semvec/pypi-packages huggingface dataset:
pyciosa 0.0.5
common utilities for new projects
Requires Python: >=3.6

# Utilidades Para Cualquier Proyecto Nuevo

![GitHub tag (latest SemVer)](https://img.shields.io/github/v/tag/marco-gallegos/pyciosa?label=pyciosa&style=for-the-badge)
[![PyPI](https://img.shields.io/badge/pip-v.20.0.2-blue.svg?style=for-the-badge)](https://pypi.org/project/pyciosa/)
![Python](https://img.shields.io/badge/python-3.6+-green.svg?style=for-the-badge)
[![Tests](https://img.shields.io/badge/tests-4%20%2F%204-brightgreen.svg?style=for-the-badge)](https://github.com/marco-gallegos/pyciosa/blob/master/tests.py)
![GitHub](https://img.shields.io/github/license/marco-gallegos/pyciosa?style=for-the-badge)

## Modules

### Periodo

A "Periodo" is another date representation as a string from the year and the month in format  YYYYMM for example: 202001,
is the representation of january of 2020.

#### Functions

 * is_valid
 * explode
 * split
 * get_periodo
 * interpolate
 * get_previous_quarter_periodo
 * get_periodo_label
 * get_periodo_range_label
 * validate_date
 * get_period_full_label
 * get_date_for_sql_filter_from_periodo
pyfirebasestockscli 1.0.7
portfolio+ command line interface for firebase operations.

[![Build Status](https://travis-ci.org/portfolioplus/pyfirebasestockscli.svg?branch=master)](https://travis-ci.org/portfolioplus/pyfirebasestockscli)
[![Coverage Status](https://coveralls.io/repos/github/portfolioplus/pyfirebasestockscli/badge.svg?branch=master)](https://coveralls.io/github/portfolioplus/pyfirebasestockscli?branch=master)
[![Codacy Badge](https://api.codacy.com/project/badge/Grade/7f42400f9e794d45a35376b4cbdccd9f)](https://www.codacy.com/manual/SlashGordon/pyfirebasestockscli?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=portfolioplus/pyfirebasestockscli&amp;utm_campaign=Badge_Grade)

# pyfirebasestockscli

portfolio+ command line interface for firebase operations.

## install

```bash
pip install pyfirebasestockscli
```

## quick start
Export the following environment variables:

```bash
export DATABASE_URL=https://<name>.firebaseio.com
export CRED_JSON=/path/to/firebase_sdk.json
export DATA_ROOT=/path/to/strategies
```

Create database and delete existing:

```bash
stocks -c
```

Update prices and filter:

```bash
stocks -u
```

Update prices:

```bash
stocks -p
```

Create strategies:

```bash
stocks -s
```

## issue tracker

[https://github.com/portfolioplus/pyfirebasestockscli/issuese](https://github.com/portfolioplus/pyfirebasestockscli/issues")
osf-pigeon 0.0.2
A utility for archiving osf storage projects at archive.org

# osf-pigeon

A utility for archiving OSF data to archive.org  


Purpose
============

This utility takes a publicly available OSF registration guid as a parameter and using that info alone it will transfer
that registration, file data, metadata et all to Internet Archive.

Install
============

Simply install the package using python's package manager pip with bash:

 ``pip3 install osf_pigeon``

To use for local development just remember to install the developer requirements using:

 ``pip3 install -r dev.txt``

Use
============

Simply import the module and enter a guid with credentials::

 from osf_pigeon import pigeon

 pigeon(
    'guid0',
    datacite_username='test_datacite_username',
    datacite_password='test_datacite_password',
    datacite_prefix='test_datacite_prefix',
    ia_access_key='test_datacite_password',
    ia_secret_key='test_datacite_password',
 )

That's it!

Assuming the registration is fully public and the DOI has been minted properly at datacite. 

## Running for development

#### Tests

Running tests are easy enough just::

 pip3 install -r dev.txt
 python3 -m pytest . 


#### Linting

Optional, but recommended: To set up pre-commit hooks (will run
formatters and linters on staged files)::

 pip install pre-commit
 pre-commit install --allow-missing-config
lupoclient 0.0.1
This client is a wrapper for the official Lupo API
Requires Python: >=3.6

# Zorro Client
`zorro-client` is a library written for use with Zorro, an algorithmic trading platform. This library includes a full API client with access to user-written indicators and strategies. In addition, it includes the backtesting framework and scripting language used by Zorro, so you can test out your strategies on your own data as well.

