# Conn
[](https://pypi.org/pypi/connpy/)
[](https://pypi.org/pypi/connpy/)
[](https://github.com/fluzzi/connpy/blob/main/LICENSE)
[](https://pypi.org/pypi/connpy/)
Connpy is a ssh and telnet connection manager and automation module for Linux, Mac and Docker
## Installation
pip install connpy
### Run it in Windows using docker
```
git clone https://github.com/fluzzi/connpy
docker compose -f path/to/folder/docker-compose.yml build
docker compose -f path/to/folder/docker-compose.yml run -it connpy-app
```
## 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
- Create in bulk, copy, move, export and import nodes for easy management.
- Run automation scripts in network devices.
- use GPT AI to help you manage your devices.
- Add plugins with your own scripts.
- Much more!
### Usage:
```
usage: conn [-h] [--add | --del | --mod | --show | --debug] [node|folder] [--sftp]
conn {profile,move,mv,copy,cp,list,ls,bulk,export,import,ai,run,api,plugin,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
-t, --sftp Connects using sftp instead of ssh
```
### Commands:
```
profile Manage profiles
move(mv) Move node
copy(cp) Copy node
list(ls) List profiles, nodes or folders
bulk Add nodes in bulk
export Export connection folder to Yaml file
import Import connection folder to config from Yaml file
ai Make request to an AI
run Run scripts or commands on nodes
api Start and stop connpy api
plugin Manage plugins
config Manage app config
```
### 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
```
## Plugin Requirements for Connpy
### General Structure
- The plugin script must be a Python file.
- Only the following top-level elements are allowed in the plugin script:
- Class definitions
- Function definitions
- Import statements
- The `if __name__ == "__main__":` block for standalone execution
- Pass statements
### Specific Class Requirements
- The plugin script must define at least two specific classes:
1. **Class `Parser`**:
- Must contain only one method: `__init__`.
- The `__init__` method must initialize at least two attributes:
- `self.parser`: An instance of `argparse.ArgumentParser`.
- `self.description`: A string containing the description of the parser.
2. **Class `Entrypoint`**:
- Must have an `__init__` method that accepts exactly three parameters besides `self`:
- `args`: Arguments passed to the plugin.
- The parser instance (typically `self.parser` from the `Parser` class).
- The Connapp instance to interact with the Connpy app.
### Executable Block
- The plugin script can include an executable block:
- `if __name__ == "__main__":`
- This block allows the plugin to be run as a standalone script for testing or independent use.
### Script Verification
- The `verify_script` method in `plugins.py` is used to check the plugin script's compliance with these standards.
- Non-compliant scripts will be rejected to ensure consistency and proper functionality within the plugin system.
-
### Example Script
For a practical example of how to write a compatible plugin script, please refer to the following example:
[Example Plugin Script](https://github.com/fluzzi/awspy)
This script demonstrates the required structure and implementation details according to the plugin system's standards.
## 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)
```
## 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:
```json
{
"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:
```json
{
"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:
```json
{
"action": "<action>",
"nodes": "<nodes>",
"commands": "<commands>",
"expected": "<expected>",
"options": "<options>"
}
```
* `action` (required): The action to be performed. Possible values: `run` or `test`.
* `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 is `test`): 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:
```json
{
"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.
Raw data
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"description": "# Conn\n[](https://pypi.org/pypi/connpy/)\n[](https://pypi.org/pypi/connpy/)\n[](https://github.com/fluzzi/connpy/blob/main/LICENSE)\n[](https://pypi.org/pypi/connpy/)\n\nConnpy is a ssh and telnet connection manager and automation module for Linux, Mac and Docker\n\n## Installation\n\npip install connpy\n\n### Run it in Windows using docker\n```\ngit clone https://github.com/fluzzi/connpy\ndocker compose -f path/to/folder/docker-compose.yml build\ndocker compose -f path/to/folder/docker-compose.yml run -it connpy-app\n```\n\n## Connection manager \n### Features\n - You can generate profiles and reference them from nodes using @profilename so you dont\n need to edit multiple nodes when changing password or other information.