semvec/pypi-packages huggingface dataset:
avanzapy 0.0.2
A Python wrapper to interact with Avanza
Requires Python: >=3.6
Keywords: avanza broker trading

With this Python wrapper you can interact with the Swedish broker Avanza. You can run two types of query: logged in and not logged in. Regarding the first ones you can query your balances and open positions, or even send orders to market. If you are not logged with your account (maybe you don't have an account or don't want to expose your data) you can still use this wrapper to query differentes instruments data (stocks, funds, certificates, etf,...). You can get both current price and historical price in different formats
prayikta 0.3
Gaussian and Binomial distributions
Requires Python: >=3.6

## Prayikta

<p> By using Prayikta module you can  calculate Gaussian distribution, Binomial Probability, pdf and can visualization of them. </p>

### Classes

* Gaussian Class
* Binomial Class

#### Gaussian Class

  ```
  # Example Fuctions

    >>> from prayikta import Gaussian

    # It has two arguments mean and standard daviation default (mean = 0 and stdev = 1)

    >>> gaussian = Gaussian()
    >>> gaussian.mean
    >>> gaussian.stdev

    # Read data from file and calculate mean and standard deviation

    >>> gaussian.read_data_file('filename.txt')
    >>> gaussian.calculate_mean()
    >>> gaussian.calculate_stdev()

    # Plot histogram of data

    >>> gaussian.plot_histogram()

    # Calculate probability density function and visualise it.

    >>> gaussian.pdf() # takes one argument
    >>> gaussian.plot_histogram_pdf()


    # Add to gaussian functions

    >>> gaussian_a = Gaussian(25,0)
    >>> gaussian_b = Gaussian(5,2)
    >>> gaussian_c = gaussian_a + gaussian_b
  ```

  #### Binomial Class

  ```
  # Example Fuctions
    >>> from prayikta import Binomial

    # It takes two arguments mean and standard daviation default (probability = 0.5 and size = 20)

    >>> binomial = Binomial()
    >>> binomial.calculate_mean()
    >>> binomial.calculate_stdev()

    # Plot bar

    >>> binomial.plot_bar()

    # Calculate pdf and visualise it.

    >>> binomial.pdf() # takes one argument
    >>> binomial.plot_bar_pdf()

    # Add to binomial functions

    >>> binomial_a = Binomial(0.5,10)
    >>> binomial_b = Binomial(0.25,20)
    >>> binomial_c = binomial_a + binomial_b
```
flask-management-blueprint 0.2.0
Flask Management Blueprint

# Flask Management Blueprint

[![Build Status](https://travis-ci.org/stone-payments/flask-management-blueprint.svg?branch=master)](https://travis-ci.org/stone-payments/flask-management-blueprint)

This repository contains a project developed with Python3 :heart: with a blueprint that describe the necessary endpoints to meet the engineering goals.

## Starting

This instructions should be enough to replicate the development enviroment of this project. If this is not the case, please, feel free to open a pull request.

## Prerequisites

After cloning the project, you will need Python 3.5.

## Environment

```bash
python3 -m venv /path/to/new/virtual/environment
source venv/bin/activate
pip install -r requirements.txt
```

## Settings

To successfully set up the project, a json file is needed. This file should be in path described in the enviroment variable CONFIG_FILE_PATH.

Besides that, all of the project's dependencies should be added with the `AppInfo`'s method `register_resource`. This method should receive a function that returns `True` or `False` depending on the dependency's health.

## Running

If all goes right, you should be run the `run.py` file inside the samples folder.

## Testing

Unit tests:

`nosetests tests/unit`

Coverage:

`nosetests --with-coverage --cover-package=flask_management_blueprint`

## Built With

Python 3.5.2

## Authors

Build with :heart: by Team Satisfação do Cliente!

## License

Copyright (C) 2018. Stone Pagamentos. All rights reserved.
python3-openid 3.2.0
OpenID support for modern servers and consumers.

This is a set of Python packages to support use of
the OpenID decentralized identity system in your application, update to Python
3.  Want to enable single sign-on for your web site?  Use the openid.consumer
package.  Want to run your own OpenID server? Check out openid.server.
Includes example code and support for a variety of storage back-ends.
ems-dataflow-testframework 1.2.5
Framework helping testing Google Cloud Dataflows

ems-dataflow-testframework
==========================

[![Codeship status](https://app.codeship.com/projects/b6f50310-b6ba-0137-4346-7a70f6e67953/status?branch=master)](https://app.codeship.com/projects/364126)
[![PyPI version](https://badge.fury.io/py/ems-dataflow-testframework.svg)](https://badge.fury.io/py/ems-dataflow-testframework)
[![semantic-release](https://img.shields.io/badge/%20%20%F0%9F%93%A6%F0%9F%9A%80-semantic--release-e10079.svg)](https://github.com/semantic-release/semantic-release)

Purpose of the project
======================

This framework aims to help test Google Cloud Platform dataflows in an end-to-end way.

How to develop locally
======================

Use [virtualenv](https://docs.python-guide.org/dev/virtualenvs/) preferably to manage Python dependencies.

```bash
pip install -r requirements.txt
```

How to run unit tests
=====================
```bash
make test
```

How to run statical code analysis
=================================
```bash
make check
```

How to contribute
=================
Fork the repository and apply your changes. Pull requests are welcome. Please pay attention on the commit message [conventions](https://github.com/semantic-release/semantic-release). Thanks in advance!

How to release
=================================
Releasing is managed by [python-semantic-release](https://github.com/relekang/python-semantic-release) which means your commit messages define the upgraded version number. Use the following convention during writing commit messages:
 1. fix({SCOPE}): {BODY} -> patch
 2. feat({SCOPE}): {BODY} -> minor
 3. xxx({SCOPE}): {BODY} -> BREAKING CHANGE -> major

If you are unsure how to write valid commit messages enforce yourself with using tools like [commitizen](https://github.com/commitizen/cz-cli).

To trigger a release merge `master` branch into `release` and push it.

License
=======
[MIT](https://choosealicense.com/licenses/mit/)
OOModellingPython 0.0.2
An object orienteded modelling package for causal models.
Requires Python: >=3.6

# Object Oriented Modelling Framework for Causal Models

# Installing the package from source code

Open terminal in [./OOModellingPython](OOModellingPython).

```
pip install -e .
```

# Publishing this package on pypi

Cd to OOModellingPython, and
```
python setup.py sdist bdist_wheel
python -m twine upload dist/*
set user and password according to pypi's api token
```