semvec/pypi-packages huggingface dataset:
gregory 3.1.1
Python framework to manage time series structured as one-level dictionaries
Requires Python: >=3.8, <3.11
Keywords: time series,ts,timeseries,temporal data

# Gregory
Python Framework to Manage Time Series structured as one-level dictionaries.

## Overview
This framework is an extension of the **[outatime](https://github.com/SynStratos/outatime)** package to facilitate operations on time series built as dictionaries.

The main requirement is that the _data_ attribute of the dataclass **TimeSeriesData** is a one-level dictionary.

E.g.
```
TimeSeriesData(
    day=date('2022-04-28'),
    data={
        'gold': 1887.77,
        'silver': 23.03
    }
)
```

Some features are added such as:
* interpolation of missing data
* trend and seasonality calculation
* methods of aggregation between dictionaries
* other

## Installation
To install it use:

```
pip install gregory
```

or download the last git version and use:

```
python setup.py install
```

## Framework Structure
```
gregory
├── dataclass
│   └── time_series_data.py --> Class used to manage daily data.
│
├── granularity
│   ├── granularity.py --> Set of classes used for managing time intervals of different length.
│   ├── granularity_factory.py --> Factory class for creating granularity objects.
│   └── utils.py --> Utils related to granularities.
│
├── timeseries
│   ├── batches.py --> Set of methods to operate on time series dividing them into batches.
│   ├── expr.py --> Set of operations between time series.
│   ├── processing.py --> Set of methods to elaborate time series.
│   └── time_series.py --> Core class that represents a series of daily records.
│
└── util
    ├── agenda.py --> Utils related to calendar info and evalutations.
    ├── bisect.py --> Utils related to binary search.
    ├── decorators.py --> Useful decorators.
    ├── dictionaries.py --> Utils related to operations on dictionaries.
    └── relativedelta.py --> Class that extends relativedelta with useful properties.
```

## License
MIT license, see ``LICENSE`` file.
sensamag 1.0.3
Utility library for sensamag data base

[![DeepSource](https://deepsource.io/gh/freezerain/sensamag_utility.svg/?label=active+issues&show_trend=true&token=tqqs40FSee57xeO0zqak7Fs1)](https://deepsource.io/gh/freezerain/sensamag_utility/?ref=repository-badge)
[![DeepSource](https://deepsource.io/gh/freezerain/sensamag_utility.svg/?label=resolved+issues&show_trend=true&token=tqqs40FSee57xeO0zqak7Fs1)](https://deepsource.io/gh/freezerain/sensamag_utility/?ref=repository-badge)

This package is used to update Sensamag database.

### Usage:
1. Install as standard pip package: `pip install sensamag`
2. Run any command with syntax: `sensamag <Optional connection params> <command> <command params>`
3. To see all available commands run: `sensamag --help`

### Examples:
1) To list all languages:`sensamag listlang`
2) Same but with different connection params: `sensamag --port 8080 --user IAmAUser listlang`
3) To add new language using helper: `sensamag addlang`
4) To add new language using oneliner: `sensamag addlang --name German --culture de-DE --priority 5`
5) To export data: `sensamag exportdb --path <path to folder to create *.csv>`

### CSV Schema:
To successfully import CSV data, headers should contain exact column names to be parsed.

Look up exact names with `sensamag csvschema`
price-alert-rhsm 0.0.4
Script to monitoring price.
Requires Python: >=3.8

# Price Alert

## Description

The purpose of the algorithm is to monitor the price of an asset and when it goes >= or <= to the prices we set, 
a pop up appears on the screen.

The script works as follows.
1. We get the asset price from the "STOCK" market (Microsoft = MSFT, Tesla=TSLA, Ambev=ABEV) using the yFinance library.
2. We monitor the target until the price we set. We have to enter a price above the current price and a price below the 
current price.

### Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install Price_alert.

```bash
pip install price-alert-rhsm
```

### Guide

```python
from price_alert.price_monitoring import PriceAlert

pa = PriceAlert(asset='TSLA', waiting_time=5)
pa.price_alert_request()
```

Output expected:

```
Consult at: 2022-10-07 12:01:09.266432
Ticker TSLA - Current price = $ 228.4
Type a price bigger than 228.4:
Type a price less than 228.4:
```

### Example:

![](static/test_package.gif)

**Note**: I ran this test on a Saturday, obviously the market was closed, to run the rule I set an equal price
current price to pop up the message box if the price is equal to or higher/lower than the current price.

After entering the values to monitor, just wait for the price movement to hit the target. When this occurs, the 
notification will appear in your window.

### Suggestion to new implementation

1. Monitor multiple assets. Consequently, we need alert for several assets.
2. Option to conversion result to others currency: BRL, EURO, BTC etc
3. Implement options to calculate the price to monitoring as percentual or value


## Author
Rafael Meireles
[LinkedIn](https://www.linkedin.com/in/rafa-hsm/)

## License
[MIT](LICENSE)