semvec/pypi-packages huggingface dataset:
enipy 0.50
Tool for analyzing Lightning Data

# Enipy tool
This is a python package used for data analysing and visualizing Lightning (https://en.wikipedia.org/wiki/Lightning) data provided by Earth Networks. 
Earth Networks is a leader in locating and collecting Lightning data for over 20 years. Enipy python package is extremely beneficial 
for Scientists and Engineers, who want to decode and use Earth networks Lightning data for research. 

The entire library is implemented using Cython (C extension for Python), which makes it very efficient to process Big data.  
If you have any questions about the package, please contact Micheal Stock (mstock@earthnetworks.com) and Jeff Lapierre (jlapierre@earthnetworks.com).
pycheckey 0.3
Ensure nested dictionary structure.
Requires Python: >3.5.2

# PyChecKey

Ever have JSON or a large dictionary that you want to validate before you jump deeper into it? PyChecKey allows you to check a dictionary-like object against a defined structure.

This works with Python 3.5+.

## Components

Below are the components and common examples of how to use them.

### KeyEnsurer

A `KeyEnsurer` allows checking against a dictionary-like structure. 

```python
from pycheckey import KeyEnsurer


data = {
    "key1": 4,
    "key2": {
        "innerKey": "hi"
    }
}

ensurer = KeyEnsurer(data=data, required_keys=['key1', 'key2.innerKey', 'key3'])

ensurer.validate()  # Will return false because key3 does not exist!
print(ensurer.missing)  # ['key3']

ensurer.key_exists(data, 'key2.inner')  # Returns true because data[key2][inner] exists

```

## Local Development

To work on this repository, you need `virtualenv`. Clone it first, then run the following two commands.

```bash
$ virtualenv -p python3 venv
$ source venv/bin/activate
```

### Running Tests

Run `pytest` from the root directory to run all tests.

### Linting

Run `pylint` from the root directory to lint the code files.