в случае отсутствия - ***result = None***.

Иницализация клиента с параметром ***VAULT_ENV*** отличном от ***LOCAL*** (например: ***PROD***), значение параметра 
будет запрашиваться из Vault по пути: ***test_client/STORAGE/PROD/host*** (при VAULT_MOUNT_POINT = test_client),
в случае отсутствия - ***result = None***.


## Unit test

Unit тесты и интеграционные тесты не разделяются. Вы можете найти их в /tests. Для проведения интеграционных тестов, требуется развёрнутый vault.

## Поддержка

Создано при поддержке fless.pro