semvec/pypi-packages huggingface dataset:
streamlit_react_jsonschema 0.1.6
streamlit component for GhostOS, render form from JSONSchema by react-jsonschema-component
License: MIT
Requires Python: !=2.7.*,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,!=3.7.*,>=3.8

# Streamlit-react-jsonschema

Streamlit component, 
building form by [react-jsonschema-form](https://react-jsonschema-form.readthedocs.io/).

This library is experimental for [GhostOS](https://github.com/ghost-in-moss/GhostOS) yet.

## Installation

install `streamlit-react-jsonschema` with pip

```bash
pip install streamlit_react_jsonschema
```

## Example

see [baseline example](examples/baseline.py)

```python
from typing import Union, List, Dict
import streamlit as st
import streamlit_react_jsonschema as srj
import inspect
from pydantic import BaseModel, Field


class Student(BaseModel):
    name: str = Field(description="name of the student")
    level: int = Field(description="level of the student")


class SomeClass(BaseModel):
    """
    test class of pydantic model Foo
    """
    name: Union[str, None] = Field(None, description="filed with optional[str]")
    age: int = Field(0, description="bar value")
    some_float: float = Field(description="test about float value")

    students: List[Student] = Field(default_factory=list, description="list of students")
    students_dict: Dict[str, Student] = Field(default_factory=dict, description="dict of students")


st.title("Streamlit-react-jsonschema Example")
with st.expander("source code of the example pydantic class", expanded=True):
    codes = inspect.getsource(SomeClass)
    st.code(codes)

value, submitted = srj.pydantic_form(model=SomeClass)

st.subheader("result:")
st.write(f"submitted: {submitted}")
st.write(f"type of the result: {type(value)}")
st.write(value)
if isinstance(value, BaseModel):
    st.write("model dump value")
    st.write(value.model_dump(exclude_defaults=False))
```

How to run this example? Check [streamlit](https://docs.streamlit.io/) first~

## Dependencies

- [Streamlit](https://streamlit.io/)
- [React-jsonschema-form](https://react-jsonschema-form.readthedocs.io/): render the form from json schema
- [Material UI](https://mui.com/) : use `@rjsf/mui` theme from the `react-jsonschema-form`
- [pydantic](https://docs.pydantic.dev/latest/) : generate json schema
TrackingNet 0.0.9
TrackingNet SDK
License: MIT
Keywords: TrackingNet, SDK, Tracking, Video


# TrackingNet devkit

```bash
conda create -n TrackingNet python pip
pip install TrackingNet
```

## Utility functions for TrackingNet

```python
from TrackingNet.utils import getListSplit

# Get list of codenames for the 12 training + testing split
TrackingNetSplits = getListSplit()
print(getListSplit())
# returns ["TEST", "TRAIN_0", "TRAIN_1", "TRAIN_2", "TRAIN_3", "TRAIN_4", "TRAIN_5", "TRAIN_6", "TRAIN_7", "TRAIN_8", "TRAIN_9", "TRAIN_10", "TRAIN_11"]


# Get list of tracking sequences
print(getListSequence(split=TrackingNetSplits[1])) # return list of tracking sequences in that split
print(getListSequence(split="TEST")) # return list of tracking sequences for testing
print(getListSequence(split=["TRAIN_0", "TRAIN_1"])) # return list of tracking sequences for train splits 0 and 1
print(getListSequence(split="TRAIN")) # return list of tracking sequences for al train splits
```

## Downloading TrackingNet

```python
from huggingface_hub import login
login(token="<TOKEN_HUGGINGFACE>") # https://huggingface.co/settings/tokens -> Create a new token

from TrackingNet.Downloader import TrackingNetDownloader
downloader = TrackingNetDownloader(LocalDirectory="path/to/TrackingNet")

downloader.downloadSplit("TRAIN_0")
downloader.downloadSplit("TEST")

from TrackingNet.utils import getListSplit
for split in getListSplit():
    downloader.downloadSplit(split)
```
ShellDonX 0.1.2
Shell code converter
License: MIT
Requires Python: >=3.11.0

# Packages
My list of APT and Twine packages

# Shell_Don

This project provides a Python script to encode and decode shell commands in various formats.  This is a command-line interface (CLI) script.
There is a GUI available in another method below.

## Features

- Encode shell commands to:
  - Hexadecimal
  - Base64
  - URL encoding
  - HTML encoding
  - JSON encoding
  - Markdown encoding
  - Binary encoding
  - Substitution cipher
- Generate decoding commands for each encoded format
- Preview decoding commands without executing them
- Custom decoding commands

## Installation

Ensure you have Python 3.x.x installed. Then, install the required packages with:

```bash
sudo dpkg -i shell_don.deb
```

```bash
pip install shell-don
```

```bash
pip install -r requirements.txt
```

For the GUI version:
```bash
git clone https://github.com/DeadmanXXXII/Shell_Don.git
```

### Usage

There are two ways to use this with a GUI which has nmore features ot the CLI for quick on the go access:

### GUI Script

To launch the GUI:

```bash
Copy code
python gui_script.py --gui
```

### CLI Script for packages

To use the CLI script:

```bash
shell_don <command> <substitution_key> [--preview] [--custom-decoding <command>]
```

### Arguments:

<command>: The shell command to encode.
<substitution_key>: The substitution cipher key (0-61).

### Options:

--preview: Preview the decoding commands without executing them.
--custom-decoding <command>: Custom decoding command. Overrides default decoding commands.

## Examples:

### Encode a command with the GUI:
Run the script with the --gui flag.
Enter your shell command and substitution key.
Click "Generate" to see the encoded formats and decoding payloads.

### Encode a command with the CLI:

```bash
shell_don "ls -la" 3 --preview
```


This will encode the command ls -la with a substitution key of 3 and display the decoding commands.

License
This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgements:
Built by DeadmanXXXII.


### Note

You can now use these scripts for encoding and decoding shell commands with both a graphical interface and command-line interface.

![Usage](https://raw.githubusercontent.com/DeadmanXXXII/Shell_Don/main/Nethunter-use_OP_Top.png)

![Usage](https://raw.githubusercontent.com/DeadmanXXXII/Shell_Don/main/Nethunter-use_OP_bottom.png)