semvec/pypi-packages huggingface dataset:
libgeohash 0.1.1
Python library for interacting with geohashes.
License: MIT
Keywords: geohash,polygon to geohash,shapely,geohashes

## libgeohash

A python library for interacting with [geohashes](https://en.wikipedia.org/wiki/Geohash).  

The library is divided into 3 modules:
- __geohash_base__: Base functions for interacting with geohashes e.g. `encode`, `decode`, `neighbors`, `bbox` etc. 
- __distance_metrics__: Distance related functions e.g. `distance`, `dimensions` etc. 
- __geometry__: Functions for conversion of a polygon to a list of geohash and vice versa. e.g. `polygon_to_geohash`, `geohash_to_polygon`. Useful for approximating geographical regions with geohashes. Makes use of [shapely](https://pypi.org/project/Shapely/) library for geometric calculations.

### Installation

Linux and Mac users can install the package via pip. 

`$ pip install libgeohash`

### Usage

```python
>>> import libgeohash as gh

>>> gh.encode(57.64911, 10.40744, precision = 10)
'u4pruydqqv'

>>> gh.decode('u4pruydqqv', errors = True)
(57.64911264181137, 10.407437682151794, 2.682209014892578e-06, 5.364418029785156e-06)

>>> gh.neighbors('u4pruydqqv')
{'ne': 'u4pruydqrn', 'e': 'u4pruydqrj', 'n': 'u4pruydqqy', 'se': 'u4pruydqrh', 
'w': 'u4pruydqqt', 'sw': 'u4pruydqqs', 'nw': 'u4pruydqqw', 's': 'u4pruydqqu'}

# Returns dimensions of the bounding box referred by the geohash in meters. (width, height)
>>> gh.dimensions('u4pruyd')
(152.9, 152.4)

# Returns the great circle distance (Haversine) between two geohashes or coordinates. 
>>> gh.distance('u4pruyd', 'u4pruyg')
173.19066702376304

```

- For more functions and their usage, please refer to the doc strings. 

### Known issues
- Fails to approximate a polygon spanning across the [International Date Line](https://en.wikipedia.org/wiki/International_Date_Line) i.e. 180/-180 longitude. Shouldn't be much of a problem since there aren't any geographical entities that actually span across it due to nature of the line itself.  

If you happen to find any other bugs, please report them in the issues section.
japana 1.3
Japanese text analysis
License: MIT

# About 

This is Japana. a Japanese analysis tool using Jim Breen's JMdict & KanjiDic2 & mecab.


You need to provide a text: novel, short story, song lyrics, article, sentence ..etc. 
The program will return a word list ordered by frequency. 
each dictionary in the list has at least the word and the number of occurrence (frequency)
and depending on configurations: pronunciation and meaning

# Requirements

all requirements all stored in `requirements.txt`


# Installation:

1. run `pip install japana` in your venv/env/virtual_env
2. go to [Jamdict](https://github.com/neocl/jamdict)  official project and follow any instructions

# Other Projects

This project has been made into:
* CLI application: [Japana-CLI](https://github.com/reem-codes/japana-cli)
* Web app: [Japana](http://japana.reem-codes.com)

# what's new?
## 1.3:
* ability to ignore words with no definitions
* JLPT level provided
AnimatedGraphs 1.0
Build and awesome animated graph easily
License: MIT
Keywords: Animated,Graph,Visualisation

# AnimatedGraphs

Build and awesome animated graph easily
![](https://github.com/lgbaeza/py-animated-graph/raw/master/news_sample.gif)

## Installation

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

```bash
pip install AnimatedGraphs
```

## Usage

```python
import AnimatedGraphs as ag
from AnimatedGraphs import AnimatedBar as agBar

GRAPH_FILENAME = agBar.CreateGraphBar(
    dataset,
    args**
)
if (GRAPH_FILENAME != ""):
    print("Succeed. Animated grahBar available at {}" + GRAPH_FILENAME)
else:
    print("something went wrong")
```

You can find a notebook with sample usage here ![](https://github.com/lgbaeza/py-animated-graph)

## Args** details

| Argument                      | Required?     | Possible Values        | Default value / action |
| -------------                 | ------------- | --------------         | -------------          |
| DS                            |  Yes          |  numpy arr             |                        |
| AGGREGATION_TYPE              |  Yes          |  "COUNT", "SUM"        |                        |
| AGGREGATION_ATTRIBUTE_NAME    |  when AGG=SUM |  String                |                        |
| BAR_ATTRIBUTE_NAME            |  Yes          |  String                |                        |
| LOOP_ATTRIBUTE_NAME           |  Yes          |  String                |                        |
| SERIES_ATTRIBUTE_NAME         |  Yes          |  String                |                        |
| SERIES_ATTRIBUTE_NAME         |  Yes          |  String                |                        |
| GRAPH_XLABEL                  |  Opcional     |  String                | Empty                  |
| GRAPH_XLABEL                  |  Opcional     |  String                | Empty                  |
| IMAGE_SET_URL                 |  Opcional     |  String: URL to Zip    | <No image>             |
| IMAGE_SET_EXT                 |  Opcional     |  String                | <No image>             |
| SORT_BARS_LIST                |  Opcional     |  Array of String       | <No sorting>           |
| GRAPH_STEPS                   |  Opcional     |  Integer               | 10                     |
| GRAPH_FRAME_DURATION          |  Opcional     |  Float (0-3]           | 1.0                    |
| GRAPH_FILENAME                |  Opcional     |  String                | "animated-graph.gif"   |

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

## License
[MIT](https://choosealicense.com/licenses/mit/)
pathing 0.1.3
Mapping keys path to value derivation.
License: MIT

## Usage
```py
import pathing

root = (
    {
        0: {
            'some': [
                'data',
                'right'
            ],
            'here': True
        },
        'is': {
            False: 'too',
            'deep': {
                'for': {
                    'this': {
                        'depth': 'level'
                    }
                },
                'but': {
                    'here': 'it is just right'
                }
            }
        }
    }
)

for keys, value in pathing.derive(root, max = 4):

    print(keys, '->', value)
```
## Installing
```
python3 -m pip install pathing
```