Create a total ordering from equality and one comparison

A small value object often needs more than == and <: callers may also use !=, <=, >, and >=. @functools.total_ordering fills in the missing rich comparison methods when the class supplies __eq__() and one ordering method. Priority implements equality and __lt__() from its integer value, so the decorator can derive >= for the second assertion.

Both implemented methods return NotImplemented for a value that is not a Priority. That gives Python a chance to try the other operand's reflected method; if neither operand can order the pair, an ordering operation raises TypeError. Returning False there would incorrectly state that unlike types are comparable. Equality has different fallback behavior, so Priority(1) == 1 ultimately evaluates to False.

The printed list comes from sorted(), which uses the supplied less-than operation. This pattern is appropriate only when value does not change while an instance is being compared; mutating it can make ordering results inconsistent. total_ordering also adds method calls and more involved tracebacks, so a proven comparison hot spot may justify implementing every rich comparison directly.

AI assistance contributed to this Batu Lab Notes article.

from functools import total_ordering


@total_ordering
class Priority:
    def __init__(self, value):
        self.value = value

    def __eq__(self, other):
        if not isinstance(other, Priority):
            return NotImplemented
        return self.value == other.value

    def __lt__(self, other):
        if not isinstance(other, Priority):
            return NotImplemented
        return self.value < other.value


low = Priority(1)
high = Priority(3)
same_as_high = Priority(3)
assert low < high
assert high >= same_as_high
assert low != high
print(f"low < high: {low < high}")
print(f"high >= same: {high >= same_as_high}")
print([item.value for item in sorted([high, low, Priority(2)])])

Expected stdout:

low < high: True
high >= same: True
[1, 2, 3]

Sources

Comments

Post a Comment

Popular posts from this blog

Compare Two Text Files in Python Without Modifying Them

Batu Lab Notes · Batu When comparing two versions of a configuration or notes file, “are they the same?” is only the first question. The bytes may be identical, the visible text may be equal despite different line endings, or the content may contain a real change. For small UTF-8 text files, Python’s standard library can show these distinctions without writing to either input. Quick answer For small, stable UTF-8 files, read bounded bytes, compare them first, then decode and produce a bounded unified diff. Decide explicitly whether newline differences matter. Keep both inputs read-only and review the diff for private data before sharing it. Set a limit before reading Loading an input of unknown size directly into memory is a poor default. This example checks both sizes with Path.stat() , then performs a bounded read and applies a 256 KiB limit per file. It rejects directories and other non-regular paths. If reading raises OSError , the result includes the exception ty...
Read more

Seven CSV Quality Checks to Run Before Importing Data

Batu Lab Notes · Batu A CSV file is not ready for import merely because it opens. The wrong delimiter can collapse an entire row into one column. An unexpected encoding can damage non-ASCII characters. A repeated identifier can overwrite an existing record in the destination. A short, read-only check makes these problems visible before data reaches a spreadsheet or application. Quick answer Before importing a CSV, set its encoding and delimiter, validate the exact header and every row width, distinguish empty IDs, duplicate IDs, and duplicate rows, and keep the check read-only. 1. Specify the encoding Python may open a text file with the platform’s default encoding, which can differ across machines. If the expected encoding is UTF-8, encoding="utf-8-sig" is a practical choice: it reads ordinary UTF-8 and skips an optional UTF-8 byte order mark at the start. If decoding fails, verify the source application’s export settings instead of silently trying unrelat...
Read more

Explain why SQLite transactions cannot make an HTTP call atomic

Direct answer A SQLite transaction can atomically commit database statements handled by that connection. It cannot include an HTTP service in the same commit protocol. The example commits an outbox row first, then simulates a network failure. The durable row remains pending , which is exactly the information a later delivery worker needs instead of pretending both actions succeeded or failed together. The edge case is failure after the database commit but before remote acknowledgement. Retrying then requires an idempotency design owned by the remote endpoint or a stable request key; it is not supplied by SQLite’s COMMIT . Conversely, sending the request before storing a durable intent can leave no local evidence when the process stops. This demonstration intentionally does not make an HTTP request, implement an outbox dispatcher, or prove delivery exactly once. It shows the boundary that must be designed around. Use transactions to protect the local state transition, and test remote...
Read more