Python data structures: lists, dictionaries, sets and tuples for networks

Why data structures matter

Almost every automation task starts with data: a list of switches, the VLANs on a trunk, the interfaces that are down. How you store that data decides how easy the rest of the script is. Python has four built-in collections, and each one fits a different job.

Lists and tuples

A list is an ordered collection you can change: add, remove, sort. A tuple is ordered too, but fixed once created, which makes it a good fit for a record that should not change, such as a (hostname, IP address) pair.

switches = ["acc-sw1", "acc-sw2", "core-sw1"]
switches.append("acc-sw3")
switches.sort()
print(switches[0], len(switches))

mgmt = ("core-sw1", "192.168.10.1")
name, ip = mgmt          # unpack a tuple
print(name, ip)

Indexes start at 0, and switches[-1] gives the last item. Slicing, such as switches[0:2], returns a new list with the first two items.

Dictionaries and sets

A dictionary (dict) maps keys to values, like a lookup table. It is the natural way to describe one device or one interface. A set holds unique values only and is excellent for comparisons, such as which VLANs are allowed on one trunk but missing on the other.

device = {"hostname": "core-sw1", "ip": "192.168.10.1", "platform": "cisco_ios"}
print(device["hostname"])
print(device.get("site", "unknown"))   # default if the key is missing
device["site"] = "london"

trunk_a = {10, 20, 30, 40}
trunk_b = {10, 20, 50}
print(trunk_a - trunk_b)   # on A but not on B: {30, 40}
print(trunk_a & trunk_b)   # on both: {10, 20}

Tip: use .get() when a key may not exist. Square brackets raise a KeyError for a missing key, which is sometimes what you want and sometimes a crash.

Nesting: modelling real network data

Real data is nested. An inventory is usually a list of dictionaries, one per device. This is also the shape you get when you load JSON (JavaScript Object Notation) or YAML from a file or an API, so learning it pays off everywhere.

inventory = [
    {"hostname": "acc-sw1", "ip": "192.168.10.11", "vlans": [10, 20]},
    {"hostname": "acc-sw2", "ip": "192.168.10.12", "vlans": [10, 30]},
]

for dev in inventory:
    print(dev["hostname"], dev["ip"])

all_vlans = {v for dev in inventory for v in dev["vlans"]}
print(sorted(all_vlans))

by_name = {dev["hostname"]: dev for dev in inventory}
print(by_name["acc-sw2"]["ip"])

The last two lines use comprehensions, a compact way to build a set or dict from a loop. Keep them short; if a comprehension needs a second line to explain it, write a normal loop instead.

Choosing well and common mistakes

• Searching a long list with in is slow; a set or dict lookup is near instant.
• Sets have no order, so sort them before printing reports.
• Copying with b = a does not copy a list; both names point to the same object. Use a.copy().
• Dict keys must be unchangeable types (strings, numbers, tuples), never lists.