semvec/pypi-packages huggingface dataset:
folklore 0.2.0
An elegant thrift service development framework

Folklore: An elegant thrift service development framework
=========================================================

.. image:: https://travis-ci.org/maralla/folklore.svg?branch=master
    :target: https://travis-ci.org/maralla/folklore



This package defines the interfaces for writing Folklore thrift services.

Install
-------

.. code:: bash

    pip install folklore


Example
-------

To define a simple app:

.. code:: python

    # app.py
    from folklore import Folklore

    app = Folklore('TestService')

    @app.api
    def say_hello(name):
        return 'Hello ' + name


To Run the app, install `folklore-cli <https://github.com/maralla/folklore-cli>`_ first, then
create the following config:

.. code:: thrift

    # ping.thrift
    service TestService {
        string say_hello(1: required string name)
    }

.. code:: yaml

    # app.yaml
    app_name: test_app
    app: app:app
    thrift_file: ping.thrift

Run the following command:

.. code:: bash

    $ folklore serve
bitmexpy 0.0.2
python client for BitMEX's API
Requires Python: >=3.6

bitmexpy
========

bitmexpy is a small project I created to learn how to create python packages. 
bitmexpy is heavily based on my bitmexr R package for accessing BitMEX's API for cryptocurrency data.

Useage
------

Currently trade data can be obtained using `trades()` and `bucket_trades()`. 

For data spanning more one API call (there is a 1000 row limit per API call) `map_bucket_trades()` can be used. 
This function creates a range of start dates and loops over the `bucket_trades()` function to capture all the required data. See examples below!

Examples
--------

Below are some simple examples of current functionality

::

        # Request: Last 100 days of data for symbol XBTUSD:

        xbt = bucket_trades(symbol = "XBTUSD", 
                            reverse = "true",
                             count = "100)


        # Request: Hourly data since 2019-01-01

        eth = map_bucket_trades(symbol = "ETHUSD",
                                start_date = "2019-01-01",
                                binSize = "1h)
py-ppnet 1.0.5.0
P2P network
Requires Python: >=3

============
PPNetwork
============
***************
简介
***************

    PPNetwork 是无中心节点的网络驱动，可以在任何环境下建立数据连接。

    PPNetwork采用UDP，自动寻找同类节点，并自动寻找到目标地址的路径，发送数据。

    至少需要添加一个初始的对等节点。可以通过对等节点获得其邻居信息，逐渐扩大自己的网络。上层应用可以通过寻找好友的方式添加对等节点。

****
安装
****
::

  pip install py-ppnet


****
使用
****

ppnetwork 不能独立运行，需要根据接口，开发上层应用。
需要至少一个可访问到的peer节点，可以通过配置也可以在运行时动态增加。

config模式
**********

config.yaml::

    node_port: 54320
    nodes: [["172.31.102.109",54320]]

程序代码::

    from ppnet import PPNetNode

    ppnetnode = PPNetNode(config=config)
    ppnetnode.start()
    ppnetnode.send(data,addr1)
    data,addr2 = ppnetnode.receive(count)
    ...
    ppnetnode.quit()


动态增加模式
************
程序代码::

 from ppnet import PPNetNode

 ppnetnode = PPNetNode(node_port=54320)
 ppnetnode.set_peer(addr)
 ppnetnode.start()
 ppnetnode.send(data,addr1)
 data,addr2 = ppnetnode.receive(count)
 ...
 ppnetnode.quit()
attorneycrm-pkg-tjdaley 0.0.1
Attorney Client Relationship Management App
Requires Python: >=3.6

# payment_redirect
Redirect clients to a payment link.

<p align="center">
    <a href="https://github.com/tjdaley/payment_redirect/issues"><img alt="GitHub issues" src="https://img.shields.io/github/issues/tjdaley/payment_redirect"></a>
    <a href="https://github.com/tjdaley/payment_redirect/network"><img alt="GitHub forks" src="https://img.shields.io/github/forks/tjdaley/payment_redirect"></a>
    <a href="https://github.com/tjdaley/payment_redirect/stargazers"><img alt="GitHub stars" src="https://img.shields.io/github/stars/tjdaley/payment_redirect"><a>
    <!-- img alt="PyPI - License" src="https://img.shields.io/pypi/l/payment_redirect" -->
    <img alt="Stage: Development" src="https://img.shields.io/badge/stage-Development-orange">
</p>
<p align="center">
    <a href="#purpose">Purpose</a> &bull;
    <a href="#installation">Installation</a> &bull;
    <a href="#author">Author</a>
</p>

## Purpose
Make it easy for clients to make the required payment on their account.
Authorized users set up a client record and update it with the amount
the client is required to pay to bring their account up to date. When the
client visits the URL and enters identifying information, the client is
redirected to a payment URL with the amount pre-filled.

## Installation
```
git clone https://github.com/tjdaley/payment_redirect
```

## Implemented Utilities

### /clients, /client

Authenticates an administrative user and let's the user CRUD client
records including payment due amount and date. Authentication is
performed through Microsoft's identity provider service API.

### /pay

Prompts the user for the last three digits of their Social Security number
and the last three digits of their driver's license. If a match is found in
the database, the user is redirected to a pre-populated payment page.

### /pay/<string:client_id>

*client_id* is formatted so that the first three characters are the last
three digits of the user's Social Security number, the next three characters
are the last three digits of the user's Driver's License number, and the last
character is a check-digit, for now A-Z.

For example, if the user's Social Security number is XXX-XX-X123 and their
driver's license number is XXXXX456, the *client_id* would be '123456V'.

## Author

Thomas J. Daley, J.D. is an active family law litigation attorney practicing primarily in Collin County, Texas, a family law mediator, and software developer. My Texas based family law practice is limited to divorce, child custody, child support, enforcment, and modification suits. [Web Site](https://koonsfuller.com/attorneys/tom-daley/)
gabi-distribution 0.7
Gaussian and Binomial distributions

# gabi-distribution package 

This package contains classes for Gaussian and Binomial distribution

# What is Gaussian distribution?

In probability theory, a normal (or Gaussian or Gauss or Laplace–Gauss) distribution is a type of continuous probability distribution for a real-valued random variable. 

# What is Binomial distribution?

In probability theory and statistics, the binomial distribution with parameters n and p is the discrete probability distribution of the number of successes in a sequence of n independent experiments, each asking a yes–no question, and each with its own boolean-valued outcome: success/yes/true/one (with probability p) or failure/no/false/zero (with probability q = 1 − p). A single success/failure experiment is also called a Bernoulli trial or Bernoulli experiment and a sequence of outcomes is called a Bernoulli process; for a single trial, i.e., n = 1, the binomial distribution is a Bernoulli distribution. The binomial distribution is the basis for the popular binomial test of statistical significance.

# Files

Generaldistribution.py - This is the base class for the Gaussian and Binomial dostribution class
Gaussiandistribution.py - This is the class for Gaussian distribution
Binomialdistribution.py - This is the class for Binomial distribution

# Installation 

Type the following command into your terminal 

pip install gabi_distribution