semvec/pypi-packages huggingface dataset:
alphasense-api-sdk 0.1.10
AlphaSense API SDK

# AlphaSense API SDK

## Installation

Before installing; you should create the virtual environment

```bash
pip install alphasense-api-sdk
```

or specify the version

```bash
pip install alphasense-api-sdk==0.1.0
```

Or adding the `alphasense-api-sdk` to the `pyproject.toml` file

```toml
dependencies = [
  "alphasense-api-sdk==0.1.0"
]
```

or `requirements.txt` file

```txt
alphasense-api-sdk==0.1.0
```

## Usage

- Create `pyproject.toml` file
- Add the following to the `pyproject.toml` file

```toml
[alphasense.auth]
username = "<your username>"
password = "<your password>"
api_key = "<your api key>"
client_id = "<your client id>"
client_secret = "<your client secret>"
```

- Writing the code to fetch the watchlists with raw GraphQL query

```python
from alphasense_api_sdk.client import Client, GraphQLField

async def main():
    client = Client()
    w = await client.query(
        GraphQLField("user { watchlists { id name }}"), operation_name="user_watchlists"
    )
    print("Watchlists: ", w)


if __name__ == "__main__":
    import asyncio

    asyncio.run(main())
```

- Or using the `Query` object to search for documents

```python
from alphasense_api_sdk.client import Client, GraphQLField
from alphasense_api_sdk.custom_queries import Query, SearchResponseFields


async def main():
    client = Client()
    df = SearchResponseFields.documents()
    search_query = Query.search(limit=5).fields(
        SearchResponseFields.documents().fields(
            df.id,
            df.title,
            df.released_at,
            GraphQLField("type { ids }"),
        )
    )
    docs = await client.query(search_query, operation_name="searchDocs")
    print("> docs: ", docs)


if __name__ == "__main__":
    import asyncio

    asyncio.run(main())

```
gym-kr1 0.1.5
A gymnasium environment for the KR1 robot.
Requires Python: <3.11,>=3.10

# Gym KR1

A gymnasium environment for the KR1 robot.


<img src="gym_kr1/assets/images/gym_kr1_ex02.png" width="50%" alt="Basic bullet-based environment for KR1"/>


## Quickstart

```python
# ex01_simple.py
import imageio
import gymnasium as gym
import numpy as np
import gym_kr1

env = gym.make("gym_kr1/KR1BoxEnv-v0")
observation, info = env.reset()
frames = []

for _ in range(1000):
    action = env.action_space.sample()
    observation, reward, terminated, truncated, info = env.step(action)
    image = env.render()
    frames.append(image)

    if terminated or truncated:
        observation, info = env.reset()

env.close()
imageio.mimsave("ex01_simple.mp4", np.stack(frames), fps=25)
```
pypasslib 1.1
A Python module containing a list of a million passwords to use for educational purposes only
Requires Python: >=3.6

## Pypasslib
pypasslib is a Python package that contains a list of a million passwords for educational purposes only. This package provides sample phrases that can be used for testing, research, and educational activities.

# Installation
You can install pypasslib using pip:

bash:
pip install pypasslib

# Usage
Once installed, you can easily access the list of passwords from the package:

python:

from pypasslib import pypass

for password in pypass:
    print(password) #...learn it urself
# License
This project is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License. You may use this package for non-commercial educational purposes only. Redistribution and modification are prohibited.

# Contributing
As this project is intended for educational purposes only, contributions are not currently accepted.

Author:
Opticz
Email: cartiscott45@gmail.com
GitHub: Opticz45