semvec/pypi-packages huggingface dataset:
django-admin-hotkeys 0.1.1
Add hotkeys to the Django admin interface to improve your workflow
Requires Python: >=3.9
Keywords: Django

# Django Admin Hotkeys

Add hotkeys to the Django admin interface to improve your workflow.

## Usage

1. `pip install django-admin-hotkeys`
2. Add `django_admin_hotkeys` to your `INSTALLED_APPS` in `settings.py`:
3. PROFIT!

## Hotkeys

- `/`: Focus the search box
- `n`: Navigate to "Add" page to create a new item
mizuhara 0.0.56
Package Description
Keywords: First, Python, Test, pypi

THIS IS A DRAFT VERSION OF README.md

# Mizuhara

---

### Create Your Telegram Bot More Easily.(Draft)

---

#### I. Introduction

When you create a telegram bot with python, you may face with PyTelegramBotAPI or python-telegram-bot.
You may recognise that it is not easy to handler both two packages to create your own telegram bot.
These package are not a framework, so you have to design all structure from the scratch. 
You have to all functions to message or callback handlers as a minimum, 
additionally you may have to create another global variables to control telegram bot more precisely.
If you have any experience to write a code with python packages related with telegram, 
you might be frustrated that your code is so verbose and seems not to be able to be done maintenance.

This project, which is called Mizuhara(the origin of water), was started to solve the difficulties during producing telegram bot.
Mizuhara is mimic Django Rest API Framework(DRF), so you have to set the route, view as well as serializers.
Only difference between Mizuhara and Django is, the previous one does not provide any models, which are charge of defining table of database.
Mizuhara was created to be used with connecting REST-API server.

---

#### II. How to Use

##### 1. Prerequisite

* Python up to 3.11 version or equal.
* pip

##### 2. Installation

Install 'Mizuhara' by executing shell command below in your virtual environment.

```commandline
pip install mizuhara
```

After installation, you can use command 'mizuhara' on your shell terminal.

```commandline
mizuhara --help
```

##### 3. Create Project or App

Like Django, 'Mizuhara' requires to create project and app folder via command 'mizuhara'.
App, like a app in Django, is a smallest unit in your telegram bot project

```commandline
# create prject
mizuhara newproject

# create application in your project
mizuhara newapp <YOUR_APP_NAME>
```
You do not have to create your project first. 
If there is no project and you try to create an app, 'Mizuhara' will create file system for your project automatically.

##### 4. Write Your Code in Your Application Folder

Please refer to the documentation at the link below.

* Documentation Link: <a href="#"> Now_Preparing </a>


#### 4. Development Logs

* 2025.03.23 : Start demo test and debugging.
* 2025.03.22 : 1st debugging on PyPi. (current Pypi version is 0.0.18)
* 2025.03.18 : Convert filesystem for PyPi packaging.
* 2025.03.13 : Complete to create a draft version.
* 2025.02.07 : Start project 'telebot_framework'


THIS IS A DRAFT VERSION OF README.md
go-django 0.0.3
Modular Django boilerplate
Requires Python: >=3.7

# Django Boilerplate → `go-django` 📦

A modular, scalable, and DRY backend boilerplate built on Django. Designed to provide production-ready patterns (service, repository, serializer, view) and a CLI command to scaffold new modules with zero friction.

---

## 🚀 Features
- Modular directory structure (Django-onion architecture)
- Base classes for `Model`, `Repository`, `Service`, `Serializer`, `APIView`
- Unified decorator for query & body validation
- Command to scaffold CRUD-ready Django apps
- Auto admin registration
- Auto test stub generation
- Pagination and soft-delete support

---

## 📦 Installation
```bash
pip install go-django
```

Or for local development:
```bash
pip install -e .
```

---

## 🧱 Generate a Module
```bash
python manage.py generate_module <app_name> <Entity>
```

### Example
```bash
python manage.py generate_module users User
```
Creates:
```
users/
├── __init__.py
├── admin.py
├── models.py
├── urls.py
├── repositories/
│   └── user_repository.py
├── serializers/
│   └── user_serializer.py
├── services/
│   └── user_service.py
├── views/
│   └── user_view.py
└── tests/
    └── test_user_service.py
```

