semvec/pypi-packages huggingface dataset:
get-spotlights 3.2
Love windows 10 spotlight images that show up on lock-screen. Then here's a simple program to copy those images and get them in your preferred directory.
License: MIT
Keywords: copy extract get windows 10 spotlight spotlights image images lockscreen wallpaper

# Get Spotlights
## Description
Love windows 10 spotlight images that show up on lock-screen. Then here's a simple program to copy those images and get them in your preferred directory.

## Installation
#### Installing python
You will need python 3 installed and available on PATH.<br>
To do that click [here](https://www.python.org/downloads/) to go to python downloads page, and download python.<br>
Now, open the downloaded installer, select `Add Python 3.* to PATH` as shown below, and click `Install Now`<br>
![Add to PATH screenshot](images/python-addtopath.PNG)<br>

#### Installing spotlights app
Now, Open command prompt, by searching `cmd` and pressing enter as follows<br>
![search-cmd-screenshot](images/search-cmd.PNG)<br>
Enter <code>python -m pip install get-spotlights</code> inside it.<br>
![install-app-command-screenshot](images/get-spotlights-installed.PNG)<br>

<br>All set!

## Usage
Inside command prompt,<br>
* Enter <code>get-spotlights-gui</code> to start the app.<br>
![App's gui screenshot](images/gui.PNG)<br>
If default settings seem sound to you, go ahead and click `Get Spotlights` button.

* Enter <code>get-spotlights --help</code> to get help if you wish to use it completely from command line.<br>
![command-line-screenshot](images/cmd.PNG)<br>
* Command line usage examples -
  * <code>get-spotlights "C:/Users/YourUserName/Pictures/"</code>
  ![result1](images/cmdusage1.PNG)<br>
  
  * <code>get-spotlights "C:/Users/YourUserName/Pictures/" --no-split</code>
  ![result2](images/cmdusage2.PNG)<br>
fickle 0.2.2
load pickled data as safely as possible
License: MIT

# Fickle: Firewalled Pickle

People abuse pickle. Especially researchers. Pickle is [not secure](https://docs.python.org/3/library/pickle.html). Published datasets and ML training weights are often distributed as pickle files (or formats which use pickle files, such as [PyTorch checkpoint.ckpt files](https://pytorch.org/tutorials/beginner/saving_loading_models.html)). Sometimes it is the only format that they are available in.

## Examples

Loading basic types is easy:

```python
>>> from fickle import DefaultFirewall
>>> import pickle
>>>
>>> my_picked_data = pickle.dumps({"list": [1, 2, "three", b"four"]})
>>>
>>> firewall = DefaultFirewall()
>>> firewall.loads(my_picked_data)
{'list': [1, 2, 'three', b'four']}
```

Safely loading PyTorch checkpoint files into numpy arrays is just as easy:

```python
>>> from fickle.ext.pytorch import fake_torch_load_zipped
>>> from zipfile import ZipFile
>>>
>>> zf = ZipFile("/path/to/sd-v1-4.ckpt")
>>> ckpt = fake_torch_load_zipped(zf)
>>> tensor = ckpt["state_dict"]["model.diffusion_model.output_blocks.3.1.norm.weight"]
>>> tensor.array
array([0.39097363, 0.3898967 , 0.35191917, ..., 0.41924757, 0.4031702 ,
       0.37156993], dtype=float32)
```

You can, optionally, even use `marshmallow` for validation!

## Alternatives

- [picklemagic](https://github.com/CensoredUsername/picklemagic)
- [pikara](https://pypi.org/project/pikara)

|                                                | fickle | picklemagic | pikara |
|------------------------------------------------|--------|-------------|--------|
| Does not rely on `pickle._Unpickler`?          | ✅      | ❌           | ✅      |
| Uses `pickletools.genops`                      | yes    | no          | yes    |
| Can load without executing?                    | ✅      | ✅           | ?      |
| Forbid importing arbitrary objects?            | ✅      | ✅           | ?      |
| Forbid calling `list.append`/`set.add`/etc?    | ✅      | ❌           | ?      |
| Forbid calling all methods by default?         | ✅      | ❌           | ?      |
| Can create dangerous circular structures?      | ✅      | ✅           | ?      |
| Safe against billion laughs DoS attack?        | ?      | ?           | ?      |
| Full support for all pickle opcodes?           | ❌      | ✅           | ?      |
| Has unit tests?                                | ✅      | ❌           | ✅      |
| Stable API?                                    | ❌      | ✅           | ✅      |