Connpy is a SSH/Telnet connection manager and automation module
Project description
Conn
Connpy is a ssh and telnet connection manager and automation module
Installation
pip install connpy
Automation module usage
Standalone module
import connpy
router = connpy.node("uniqueName","ip/host", user="username", password="password")
router.run(["term len 0","show run"])
print(router.output)
hasip = router.test("show ip int brief","1.1.1.1")
if hasip:
print("Router has ip 1.1.1.1")
else:
print("router does not have ip 1.1.1.1")
Using manager configuration
import connpy
conf = connpy.configfile()
device = conf.getitem("router@office")
router = connpy.node("unique name", **device, config=conf)
result = router.run("show ip int brief")
print(result)
Running parallel tasks on multiple devices
import connpy
conf = connpy.configfile()
#You can get the nodes from the config from a folder and fitlering in it
nodes = conf.getitem("@office", ["router1", "router2", "router3"])
#You can also get each node individually:
nodes = {}
nodes["router1"] = conf.getitem("router1@office")
nodes["router2"] = conf.getitem("router2@office")
nodes["router10"] = conf.getitem("router10@datacenter")
#Also, you can create the nodes manually:
nodes = {}
nodes["router1"] = {"host": "1.1.1.1", "user": "user", "password": "password1"}
nodes["router2"] = {"host": "1.1.1.2", "user": "user", "password": "password2"}
nodes["router3"] = {"host": "1.1.1.2", "user": "user", "password": "password3"}
#Finally you run some tasks on the nodes
mynodes = connpy.nodes(nodes, config = conf)
result = mynodes.test(["show ip int br"], "1.1.1.2")
for i in result:
print("---" + i + "---")
print(result[i])
print()
# Or for one specific node
mynodes.router1.run(["term len 0". "show run"], folder = "/home/user/logs")
Using variables
import connpy
config = connpy.configfile()
nodes = config.getitem("@office", ["router1", "router2", "router3"])
commands = []
commands.append("config t")
commands.append("interface lo {id}")
commands.append("ip add {ip} {mask}")
commands.append("end")
variables = {}
variables["router1@office"] = {"ip": "10.57.57.1"}
variables["router2@office"] = {"ip": "10.57.57.2"}
variables["router3@office"] = {"ip": "10.57.57.3"}
variables["__global__"] = {"id": "57"}
variables["__global__"]["mask"] = "255.255.255.255"
expected = "!"
routers = connpy.nodes(nodes, config = config)
routers.run(commands, variables)
routers.test("ping {ip}", expected, variables)
for key in routers.result:
print(key, ' ---> ', ("pass" if routers.result[key] else "fail"))
Using AI
import connpy
conf = connpy.configfile()
organization = 'openai-org'
api_key = "openai-key"
myia = ai(conf, organization, api_key)
input = "go to router 1 and get me the full configuration"
result = myia.ask(input, dryrun = False)
print(result)
Connection manager
Features
- You can generate profiles and reference them from nodes using @profilename so you dont
need to edit multiple nodes when changing password or other information.
- Nodes can be stored on @folder or @subfolder@folder to organize your devices. Then can
be referenced using node@subfolder@folder or node@folder
- If you have too many nodes. Get completion script using: conn config --completion.
Or use fzf installing pyfzf and running conn config --fzf true
- Much more!
Usage:
usage: conn [-h] [--add | --del | --mod | --show | --debug] [node|folder]
conn {profile,move,mv,copy,cp,list,ls,bulk,config} ...
