semvec/pypi-packages huggingface dataset:
ssb-datahub 0.1.3
Client for the SSB datahub platform
License: MIT
Requires Python: >=3.10,<4.0

<br />
<div align="center">
  <img src="images/logo.png" alt="Logo" width="80" height="80">
  <br />
  <h2 align="center">DATAHUB PYTHON CLIENT</h2>
  <br />
  <p align="center">

[![Poetry](https://img.shields.io/endpoint?url=https://python-poetry.org/badge/v0.json)](https://python-poetry.org/)
[![Black](https://img.shields.io/badge/code%20style-black-000000.svg)][black]
[![PyPI](https://img.shields.io/pypi/v/ssb-datahub.svg)][pypi status]
[![Python Version](https://img.shields.io/pypi/pyversions/ssb-datahub)][pypi status]
[![License](https://img.shields.io/pypi/l/ssb-datahub)][license]
  </p>
  <p align="center">
    Client library for DataHub, a data platform developed at Statistics Norway
  </p>
  <br />
</div>

[license]: https://github.com/statisticsnorway/ssb-datahub/blob/main/LICENSE
[pypi status]: https://pypi.org/project/ssb-datahub/
[black]: https://github.com/psf/black

## Getting started

### Prerequisites

* [Install poetry](https://python-poetry.org/)

### Development environment

* Clone the repository
* Install the poetry environment

  ```sh
    poetry install
  ```

## Usage

```sh
pip install ssb-datahub
```

```python
from ssb_datahub import Client
dh = Client()

# Collect variables
kjonn = dh.get_variable("FREG", "BEFOLKNING_KJONN", "1.0.0")
fornavn = dh.get_variable("FREG", "BEFOLKNING_FORNAVN", "1.0.0")
fodt_aar = dh.get_variable("FREG", "BEFOLKNING_FODT_AAR", "1.0.0")

# Get the most popular names of men born in 1993
navnestatistikken_menn = (
    kjonn
        .left_join(fornavn, "IDENTIFIER")
        .filter("BEFOLKNING_KJONN", "1")
        .left_join(fodt_aar, "IDENTIFIER")
        .filter("BEFOLKNING_FODT_AAR", 1993)
        .count_values("BEFOLKNING_FORNAVN")
        .sort("BEFOLKNING_FORNAVN")
)
navnestatistikken_menn.sources
```
raster2polygon 0.0.1
A package for extracting vector prints from raster image
License: MIT

## Raster 2 Polyon

Extracting vector polygons from raster images 

### Installation 
```
pip install raster2polygon
```

### Example : 
 
```python
from raster2polygon import polygonize

polygonize("data/masks_v2/4", "labels.geojson")
```

### Args : 

```
input_path: Path of the directory where the image files are stored.
output_path: Path of the output file.
remove_inputs: Clears the input image after geojson is produced
simplify_tolerance : the simplification accuracy as max. percentage of the arc length, in [0, 1] , Percentage Tolerance= ( Tolerance in Meters​ / Arc Length in Meters)×100
merging_distance_threshold : Minimum distance to define adjacent polygons, in meters , default 0.5 m
area_threshold (float, optional): Threshold for filtering polygon areas. Defaults to 1 sqm.
```
kot-secret 0.1.1
The cloud secret save system for your python applications !
License: MIT
Requires Python: >= 3

# KOT Secret

The cloud secret save system for your python applications ! Control everything from one place and distribute all clients without effort.

[Website](https://kotdatabase.dev/) | [Discord](https://discord.gg/QtnKf532Er) | [Twitter](https://twitter.com/kot_database)




## Installation
You can install KOT by pip3:

```console
pip3 install kot_secret
```




# Implementing

## 1) Encrypted and Free Version
We suggest to use in your individual projects because this way not provide any control process so everyone can add credientials.

*Creating Your Free Cloud Key
```console
KOT cloud_key
```

```python
from kot_secret import KOT_Secret
secrets = KOT_Secret("YOUR_ENCRYPTION_KEY", "YOUR_CLOUD_KEY")

secrets.add_secret("SECRET_NAME", "SECRET")
#secrets.delete_secret("SECRET_NAME")

secrets.get_secret("SECRET_NAME") # In another.py, Diffferent Machine, Different Environment
```


## 2) Encrypted and Pro Version
We suggest to use in your individual projects because this way not provide any control process so everyone can add credientials.

*For this you should have [KOT Cloud Pro](https://docs.kotdatabase.dev/kot_cloud.html#cloud-pro--)

```python
from kot_secret import KOT_Secret_Pro
secrets = KOT_Secret_Pro("YOUR_ENCRYPTION_KEY", "YOUR_CLOUD_PRO_KEY", "YOUR_ACCESS_KEY")

secrets.add_secret("SECRET_NAME", "SECRET")
#secrets.delete_secret("SECRET_NAME")

secrets.get_secret("SECRET_NAME")# In another.py, Diffferent Machine, Different Environment
```

## 3) Encrypted and Secure Version
You can free for all purposes.


*For this you should have [KOT Cloud Dedicated](https://docs.kotdatabase.dev/kot_cloud.html#cloud-dedicated)


```python
from kot_secret import KOT_Secret_Dedicated
secrets = KOT_Secret_Dedicated("YOUR_ENCRYPTION_KEY", "YOUR_DATABASE_NAME", "YOUR_ADMIN_PASSWORD", "YOUR_DEDICATED_KEY")

secrets.add_secret("SECRET_NAME", "SECRET")
#secrets.delete_secret("SECRET_NAME")

secrets = KOT_Secret_Dedicated("YOUR_ENCRYPTION_KEY", "YOUR_DATABASE_NAME", "YOUR_USER_PASSWORD", "YOUR_DEDICATED_KEY")

secrets.get_secret("SECRET_NAME") # In another.py, Diffferent Machine, Different Environment and CUSTOMER
```





## Contributing
Contributions to KOT Secret are welcome! If you have any suggestions or find a bug, please open an issue on the GitHub repository. If you want to contribute code, please fork the repository and create a pull request.

## License
KOT Secret is released under the MIT License.

<h2 align="center">
    Contributors
</h2>
<p align="center">
    Thank you for your contribution!
</p>
<p align="center">
    <a href="https://github.com/KOT-database/KOT-Secret/graphs/contributors">
      <img src="https://contrib.rocks/image?repo=KOT-database/KOT-Secret" />
    </a>
</p>