semvec/pypi-packages huggingface dataset:
pypi-analyser 1.0.0
A Python library to monitor PyPi packages!
Requires Python: >=3.9.7

# Overview
-----------------------------------------------------------------------------

pypi_analyser is a Python library to monitor PyPi packages! 

## Package Installer 

    pip install pypi-analyser

## Usage

    from pypi_analyser import pypi_analyser
    '''
      package_name -> string pypi package name.
    '''
    package_name = 'pandas'
    package_details = pypi_analyser(package_name)
    
    print(package_details.package_name)
    print(package_details.latest_version)
    print(package_details.license)
    print(package_details.homepage)
    print(package_details.stars)
    print(package_details.forks)
    print(package_details.dependency_count)
    print(package_details.dependencies)
    
**Utilities**

| Name           | Description  |
| ------------- | -----|
| package_name | Returns the pypi package name! |
| description | Returns the description of pypi package! |
| latest_version | Returns the latest version of pypi package! |
| released | Returns the released date of the pypi package! |
| latest_release | Returns the latest release date of pypi package! |
| license | Returns the license of the pypi package! |
| author | Returns the author of the pypi package! |
| maintainer | Returns the maintainer of the pypi package! |
| homepage | Returns the homepage of the pypi package! |
| repository | Returns the repository of the pypi package! |
| dependency_count | Returns the unique dependency count of the pypi package! |
| dependencies | Returns the list of dependendencies for the pypi package! |
| stars | Returns the github stars count of the pypi package! |
| forks | Returns the github forks count of the pypi package! |


## Requirements

The `requirements.txt` file has details of all Python libraries for this package, and can be installed using 
```
pip install -r requirements.txt
```

## Organization

    ├── src
    │   ├── pypi_analyser
              ├── init             <- init
              ├── pypi_analyser    <- package source code for pypi analyser
    ├── setup.py             <- setup file 
    ├── LICENSE              <- LICENSE
    ├── README.md            <- README
    ├── CONTRIBUTING.md      <- contribution
    ├── test.py              <- test cases for unit testing
    ├── requirements.txt     <- requirements file for reproducing the code package

## License

MIT

## Contributions

For steps on code contribution, please see [CONTRIBUTING](./CONTRIBUTING.md).
r2server 0.0.5
python SDK for R2SERVER
Requires Python: >=3.0

## About
r2server python sdk makes it easier for you to work with your r2server server using the python programming language. The SDK uses an object-oriented design and tries to look like r2server API.

## Installation 

#### with pip3

```sh
pip install r2server
```

#### from repo

```sh
make install
make doc # for generate documentation
```

## Quick start

```python
import r2server.api

# init api
network = r2server.api()

# get all observations of METEOR-M2
obs = network.observation(33591)

# print all filtred observations ids
for ob in obs:
    print("Observation " + str(ob.id) + " by " + ob.name)

```
filtermui 1.0.0
Converts MUI filters into a Django query.
Requires Python: >=3.9

# filter-mui

This program converts MUI DataGrid filters into Django queries. 

# How to Use

Submit your MUI filters to your Django backend via a JSON String. Create a query set and then run the function add_mui_filters(query_set, json_string_filters, column_field_mappings). This will apply all of the MUI filters to the QuerySet and then return that updated QuerySet. By default all of the columnFields are convertdc from camelCase to snake_case. For example, the column medicalRecordNumber will be converted to medical_record_number. Say the field is called MRN on the frontend then it would convert to M_R_N, but this is not consistent with the database so you need to pass in {"MRN": "medical_record_number"} to the column_field_mappings. The column_field_mappings is also needed for traversing tables as seen below.

# Installation

Run the following:

```python
pip install filtermui
```

# Example

The following example allows the user to filter a MUI DataGrid displaying the following data of a patient model with the attributes medical_record_number (stored as "MRN" on front-end), first_name, last_name, date_of_birth, and place_of_birth (ForeignKey):

```python
from filtermui import add_mui_filters

# Made up function called when user submits new query.
def patient_table_query(filter):
  patients = patient.objects.all()
  
  patients = add_mui_filters(
    patients,
    filter,
    {"MRN": "medical_record_number", "placeOfBirth": "__place_of_birth__name"},
  ) 
  
  return patients # This returns a QuerySet - you will often encode this into JSON. 
  
```

Note how in the mappings placeOfBirth is in camelCase. This is becuase it's submitted in cammel case and it is more efficent not to convert it if you are providing a mapping. It uses __ in place of birth becuase it is a diffrent table - we must specify when we traverse tables.

# Active Areas of Improvment

- Performance
- Documentation