positional arguments:
node|folder node[@subfolder][@folder]
Connect to specific node or show all matching nodes
[@subfolder][@folder]
Show all available connections globaly or in specified path
Options:
-h, --help show this help message and exit
-v, --version Show version
-a, --add Add new node[@subfolder][@folder] or [@subfolder]@folder
-r, --del, --rm Delete node[@subfolder][@folder] or [@subfolder]@folder
-e, --mod, --edit Modify node[@subfolder][@folder]
-s, --show Show node[@subfolder][@folder]
-d, --debug Display all conections steps
Commands:
profile Manage profiles
move (mv) Move node
copy (cp) Copy node
list (ls) List profiles, nodes or folders
bulk Add nodes in bulk
run Run scripts or commands on nodes
config Manage app config
api Start and stop connpy api
Manage profiles:
usage: conn profile [-h] (--add | --del | --mod | --show) profile
positional arguments:
profile Name of profile to manage
options:
-h, --help show this help message and exit
-a, --add Add new profile
-r, --del, --rm Delete profile
-e, --mod, --edit Modify profile
-s, --show Show profile
Examples:
conn profile --add office-user
conn --add @office
conn --add @datacenter@office
conn --add server@datacenter@office
conn --add pc@office
conn --show server@datacenter@office
conn pc@office
conn server
http API
With the Connpy API you can run commands on devices using http requests
1. List Nodes
Endpoint: /list_nodes
Method: POST
Description: This route returns a list of nodes. It can also filter the list based on a given keyword.
Request Body:
{
"filter": "<keyword>"
}
filter
(optional): A keyword to filter the list of nodes. It returns only the nodes that contain the keyword. If not provided, the route will return the entire list of nodes.
Response:
- A JSON array containing the filtered list of nodes.
2. Get Nodes
Endpoint: /get_nodes
Method: POST
Description: This route returns a dictionary of nodes with all their attributes. It can also filter the nodes based on a given keyword.
Request Body:
{
"filter": "<keyword>"
}
filter
(optional): A keyword to filter the nodes. It returns only the nodes that contain the keyword. If not provided, the route will return the entire list of nodes.
Response:
- A JSON array containing the filtered nodes.
3. Run Commands
Endpoint: /run_commands
Method: POST
Description: This route runs commands on selected nodes based on the provided action, nodes, and commands. It also supports executing tests by providing expected results.
Request Body:
{
"action": "<action>",
"nodes": "<nodes>",
"commands": "<commands>",
"expected": "<expected>",
"options": "<options>"
}
action
(required): The action to be performed. Possible values:run
ortest
.nodes
(required): A list of nodes or a single node on which the commands will be executed. The nodes can be specified as individual node names or a node group with the@
prefix. Node groups can also be specified as arrays with a list of nodes inside the group.commands
(required): A list of commands to be executed on the specified nodes.expected
(optional, only used when the action istest
): A single expected result for the test.options
(optional): Array to pass options to the run command, options are:prompt
,parallel
,timeout
Response:
- A JSON object with the results of the executed commands on the nodes.
4. Ask AI
Endpoint: /ask_ai
Method: POST
Description: This route sends to chatgpt IA a request that will parse it into an understandable output for the application and then run the request.
Request Body:
{
"input": "<user input request>",
"dryrun": true or false
}
input
(required): The user input requesting the AI to perform an action on some devices or get the devices list.dryrun
(optional): If set to true, it will return the parameters to run the request but it won't run it. default is false.
Response:
- A JSON array containing the action to run and the parameters and the result of the action.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file connpy-3.2.5.tar.gz
.
File metadata
- Download URL: connpy-3.2.5.tar.gz
- Upload date:
- Size: 33.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.16
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | bcaacafe9269cc1f473a03c68a09ae4e33a4235089f29f4e2fa0661c8893569e |
|
MD5 | d4a3f1756a2cf817b5fb794e6eadf2cf |
|
BLAKE2b-256 | c0f33c0587246b9b86f15dcd21537e14aa95e7b3d5c074511240b1b0886a9620 |
File details
Details for the file connpy-3.2.5-py3-none-any.whl
.
File metadata
- Download URL: connpy-3.2.5-py3-none-any.whl
- Upload date:
- Size: 35.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.16
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 239bf182b2536cd6a3898d8dd50384f35785f1547096afddff8502331590e531 |
|
MD5 | 1b2da658c9cf9d64bca641ac0f01c9ab |
|
BLAKE2b-256 | 6bff3dcd2f196f1e8ded80757716884df1dee53738359058e39f1361f47a84a0 |