semvec/pypi-packages huggingface dataset:
drt-sdk-cli 0.0.1
Dharitri Smart Contracts Tools
Requires Python: >=3.8

# Description

## Documentation

[docs.dharitri.com](https://docs.dharitri.com/sdk-and-tools/sdk-py/)

## CLI

[CLI](CLI.md)

## Distribution

[drtpy-up](https://docs.dharitri.com/sdk-and-tools/sdk-py/installing-drtpy/) and [PyPi](https://pypi.org/project/drt-sdk-cli/#history)

## Development setup

Clone this repository and cd into it:

```
git clone https://github.com/DharitriOne/drt-sdk-py-cli.git
cd drt-sdk-py-cli
```

### Virtual environment

Create a virtual environment and install the dependencies:

```
python3 -m venv ./venv
source ./venv/bin/activate
pip install -r ./requirements.txt --upgrade
```

Install development dependencies, as well:

```
pip install -r ./requirements-dev.txt --upgrade
```

Above, `requirements.txt` should mirror the **dependencies** section of `setup.py`.

If using VSCode, restart it or follow these steps:

- `Ctrl + Shift + P`
- _Select Interpreter_
- Choose `./venv/bin/python`.

### Using your local `drtpy`

If you want to test the modifications you locally made to `drtpy`, set `PYTHONPATH` with the path to your local repository path.

For example, if you cloned the repository at `~/drt-sdk-py-cli`, run:

```
export PYTHONPATH="~/drt-sdk-py-cli"
```

Then `drtpy` will use the code in your local repository.
griffin-vision 0.0.0
A package for performing text-to-image and image-to-image searches using embedding-based techniques


### _Griffin-Vision_


`A package for performing text-to-image and image-to-image searches using embedding-based techniques`

#### _IMPORTANT_!

` Note: Before using the package , ensure your have follwing env variables "QDRANT_URL","QDRANT_API_KEY" `



#### _Usage_ 
```python
`Import`  
from griffin_vision.Core import Griffin

`Class initialization`

griffin_obj=Griffin(
    model_type="clip",
    vectorstore="qdrant",
    collectionname="user:project"
)
`Image Embeddings  Generation and Saving in VectorStore`

griffin_obj.generate_image_embeddings(
    new_collection=True , # OR False if collection already exists,
    imageurls=["https://samplelink/to/image1.jpg","https://samplelink/to/image2.jpg"]
)


`Text to Image Similarity Search`

search_result=griffin_obj.search_similar_images(text="query text",result_limit=1)
print(search_result)

```


> Author:Junaid Bashir
> Note:Currently Qdrant is the only supported vectorstore (new stores coming soon)
latestearthquake-indonesia-sokawera-PRIANTHON 0.0.1
This package will get the latest earthquake from BMKG | Meteorological, Climatological, and Geophysical Agency

# Latest Indonesia Earthquake
This package will get the latest earthquake from BMKG | Meteorological, Climatological, and Geophysical Agency

## HOW IT WORK?
This package will scrape from [BMKG](https://bmkg.go.id/) to get latest quake happened in Indonesia.

This package will use BeautifulSoup4 and Requests, to produce output in the form of JSON that is ready to be used in web of mobile applications
PyTouchBar 0.2.1
Use MacBook Pro's TouchBar in Python
Requires Python: >=3.2

Use MacBook Pro's TouchBar in Python. PyTouchBar make easy the use of the TouchBar with Python graphical modules Tkinter and Pygame (other are coming). Currently works with Buttons, Labels, Sliders, Steppers, ColorPickers, Popovers, Segmented Controls and Spaces.
See <a href="https://github.com/Maxmad68/PyTouchBar/wiki">my Github for docs</a>
drt-sdk-network-providers 0.0.1
Network providers for Dharitri Python SDK.
Requires Python: >=3.8

# drt-sdk-py-network-providers

Network providers for Dharitri Python SDK.

