semvec/pypi-packages huggingface dataset:
orm-2-sql-visualizer 1.0.1
Visualize your ORM queries as SQL queries and get additional stats about your queries.
License: MIT
Requires Python: >=3.11

Django Middleware Package
=========================

Visualize what SQL Query is being executed with additional stats.


Installation
------------
1. Install the package using pip:

    pip install django-orm-2-sql-visualizer

2. Add the middleware to your settings.py file:

    'orm-2-sql-visualizer.middleware.new_middleware',
drug-smile-fet 1.0.5
This tool provides methods to extract meaningful features from drug SMILES for AI-Based Drug Development.
License: MIT
Requires Python: >=3.8
Keywords: Drug SMILE,Feature Extraction,NLP,Morgan Fingerprints,Drug Discovery,Drug Development,AI-Based Drug Discovery,AI-Based Drug Development

## Pre-requisites
Install RdKit library:
- instllation through [anaconda](https://anaconda.org/rdkit/rdkit)
- instllation through [pip](https://pypi.org/project/rdkit-pypi/) 

## Usage

- Make sure you have Python installed in your system.
- Run Following command in the CMD.
 ```
  pip install drug-smile-fet
  ```
## Example

 ```
# example.py
from dsfet import fe_1mol
import pandas as pd
train_smiles = {'DRUG_NAME': {0: 'Luminespib', 1: 'Trametinib', 2: 'Venetoclax', 3: 'Olaparib', 4: 'Axitinib'},
                'PUBCHEM_ID': {0: 135539077.0, 1: 11707110.0, 2: 49846579.0, 3: 23725625.0, 4: 6450551.0},
                'SMILES': {0: 'CCNC(=O)C1=NOC(=C1C2=CC=C(C=C2)CN3CCOCC3)C4=CC(=C(C=C4O)O)C(C)C',
                           1: 'CC1=C2C(=C(N(C1=O)C)NC3=C(C=C(C=C3)I)F)C(=O)N(C(=O)N2C4=CC=CC(=C4)NC(=O)C)C5CC5',
                           2: 'CC1(CCC(=C(C1)C2=CC=C(C=C2)Cl)CN3CCN(CC3)C4=CC(=C(C=C4)C(=O)NS(=O)(=O)C5=CC(=C(C=C5)NCC6CCOCC6)[N+](=O)[O-])OC7=CN=C8C(=C7)C=CN8)C',
                           3: 'C1CC1C(=O)N2CCN(CC2)C(=O)C3=C(C=CC(=C3)CC4=NNC(=O)C5=CC=CC=C54)F',
                           4: 'CNC(=O)C1=CC=CC=C1SC2=CC3=C(C=C2)C(=NN3)/C=C/C4=CC=CC=N4'}
                }
train_smiles_df = pd.DataFrame(data=train_smiles)

test_smile = train_smiles
test_smile_df = pd.DataFrame(test_smile)

#Example 1: to call NLP-based feature extraction method
#Train, Test, feature_sequences, feature_to_token_map = fe_1mol.oneMolFeatureExtraction(trainSMILES=train_smiles_df, testSMILES=train_smiles_df,ngram_list=[1,2,3,4,5,6,7,8])
Train, Test, feature_sequences, feature_to_token_map = fe_1mol.oneMolFeatureExtraction(trainSMILES=train_smiles_df, testSMILES=None,ngram_list=[1,2,3,4,5,6,7,8])

#Example 2: to call Morgan Fingerprints based feature extraction method
#nBits is the number of bits in the fingerprint
result= fe_1mol.morganFingerPrint(train_smiles_df, nBits=1024)

```
### Note: 
The input to the method ```oneMolFeatureExtraction() and morganFingerPrint()``` must be a pandas DataFrame and the Drug SMILES column name must be in uppercase:
- e.g., SMILES

### Cite us at:
Rahul Sharma, & Jake Y. Chen. (2022). Drug SMILE Feature Extraction Tool (1.0.3). Zenodo. [https://doi.org/10.5281/zenodo.7072304](https://doi.org/10.5281/zenodo.7072304)
farcaster-cli 0.1.5
Farcaster CLI Client
License: MIT
Requires Python: >=3.7.2,<4.0.0

# farcaster-cli

<div align="center">

[![Python Version](https://img.shields.io/pypi/pyversions/farcaster-cli.svg)](https://pypi.org/project/farcaster-cli/)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![chat](https://img.shields.io/badge/chat-telegram-blue)](https://t.me/+aW_ucWeBVUZiNThh)

farcaster-cli is a CLI client for the Farcaster protocol<br></br>

</div>

## Installation

```bash
pip install farcaster-cli
```

or install with [Poetry](https://python-poetry.org/):

```bash
poetry add farcaster-cli
```

## Usage

This client leverages the Warpcast API. [Warpcast](https://warpcast.com/) is one of many Farcaster [clients](https://github.com/a16z/awesome-farcaster#clients). As more APIs are created and hosted by different clients, these will be added to the CLI.

To use the Warpcast API you need to have a Farcaster account. We will use the mnemonic or private key of the Farcaster custody account (not your main wallet) to connect to the API.

First, save your Farcaster mnemonic or private key to a $MNEMONIC environment variable. Now you can initialize the client, and automatically connect.


```bash
export MNEMONIC = <your custody seed phrase here>
```

```bash
farcaster-cli $MNEMONIC --watch-all
```

This subscribes to all recent casts. If you want only the casts of people you follow, remove `--watch-all`.
You can also include `--skip-existing` to only get new casts after the client starts.