semvec/pypi-packages huggingface dataset:
neso-utils 1.0.6
Library of utilities for NESO.
Requires Python: <4.0,>=3.10

<!-- <p align='center'>
    <img src='./.docs/cctv.png' width='20%' height='20%'>
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<h1 align='center'>
    <strong> neso-utils </strong>
</h1>

<p align='center'>
    Library of utilities for NESO.
</p>

### **1. Installation**

```bash
pip install neso-utils
```

### **2. Utilities**

- [Synthetic Data Generator](./neso_utils/synthetic_data_generator/README.md) [![coverage](https://img.shields.io/badge/coverage-100%25-brightgreen) ![tests](https://img.shields.io/badge/tests-35%20passed%2C%200%20failed-brightgreen) ![python](https://img.shields.io/badge/python-3.10-blue?logo=python&logoColor=white)]

- [Assessment Report](./neso_utils/assessment_report/README.md) [![coverage](https://img.shields.io/badge/coverage-98%25-brightgreen) ![tests](https://img.shields.io/badge/tests-14%20passed%2C%200%20failed-brightgreen) ![python](https://img.shields.io/badge/python-3.10-blue?logo=python&logoColor=white)]

- [Schema Validation](./neso_utils/schema_validation/README.md) [![coverage](https://img.shields.io/badge/coverage-99%25-brightgreen) ![tests](https://img.shields.io/badge/tests-62%20passed%2C%200%20failed-brightgreen) ![python](https://img.shields.io/badge/python-3.10-blue?logo=python&logoColor=white)]

### **3. Example of Usage**

#### **3.1. Synthetic Data Generator**

```python
from neso_utils import SyntheticDataGenerator
```

#### **3.2. Assessment Report**

```python
from neso_utils import AssessmentReport
```

#### **3.3. Schema Validation**

```python
from neso_utils import SchemaCertifier
```

### **4. Documentation [TBC]**

[Documentation](https://neso-utils.readthedocs.io/en/latest/)
stocks-historical 1.0.1
A Python package to access historical stock data for NASDAQ and NYSE.
Requires Python: >=3.7

# Stocks Historical Library 📊

A Python library for accessing historical stock data from major stock exchanges and equity markets. This library simplifies the process of fetching and formatting stock data using the [Stocks Historical API](https://github.com/mantey-github/stock-fetcher-api), making it easy to retrieve and analyze stock data programmatically. Currently, it supports data for top 100 stocks from NYSE and NASDAQ markets, with plans to include data from additional markets in the future.

Library inspired by [Yahoo Historical](https://github.com/AndrewRPorter/yahoo-historical).

---

## Features
- Retrieve historical stock data for NASDAQ and NYSE.
- Supports specifying date ranges with start and optional end dates.
- Formats data into Pandas DataFrames for easy analysis.
- Fetch Open, High, Low, and Close data.

---

## Installation
Install the library via pip:
```bash
pip install stocks-historical
```

---

## Usage

#### **Import and Initialize**
You can use the `Nasdaq` or `Nyse` classes to fetch stock data:
```bash
from stocks_historical import Nasdaq, Nyse

# Fetch NASDAQ data
nasdaq_data = Nasdaq(symbol="AAPL", start="2023-01-03", end="2023-01-09")  # Start and end are dates (YYYY-MM-DD)
data = nasdaq_data.get_data()
print(data.head())

# Fetch NYSE data
nyse_data = Nyse(symbol="GE", start="2023-01-03")  # End is optional
data = nyse_data.get_data()
print(data.head())

```

**Output**:
The data is returned as a Pandas DataFrame with columns:

- `Date:` Timestamp of the record (in human-readable format).
- `Open:` Opening price of the stock.
- `High:` Highest price of the stock.
- `Low:` Lowest price of the stock.
- `Close:` Closing price of the stock.

**Example DataFrame:**
```bash
Fetched Data:
                 Date     Open     High     Low   Close
0 2023-01-03 01:00:00  130.280  130.900  124.17  125.07
1 2023-01-04 01:00:00  126.890  128.656  125.08  126.36
2 2023-01-05 01:00:00  127.130  127.770  124.76  125.02
3 2023-01-06 01:00:00  126.010  130.290  124.89  129.62
4 2023-01-09 01:00:00  130.465  133.410  129.89  130.15
```

---

## API Reference
This library is built on top of the Stocks Historical API. If you prefer to work directly with the API, refer to the API repository for documentation: [Stocks Historical API](https://github.com/mantey-github/stock-fetcher-api)


---

## Credits
The stock data used in this library is sourced from **Kaggle Datasets**:

1. [Top 100 NYSE Daily Stock Prices](https://www.kaggle.com/datasets/svaningelgem/nyse-100-daily-stock-prices) by Steven Van Ingelgem

2. [Top 100 NASDAQ daily stock prices](https://www.kaggle.com/datasets/svaningelgem/nasdaq-100-daily-stock-prices) by Steven Van Ingelgem

All credits goes to the Kaggle community for providing these datasets!

---

## Contributions
Contributions are welcome 🤗! If you'd like to improve this library, feel free to fork the repository and submit a pull request.
quectel-at 1.1.0
This is a library for Quectel Modules.

# Quectel-5G-LTE-Module-Library
This is a library for Quectel Modules.

<img src="https://market.samm.com/Data/EditorFiles/RM520N-GL-details-size.jpg" alt="Connections tab" width="300"/>

## Installation
```
pip install quectel_at
```

Thanks to[![GitHub](https://img.shields.io/badge/GitHub-black?style=flat&logo=GitHub)](https://github.com/iXenonN) @iXenonN
Quectel-AT 1.0.0
This is a library for Quectel Modules.

# Quectel-5G-LTE-Module-Library
This is a library for Quectel Modules.

<img src="https://market.samm.com/Data/EditorFiles/RM520N-GL-details-size.jpg" alt="Connections tab" width="300"/>

## Installation
```
pip install Quectel-AT
```

Thanks to[![GitHub](https://img.shields.io/badge/GitHub-black?style=flat&logo=GitHub)](https://github.com/iXenonN) @iXenonN