semvec/pypi-packages huggingface dataset:
EasyDataR 1.0
EasyDataR is a unofficial R package to read in data from EasyData platform of the State Bank of Pakistan
Keywords: R,EasyData,EasyDataR

# EasyDataR
EasyDataR is a unofficial R package to read in data from EasyData platform of the State Bank of Pakistan

# Details about EasyData of the State Bank of Pakistan
EasyData platform of the State Bank of Pakistan is the largest repository of Macroeconomic time-series. It has more than 2 million observations covering more than 11,000 time-series related to economy of Pakistan. 

# About the package
This package is intended to identify a session with EasyData API key, obtain information about a particular series of interest, and download a series of interest to R for further analysis. Although, I could have added reading in the series as time-series object in R and conduct basic analysis such as:

1. Plotting the time-series
2. Unit-Root tests
3. Seasonality tests
4. Cointegration tests and Cointegrated vector autoregressive model
5. Autoregressive and Vector Autoregressive models
6. Forecasting using Machine Learning and Dynamic Factor models (Rolling and Fixed Window Forecast)
7. In and Out-of-Sample Forecasts

But this package is not intended to conduct these analysis but I am programming another one, which will be able to perform all of these operations. Stay Tuned!

# How to install and use
The following provides detailed guide on how to install the EasyDataR package through Github and use functions within the EasyDataR

library(devtools)

devtools::install_github(("drateeb/EasyDataR"))

library(EasyDataR)

# Verifying EasyData API Key
EasyData_key_setup("C10D3D29160CE5693F56AA9846ABB2C423D8B123") <- type in/paste your EasyData API Key! 

# Finding if the EasyData API Key has been verified

session_has_Easydata_key()

# Getting the entered key for further use

get_Easydata_key()

# using the API key to get information on Weighted-average Overnight Repo Rate

get_info_on_series("TS_GP_IR_REPOMR_D.ORR",8)

# get data of the Weighted-average Overnight Repo Rate

WAORR<- download_series("TS_GP_IR_REPOMR_D.ORR",Easydata_key, "2015-05-25" ,"2023-12-20", "csv")

# taking a look at the head of the data

head(WAORR)

# Tranforming WAORR data to a usable time-series

build_time_series(WAORR)

# Plotting the time-series saved through build_time_series in object called "time_series"

plot_time_series(time_series)
streamlit-g2 0.1.1
Render G2 charts in Streamlit
Requires Python: >=3.6
Keywords: antv,g2,streamlit-component,streamlit-g2

<h1 align="center">
  <b>Streamlit G2</b>
</h1>

<div align="center">

[G2](https://github.com/antvis/G2) is a visualization grammar for dashboard building, data exploration and storytelling.

This project was created to allow us to render [G2](https://github.com/antvis/G2) charts in streamlit. [Live Demo](https://antv-g2.streamlit.app/).

![examples](https://mdn.alipayobjects.com/huamei_qa8qxu/afts/img/A*_GfqQoRCqQkAAAAAAAAAAAAADmJ7AQ/fmt.webp)

[![PyPI version](https://badge.fury.io/py/streamlit-g2.svg)](https://badge.fury.io/py/streamlit-g2)
[![Build Status](https://github.com/antvis/g2/workflows/build/badge.svg?branch=v5)](https://github.com/antvis//actions)
[![Coverage Status](https://img.shields.io/coveralls/github/antvis/g2/v5.svg)](https://coveralls.io/github/antvis/g2?branch=v5)
[![npm Version](https://img.shields.io/npm/v/@antv/g2.svg)](https://www.npmjs.com/package/@antv/g2)
[![npm Download](https://img.shields.io/npm/dm/@antv/g2.svg)](https://www.npmjs.com/package/@antv/g2)
[![npm License](https://img.shields.io/npm/l/@antv/g2.svg)](https://www.npmjs.com/package/@antv/g2)

</div>


## Installation

```
pip install streamlit-g2 
```


## Usage

```py
import streamlit as st
from streamlit_g2 import g2

options = {
    "type": "interval",
    "data": [
        { "genre": 'Sports', "sold": 275 },
        { "genre": 'Strategy', "sold": 115 },
        { "genre": 'Action', "sold": 120 },
        { "genre": 'Shooter', "sold": 350 },
        { "genre": 'Other', "sold": 150 },
    ],
    "encode": {
        "x": "genre",
        "y": "sold",
        "color": "genre",
    }
}

g2(options=options, style=None, key="streamlit_g2")
```

