semvec/pypi-packages huggingface dataset:
azure-utils 0.4.0
Azure Utilities
Requires Python: >=3.6

# Azure Utils
[![PyPI version](https://badge.fury.io/py/azure_utils.svg)](https://badge.fury.io/py/azure_utils)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

Azure Utilities for python

## Documentation
[Technical documentation](https://connor-makowski.github.io/azure_utils/azure_utils/blob_storage.html) can be found [here](https://connor-makowski.github.io/azure_utils/azure_utils/blob_storage.html).

## Setup

Make sure you have Python 3.6.x (or higher) installed on your system. You can download it [here](https://www.python.org/downloads/).
<details>
<summary>
Recommended (but Optional) -> Expand this section to setup and activate a virtual environment.
</summary>

  - Install (or upgrade) virtualenv:
  ```
  python3 -m pip install --upgrade virtualenv
  ```
  - Create your virtualenv named `venv`:
  ```
  python3 -m virtualenv venv
  ```
  - Activate your virtual environment
    - On Unix (Mac or Linux):
    ```
    source venv/bin/activate
    ```
    - On Windows:
    ```
    venv\scripts\activate
    ```
</details>

```
pip install azure_utils
```

### Basic Usage
```py
import os, sys
from azure_utils.blob_storage import AZContainer

# Get the working directory of this file
wd=os.path.abspath(os.path.dirname(sys.argv[0]))

# Create a container object
az = AZContainer(
    account_url="https://<account_name>.blob.core.windows.net",
    account_key="<account_key>",
    container_name="<container_name>"
)

# Get a list of all files in the container and print the first 5
files = az.list_files(remote_folderpath='/')
print(files[:5])

# Upload a file to the container
az.upload_file(
    remote_filepath='/test.csv',
    local_filepath=f'{wd}/test_data/upload/test.csv',
    overwrite=True
)

# Download the file from the container
az.download_file(
    remote_filepath='/test.csv',
    local_filepath=f'{wd}/test_data/download/test.csv',
    overwrite=True,
    smart_sync=True
)

# Delete the file from the container
az.delete_file(
    remote_filepath='/test.csv'
)

# Upload a folder to the container
az.sync_to_remote(
    remote_folderpath='/',
    local_folderpath=f'{wd}/test_data/upload/',
    overwrite=True,
)

# Download the folder from the container
az.sync_to_local(
    remote_folderpath='/',
    local_folderpath=f'{wd}/test_data/download/',
    overwrite=True,
    smart_sync=True,
)

# Delete all files in the container
az.delete_folder(
    remote_folderpath='/',
)

# Delete all local metadata
az.clear_local_meta(f'{wd}/test_data/')
```

Contributors:

- Alice Zhao
- Connor Makowski
personalcolorchecker 0.0.4
Shows your personal color check
Requires Python: >=3.7

# personalcolorchecker

By giving your photo as data, it will tell you your personal color based on your eye color and skin color.

# how to install personalcolorchecker
$ pip install personalcolorchecker

# how to personalcolor
Download "haarcascade_frontalface_default.xml"


$ import personalcolorchecker

$ import cv2


$ img = cv2.imread("image.jpg")

$ personalcolorchecker.personal_color(img)


<img src='https://github.com/harunearakage/personalcolor/blob/main/result.png' width=640 hight=480>
ua-clarity-api 1.1.6
Provides a simple REST implementation for use with Clarity endpoints.
Requires Python: >=3.11,<4.0

# UA-Clarity-API

Provides a simple REST implementation for use with Clarity endpoints.

## Motivation

Was designed to implement a simple way to interact with Clarity REST architecture.

## Features

- Get will do a batch get if that end point exists, otherwise it will return a response similar to what a batch get returns.
- Caller can add queries to get using a keyword.
- Caches every get to eliminate excessive get calls.
- All REST calls will throw an exception if they failed.