- Registers `User` in `admin.py`
- Adds app to `INSTALLED_APPS`
- Includes unit test stub for service

---

## 📚 Structure Summary
### 🔹 BaseModel
- Common fields: `created_at`, `updated_at`, `is_active`
- Methods: `soft_delete()`, `restore()`

### 🔹 BaseService
- CRUD methods: `create`, `retrieve`, `update`, `delete`
- Supports pagination out of the box

### 🔹 BaseRepository
- ORM encapsulation: `get_by_id`, `filter`, `exists`, etc.

### 🔹 BaseAPIView
- Handles all HTTP verbs via service layer
- Unified error handling using custom exceptions

### 🔹 Decorator: `@validate_request`
- Combines `request.data` and `request.query_params`
- Injects validated data into `request.validated_data`

---

## 🧪 Testing
Each generated module includes test stubs inside:
```bash
<app_name>/tests/test_<entity>_service.py
```
Use Django's `TestCase` or plug in pytest if preferred.

---

## 🧰 Advanced
- Add signals, permissions, or mixins by extending `shared/`
- Create custom decorators for logging, audit, auth, etc.

---

## ✅ License
[MIT](LICENSE)

---

## 👨‍💻 Maintainer
Created by Sivakumar & Selva • Contributions welcome!
Myosotis-Researches 0.1.42
A repository for storing my progress of researches.
Requires Python: >=3.6

# Myosotis-Researches

## `CcGAN` (`myosotis_researches.CcGAN`)

### `visualize`

The visualize module can display datasets as a webpage

Import with code

```python
from myosotis_researches.CcGAN.visualize import *
```

Now we only have `visualize_datasets` function, defined as

```python
visualize_datasets(
  indexes,
  datasets_path,
  list_path,
  template_path = resources.files("myosotis_researches").joinpath("CcGAN", "visualize", "src", "template,html"),
  host = "127.0.0.1",
  port = 8000,
  debug = True,
  img_size = 64
)
```

### `internal`

The `internal` module is used for setting the local package itself, like installing datasets and so on.

Import with code

```python
from myosotis_researches.CcGAN.internal import *
```

| Function                          | Desctiption                                                          |
| --------------------------------- | -------------------------------------------------------------------- |
| `install_datasets(datasets_name)` | Install the datasets in `datasets_name` to the local python package. |
| `uninstall_datasets()`            | Remove all the datasets installed to the local python package.       |
| `show_datasets()`                 | Show all datasets installed.                                         |

**Note**:

1. The path of the installed datasets are

   `resources.files("myosotis_researches").join("CcGAN", "<datasets_name>")`

   To run this code, remember to add `from importlib import resources` at the beginning.

### `utils`

The `utils` module contains some basic functions and classes which are frequently used during the CcGAN research.

Import with code

```python
from myosotis_researches.CcGAN.utils import *
```

| Function                                                     | Description                               |
| ------------------------------------------------------------ | ----------------------------------------- |
| `concat_image(img_list, gap=2, direction="vertical")`        | Concat images vertically or horizontally. |
| `make_h5(old_datasets_name, size, new_datasets_path, image_indexes, train_indexes, val_indexes)` | Get piece of original HDF5 datasets.      |
| `parse_opts()`                                               | Parse arguments.                          |
| `print_hdf5(name, obj)`                                      | Print a basic structure of an HDF5 file.  |

| Class               | Description           |
| ------------------- | --------------------- |
| `IMGs_dataset`      | Images dataset.       |
| `SimpleProgressBar` | Simple progress bars. |

**Note**:

1. Function `print_hdf5` should be used within a `with` block:

   ```python
   import h5py
   
   with h5py.File(<HDF5_file_path>, "r") as f:
     f.visititems(print_hdf5)
   ```