semvec/pypi-packages huggingface dataset:
uvcclient 0.12.2
A remote control client for Ubiquiti's UVC NVR
Requires Python: >=3.10

Client for Ubiquiti's Unifi Camera NVR
======================================

.. image:: https://travis-ci.org/kk7ds/uvcclient.svg?branch=master
    :target: https://travis-ci.org/kk7ds/uvcclient

This is extremely raw at the moment. Use at your own risk.

Hopefully this is enough to get you going::

  Usage: uvc [options]

  Options:
    -h, --help            show this help message and exit
    -H HOST, --host=HOST  UVC Hostname
    -P PORT, --port=PORT  UVC Port
    -K APIKEY, --apikey=APIKEY
                          UVC API Key
    -v, --verbose
    -d, --dump
    -u UUID, --uuid=UUID  Camera UUID
    --name=NAME           Camera name
    -l, --list
    --recordmode=RECORDMODE
                          Recording mode (none,full,motion)
    --recordchannel=RECORDCHANNEL
                          Recording channel (high,medium,low)
    -p, --get-picture-settings
                          Return picture settings as a string
    --set-picture-settings=SET_PICTURE_SETTINGS
                          Set picture settings with a string like that returned
                          from --get-picture-settings
    --set-led=ENABLED     Enable/Disable front LED (on,off)
    --get-snapshot        Get a snapshot image and write to stdout
    --prune-zones         Prune all but the first motion zone
    --list-zones          List motion zones
    --set-password        Store camera password

For example::

 $ export UVC="http://192.168.1.1:7080/?apiKey=XXXXXXXX"
 $ uvc --name Porch --recordmode motion --recordchannel high

or::

 $ export UVC="http://192.168.1.1:7080/?apiKey=XXXXXXXX"
 $ uvc -l
 fb9e6d48-6f5a-42b2-8cb4-e3705a99a0e2: Inside                   [    online]
 f0579c60-e400-477e-8f89-f8861ef58f80: Parking                  [    online]
 998b134e-13ea-4465-ad39-6ad27b067ac4: Spare                    [   offline]
 5474242a-51d5-428e-97de-826675068e70: Front Porch              [    online]
 715f0725-e7e1-4214-a551-41071c82bacd: Garage                   [    online]

In order to take actions on cameras directly (such as change the LED
state on a UVC Micro or get a snapshot from the camera) you need to
set the admin password for it. The NVR tells us the username, but we
must store the password. To do this::

 $ uvc --name Porch --set-password
 This will store the administrator password for a camera
 for later use. It will be stored on disk obscured, but
 NOT ENCRYPTED! If this is not okay, cancel now.

 Password:
 Confirm:
 Password set

Then you can do things like get a snapshot from the camera directly::

 $ uvc --name Porch --get-snapshot > foo.jpg
NofearDB 1.0.0
A small database management system package for an embedded NoSQL database which can be used by multiple hosts in parallel.
Requires Python: >=3.6

# NofearDB

Welcome to NofearDB, the NoSQL database system without the headache.

NOFEAR stands for:

- **No**SQL: NofearDB is document based and relies on json.
- **F**ast: NofearDB is designed for good performance despite many read and write accesses on the filesystem.
- **E**mbedded: NofearDB does not require to run a database server.
- **A**nd: Thats not all!
- **R**eliable: Despite its simplicity and design, NofearDB enables stable data storage, even with concurrent access in multi-user environments.

NofearDB combines the simplicity and flexibility of NoSQL databases like MongDB with schema based approaches of relational databases like MySQL. Therefore you get a handy ORM workflow but with json documents instead of database tables. Because there is no need for a database server and fixed schema tables, every database and every document is self contained, easily backupable and very insusceptible to programming and user errors. This makes NofearDB a perfect fit for small and medium sized applications, where relational data is to be persisted without much effort.

## Features

- Combines the best of both worlds: Relational and NoSQL Database.
- Full Object-Relational-Mapping.
- Simple and with minimal setup requirements. No database Server is needed.
- Works with concurrent read and write operations.
- High performance for small datasets (up to a few thousand entities).
- Dependency free.
- 100% test coverage.

## Documentation

The full documentation can be found here: https://no-fear-db.readthedocs.io

## Disclaimer

Even though NofearDB is designed to work with concurrency, a serverless database system can never be as secure as a conventional system. Every effort has been made to manage concurrent read and write accesses, but the risk of problems occurring can only be reduced to a minimum. There is no guarantee that problems with concurrent accesses are 100% excluded. It is therefore not recommended to use NofearDB in multi-user environments for critical data.

NofearDB is in an early beta stage. Despite sufficient testing, there is no guarantee that it is error-free. The use of NofearDB is at your own risk. In the event of damage, no liability is assumed by the developers or the author.

## Contributing

Whether reporting bugs, discussing improvements and new ideas or writing extensions: Contributions to NofearDB are welcome! Here's how to get started:

1. Check for open issues or open a fresh issue to start a discussion around a feature idea or a bug.
2. Fork the repository on Github, create a new branch off the master branch and start making your changes (known as GitHub Flow).
3. Write a test which shows that the bug was fixed or that the feature works as expected.
4. Send a pull request and bug the maintainer until it gets merged and published.
chep 0.1
Un paquete para extraer el puerto SSH del servicio chep
Requires Python: >=3.6

# chep

Este paquete permite extraer el puerto SSH desde el estado del servicio `chep` ejecutado con `systemctl`.

