semvec/pypi-packages huggingface dataset:
lock-unlock-python-lib 1.6.530
(en) A simple encryption and decryption library for folders (tr) Klasörler için basit bir şifreleme ve şifre çözme kütüphanesi
Requires Python: >=3.7

# Lock-Unlock-Python-Lib

Lock-Unlock-Python-Lib, AES şifrelemesini kullanarak klasörleri şifreleyen ve şifresini çözen bir Python kütüphanesidir.
Dosyalarınızı güvence altına almak ve gerektiğinde geri almak için basit bir yol sağlar.

## 📌 Özellikler

- Tüm klasörleri güvenli bir `.lock` dosyasına şifreler.
- Şifreleme için rastgele 16 karakterli bir parola oluşturur.
- Güçlü güvenlik için AES (CBC modu) şifrelemesini kullanır.
- Şifreleme sırasında bellek ve disk kullanımını otomatik olarak yönetir.
- `.lock` dosyalarını orijinal klasör yapılarına geri şifresini çözer.

## 🔧 Kurulum

Kitaplığı pip kullanarak kurabilirsiniz:

```
pip install lock-unlock-python-lib
```

### 🚀 Kullanım

Bir Klasörü Şifrele

```
from lock_unlock_lib import encrypt_folder

encrypt_folder("my_folder", "encrypted_data.lock")
```

Bu, şifrelenmiş bir .lock dosyası ve şifreleme anahtarını içeren bir pass.key dosyası oluşturacaktır.

Bir Klasörün Şifresini Çöz

```
from lock_unlock_lib import decrypt_file

decrypt_file("encrypted_data.lock", "pass.key")
```

Bu, klasörü şifrelenmiş dosyadan geri yükler.

### 🛠 Gereksinimler

- Python 3.7+

```
pip install -r req.txt
```

### 📜 Lisans

Bu proje MIT Lisansı altında lisanslanmıştır - ayrıntılar için LİSANS dosyasına bakın.

### 🤝 Katkıda Bulunma

[GitHub](https://github.com/razzy-code/lock-unlock-python-lib) ve [Website](https://razzy-code.glitch.me/) üzerinden sorun veya çekme isteği göndererek katkıda bulunmaktan çekinmeyin
chemparse 0.3.2
Chemical formula parser
Requires Python: >=3.6

# chemparse

**Authors:** Grayson Boyer and Victor Ignatenko

A lightweight package for parsing chemical formula strings into python dictionaries. 

## Features

* Convert a chemical formula string into a python dictionary.
    - example: `"CH4"` returns `{"C":1.0, "H":4.0}`
* Handles fractional stoichiometry.
    - example: `"C1.5O3"` returns `{"C":1.5, "O":3.0}`
    - example: `"H2e-1O1e-1"` returns `{"H":0.2, "O":0.1}`
* Handles groups with parentheses.
    - example: `"(CH3)2(CH2)4"` returns `{"C":6.0, "H":14.0}`
* **New in 2024:** Chemparse now handles nested paretheses!
    - example: `"((CH3)2)3"` returns `{'C': 6, 'H': 18}`
* **New in 2024:** Chemparse now handles square brackets
    - example: `"K4[Fe(SCN)6]"` returns `{'Fe': 1.0, 'K': 4.0, 'N': 6.0, 'S': 6.0, 'C': 6.0}`

## Installation

Install `chemparse` with pip:

```
$ pip install chemparse
```

## Usage

Import chemparse in python and use the parse_formula function:

```
import chemparse

print(chemparse.parse_formula("C6H12O6"))
```

## Contribute

Install python

Clone `chemparse` using git: \
`git clone https://github.com/gmboyer/chemparse.git`

Go to the `chemparse` directory: \
`cd chemparse`

Install requirements: \
`pip install -r requirements.txt`

Now you are ready to contribute!
instafill 0.0.7
A tool to automatically fill PDF forms
Requires Python: >=3.8

# Instafill AI Python Library

## Introduction
Instafill AI is an innovative platform designed to automate the filling of PDF forms using advanced AI technologies. This Python library allows developers to easily integrate Instafill AI's capabilities into their applications, streamlining form processing workflows.

