semvec/pypi-packages huggingface dataset:
PyCertGen 23.12.2
Package for certificate generation
Requires Python: >=3.6,<4.0

# PyCertGen
Looking to generate multiple certificates with just a single-line command? PyCertGen is the perfect solution for you.


## Installation
```shell
$ pip install PyCertGen
```

## Usage
For gui usage:
```shell
python3 pycertgen --show_gui
```

for cli usage:

```
python3 pycertgen --certified_path="input/data.xlsx" --template_path="input/template.pptx" --key_autogen  --to_pdf_method="libreoffice" --output_path="output/"
```

## Templates consistency
You can create any template format based on your own needs. Follow the consistency rule:
Ensure that when creating or modifying any PowerPoint templates or Excel file, every column name from the Excel file must be represented as a placeholder in the [column_name] (column name between square brackets) format within the PowerPoint slides. This helps maintain consistency and clarity when populating the slides with data from the Excel columns.
NamasteiG 0.3.14
Most PowerFull Instagram Library
Requires Python: >=3.9

Best Instagram Python Library For Scrape Instagram Data

Check example.py To Use This Library.

Github => https://github.com/NamasteAbhi/NamasteiG

More Features Comming Soon And Tell Me Which Types Of Features You Want To Add In This Library?

Drop Your Suggestion Here => https://t.me/namastehackersgroup
douban-crack 0.0.2
crack douban DATA
Requires Python: >=3.7
Keywords: douban

# douban-crack

[![PyPI - Version](https://img.shields.io/pypi/v/douban-crack.svg)](https://pypi.org/project/douban-crack)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/douban-crack.svg)](https://pypi.org/project/douban-crack)

-----

**Table of Contents**

- [Installation](#installation)
- [License](#license)

## Installation

```console
pip install douban-crack
```

## License

`douban-crack` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
mentalics 0.2.0
Python NSKeyedArchiver explorer, archiver, and dearchiver
Requires Python: >=3.9,<4.0

# Mentalics

> [!WARNING]  
> This library is not stable yet.

`mentalics` is designed primarily to read, write, and analyze NSKeyedArchiver-generated archives as Python object graphs. It is designed to reflect the `NSCoder` interface, handle circular references, and efficiently work through unknown classes and files.

## Usage

Exploring an unknown archive (not stable):

```python3
from mentalics import Explorer

with open("my.plist", "rb") as file:
    explorer = Explorer(file)

print(explorer._classes)
```

Decoding a known archive:

```python3
from mentalics import Unarchiver, NSCoding
from dataclasses import dataclass


@dataclass
class MyClass(NSCoding):
    my_attr: str

    def __init_from_archive__(self, decoder) -> "NSCoding":
        my_attr = decoder.decode("myAttr")
        return self.__init__(my_attr)

    def encode_archive(self, encoder) -> None:
        encoder.encode(self.my_attr, for_key="myAttr")


with open("my.plist", "rb") as file:
    dearchiver = Unarchiver(file)
    dearchiver.set_class(MyClass, "MyClass")
    
root = dearchiver.decode()
print(root)
```

## Why `mentalics`?

There are many other libraries for parsing plists and archives: [plistlib](https://docs.python.org/3/library/plistlib.html) and [bplist-python](https://github.com/farcaller/bplist-python) (plists, not archives), [bpylist](https://github.com/Marketcircle/bpylist) and [bpylist2](https://github.com/parabolala/bpylist2), [plistutils](https://github.com/strozfriedberg/plistutils), [ccl-bplist](https://github.com/cclgroupltd/ccl-bplist), and probably others.

However, there is mismatched support for desirable features:

- Handling circular references (ccl-bplist)
- NSCoder/NSCoding-like interface (bpylist, bpylist2)
- Simple handling of NSValues (none)
- Exploring archives with unknown structure (ccl-bplist)
- Generating code for classes from archives (none)

All of these are either a part of `mentalics` or a planned feature.
data-diode 0.0.4
Send and receive data over serial diode
Requires Python: >=3.9
Keywords: diode,data diode

# Serial Diode

Generic wire protocol and implementation for one-way data transfer over UART serial.

## Usage

### General

The serial device can be specified with `--device` and baudrate with `--baudrate`.
If device is unspecified, it will attempt to guess the correct device based on platform and name.
If baudrate is unspecified, it defaults to 115200 Hz.

See `--help` for detailed usage information.

### Send

Run `diode send <path/to/file>` to send `<file>`.

### Receive

Run `diode listen`, which will listen forever. When it receives a valid payload, it will write it to `out/<file>` where `<file>` was specified in the payload metadata.

Note that on some systems this may need to be run as root to allow access to the serial port.
It is generally preferable to add the user to the appropriate group with something similar to `usermod -a -G uucp <username>`.

## Wire format

    ┌─────┬──────────┬─────────────┬──────┬─────┬───────┐
    │ SOT │ metadata │ data_length │ data │ EXT │ crc32 │
    └─────┴──────────┴─────────────┴──────┴─────┴───────┘

Here:
* `metadata` is 32 bytes,
* `data_length` is 8 bytes,
* `data` is `data_length` bytes,
* `crc32` is 8 bytes,
* `SOT` and `EXT` are the bytes `x02`, `x03`,
* `crc32` is the value of the CRC32 function acting on `metadata || data`.

## Installation

Install in developer mode with `make install_dev && source venv/bin/activate`.

Install as user with `make install`.

Install [from PyPI](https://pypi.org/project/data-diode/) with `pip install data-diode`.

Install Bash completion with `source bash_completion/diode`.

## Testing

Run `make test`.

For ad-hoc testing, `socat -d -d pty,raw,echo=0 pty,raw,echo=0` can be useful to connect two virtual serial devices.
If a physical serial device exists, connect with `screen /dev/<device_name> [<baud_rate>]` where `<baud_rate>` is likely 115200.