## Distribution
 
 - GitHub: `git+https://git@github.com/DharitriOne/drt-sdk-py-network-providers.git@v{Version}#egg=drt_sdk_network_providers`
 - [PyPi](https://pypi.org/user/xfactor.toml/)

## Documentation
[docs.dharitri.com](https://docs.dharitri.com/sdk-and-tools/moapy/)

## Development setup

Create a virtual environment and install the dependencies:

```
python3 -m venv ./venv
source ./venv/bin/activate
pip install -r ./requirements.txt --upgrade
```


Install development dependencies, as well:

```
pip install -r ./requirements-dev.txt --upgrade
```

Above, `requirements.txt` should mirror the **dependencies** section of `pyproject.toml`.

If using VSCode, restart it or follow these steps:
 - `Ctrl + Shift + P`
 - _Select Interpreter_
 - Choose `./venv/bin/python`.
 
### Tests

Run the tests as follows:

```
pytest .
```

### Linting

First, install [`pyright`](https://github.com/microsoft/pyright) as follows:

```
npm install --global pyright
```

Run `pyright`:

```
pyright
```

Run `flake8`:

```
flake8 drt_sdk_network_providers
```
pythonlemmy 0.3.0
A Python package for accessing the LemmyHttp API
Requires Python: >=3.7

# Pythonlemmy: a Python package for accessing the Lemmy API

<img src="https://github.com/Fedihosting-Foundation/plemmy/blob/main/img/plemmy.png" alt="drawing" width="325"/>

[![PyPI version](https://badge.fury.io/py/pythonlemmy.svg)](https://badge.fury.io/py/plemmy)
[![GitHub license](https://img.shields.io/badge/license-Apache-blue.svg)](https://raw.githubusercontent.com/Fedihosting-Foundation/plemmy/master/LICENSE.txt)

Pythonlemmy allows you to interact with any Lemmy instance using Python and the [LemmyHttp API](https://join-lemmy.org/api/classes/LemmyHttp.html).

Pythonlemmy is a fork of [plemmy](https://github.com/Fedihosting-Foundation/plemmy) that uses automatic code generation to keep the models and client as up to date as possible. The aim is to maintain an interface similar to plemmy.

**WARNING:** Pythonlemmy is still in development and needs testing!

## Installation ##

A PyPI repository is updated whenever a new version is available:

```
python -m pip install pythonlemmy
```

## Basic usage ##

Interact with a Lemmy instance using the _LemmyHttp_ object:

```python
from pythonlemmy import LemmyHttp

# create object for Lemmy.world, log in
srv = LemmyHttp("https://lemmy.world")
srv.login("<username_or_email>", "<password>")
```

Access specific communities:

```python
from pythonlemmy.responses import GetCommunityResponse

# obtain community, parse JSON
api_response = srv.get_community(name="Lemmy")
response = GetCommunityResponse(api_response)

# community info
community = response.community_view.community
print(community.name)
print(community.actor_id)
print(community.id)

# list community moderators
for person in response.moderators:
    print(person.moderator.name, person.community.name)
```

Create a post:

```python
from pythonlemmy.responses import PostResponse

# create post, parse JSON
api_response = srv.create_post(community.id, "Test post please ignore", "Body text")
response = PostResponse(api_response)

# post info
post = response.post_view.post
print(post.creator_id)
print(post.community_id)
print(post.name)
print(post.body)
```

Full documentation is on its way, but in the meantime check out our source code and some [examples](https://github.com/Fedihosting-Foundation/plemmy/tree/main/examples).

## Reporting issues, making contributions, etc. ##

Don't hesitate to report a bug or unexpected results! Want to contribute? Make a pull request.

## Credits

Pythonlemmy is a fork of [plemmy](https://github.com/Fedihosting-Foundation/plemmy), and credit for the structure and supporting functionality goes to its authors.
The client files (objects, views, responses, and lemmyhttp methods) are generated from parsing the source files of the [lemmy-js-client](https://github.com/LemmyNet/lemmy-js-client) project.
Documentation is automatically generated using the [lemmy_openapi_spec](https://github.com/MV-GH/lemmy_openapi_spec) project.