## Features
- **Automated Form Filling**: Leverage Instafill AI's AI-driven form filling capabilities to efficiently process PDF forms.
- **Batch Processing**: Handle multiple forms simultaneously for large-scale applications.
- **Digital Signatures**: Add digital signatures to completed forms, enhancing workflow efficiency.

## Prerequisites
Before using this library, ensure you have:
- Python 3.8 or later installed.
- An Instafill AI account with API credentials. To obtain an API key, contact us at [api@instafill.ai](mailto:api@instafill.ai).

## Installation
To install the library, run:
```bash
pip install instafill
```

## Usage
```python
from instafill import InstaFillClient

client = InstaFillClient("your_api_key_here")

try:
    form_id = "w-9-2024"
    response = client.get_form(form_id)
    print("Get Form Response:", response)
except Exception as error:
    print("Error:", error)
```

## Home Page
Visit our [home page](https://instafill.ai) to learn more about Instafill AI and its capabilities.

## ChatGPT Integration
You can also use Instafill AI directly within ChatGPT to fill PDF forms effortlessly. Try it out here: [Fill PDF Forms with ChatGPT](https://chat.openai.com/g/g-WFalxIZ4n-fill-pdf-forms).
traceable-agent 2.0.1
Traceable.ai Python Agent
Requires Python: >=3.8

# Python Agent

### Usage
Python traceable agent requires Python >= 3.7

Additionally, to use the traceable filter, you must be on a supported OS. 
- Ubuntu 18.04+
- Centos 7+
- Debian 10+
- Amazon Linux 2+

### Instrumentation methods
There are two ways to instrument your application, auto-instrumentation and code based instrumentation.

#### Autoinstrumentation
Simply prepend `traceableai-instrument` to your applications startup command.

ex: `traceableai-instrument flask run`


#### Code based instrumentation
Add the following snippet to your python apps entrypoint file:
```python
from traceableai.agent import Agent

app = Flask(__name__)

agent = Agent()
agent.instrument(app) # This will instrument the flask app + any other modules that are supported
agent.add_traceable_filter() # add the traceable filter to enable blocking
```

### Developing
```bash
# Create a virtual env & install dependencies
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt -r dev-requirements.txt 
```

_Note: if you run into an error installing grpc:_
> File "/Users/user/.pyenv/versions/3.9.4/lib/python3.9/distutils/unixccompiler.py", line 120, in _compile
> raise CompileError(msg)
> distutils.errors.CompileError: command '/usr/bin/clang' failed with exit code 1

_prepend this env var to the above pip install command:_ 
`GRPC_PYTHON_BUILD_SYSTEM_ZLIB=true`

### Building
```bash
pip install -r requirements.txt
python3 -m build
```

### Instrumenting
```bash
traceableai-instrument your_startup_command
# ex: traceableai-instrument flask run -p 5000 
```

### Updating Libtraceable
1. Update the `libtraceable.h` header file if it has changed.
1. Edit `./src/download.py` and update the constant `LIBTRACEABLE_VERSION`.  
1. Verify using a test application in `docker/test_apps`. It will fail to build if libtraceable cannot be downloaded.
### Updating the Proto
```bash
git submodule update --init --recursive
./scripts/build_proto.sh
```
### Testing
- Unit tests
    1. Build the *.whl files. `build_artifacts.sh` builds all the whl files. Intentionally use the `CIBW_SKIP` environment variable to skip versions to save time. The example below only tests on 3.6.
        ```
        CIBW_SKIP="*37* *38* *39* *310*" ./build_artifacts.sh
        ```
    1. Build and run test in docker.
        ```
        docker build -f docker/test_apps/unittest.Dockerfile -t pythonunittest .
        docker run --rm pythonunittest
        ```
- Test applications
    1. Refer to `docker/test_apps/`.