semvec/pypi-packages huggingface dataset:
cryptocompare-python 0.0.2
See currency changes
Requires Python: >=3.0

# cryptocompare-Python-API

[![CodeQL](https://github.com/Alejandro193/CryptoCurrency/actions/workflows/codeql-analysis.yml/badge.svg)](https://github.com/Ventura94/NOWPayments-Python-API/actions/workflows/codeql-analysis.yml)
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A Python wrapper for the [Cryptocompare API](https://min-api.cryptocompare.com/documentation). 

The api call descriptions are from the official documentation.

## Getting Started
To get your API Key visit [Cryptocompare Web Site](https://www.cryptocompare.com/cryptopian/api-keys) but is not implemented yet in this package


To install the wrapper, enter the following into the terminal.
```bash
pip install cryptocompare-python
```

API Key is optional here
```python
from cryptocompare-py import CryptoCurrency
currency = CryptoCurrency()

simple_exchange_rate = currency.get_single_exchange_rate('BTC','USD')
print(simple_exchange_rate)

multiple_exchange_rate = currency.get_multiple_exchange_rate('BTC','USD','EUR','CAD')
print(multiple_exchange_rate)
```
data-drift-detector-mightyhive 0.0.4
A data drift detection and schema validation package
Requires Python: ==3.8

## About The Package
The package is a wrapper of tensorflow data validation for our specific needs.
It can analyze training data and serving data to compute desscriptive
statistics, infer a schema, and detect anomalies.

## Dependencies

* [tensorflow-data-validation](https://www.tensorflow.org/tfx/data_validation/get_started)


## Installation
```sh
pip install data-drift-detector
```
<!-- USAGE EXAMPLES -->
## Usage

Initialize a Harvest client:
```python
# The Dataset, TrainDataset, ServeDataset can be initialized with different methods.

train = TrainDataset.from_GCS()
train = TrainDataset.from_bigquery()
train = TrainDataset.from_dataframe()
train = TrainDataset.from_stats_file()
```

Populate the class variables and submit.
```python
# Get training dataset schema
schema = train.schema_dict()
```