semvec/pypi-packages huggingface dataset:
SimpleQualtrics-CharlesWeir 1.0.1
Python module to support Qualtrics APIs
Requires Python: >=3.7
Keywords: qualtrics API https

# SimpleQualtrics

Python module to support Qualtrics' APIs.

SimpleQualtrics is a stand-alone single-class API to access the Qualtrics APIs directly,
handling all of the Qualtrics web-specific protocols in a robust manner and
answering data structures that are easy to process in Python.

Specifically, it implements separating credentials from code,
configuration handling, choice of API server, practical error handling, call timeouts,
call logging, and Python-friendly decoding of Qualtrics response formats and protocols.

See https://simplequaltrics.readthedocs.io/ for full documentation.
pdf-aggregator 0.0.1
Aggregate account PDF statements into JSON and visualize aggregated financial data as timeline
Requires Python: >=3.6
Keywords: pdf aggregate extract banking financial statement

# PDF aggregator

Aggregate account PDF statements into JSON and visualize aggregated financial data as timeline.

![PDF aggregator](https://raw.githubusercontent.com/finetjul/pdf-aggregator/master/docs/pdf-aggregator.svg)

Works offline and relies on [tika](https://tika.apache.org/) for PDF parsing and [matplotlib](https://matplotlib.org/) for plotting.
It relies on regular expressions stored in simple configuration files to extract bank statements balance, date, account number...

## Installation

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

## Usage

### Aggregate
Scan PDF files and aggregate financial data into an accounts.json summary file:

```
python aggregate.py path/to/folder/with/PDF
```

or

```
python aggregate.py path/to/file.pdf
```

```--help``` for more options.

### Add a new config

```
python aggregate.py path/to/PDF/file --test
```

It should print out the content of the pdf. Then test regular expression:

```
python aggregate.py path/to/PDF/file --test 'Ending balance on (\d+)/(\d+)/(\d+)
```

You can then create conf file and test detection with -vvv:

```
python aggregate.py path/to/PDF/file -vvv
```


### Plot
Plot aggregated data:

```
python plot.py path/to/folder/with/multiple/accounts.json
```

or

```
python plot.py path/to/accounts.json
```

```--help``` for more options.

Example:

```
python.exe .\plot.py .\accounts\ --subtotals --no_real_estate_appreciation
```
mopidy_async_client 0.1
Async Mopidy Client via JSON/RPC Websocket interface
Requires Python: >=3.7

# Mopidy-Async-Client 

### Fork of [Mopidy-json-client](https://github.com/ismailof/mopidy-json-client), but from scratch and async


Async Mopidy Client via JSON/RPC Websocket interface

## Usage

mopidy-async-client provides a main class `MopidyClient`, which manages the connection and methods to the Mopidy Server.
Use the `bind_event` function to subscribe to mopidy events.

```python
from mopidy_async_client import MopidyClient


async def main():
    async with MopidyClient() as mopidy:
        mopidy.bind_event('track_playback_started', print_track_info)
        await mopidy.playback.play()
```

## Installation

 `pip install mopidy-async-client`


## References
- [Mopidy Core API](https://mopidy.readthedocs.org/en/latest/api/core)
innateml 1.1.0
Innate stands for Integrated Neural Network Automatic Trainer and Evaluator

Innate stands for Integrated Neural Network Automatic Trainer and Evaluator. It is a framework for training neural networks and optimizing their hyperparameters. The base concept is to provide, at the user level, a complete abstraction of the training of a neural network on a cluster. The user can use the interface to launch tasks and get results as if they were executed on its own machine. The runtime provided by the framework simplify also the necessary code for training.

This package is the interface library to connect to an innate server and execute training.