## InstalaciÃ³n

InstÃ¡lalo directamente desde PyPI con:

```bash
pip install chep
```

## Uso

```python
from chep import chep

puerto = chep()
print(puerto)
```
day-trading-models 0.1.0
SQL models for day trading
Requires Python: >=3.6

# Day Trading Models
![Unit Test](https://github.com/Andimeo/day-trading-models/actions/workflows/unittest.yml/badge.svg)


This repository contains a collection of SQLAlchemy models for day trading analysis and data management. These models are designed to be used in various projects related to stock market analysis, particularly focusing on the Chinese A-share market.

## Features

- Comprehensive set of models covering various aspects of day trading:
  - Opening dates
  - Fund flows
  - Limit up (涨停) and limit down (跌停) stocks
  - Large orders (龙虎榜)
  - Quotations
  - Strong stocks
  - Sub-new stocks
  - And more...
- SQLAlchemy ORM for easy database integration
- Designed for flexibility and reusability across different projects

## Installation

You can install this package using pip:

```bash
pip install day_trading_models
```

## Usage

Here's a basic example of how to use these models:

```python
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from day_trading_models import OpeningDate, Dt, Zt, Lhb, Fund

# Create an engine and session
engine = create_engine('your_database_url')
Session = sessionmaker(bind=engine)
session = Session()

# Create tables
OpeningDate.__table__.create(engine, checkfirst=True)
Dt.__table__.create(engine, checkfirst=True)
Zt.__table__.create(engine, checkfirst=True)
Lhb.__table__.create(engine, checkfirst=True)
Fund.__table__.create(engine, checkfirst=True)

# Example: Add an opening date
new_date = OpeningDate(date='2023-05-01')
session.add(new_date)

# Example: Query Zt (limit up) stocks
zt_stocks = session.query(Zt).filter(Zt.date == '2023-05-01').all()

# Example: Add a new fund flow record
new_fund = Fund(
    date='2023-05-01',
    sse_close_price=3000.0,
    sse_change=0.02,
    # ... other fields ...
)
session.add(new_fund)

session.commit()
```

## Models

- `OpeningDate`: Trading calendar dates
- `Dt`: Stocks hitting lower price limits
- `Fund`: Fund flow information
- `Lhb`: Large order ("龙虎榜") data
- `LhbHyyyb`: Active brokerage branches in large orders
- `LhbPlayer`: Individual players in large orders
- `Quotation`: Stock quotations
- `Strong`: Strong performing stocks
- `Subnew`: Newly listed stocks
- `Zb`: Stocks that hit the upper price limit but failed to maintain it until market close (炸板股)
- `Zt`: Stocks hitting upper price limits

## Development

To set up the development environment:

1. Clone the repository
2. Install development dependencies:
   ```bash
   pip install -r requirements-dev.txt
   ```
3. Run tests:
   ```bash
   pytest
   ```

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## License

This project is licensed under the MIT License.
tekdate 0.1
tekdate format is a clear, human-readable date format designed to simplify global date handling and eliminate regional confusion.
Requires Python: >=3.6

# **tekdate** Format

Yes, I am done with ISO date format. thats why i come up the new format.

**tekdate** is a new date and time format designed for clarity and consistency across platforms.
Each component of the date and time is explicitly labeled to remove any ambiguity, making it easier to read and process.
It supports optional timezone information and can be used across programming languages and systems.

## Why this format?

We donâ€™t need colons, slashes, or other date separators because they can sometimes make it difficult to distinguish between the day and month, and we might not always be sure which format is being used. This often depends on the country or format settings in software like Excel. This format is designed to be more human-readable, avoiding confusion while still adhering to common standards. The reason I didnâ€™t use capital letters is to emphasize the date itself, making it easier for the eye to distinguish between numbers and letters.

## tekdate Format Structure

### Components:

- `yYYYY`: Year (e.g., `y2024` for the year 2024)
- `mMM`: Month (e.g., `m03` for March)
- `dDD`: Day (e.g., `d02` for the 2nd day)
- `hHH`: Hour in 24-hour format (e.g., `h20` for 8 PM)
- `mMM`: Minute (e.g., `m15` for 15 minutes)
- `sSSS`: Seconds and milliseconds (e.g., `s205` for 205 milliseconds)
- `zÂ±ZZZZ` (Optional): Timezone offset from UTC (e.g., `z+0530` for Indian Standard Time)

### Example with Timezone:

-> y2024m10d04h13m59s000z+0000

## Key Features

- **Clarity**: Every part of the date and time is explicitly labeled (year, month, day, etc.).
- **Time Zone Support**: Optional timezone component (`zÂ±ZZZZ`), or omit it for local/unspecified time.
- **Consistency**: WIll Work across platforms and programming languages(Soon).
- **Machine-Readable**: Predictable structure that is easy to parse and generate programmatically.

## Clear and Distinguishable Date Format for Simplified Handling

The custom date format y2024m10d04h13m59s000z+0000 is designed to prevent confusion and improve human readability. By clearly labeling each date and time component (e.g., "y" for year, "m" for minute), it ensures that the format is immediately understandable and eliminates ambiguity. This structure makes it easy to distinguish between different elements without relying on traditional delimiters like dashes or colons, simplifying parsing for both humans and systems. Additionally, concerns over storage efficiency are minimal given modern capacities, so the focus on clarity and ease of interpretation offers a more practical approach. This format is highly intuitive and ready for use in any context where both accuracy and simplicity are prioritized.

## Installation

...
pip install tekdate

### Python Installation

...

### Node installation

...