semvec/pypi-packages huggingface dataset:
roboweb-extension 0.1.42
Roboweb JupyterLab extension
Requires Python: >=3.7
Keywords: Jupyter,JupyterLab,JupyterLab3

# roboweb-extension

![Github Actions Status](https://github.com/github_username/roboweb-extension/workflows/Build/badge.svg)

Roboweb extension

## Requirements

* JupyterLab >= 3.1

## Install

```bash
pip install roboweb-extension
```

## Contributing

### Development install

Note: You will need NodeJS to build the extension package.

The `jlpm` command is JupyterLab's pinned version of
[yarn](https://yarnpkg.com/) that is installed with JupyterLab. You may use
`yarn` or `npm` in lieu of `jlpm` below.

```bash
# Clone the repo to your local environment
# Change directory to the roboweb-extension directory
# Install package in development mode
pip install -e .
# Link your development version of the extension with JupyterLab
jupyter labextension develop . --overwrite
# Rebuild extension Typescript source after making changes
jlpm run build
```

You can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.

```bash
# Watch the source directory in one terminal, automatically rebuilding when needed
jlpm run watch
# Run JupyterLab in another terminal
jupyter lab
```

With the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).

By default, the `jlpm run build` command generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:

```bash
jupyter lab build --minimize=False
```

### Uninstall

```bash
pip uninstall roboweb-extension
```

## Updating the version

To update the version, install tbump and use it to bump the version.
By default it will also create a tag.

```bash
pip install tbump
tbump <new-version>
```
moonstream-entity 0.0.5
Moonstream entity API client library

## Moonstream Entity Python Client and CLI

In order to use this client, you will need a Moonstream access token. You can generate one at https://moonstream.to/account/tokens.

Detailed documentation you can find at https://docs.moonstream.to/engine/entity

The client library reads this token from the `MOONSTREAM_ACCESS_TOKEN` environment variable. To set it:

```bash
export MOONSTREAM_ACCESS_TOKEN="<your_access_token>"
```

Install package from PyPI:

```bash
pip install moonstream-entity
```

Import and initialize client in your code:

```python
import os

from entity.client import Entity

MOONSTREAM_ACCESS_TOKEN = os.environ.get("MOONSTREAM_ACCESS_TOKEN")

ec = Entity()
response = ec.list_collections(
    token=MOONSTREAM_ACCESS_TOKEN,
    timeout=10,
)

print(response.json())
```

### Work with collections via CLI

Create collection:

```bash
entity --token "$MOONSTREAM_ACCESS_TOKEN" collections create --name "My Ethereum addresses"
```

List collections:

```bash
entity --token "$MOONSTREAM_ACCESS_TOKEN" collections list
```

Delete collection:

```bash
export MOONSTREAM_ENTITY_COLLECTION_ID="<your_collection_id>"

entity --token "$MOONSTREAM_ACCESS_TOKEN" collections delete --collection_id "$MOONSTREAM_ENTITY_COLLECTION_ID"
```

### Work with entities via CLI

```bash
export MOONSTREAM_ENTITY_COLLECTION_ID="<your_collection_id>"
```

Create entity:

```bash
entity --token "$MOONSTREAM_ACCESS_TOKEN" entities create --collection_id "$MOONSTREAM_ENTITY_COLLECTION_ID" --address "0x000000000000000000000000000000000000dEaD" --blockchain ethereum --name "Dead address" --required_field '{"dead": true}' --required_field '{"owner": "unknown"}' --secondary_field '{"description": "Dangerous address for tokens burning mechanism."}'
```

Create entity bulk from csv:

Input file `addresses.csv` contains list of addresses:

```csv
address,name
0xe1991fFb1f2271Bc645293cCDf4e38a3f1b7a13c,Address 1
0x37309157eC7863b04c66B6fB2bf7b21EE8B03bA1,Address 2
```

```bash
entity --token "$MOONSTREAM_ACCESS_TOKEN" entities bulk --blockchain ethereum --collection_id "$MOONSTREAM_ENTITY_COLLECTION_ID" --input addresses.csv --required_field '{"owner": "me"}' --secondary_field '{"description": "My bot address"}'
```

List entities in collection:

```bash
entity --token "$MOONSTREAM_ACCESS_TOKEN" entities list --collection_id "$MOONSTREAM_ENTITY_COLLECTION_ID"
```

Delete entity:

```bash
export MOONSTREAM_ENTITY_ID="<your_entity_id>"

entity --token "$MOONSTREAM_ACCESS_TOKEN" entities delete --collection_id "$MOONSTREAM_ENTITY_COLLECTION_ID" --entity_id "$MOONSTREAM_ENTITY_ID"
```
Streamlit-DragDrop 0.0.1
Streamlit component of draggable list
Requires Python: >=3.6

Streamlit component
Example:

> pip install streamlit-component-DragDrop </br>


<code>
import streamlit as st </br>
from st_dragdrop_list import ST_DragDropList </br>

st.title("Streamlit DragDropList")

data = [</br>
    {"id": "element_1", "order": 0, "name": "Test regel 1"}, </br>
    {"id": "element_2", "order": 1, "name": "Test regel 2"}, </br>
    {"id": "element_3", "order": 2, "name": "Test regel 3"}, </br>
]

st_list = ST_DragDropList(data, key="my_list") </br>
elements = [element['name'] for element in st_list] </br>
st.write(elements)
</code>