semvec/pypi-packages huggingface dataset:
json-repr 1.1.12
Handle JSON like data structures with a "repr(...)" fallback, e.g. for MongoDB types
Requires Python: >=3.6
Keywords: JSON,MongoDB,dumps,eval,repr

# json-repr

Pretty print JSON like data structures with a "repr(...)" fallback, e.g. for MongoDB types

## Usage

```python
import json_repr

# JSON: Legacy Mongo Shell Format
original_source = """{
    "_id": ObjectId("507f1f77bcf86cd799439011"),
    "employees": [
        {
            "firstName": "Alice",
            "middleName": null,
            "id": NumberInt(1),
            "active": true
        },
        {
            "firstName": "Bob",
            "middleName": null,
            "id": NumberInt(2),
            "active": false
        }
    ]
}"""

document = json_repr.eval_mongo_db_json(original_source)

print(document["employees"][0])

dumped_source = json_repr.dumps(document)
print(dumped_source)

print(dumped_source == original_source)
```

## MongoDB

Currently supported (legacy) mongo shell types:

* ObjectId
* NumberInt
* NumberLong
* NumberDecimal

and

* null
* true
* false
ak_cache 0.0.5
General Cache File to cache anything you like

<!--- Heading --->
<div align="center">
  <h1>ak_cache</h1>
  <p>
    Cache any data for your python projects
  </p>
<h4>
    <a href="https://github.com/rpakishore/ak_cache/">View Demo</a>
  <span> · </span>
    <a href="https://github.com/rpakishore/ak_cache">Documentation</a>
  <span> · </span>
    <a href="https://github.com/rpakishore/ak_cache/issues/">Report Bug</a>
  <span> · </span>
    <a href="https://github.com/rpakishore/ak_cache/issues/">Request Feature</a>
  </h4>
</div>
<br />

![GitHub commit activity](https://img.shields.io/github/commit-activity/m/rpakishore/ak_cache)
![GitHub last commit](https://img.shields.io/github/last-commit/rpakishore/ak_cache)
<!-- Table of Contents -->
<h2>Table of Contents</h2>

- [1. About the Project](#1-about-the-project)
  - [1.1. Features](#11-features)
- [2. Getting Started](#2-getting-started)
  - [2.1. Prerequisites](#21-prerequisites)
  - [2.2. Installation](#22-installation)
- [3. Usage](#3-usage)
- [4. Roadmap](#4-roadmap)
- [5. License](#5-license)
- [6. Contact](#6-contact)
- [7. Acknowledgements](#7-acknowledgements)

<!-- About the Project -->
## 1. About the Project

<!-- Features -->
### 1.1. Features

- Read and write data to a Cached Pickle File

<!-- Getting Started -->
## 2. Getting Started

<!-- Prerequisites -->
### 2.1. Prerequisites

<!-- Installation -->
### 2.2. Installation

Install my-project with flit

```bash
git clone https://github.com/rpakishore/ak_cache.git
cd ak_cache
pip install flit
flit install
```

Alternatively, you can use pip

```bash
pip install ak_cache
```

<!-- Usage -->
## 3. Usage

Use this space to tell a little more about your project and how it can be used. Show additional screenshots, code samples, demos or link to other resources.

```python
$ from ak_cache import Cache
$ cache_file = Cache(r'Path\to\Cache\file.pkl')
$ cache_file.write('This is a text')
$ cache_file.read()
'This is a text'
```

Encrypt your pickle file as below

```python
$ cache_file = Cache(r'Path\to\Cache\encr_file.pkl', password="Strong_Password")

$ cache_file.write('This is an encrypted text')
$ cache_file.read()
'This is an encrypted text'
```
<!-- Roadmap -->
## 4. Roadmap

- [x] Add encryption option to the cache file

<!-- License -->
## 5. License

See LICENSE.txt for more information.

<!-- Contact -->
## 6. Contact

Arun Kishore - [@rpakishore](mailto:rpakishore@gmail.com)

Project Link: [https://github.com/rpakishore/](https://github.com/rpakishore/ak_cache)

<!-- Acknowledgments -->
## 7. Acknowledgements

Use this section to mention useful resources and libraries that you have used in your projects.

- [Awesome README Template](https://github.com/Louis3797/awesome-readme-template/blob/main/README-WITHOUT-EMOJI.md)
- [Banner Maker](https://banner.godori.dev/)
- [Shields.io](https://shields.io/)
- [Carbon](https://carbon.now.sh/)
visChem 0.1.3
A tool for chemical space visualization and clustering.

# visChem v0.1.3

Steve Niu[^1]

`visChem` is a Python module designed for visualizing chemical space using UMAP and clustering techniques. This tool facilitates the transformation of chemical structures into a 2D space and visualizes clusters of similar compounds.


## Installation
Install using pypi
```
pip install visChem
```

Install using conda
```
conda install -c stevexniu vischem
```

**Note**: Some packages like `rdkit` might require special installation instructions. Please refer to their official documentation for details.

## Usage

1. See `example.py` for details.
2. Run ```python example.py```.

The `example.py` script will execute the main function which:  
- Load example 1000 SMILES from RDKit NCI/first_5K.smi.  
- Converts SMILES to molecular representations.  
- Generates molecular fingerprints.  
- Computes Tanimoto similarity.  
- Reduces dimensionality using UMAP.  
- Performs clustering.  
- Visualizes the chemical structures in the clustered chemical space below.

![output](output_image.png)

Refer to `example.py` for details and any potential modifications you might want to make for your specific use case.

[^1]: Safety Assessment, niu.steve@gene.com