semvec/pypi-packages huggingface dataset:
subprocess-alive 0.10
Checks if a process (pid) is alive on Windows
License: MIT
Keywords: pid,isalive

# Checks if a process (pid) is alive on Windows 

### pip install subprocess-alive

#### Tested against Windows 10 / Python 3.10 / Anaconda


```python

from subprocess_alive import is_process_alive
import subprocess
from time import perf_counter
p = subprocess.Popen("ping 8.8.8.8", shell=True)

start = perf_counter()
while is_process_alive(p.pid):
    print(f"{p.pid} is alive", end="\r")
print(f"{p.pid} is not alive - execution time: {perf_counter()-start}")

start = perf_counter()
p = subprocess.Popen("ping 8.8.8.8", shell=False)
while is_process_alive(p.pid):
    print(f"{p.pid} is alive", end="\r")
print(f"{p.pid} is not alive - execution time: {perf_counter()-start}")



#output
Pinging 8.8.8.8 with 32 bytes of data:
Reply from 8.8.8.8: bytes=32 time=9ms TTL=119
Reply from 8.8.8.8: bytes=32 time=11ms TTL=119
Reply from 8.8.8.8: bytes=32 time=9ms TTL=119
Reply from 8.8.8.8: bytes=32 time=10ms TTL=119
Ping statistics for 8.8.8.8:
    Packets: Sent = 4, Received = 4, Lost = 0 (0% loss),
Approximate round trip times in milli-seconds:
    Minimum = 9ms, Maximum = 11ms, Average = 9ms
18404 is not alive - execution time: 3.170662900000025
Pinging 8.8.8.8 with 32 bytes of data:
Reply from 8.8.8.8: bytes=32 time=10ms TTL=119
Reply from 8.8.8.8: bytes=32 time=9ms TTL=119
Reply from 8.8.8.8: bytes=32 time=10ms TTL=119
Reply from 8.8.8.8: bytes=32 time=9ms TTL=119
Ping statistics for 8.8.8.8:
    Packets: Sent = 4, Received = 4, Lost = 0 (0% loss),
Approximate round trip times in milli-seconds:
    Minimum = 9ms, Maximum = 10ms, Average = 9ms
6788 is not alive - execution time: 3.1898495000023104

```
TerraVide 0.1.6
An open source python package to process and simulate large urban environments mapped with LiDAR data
License: MIT
Requires Python: >=3.6

# TerraVide

TerraVide is an open source python package to process large urban environments mapped with LiDAR(Light Detection and Ranging) data.

It offers the ability to enrich raw lidar data and extract individual tree canopies from raw point clouds. Additionally it offers a suite of modules to simulate and analyze the classified enviroment and quantify shade impacts through interactive visualiztions

TerraVide aims to facilitate large-scale forest management and make more robust and generic tree extraction methods with equitable tree planting decisions. The package is designed to be scalable and can handle large datasets with minimal computational overhead.

# Installation

```python
pip install terravide
```

# Documentation

Visit Terravide's official documentation here : [TerraVide Docs](https://terravide.readthedocs.io/en/latest/)

# License

TerraVide is released under the MIT license.