Chopsticks is an orchestration library: it lets you manage and configure remote hosts over SSH.
Naturally this is agentless and nothing needs to be installed on the remote host except Python and an SSH agent.
It also has support for executing code in Docker containers.
It's perhaps best compared to Ansible or Fabric, but has some clever transport magic which means it's very easy to develop with: you just write Python functions that can be called from the orchestration host. No invoking bash commands (eg. Fabric) or writing self-contained scripts with constrained input and output formats (eg. Ansible).
One might also draw a comparison with Python's built-in multiprocessing
library, but instead of calling code in subprocesses on the same host, the
code may be run on remote hosts.
With chopsticks you can simply import functions and hand them to the remote host to be executed.
First stand up an SSH Tunnel:
from chopsticks.tunnel import Tunnel
tun = Tunnel('troy.example.com')Then you can pass a function, to be called on the remote host:
import time
print('Time on %s:' % tun.host, tun.call(time.time))You can use any pure-Python function in the current codebase, meaning you can create your own libraries of orchestration functions to call on remote hosts (as well as functions that call out to remote hosts using Chopsticks).
Tunnel provides support for executing on a single host; there is also a
Group that can execute a callable on a number of hosts in parallel:
from chopsticks.group import Group
group = Group([
'web1.example.com',
'web2.example.com',
'web3.example.com',
])
for host, addr in group.call(ip).successful():
print('%s ip:' % host, addr)Subclasses of tunnels allow connecting using streams other than SSH, such as
using sudo, or to fresh Docker containers for sandboxing:
from chopsticks.tunnel import Docker
from chopsticks.group import Group
from chopsticks.facts import python_version
group = Group([
Docker('worker-1', image='python:3.4'),
Docker('worker-2', image='python:3.5'),
Docker('worker-3', image='python:3.6'),
])
for host, python_version in group.call(python_version).items():
print('%s Python version:' % host, python_version)Tunnels and Groups connect lazily (or you can connect them proactively by
calling connect()). They are also usable as context managers:
# Explictly connect and disconnect
group.connect()
group.call(time.time)
group.close()
# Reconnect and disconnect as context manager
with group:
group.call(time.time)
# Implicit reconnect
group.call(time.time)
# Disconnect when destroyed
del groupNaturally, any remote state (imports, globals, etc) is lost when the Tunnel/Group is closed.
Chopsticks can be used directly from a clone of the repo; or installed with pip:
$ pip install chopsticksSee the full documentation on Read The Docs.
Chopsticks supports both Python 2 and Python 3.
Because Chopsticks takes the view that agents run out of the same codebase as the controller, agents will attempt to use a similar Python interpreter to the one for the controller process:
/usr/bin/python2if the controller process is (any) Python 2./usr/bin/python3if the controller process is (any) Python 3.
The SSH tunnel invokes the python binary on the remote host, and feeds it a
bootstrap script via stdin.
Once bootstrapped, the remote "agent" sets up bi-directional communication over the stdin/stdout of the tunnel. This communication is used (currently) for two purposes:
- An RPC system to invoke arbitrary callables within the remote agent and pass the returned values back to the controller.
- A PEP-302 import hook system, allowing the remote agent to import pure-Python code from the controller (NB. the controller can only serve Python modules that live within the filesystem - import hooks such as zipimport/compressed eggs are not currently supported).
stderr is echoed to the controlling console, prefixed with a hostname to
identify which Tunnel it issued from. This can therefore be used to feed
debugging information back to the orchestration host.