<img src="https://mdn.alipayobjects.com/huamei_qa8qxu/afts/img/A*XqCnTbkpAkQAAAAAAAAAAAAADmJ7AQ/fmt.webp" width="640" alt="example">


## API

Now, There is only one API for `streamlit-g2`, named `g2`, see the `options` in [G2 Spec API](https://g2.antv.antgroup.com/manual/core/api).

| Property | Description                                                                                                     | Type                  | Default |
| -------- | --------------------------------------------------------------------------------------------------------------- | --------------------- | ------- |
| options  | the [options](https://g2.antv.antgroup.com/manual/core/api) for the visualization, say `chart.options(options)` | `G2options` \| `null` | -       |
| style    | the style of the container                                                                                      | `CSSProperties`       | -       |


## Development

- Building frontend code by running `npm run start` in fold `streamlit_g2/frontend`.
- Run the example by running `streamlit run streamlit_g2/__init__.py` with `_RELEASE = False`.


## License

MIT@[hustcc](https://github.com/hustcc).
hikvision-isapi-py 1.1.1
HIKVision ISAPI python library
Requires Python: >=3.8

# hikvision-isapi-py

Simple client to interact with Hikvision devices using the ISAPI protocol.

Source code: <https://github.com/jackblk/hikvision-isapi-py>

## Ignore SSL verification

Can be useful if you are using self-signed certificates or the web server
certificate is not trusted by your client.

Set the environment variable `VERIFY_SSL` to `false` (anything but `true` will skip the check)
resistorcalc 0.0.2
The ResistorCal is an tool used to find the resistor values by giving the input colors
Keywords: resistor value calculator,color code resistor calculator,resistor color to value,resistor code decoder,Electronics,Resistor value finder,color code,color bands,numeric values,calculate resistor value from color bands,online resistor color code tool,how to identify resistor value by color,resistor value conversion tool,resistorcal,resistorcal tool,resistorcal color code calculator,electronics component calculator,electrical engineering tool,color code to resistance converter,electronic projects resistor tool,learn resistor color code,resistor coding guide,educational resistor tool,understanding resistor color bands,DIY electronics resistor tool,compare resistor calculators,best resistor value tool,india resistor color code tool

# ResistorCalc

ResistorCalc is a graphical user interface (GUI) application built with Tkinter for calculating the resistance value and tolerance of resistors based on their color bands. This tool provides an interactive way to input color bands, visualize the resistor code, and obtain accurate resistance information.

![resistorcalc](../banner/resistorcalc.png)


## Features

- **Color Code Visualization:** The application visually represents the color code of resistors on a canvas for easy interpretation.
  
- **Flexible Band Selection:** Users can select the number of bands (4, 5, or 6) to accommodate various resistor types.
  
- **Calculation Accuracy:** The tool follows the standard resistor color code to accurately calculate resistance values and tolerances.
  
- **Clear and Calculate:** Clear input fields and results with the "Clear" button, and calculate the resistor values with the "Calculate" button.

## Getting Started

1. **Installation:**
   - Ensure you have Python3 installed on your system.
   - Clone this repository: `https://gitlab.com/harichella005/resistorcalc.git`
   - Navigate to the project directory: `cd ResistorCalc`
   - `cd lib && chmod +x resistorcalc.py`
   - `sudo ln -s "$(pwd)/resistorcalc.py" /usr/bin/resistorcalc`
   - `resistorcalc`

2. **Run the Application:**
   - Execute the following command: `python3 resistorcalc.py`

3. **Usage:**
   - Enter the color bands of the resistor in the entry field.
   - Select the number of bands using checkboxes.
   - Click the "Calculate" button to obtain the resistor value and tolerance.
   - Use the "Clear" button to reset the input and results.

## Happy Resistor Calculations!

ResistorCalc is designed to simplify the process of resistor value and tolerance calculations. Enjoy exploring the colorful world of resistors, and may your electronic projects be as harmonious as a well-calculated resistor network!
ResistorCalc 0.0.1
The ResistorCal is an tool used to find the resistor values by giving the input colors
Keywords: resistor value calculator,color code resistor calculator,resistor color to value,resistor code decoder,Electronics,Resistor value finder,color code,color bands,numeric values,calculate resistor value from color bands,online resistor color code tool,how to identify resistor value by color,resistor value conversion tool,resistorcal,resistorcal tool,resistorcal color code calculator,electronics component calculator,electrical engineering tool,color code to resistance converter,electronic projects resistor tool,learn resistor color code,resistor coding guide,educational resistor tool,understanding resistor color bands,DIY electronics resistor tool,compare resistor calculators,best resistor value tool,india resistor color code tool

# ResistorCalc

ResistorCalc is a graphical user interface (GUI) application built with Tkinter for calculating the resistance value and tolerance of resistors based on their color bands. This tool provides an interactive way to input color bands, visualize the resistor code, and obtain accurate resistance information.

