Modifying a list/dict effects all variables sharing that address

[64andy]

BPO	32712
Nosy	@bitdancer, @64andy

^{Note: these values reflect the state of the issue at the time it was migrated and might not reflect the current state.}

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GitHub fields:

assignee = None
closed_at = <Date 2018-01-29.14:15:53.381>
created_at = <Date 2018-01-29.13:57:45.806>
labels = ['type-bug', 'invalid']
title = 'Modifying a list/dict effects all variables sharing that address'
updated_at = <Date 2018-01-29.14:15:53.359>
user = 'https://github.com/64andy'

bugs.python.org fields:

activity = <Date 2018-01-29.14:15:53.359>
actor = 'r.david.murray'
assignee = 'none'
closed = True
closed_date = <Date 2018-01-29.14:15:53.381>
closer = 'r.david.murray'
components = []
creation = <Date 2018-01-29.13:57:45.806>
creator = '64andy'
dependencies = []
files = []
hgrepos = []
issue_num = 32712
keywords = []
message_count = 2.0
messages = ['311135', '311140']
nosy_count = 2.0
nosy_names = ['r.david.murray', '64andy']
pr_nums = []
priority = 'normal'
resolution = 'not a bug'
stage = 'resolved'
status = 'closed'
superseder = None
type = 'behavior'
url = 'https://bugs.python.org/issue32712'
versions = ['Python 3.6']

[64andy]

If multiple lists/dictionaries are in the same memory address (usually caused by var1 = var2), then altering one will effect every variable in that address.
The ways I've found to achieve this are:
>>> my_list[2] = "Spam"
>>> my_list += "9"
>>> my_list.insert(4, "Hello")
>>> dictvar.update({"Three": "Four"})

This was achieved using Python 3.6.4 32-bit and 3.6.3 64-bit (CPython), and happened in both IDLE and python.exe

List Example code:
x = ['a','b','c']
y = x #Now y and x share a memory address, because CPython does that
print(f"Sanity test - x and y share the same address = {x is y}")

y[1] = '123'
y += ["Foo"]
y.insert(-1, "Eleven")

#x's Expected Value: ['a','b','c']
print(x) #Actual Value

[bitdancer]

Yep, that's the way Python works. You are modifying the same object through different names. Remember that in Python it is the objects that matter (which are identified in CPython via their memory address, but that's an implementation detail) and names are just handy references to those objects. There can be any number of names that reference a single object.