pyperf2 0.4.8

Abstraction layer for iperf2 linux binary

Pyperf2 is an abstraction layer to simplify programatic use of the iperf2 binary for linux. It was written to have a simple interface for network test setups. It is mostly used for unicast/multicast network convergence tests so the defaults are tcp 1000pps per instance to have packetloss == 1ms/second. Nevertheless all options are configurable.

Why iperf2 and not iperf3

The reason is simple, iperf3 does not support multicast streams as of now. I need multicast testing capability, so I chose iperf2.

Features

Pyperf2 has following features:

• create and manage iperf2 server instances

• create and manage iperf2 client instances

• get results of client and server instances by parsing output to python datastructures.

• register callbacks for packetloss and intermediate results.

• linux namespace support (requires ip command of iproute2 package)

Installation

Install pyperf2 by running:

pip3 install pyperf2

Examples

Create a unicast udp 1000pps setup and test for 10 seconds

from pyperf2 import Server, Client
from time import sleep
from pprint import pformat


def on_data_callback(message, **kwargs):
    print(f"got message {pformat(message)} \n\n kwargs are {pformat(kwargs)}")
    print("----------------------------------------------------------------------")


receiver = Server()
sender = Client()

receiver.set_options(protocol="udp", server_ip="127.0.0.1", test_duration=12)
receiver.register_on_data_callback(
    on_data_callback, some_custom_parameter="some_custom_value"
)
receiver.start()


sender.set_options(protocol="udp", server_ip="127.0.0.1", test_duration=10)
sender.start()

while sender.status != "stopped":
    print(f"status sender: {sender.status}\nstatus receiver: {receiver.status}\n")
    print("do something usefull in the main thread -> sleeping for 1 second\n")
    sleep(1)

Supported Parameters

To see all supported parameters for the set_options function, review the constructor of the IPerfInstance object.

Contribute

• Issue Tracker: https://github.com/jinjamator/pyperf2/issues

• Source Code: https://github.com/jinjamator/pyperf2

Roadmap

Selected Roadmap items:

• add class documentation

For documentation please refer to https://pyperf2.readthedocs.io/en/latest/

License

This project is licensed under the Apache License Version 2.0