semvec/pypi-packages huggingface dataset:
anders-sdk-jupyterlite 2.34.0
Jupyterlite client library for Cognite Data Fusion (CDF)
Requires Python: >=3.5

<a href="https://cognite.com/">
    <img src="https://github.com/cognitedata/cognite-python-docs/blob/master/img/cognite_logo.png" alt="Cognite logo" title="Cognite" align="right" height="80" />
</a>

Cognite Python SDK
==========================
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This is the Cognite Python SDK for developers and data scientists working with Cognite Data Fusion (CDF). 
The package is tightly integrated with pandas, and helps you work easily and efficiently with data in Cognite Data 
Fusion (CDF).

## Documentation
* [SDK Documentation](https://cognite-docs.readthedocs-hosted.com/en/latest/)
* [API Documentation](https://doc.cognitedata.com/)
* [Cognite Developer Documentation](https://docs.cognite.com/dev/)

## Prerequisites
In order to start using the Python SDK, you need
- Python3 (>= 3.5) and pip
- An API key. Never include the API key directly in the code or upload the key to github. Instead, set the API key as an environment variable. See the usage example for how to authenticate with the API key.

This is how you set the API key as an environment variable on Mac OS and Linux:
```bash
$ export COGNITE_API_KEY=<your API key>
```

On Windows, you can follows [these instructions](https://www.computerhope.com/issues/ch000549.htm) to set the API key as an environment variable.

## Installation
To install this package:
```bash
$ pip install cognite-sdk
```

To install this package without the pandas and NumPy support:
```bash
$ pip install cognite-sdk-core
```

## Examples
For a collection of scripts and Jupyter Notebooks that explain how to perform various tasks in Cognite Data Fusion (CDF) 
using Python, see the GitHub repository [here](https://github.com/cognitedata/cognite-python-docs)

## Changelog
Wondering about upcoming or previous changes to the SDK? Take a look at the [CHANGELOG](https://github.com/cognitedata/cognite-sdk-python/blob/master/CHANGELOG.md).

## Contributing
Want to contribute? Check out [CONTRIBUTING](https://github.com/cognitedata/cognite-sdk-python/blob/master/CONTRIBUTING.md).
cv-io 1.1.0
A collection of I/O scripts for computer vision formats.
Requires Python: >=3.5

# Computer Vision I/O
This python package, Computer Vision I/O which is knwon as **_cv\_io_**, is a collection of existing python scripts which provides a set of I/O functions for normal and irregular image formats in computer vision.

## File Format Support
File format | Desciption
------------|-------------
*.png, *.jpg, ... | All normal images
*.flo | Middleburry optical flow
*.dpt | Middleburry floating point depth
*.pfm | Freiburg floating point disparity
*.exr | OpenXR hdr format
*.jxr | MicroSoft JPEG-XR hdr format


## Main Fucntions
Function | Desciption
---------|------------
imread (file\_name) | Reads an image from "file\_name"
imwrite (file\_name, image) | Saves the "image" array to "file\_name"
imshow (image) | Displays the "image" array by matplotlib
imshow (file\_name) | Displays an image file from "file\_name"

## Requirements
Package requirement are listed in [requirements.txt](requirements.txt) file and it will be installed through `pip` isntallation. If you clone the repository you may install requirements manually:

```shell
pip install -r requirements.txt
```

***
# Install as a Python Package

You can also download and install the **Simple Image Viewer** as a python package by:
```
python -m pip install cv_io
```
or simply 
```
pip install cv_io
```
Then you can simply import it in a python code and use it as follows:
```python
import cv_io
image = cv_io.imread('samples/0512.pfm')
cv_io.imshow(image)
cv_io.imwrite('test.pfm', image)
```
You also have acess to the original libraries like `sintel_io` through the `cv_io` as a sub-module: 
```python
import cv_io
image = cv_io.sintel_io.depth_read ('samples/frame_0020.dpt')
cv_io.sintel_io.depth_write('test.dpt', image)
```

***
_Copyright &copy; 2020 [Saeid Hosseinipoor](https://saeid-h.github.io/). Released under the [MIT License](LICENSE)._
gsk-geo-encryption 1.0
Geological Password Encryption

# Note: Internet is mandatory for getting your current location

## Project Description

This program is to create a encryption password with a given Key and can get access when both the encryption  is at same location as 
   the password is created with the latitude and longitude
----------------------------------------------------------------
# Change the ipinfo API Token (if needed):

Code:
     <p>gsk_geo_encryption.TOKEN="API_TOKEN"</p>
----------------------------------------------------------------
## Getting the encrypted_password and timer with a class:


Code:
<p>object1=gsk_geo_encryption.Keys()<p>
password,seconds=object1.password_encrypted()

----------------------------------------------------------------
Classes: 
        <p> Keys
----------------------------------------------------------------
Inbuilt Functions(Unchangable):
<p>
                  geo_lat_long_convertor()
<p>
                  encryption()
<p></p>
----------------------------------------------------------------
<p>
Usable Functions(Changable):<p>
                            password_encrypter
<p>

---------------------------------------------------------------
Exceptions:
<p>
           ConnectionError