semvec/pypi-packages huggingface dataset:
ifood-databricks-alcatraz 0.1.29
The iFood Databricks Alcatraz library anonymizes PII data in a Spark DataFrame. It is designed to be used in Databricks notebooks and jobs.
Requires Python: <4.0,>=3.10

# iFood Databricks Alcatraz

The iFood Databricks Alcatraz library anonymizes PII data in a Spark DataFrame.
It is designed to be used in Databricks notebooks and jobs.


## Example Usage

To get more examples, check the [`examples`](examples) folder.

```python
from pyspark.sql import SparkSession

from ifood_databricks_alcatraz import IFoodAnonymizer, Entities

# We allocate 4GB of memory to the Spark driver to avoid memory issues with the UDF
# This is a common issue when working with UDFs in Spark locally
spark = SparkSession.builder \
    .appName("AppName") \
    .config("spark.driver.memory", "4g") \
    .getOrCreate()


# Data to be included in the DataFrame
data = [
    (
        "John Doe",
        40,
        "São Carlos",
        "My phone is 19 967288744",
        "My cpf is 831.756.690-00",
        "My ip is 200.122.22.1",
        "My email address is john@ee.com",
    ),
    (
        "André Osti",
        30,
        "Campinas",
        "My phone is 21 88367-8333",
        "My cpf is 831.756.690-01",
        "My address 10.22.22.1",
        "My address is andre.doe@gmail.com",
    ),
]

columns = ["Name", "Age", "City", "Phone", "CPF", "IP_ADDRESS", "Email"]

df = spark.createDataFrame(data, columns)

df.show(truncate=False)

anonymizer = IFoodAnonymizer()

entities = [Entities.PHONE_NUMBER]

# Apply the anonymization UDF to the 'Name' column
anonymized_df = anonymizer.anonymize_column(df, "Phone", entities=entities)
anonymized_df = anonymizer.anonymize_column(anonymized_df, "IP_ADDRESS", entities=[Entities.IP_ADDRESS])
anonymized_df = anonymizer.anonymize_column(anonymized_df, "CPF", entities=[Entities.CPF])
anonymized_df = anonymizer.anonymize_column(anonymized_df, "Email", entities=[Entities.EMAIL_ADDRESS])

# Show the results
anonymized_df.show(truncate=False)


```
typhoon-robotic-arm 1.0.3
Library to communicate with Typhoon robotic arm.
Requires Python: >=3.8

# Typhoon Robotic Arm

[![en](https://img.shields.io/badge/lang-en-red.svg)](README.md)
[![sk](https://img.shields.io/badge/lang-sk-green.svg)](README.sk.md)

`typhoon-robotic-arm` is a Python library that enables control of the Typhoon robotic arm. This library provides various functionalities, including calculations, communication and movement of the arm.

## Installation

Requires **Python 3.8+**. Download and install the latest release:

```bash
pip install typhoon-robotic-arm
```

## Quickstart

```python
from typhoon import Typhoon

typhoon = Typhoon("COM3", 0, 170, 130, output=True)

typhoon.move_to(100, 0, 0)
typhoon.tool(pw9=255)
typhoon.move_to(0, 0, 0)

typhoon.close()
```

## References

*class* **Typhoon**(*port: str, start_x: int, start_y: int, start_z: int, tool_offset_x: int = 0, tool_offset_y: int = 0, tool_offset_z: int = 0, output: bool = False*)

- Controls a Typhoon robotic arm through serial communication. Offers a user-friendly interface for various arm operations.

- **Parameters:**

    - **port** (*required*) - Port on which is typhoon robotic arm connected. You can check this in your Device Manager on Windows under USB Connector Managers.
    - **start_x** (*required*): - Startring X position of robotic arm.
    
    - **start_y** (*required*) - Startring Y position of robotic arm.
    
    - **start_z** (*required*) - Startring Z position of robotic arm.
    
    - **tool_offset_x** - X offset of the tool.
    
    - **tool_offset_y** - Y offset of the tool.
    
    - **tool_offset_z** - Z offset of the tool.
    
    - **output** - If you want to see output from the Arduino board.


- **Methods:**

    - **move_to**(*x: int, y: int, z: int*):
        - Moves the arm to the specified coordinates.
        - Calculates the required angles and sends them to the arm.

    - **move_home**():
        - Moves the arm to the starting position.

    - **tool**(*pw8: int = 0, pw9: int = 0, pw10: int = 0*):

        - Controls the state of the tool (e.g., gripper open/close, suction on/off).
        - Sends PWM values to the arm to activate the desired tool functions.

    - **get_angles**():

        - Returns the current base, upper, and lower arm angles as a tuple.

    - **get_coords**():

        - Returns the current X, Y, and Z coordinates of the arm tip as a tuple.

    - **send_file**(*file_path: str, separator: str = " "*):

        - Moves the arm according to coordinates specified in a text file.
        - Each coordinate must be written on **new line** in format `x y z`.
        - When you set `separator` to `, `, program expects on each line data in format `x, y, z`

    - **close**():

        - Closes the serial connection to the arm.
supercollect 1.1.1
Supercharge collectstatic for remote storages
Requires Python: >=3.11

# Supercollect
#### Install
`pip install supercollect`
or
`poetry add supercollect`

Add `supercollect` to INSTALLED_APPS before `django.contrib.staticfiles`
```py
INSTALLED_APPS = [
    ...
    "supercollect",
    "django.contrib.staticfiles",
    ...
]
```
Set `STATIC_ROOT` setting

#### Usage
```py
python manage.py collectstatic --turbo
```

#### How
This package is built around a very simple idea. Perform collectstatic in a temporary local storage and upload all files in parallel after it's finished. Out of the box this should support any remote storage as well as manifest storages.  

```py
def collect(self):
    if collect_super_fast:
        self.storage = use_temporary_file_system_storage() # super.simple

    files_collected = super().collect() # super.collect
    
    if not collect_super_fast:
        return files_collected # super.pluggable

    self.storage = real_s3_storage
    multithreaded_upload() # super.fast
```
aijson-meta 0.1.9
AI JSON Quickstart | Low-code config language for AI Pipelines
Requires Python: <3.13,>=3.10

# AI JSON – meta

This is a metapackage.

`pip install aijson-meta` is a shortcut for installing:
- [`aijson-core`](https://github.com/aijson/aijson) (core package)
- [`aijson-ml[api]`](https://github.com/aijson/aijson-ml) (LLM and transformers actionpack)
- [`aijson-db[all]`](https://github.com/aijson/aijson-db) (database actionpack)
- [`aijson-pdf[all]`](https://github.com/aijson/aijson-pdf) (PDF actionpack)
- [`aijson-utils[all]`](https://github.com/aijson/aijson-utils) (common utilities actionpack)