semvec/pypi-packages huggingface dataset:
toomoss-py 0.1.2
Python Wrapper for Toomoss USB
Requires Python: >=3.9

# TOOMOSS SDK

TOOMOSS USB to CAN, CANFD, LIN, PWM python SDK

source code adapted from [usb2can_lin_pwm_example](https://gitee.com/toomoss/usb2can_lin_pwm_example)

## Installation
```
$ uv venv
$ uv pip install toomoss-py
```

## Example

```py
from ctypes import byref, c_uint

from toomoss_py.api.usb_device import USB_ScanDevice

dev_handles = (c_uint * 8)()
ret = USB_ScanDevice(byref(dev_handles))
if ret == 0:
    raise Exception("ToomossLIN: No device connected!")
```
system-calls 6.17.0
Python module to check for system call number/name andavailability
Requires Python: >=3.6

# System calls table on different architectures

## What and why?

Linux kernel has a set of system calls (called syscalls in short) offered for userspace.
Each architecture can support them but the numbers used for their identification
can vary between archs.

And those numbers can be important for some projects (like Valgrind for example).

## How to help?

Check issues list and work on any of them.

## Where to see HTML table?

I keep a copy at https://marcin.juszkiewicz.com.pl/download/tables/syscalls.html page.


## Python support

As a part of this project I provide code to get system call number/name and
availability from Python level.

### Usage

Please check "bin/syscall" script and files in "examples/" directory.


## Why this project looks like python-syscalls one?

I needed to merge both projects to make it more manageable. Now all data is
kept in one place so I do not need to synchronize it between projects.

The plan is to have some kind of CI which would handle updates.
ga4-analytics-processor 0.2.0
A Python library for processing Google Analytics 4 data
Requires Python: >=3.8

# GA4 Analytics Processor

A Python library for processing Google Analytics 4 data with built-in data transformations and channel grouping logic.

## Installation

```bash
pip install ga4-analytics-processor
```

## Quick Start

```python
from ga4_analytics import GA4Processor
from datetime import datetime, timedelta

# Initialize processor
processor = GA4Processor(
    credentials_path="/path/to/your/credentials.json",
    property_id="your_ga4_property_id"
)

# Define date range
end_date = datetime.now().date()
start_date = end_date - timedelta(days=7)

# Fetch and process general report with default dimensions/metrics
df = processor.get_general_report(start_date, end_date)

# Or specify custom dimensions and metrics
custom_dimensions = ["date", "sessionDefaultChannelGroup", "deviceCategory"]
custom_metrics = ["sessions", "totalRevenue", "transactions"]
df_custom = processor.get_general_report(
    start_date, end_date,
    dimensions=custom_dimensions,
    metrics=custom_metrics
)

# For completely custom reports with optional processing
df_raw = processor.get_custom_report(
    start_date, end_date,
    dimensions=custom_dimensions,
    metrics=custom_metrics,
    apply_processing=False  # Get raw data without transformations
)

print(df.head())
```

## Features

- Easy GA4 API integration
- **Flexible dimensions and metrics** - specify your own or use defaults
- **Custom report generation** - with optional data processing
- Built-in data transformations and cleaning
- Channel grouping and campaign labeling
- Revenue reallocation logic
- Email campaign data integration
- Configurable data formatting

## New in v0.2.0

- ✅ **Custom dimensions and metrics** in `get_general_report()`
- ✅ **New `get_custom_report()` method** for full flexibility
- ✅ **Optional data processing** - get raw data or processed data
- ✅ **Backward compatible** - existing code continues to work

## Requirements

- Python 3.8+
- Google Analytics Data API credentials
- pandas, numpy, google-analytics-data

## License

MIT License