## Code Example

```python
from ua_clarity_api import ua_clarity_api


api = ua_clarity_api.ClarityApi(host, username, password)
uris_files = api.download_files("some file uri")
data = api.get("some endpoint")
```

## Installation

```bash
pip install ua-clarity-api
```

## Tests

```bash
pip install --update nose
cd ./repo
cd ./tests
nosetests test_ua_clarity_api.py
```

## How to Use

- You'll need to instantiate a ClarityApi object with a correct host, and the username/password to access that host's endpoints.
- Get can retrieve resources from endpoints and can utilize queries with the "parameters" keyword.
- Put and Post can update or create new resources given the appropriate endpoint and a well-formed payload.
- Delete can remove a resource from an endpoint.
- Download_files will create temporary files from a list of file uris and returns them as a dictionary mapping of uri: tempfile.

## Credits

[sterns1](https://github.com/sterns1)
[raflopjr](https://github.com/raflopjr)
[RyanJohannesBland](https://github.com/RyaJohannesBland)

## License

MIT
personalcolorcheck 0.0.3
Shows your personal color check
Requires Python: >=3.7

# personalcolorcheck

By giving your photo as data, it will tell you your personal color based on your eye color and skin color.

# how to install personalcolorcheck
$ pip install personalcolorcheck

# how to personalcolor
Download "haarcascade_frontalface_default.xml"


$ import personalcolorcheck

$ import cv2


$ img = cv2.imread("image.jpg")

$ personalcolorcheck.main()


<img src='https://github.com/harunearakage/personalcolor/blob/main/result.png' width=640 hight=480>
personalcolor0.0.2 0.0.2
Shows your personal color
Requires Python: >=3.7

# personalcolor0.0.2

By giving your photo as data, it will tell you your personal color based on your eye color and skin color.

# how to install personalcolor
$ pip install personalcolor

# how to personalcolor
Download "haarcascade_frontalface_default.xml"


$ import personalcolor

$ import cv2


$ img = cv2.imread("image.jpg")

$ personalcolor.main()


<img src='https://github.com/harunearakage/personalcolor/blob/main/result.png' width=640 hight=480>
apiperu 0.0.3
API de los 24 departamentos del Perú

# Api de los 24 departamentos del Perú

Paquete básico de los 24 departamentos del Perú

**Pasos:**
1. Instale Python mediante la página oficial: [Python](https://www.python.org/).
2. Asegúrese de tener el comando pip en el path de su ordenador.
3. Abra su terminal favorito y escriba el siguiente codigo:
   `pip install apiperu`
4. Listo, eso es todo.
housingLibrary-5508 0.1
Sample code for coding practice
Requires Python: >=3.11
Keywords: housing,data training

#This change is for the Pull request

# Median housing value prediction

The housing data can be downloaded from https://raw.githubusercontent.com/ageron/handson-ml/master/. The script has codes to download the data. We have modelled the median house value on given housing data. 

The following techniques have been used: 

 - Linear regression
 - Decision Tree
 - Random Forest

## Steps performed
 - We prepare and clean the data. We check and impute for missing values.
 - Features are generated and the variables are checked for correlation.
 - Multiple sampling techinuqies are evaluated. The data set is split into train and test.
 - All the above said modelling techniques are tried and evaluated. The final metric used to evaluate is mean squared error.

 ##Packaging python code and test it using score.py
 >> python -m build (Create a .tgz and .whl files of our project for the packing)
 >> twine upload dist.* (Upload our packaging files to the pypi to make it globally accesable to all users)
 -> Inorder to do upload the files to pypi we need to create an account in the pypi and generate and token.

## How to install the package and import the methods
1. Install the package name = housing-library-5512==0.1 
 >> pip install housing-library-5512==0.1
2. In code file use these statements to import the required methods.
 >> from src import fetch_housing_data, load_housing_data

## Testing with sample code for the package
-> We tested it by running score.py file to test the package