\n - Nodes can be stored on @folder or @subfolder@folder to organize your devices. Then can \n be referenced using node@subfolder@folder or node@folder\n - If you have too many nodes. Get completion script using: conn config --completion.\n Or use fzf installing pyfzf and running conn config --fzf true\n - Create in bulk, copy, move, export and import nodes for easy management.\n - Run automation scripts in network devices.\n - use GPT AI to help you manage your devices.\n - Add plugins with your own scripts.\n - Much more!\n\n### Usage:\n```\nusage: conn [-h] [--add | --del | --mod | --show | --debug] [node|folder] [--sftp]\n conn {profile,move,mv,copy,cp,list,ls,bulk,export,import,ai,run,api,plugin,config} ...\n\npositional arguments:\n node|folder node[@subfolder][@folder]\n Connect to specific node or show all matching nodes\n [@subfolder][@folder]\n Show all available connections globaly or in specified path\n```\n\n### Options:\n```\n -h, --help show this help message and exit\n -v, --version Show version\n -a, --add Add new node[@subfolder][@folder] or [@subfolder]@folder\n -r, --del, --rm Delete node[@subfolder][@folder] or [@subfolder]@folder\n -e, --mod, --edit Modify node[@subfolder][@folder]\n -s, --show Show node[@subfolder][@folder]\n -d, --debug Display all conections steps\n -t, --sftp Connects using sftp instead of ssh\n```\n\n### Commands:\n```\n profile Manage profiles\n move(mv) Move node\n copy(cp) Copy node\n list(ls) List profiles, nodes or folders\n bulk Add nodes in bulk\n export Export connection folder to Yaml file\n import Import connection folder to config from Yaml file\n ai Make request to an AI\n run Run scripts or commands on nodes\n api Start and stop connpy api\n plugin Manage plugins\n config Manage app config\n```\n\n### Manage profiles:\n```\nusage: conn profile [-h] (--add | --del | --mod | --show) profile\n\npositional arguments:\n profile Name of profile to manage\n\noptions:\n -h, --help show this help message and exit\n -a, --add Add new profile\n -r, --del, --rm Delete profile\n -e, --mod, --edit Modify profile\n -s, --show Show profile\n\n```\n\n### Examples:\n```\n conn profile --add office-user\n conn --add @office\n conn --add @datacenter@office\n conn --add server@datacenter@office\n conn --add pc@office\n conn --show server@datacenter@office\n conn pc@office\n conn server\n``` \n## Plugin Requirements for Connpy\n\n### General Structure\n- The plugin script must be a Python file.\n- Only the following top-level elements are allowed in the plugin script:\n - Class definitions\n - Function definitions\n - Import statements\n - The `if __name__ == \"__main__\":` block for standalone execution\n - Pass statements\n\n### Specific Class Requirements\n- The plugin script must define at least two specific classes:\n 1. **Class `Parser`**:\n - Must contain only one method: `__init__`.\n - The `__init__` method must initialize at least two attributes:\n - `self.parser`: An instance of `argparse.ArgumentParser`.\n - `self.description`: A string containing the description of the parser.\n 2. **Class `Entrypoint`**:\n - Must have an `__init__` method that accepts exactly three parameters besides `self`:\n - `args`: Arguments passed to the plugin.\n - The parser instance (typically `self.parser` from the `Parser` class).\n - The Connapp instance to interact with the Connpy app.\n\n### Executable Block\n- The plugin script can include an executable block:\n - `if __name__ == \"__main__\":`\n - This block allows the plugin to be run as a standalone script for testing or independent use.\n\n### Script Verification\n- The `verify_script` method in `plugins.py` is used to check the plugin script's compliance with these standards.\n- Non-compliant scripts will be rejected to ensure consistency and proper functionality within the plugin system.\n- \n### Example Script\n\nFor a practical example of how to write a compatible plugin script, please refer to the following example:\n\n[Example Plugin Script](https://github.com/fluzzi/awspy)\n\nThis script demonstrates the required structure and implementation details according to the plugin system's standards.