## Install
```
$ pip3 install zorro-client
```

## Example
```python
import zorro

theAPI = zorro.Api(
    api_key="your-api-key",
    secret_key="your-secret-key")

my_indicator = theAPI.indicators['indicator-id']
my_strategy = theAPI.strategies['strategy-id']

stock_data = zorro.StockData.create(
	["AAPL",  "AMZN"],
	"2020-01-03",
	"2020-07-11",
	"1d")

# backtest the strategy
backtest = my_strategy.create_backtest(stock_data)
backtest.simulate()

# find important details
backtest_results = backtest.analyze()
sharpe_ratio = backtest_results['sharpe_ratio']
alpha = backtest_results['alpha']
beta = backtest_results['beta']
profit_pct = backtest_results['profit_percent']
profit = backtest_results['profit']
trade_history = backtest.trade_history

print(backtest_results)
```

## Usage

### Import
```python
import zorro
```

### Create a strategy
```python
my_strategy = zorro.Strategy(
	{
		"type": "order",
		"stock": "AAPL",
		"qty": "10"
	}
)
```

### Execute the strategy on a paper API
No setup required.
```python
paper_broker = zorro.PaperBroker()
my_strategy.execute(handler=paper_broker)
```

### Execute the strategy on a live API
To do this, you will need an Alpaca account. You can create one [here](http://alpaca.markets). 
```python
live_broker = zorro.LiveBroker(
	alpaca_api_key_id="<Your API key>",
	alpaca_api_secret="<Your API secret")

my_strategy.execute(handler=live_broker)
```

## Thank you for using Zorro!
If you have any questions, reach out to us at [our email](mailto:tradewithzorro@gmail.com).
zorroclient 0.0.1a0
This client is a wrapper for the official Zorro API
Requires Python: >=3.6

# Zorro Client
`zorro-client` is a library written for use with Zorro, an algorithmic trading platform. This library includes a full API client with access to user-written indicators and strategies. In addition, it includes the backtesting framework and scripting language used by Zorro, so you can test out your strategies on your own data as well.

## Install
```
$ pip3 install zorro-client
```

## Example
```python
import zorro

theAPI = zorro.Api(
    api_key="your-api-key",
    secret_key="your-secret-key")

my_indicator = theAPI.indicators['indicator-id']
my_strategy = theAPI.strategies['strategy-id']

stock_data = zorro.StockData.create(
	["AAPL",  "AMZN"],
	"2020-01-03",
	"2020-07-11",
	"1d")

# backtest the strategy
backtest = my_strategy.create_backtest(stock_data)
backtest.simulate()

# find important details
backtest_results = backtest.analyze()
sharpe_ratio = backtest_results['sharpe_ratio']
alpha = backtest_results['alpha']
beta = backtest_results['beta']
profit_pct = backtest_results['profit_percent']
profit = backtest_results['profit']
trade_history = backtest.trade_history

print(backtest_results)
```

## Usage

### Import
```python
import zorro
```

### Create a strategy
```python
my_strategy = zorro.Strategy(
	{
		"type": "order",
		"stock": "AAPL",
		"qty": "10"
	}
)
```

### Execute the strategy on a paper API
No setup required.
```python
paper_broker = zorro.PaperBroker()
my_strategy.execute(handler=paper_broker)
```

### Execute the strategy on a live API
To do this, you will need an Alpaca account. You can create one [here](http://alpaca.markets). 
```python
live_broker = zorro.LiveBroker(
	alpaca_api_key_id="<Your API key>",
	alpaca_api_secret="<Your API secret")

my_strategy.execute(handler=live_broker)
```

## Thank you for using Zorro!
If you have any questions, reach out to us at [our email](mailto:tradewithzorro@gmail.com).
dexcomapi 0.4.5
Uses Dexcom APIs to download blood glucose data
Requires Python: >=3.6

# dexcomapi


This simple package allows you to setup a authenticated channel to download blood glucose numbers from the Dexcom api. The intent is to use this with HomeAssistant.io.

 You can use
[Github-flavored Markdown](https://guides.github.com/features/mastering-markdown/)
to write your content.