![resistorcalc](../banner/resistorcalc.png)


## Features

- **Color Code Visualization:** The application visually represents the color code of resistors on a canvas for easy interpretation.
  
- **Flexible Band Selection:** Users can select the number of bands (4, 5, or 6) to accommodate various resistor types.
  
- **Calculation Accuracy:** The tool follows the standard resistor color code to accurately calculate resistance values and tolerances.
  
- **Clear and Calculate:** Clear input fields and results with the "Clear" button, and calculate the resistor values with the "Calculate" button.

## Getting Started

1. **Installation:**
   - Ensure you have Python3 installed on your system.
   - Clone this repository: `https://gitlab.com/harichella005/resistorcalc.git`
   - Navigate to the project directory: `cd ResistorCalc`
   - `cd lib && chmod +x resistorcalc.py`
   - `sudo ln -s "$(pwd)/resistorcalc.py" /usr/bin/resistorcalc`
   - `resistorcalc`

2. **Run the Application:**
   - Execute the following command: `python3 resistorcalc.py`

3. **Usage:**
   - Enter the color bands of the resistor in the entry field.
   - Select the number of bands using checkboxes.
   - Click the "Calculate" button to obtain the resistor value and tolerance.
   - Use the "Clear" button to reset the input and results.

## Happy Resistor Calculations!

ResistorCalc is designed to simplify the process of resistor value and tolerance calculations. Enjoy exploring the colorful world of resistors, and may your electronic projects be as harmonious as a well-calculated resistor network!
compute-geometry 0.1.0
Computational Geometry Library
Requires Python: >=3.8,<4.0.0

<h1 align="center">
<img src="logo.png" width="400">
</h1>

Welcome to the **compute-geometry** library, a comprehensive computational geometry library for Python. This library is designed to provide a set of tools and algorithms for solving geometric problems, making it a valuable resource for developers and researchers working in areas such as computer graphics, robotics, and geographic information systems.

## Features

- **Geometry Primitives:** Efficient implementations of fundamental geometric primitives, including points, lines, and polygons.
  
- **Algorithms:** A variety of computational geometry algorithms, such as convex hull computation, line segment intersection, and Voronoi diagram generation.

- **Geometry Operations:** Functions for performing common geometric operations, such as distance calculations, area computations, and geometric transformations.

- **Visualization:** Functions for visualizing geometric objects and algorithms using Matplotlib.

- **Documentation:** Comprehensive documentation with usage examples to help you quickly integrate the library into your projects.

## Installation

You can install the **compute-geometry** library using `pip`:

```bash
pip install compute-geometry
```

## Getting Started

To get started with the _compute-geometry_ library, import it into your Python script or project:

```python
import compute-geometry as cgeom
```

Explore the library's documentation to understand the available functionality and how to use it effectively.

## Examples

Here are some examples to demonstrate how to use the Geometry library:

```python
# Example 1: Compute the convex hull of a set of points

from cgeom.algorithms import ConvexHull

# create a list of points
points = [(326, 237),(373, 209), (378, 265), (443, 241), (396, 231), (416, 270), (361, 335), (324, 297)]

# create a convex hull object with the list of points
convex_hull = ConvexHull(points)

# plot the convex hull
convex_hull.plot()

# print the indexes of the points that form the convex hull
print('Convex Hull: ', convex_hull.get_indexes())


# Example 2: Compute Voronoi diagram of a set of points

from cgeom.voronoi import VoronoiDiagram

# load a set of points
points = np.loadtxt("./points1.txt")

# create a voronoi diagram object
voronoi = VoronoiDiagram(points)

# build the voronoi diagram
cells = voronoi.build_voronoi_diagram()

# plot the voronoi diagram
voronoi.plot_voronoi(cells)

```

## Contributing

Contributions to the _compute-geometry_ library are welcome! If you have additional algorithms, improvements, or bug fixes, please submit a pull request. Be sure to follow the [contribution guidelines](CONTRIBUTING.md) outlined in the repository.

## License

This library is licensed under the [MIT License](LICENSE), allowing you to use, modify, and distribute it for both commercial and non-commercial purposes.

Start exploring the world of computational geometry with the _compute-geometry_ library in Python!