\n\n## Automation module usage\n### Standalone module\n```\nimport connpy\nrouter = connpy.node(\"uniqueName\",\"ip/host\", user=\"username\", password=\"password\")\nrouter.run([\"term len 0\",\"show run\"])\nprint(router.output)\nhasip = router.test(\"show ip int brief\",\"1.1.1.1\")\nif hasip:\n print(\"Router has ip 1.1.1.1\")\nelse:\n print(\"router does not have ip 1.1.1.1\")\n```\n\n### Using manager configuration\n```\nimport connpy\nconf = connpy.configfile()\ndevice = conf.getitem(\"router@office\")\nrouter = connpy.node(\"unique name\", **device, config=conf)\nresult = router.run(\"show ip int brief\")\nprint(result)\n```\n### Running parallel tasks on multiple devices \n```\nimport connpy\nconf = connpy.configfile()\n#You can get the nodes from the config from a folder and fitlering in it\nnodes = conf.getitem(\"@office\", [\"router1\", \"router2\", \"router3\"])\n#You can also get each node individually:\nnodes = {}\nnodes[\"router1\"] = conf.getitem(\"router1@office\")\nnodes[\"router2\"] = conf.getitem(\"router2@office\")\nnodes[\"router10\"] = conf.getitem(\"router10@datacenter\")\n#Also, you can create the nodes manually:\nnodes = {}\nnodes[\"router1\"] = {\"host\": \"1.1.1.1\", \"user\": \"user\", \"password\": \"password1\"}\nnodes[\"router2\"] = {\"host\": \"1.1.1.2\", \"user\": \"user\", \"password\": \"password2\"}\nnodes[\"router3\"] = {\"host\": \"1.1.1.2\", \"user\": \"user\", \"password\": \"password3\"}\n#Finally you run some tasks on the nodes\nmynodes = connpy.nodes(nodes, config = conf)\nresult = mynodes.test([\"show ip int br\"], \"1.1.1.2\")\nfor i in result:\n print(\"---\" + i + \"---\")\n print(result[i])\n print()\n# Or for one specific node\nmynodes.router1.run([\"term len 0\". \"show run\"], folder = \"/home/user/logs\")\n```\n### Using variables\n```\nimport connpy\nconfig = connpy.configfile()\nnodes = config.getitem(\"@office\", [\"router1\", \"router2\", \"router3\"])\ncommands = []\ncommands.append(\"config t\")\ncommands.append(\"interface lo {id}\")\ncommands.append(\"ip add {ip} {mask}\")\ncommands.append(\"end\")\nvariables = {}\nvariables[\"router1@office\"] = {\"ip\": \"10.57.57.1\"}\nvariables[\"router2@office\"] = {\"ip\": \"10.57.57.2\"}\nvariables[\"router3@office\"] = {\"ip\": \"10.57.57.3\"}\nvariables[\"__global__\"] = {\"id\": \"57\"}\nvariables[\"__global__\"][\"mask\"] = \"255.255.255.255\"\nexpected = \"!\"\nrouters = connpy.nodes(nodes, config = config)\nrouters.run(commands, variables)\nrouters.test(\"ping {ip}\", expected, variables)\nfor key in routers.result:\n print(key, ' ---> ', (\"pass\" if routers.result[key] else \"fail\"))\n```\n### Using AI\n```\nimport connpy\nconf = connpy.configfile()\norganization = 'openai-org'\napi_key = \"openai-key\"\nmyia = ai(conf, organization, api_key)\ninput = \"go to router 1 and get me the full configuration\"\nresult = myia.ask(input, dryrun = False)\nprint(result)\n```\n## http API\nWith the Connpy API you can run commands on devices using http requests\n\n### 1. List Nodes\n\n**Endpoint**: `/list_nodes`\n\n**Method**: `POST`\n\n**Description**: This route returns a list of nodes. It can also filter the list based on a given keyword.\n\n#### Request Body:\n\n```json\n{\n \"filter\": \"<keyword>\"\n}\n```\n\n* `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.\n\n#### Response:\n\n- A JSON array containing the filtered list of nodes.\n\n---\n\n### 2. Get Nodes\n\n**Endpoint**: `/get_nodes`\n\n**Method**: `POST`\n\n**Description**: This route returns a dictionary of nodes with all their attributes. It can also filter the nodes based on a given keyword.\n\n#### Request Body:\n\n```json\n{\n \"filter\": \"<keyword>\"\n}\n```\n\n* `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.\n\n#### Response:\n\n- A JSON array containing the filtered nodes.\n\n---\n\n### 3. Run Commands\n\n**Endpoint**: `/run_commands`\n\n**Method**: `POST`\n\n**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.\n\n#### Request Body:\n\n```json\n{\n \"action\": \"<action>\",\n \"nodes\": \"<nodes>\",\n \"commands\": \"<commands>\",\n \"expected\": \"<expected>\",\n \"options\": \"<options>\"\n}\n```\n\n* `action` (required): The action to be performed. Possible values: `run` or `test`.\n* `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.\n* `commands` (required): A list of commands to be executed on the specified nodes.\n* `expected` (optional, only used when the action is `test`): A single expected result for the test.\n* `options` (optional): Array to pass options to the run command, options are: `prompt`, `parallel`, `timeout` \n\n#### Response:\n\n- A JSON object with the results of the executed commands on the nodes.\n\n---\n\n### 4. Ask AI\n\n**Endpoint**: `/ask_ai`\n\n**Method**: `POST`\n\n**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.\n\n#### Request Body:\n\n```json\n{\n \"input\": \"<user input request>\",\n \"dryrun\": true or false\n}\n```\n\n* `input` (required): The user input requesting the AI to perform an action on some devices or get the devices list.\n* `dryrun` (optional): If set to true, it will return the parameters to run the request but it won't run it. default is false.\n\n#### Response:\n\n- A JSON array containing the action to run and the parameters and the result of the action.\n\n\n",
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