semvec/pypi-packages huggingface dataset:
PyFineract 0.1.3
A fineract API wrapper
Requires Python: >=3.4

Tutorial (Short)
----------------

First create a Fineract instance::

    from fineract import Fineract

    # First create a Fineract instance

    # using username, password, tenant and base url
    f = Fineract("mifos", "password", "default, "https://localhost/fineract-provider/api/v1")

Then work with your Fineract objects::

    for client in f.get_clients():
        print(client.full_name)
pms7003 1.1.0
A python driver for plantower pms7003 pm sensor
Requires Python: >=3

# A minimalistic python interface for PMS7003 sensor

The code reads PM values from serial port. Tested on Raspberry Pi, but it should work on any machine with Python and serial port.

Device description: <https://aqicn.org/sensor/pms5003-7003/>

## Setup

To install the driver, simply do:
```bash
pip3 install pms7003
```

## Usage example

```python
from pms7003 import Pms7003Sensor, PmsSensorException

if __name__ == '__main__':

    sensor = Pms7003Sensor('/dev/serial0')

    while True:
        try:
            print(sensor.read())
        except PmsSensorException:
            print('Connection problem')

    sensor.close()
```

The read function has an option of returning values as a dict or OrderedDict.

```python
sensor.read(ordered=True)
```

## Usage example with threading:

```python
import time
from pms7003 import Pms7003Thread

if __name__ == "__main__":

    with Pms7003Thread("/dev/serial0") as sensor:

        while True:
            print(sensor.measurements)
            # We're free to do computation in main thread 
            a = 2**32
            time.sleep(1)
```
whitehole 0.0.3
Package for read and backtest data of financial assets in the most storage-efficient way, taking care of performance and store using zarr format files
Requires Python: >=3.5

![logo_website](https://user-images.githubusercontent.com/49825286/90585259-06971800-e19a-11ea-88e2-c4866aa8caaf.png)
<br />
Whitehole is a zarr-format-based-tool that allows individuals or small teams interested in processing financial information to make investment decisions.


## What do I need to know to start?
<br />

Whitehole was thought to fill the gap between the techniques used by the industry and some retail quantitative investors. Thus, the first step to think about is that there is a huge amount of data that is necessary to process for different purposes, specially for **ticks** market data instead of **candlebars**. That's why we need a format to store all the data in less storage space. In that sense, [Quantmoon Technologies](https://www.quantmoon.com/) provides [tick data using Zarr format](https://www.quantmoon.com/tickdata). [Zarr](https://github.com/zarr-developers/zarr-python) allows to chunk this tick data and store it in binary structure with metadata as labels.

Whithole use this light data files to upload and read it in Python environments, such as Jupyter, Spyder, PyCharm and more. The idea behind this is to get useful data arrays to work efficiently through any required process. So, [xarray](https://github.com/pydata/xarray) is the main library useful for hold the data and work with it. 

As an additional features, Whitehole allows to use [numpy](https://github.com/numpy/numpy/blob/master/README.md) and [pandas](https://github.com/pandas-dev/pandas) to work with the data for different purposes, specially when the processing has to be done just once in the workflow.

Whitehole is fully developed in Windows.

## Features:
<br />

* Decryptor: because of zarr store data in binary, with this class is possible to transform it in a more human-comprenhensive way.
* Whitehole is thought to have different features, the processing of the information will be realized in future versions.

## How do I get it?
<br />

Whitehole can be installed from PyPI using pip:
```
pip install whitehole
```


## Quick Start
<br />

To have a better understanding of the features, please check the notebooks on the [notebook](https://github.com/quantmoon/whitehole/tree/master/whitehole/notebooks) folder
edelweiss-data-cli 0.1.0a2
CLI client for EdelweissData
Requires Python: >=3.6,<4.0

# Edelweiss Data CLI

A CLI tool for [Edelweiss Data](https://edelweissdata.com):
Convenient publishing of scientific data with proper versioning, rich metadata support and a powerful API

## Installation

Install globally from [PyPi](https://pypi.org/project/edelweiss-data/) using [pip](https://pip.pypa.io/):

```bash
pip install edelweiss-data-cli

```

## Usage

Run `edelweiss --help` to see a list of available commands.

By default, the tool uses the public edelweiss api at `https://api.edelweissdata.com`.
The `--url` flag lets you use an alternative edelweiss api:

```bash
edelweiss --url https://${MY_DOMAIN} <command>
```

For each command, use the `--help` flag for more information:

```bash
edelweiss <command> --help
```

## Commands

### Authenticate

Use the `authenticate` command to generate access tokens and refresh tokens.

```bash
edelweiss authenticate
```

The CLI responds with:

```
Visit this url in your web browser to sign into edelweiss:
https://edelweiss.eu.auth0.com/activate?user_code=XXXX-XXXX

Your authorization token is XXXX-XXXX
Waiting for authentication.....
```

Open the url in your web browser and follow the instructions to sign up or sign in. After you have signed in via the web browser, the CLI will print out the result:

- `access_token` - this is the bearer token for you to attach to all http requests.
- `expires_in` - the number of seconds until your access token expires; by default 86400 seconds.


Use the `--help` flag to see what options are available with the authenticate command:

```bash
yarn run authenticate -- --help
```

*Caution*: If you sign up with a new email/password then you will receive an email to let you validate your address.  Access tokens generated by the CLI tool are not valid until you have validated your email address.

### Other commands

We have lots of ideas for other Edelweiss commands, but they are not implemented yet. For example:

- Create a dataset
- Fetch a dataset
- Search for datasets
- Manage read/write permissions

Please [create an issue](https://github.com/DouglasConnect/edelweiss-data-cli-python/issues) to lend your support to any of these suggested features.