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Parquery
icontract
Python2020–2026
Parquery / icontract

icontract

Design-by-contract in Python3 with informative violation messages and inheritance

4Distinct people
8Mentions
0Explicit recommenders
420GitHub stars
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Design-by-contract in Python3 with informative violation messages and inheritance

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This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:03:16 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year8 dated mentions

Observed mentions: 2020-12-14 21:43:46 UTC to 2026-03-17 06:11:17 UTC.

0122020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20232024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2026-01-01 00:00:00 UTC to 2027-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments. Incomplete calendar period.2026*

* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC101
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC101
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC000
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC101
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC101
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC202
2026 (partial)2026-01-01 00:00:00 UTC2027-01-01 00:00:00 UTC202

What Hacker News says

8 sources
Parquery/icontract: https://github.com/Parquery/icontract mristin/icontract-hypothesis: https://github.com/mristin/icontract-hypothesis : > The result is a powerful combination that allows you to automatically test your code. Instead of writing manually the Hypothesis search strategies for a function, icontract-hypothesis infers them based on the function's precondition. This makes automatic testing as effortless as it goes. pschanely/CrossHair: An analysis tool for Python that blurs the line between testing and type systems https://github.com/pschanely/CrossHair : > If you have a function with type annotations and add a contract in a supported syntax, CrossHair will attempt to find counterexamples for you: [gif] > CrossHair works by repeatedly calling your functions with symbolic inputs. It uses an SMT solver (a kind of theorem prover)
Read the rest
to explore viable execution paths and find counterexamples for you
In Comparing Python Type Checkers: Typing Spec Conformance
- /?hnlog pycontract icontract https://westurner.github.io/hnlog/ : From https://news.ycombinator.com/item?id=14246095 (2017) : > PyContracts supports runtime type-checking and value constraints/assertions (as @contract decorators, annotations, and docstrings). > Unfortunately, there's yet no unifying syntax between PyContracts and the newer python type annotations which MyPy checks at compile-type. Or beartype. Pycontracts has: https://andreacensi.github.io/contracts/ : @contract def my_function(a : 'int,>0', b : 'list[N],N>0') -> 'list[N]': @contract(image='array[HxWx3](uint8),H>10,W>10') def recolor(image): For icontract, there's icontract-hyothesis. parquery/icontract: https://github.com/Parquery/icontract : > There exist a couple of contract libraries. However, at the time of this writing (September 2018), they all requir
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ed the programmer either to learn a new syntax (PyContracts) or to write redundant condition descriptions ( e.g., contracts, covenant, deal, dpcontracts, pyadbc and pcd). @icontract.require(lambda x: x > 3, "x must not be small") def some_func(x: int, y: int = 5) -> None: icontract with numpy array types: @icontract.require(lambda arr: isinstance(arr, np.ndarray)) @icontract.require(lambda arr: arr.shape == (3, 3)) @icontract.require(lambda arr: np.all(arr >= 0), "All elements must be non-negative") def process_matrix(arr: np.ndarray): return np.sum(arr) invalid_matrix = np.array([[1, -2, 3], [4, 5, 6], [7, 8, 9]]) process_matrix(invalid_matrix) # Raises icontract.ViolationError
In Comparing Python Type Checkers: Typing Spec Conformance
PMap and PVector, functional Python libraries, "PEP 351 – The freeze protocol" (2005, rejected) https://peps.python.org/pep-0351/ ; IIUC the freeze protocol proposed basically: def freeze(obj) return cache.setsefault(hash(obj), obj.__freeze__()) /? "Existing threads re: consts and applications thereof" I wasn't able to find a URL to this post (2021) from the python-ideas mailing list archives using a double quoted search term today; I had to use the python mailing list search engine? Did something break crawling of mailing lists? Old mailman HTML archives were very simple to crawl.. ENH: pypa: add a sitemap.xml for/of mailing list archives, forums; @pypa: ask for search engine indexing advice: "How do we make sure that the python mailing list archives will be search indexed?" (as they traditionally were) How to find the .t
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xt of mailing list archives posts these days? From "[Python-ideas] Re: Introduce constant variables in Python" (2021) https://mail.python.org/archives/list/python-ideas@python.or... : - pyrsistent: PMap, PVector I'm out of time for this; (reformatting this for HN so that URLs will be auto-linkified but newlines won't be eliminated) here's the full email as .txt, the mailing list archive has a hyperlinkified version with newlines preserved. GH Markdown and CommonMark Markdown also preserve newlines and auto-linkify: From: [@westurner] Date: Thu, Jun 17, 2021, 10:43 AM Subject: Re: [Python-ideas] Re: Introduce constant variables in Python Cc: python-ideas <python-ideas@python.org> On Mon, May 24, 2021 at 5:43 PM Chris Angelico <rosuav@gmail.com> wrote: Requiring that a name not be rebound is well-defined and testable. Requiring that an object not change is either trivial (in the case of, say, an integer) or virtually impossible (in the case of most objects). What would be the advantage of such a declaration? ChrisA ## Existing threads re: consts and applications thereof So, `/? from:me pyrsistent` I found a few results: - "[Python-Dev] Challenge: Please break this! (a.k.a restricted mode revisited)" 2016-04 https://mail.python.org/pipermail/python-dev/2016-April/143958.html - ~Sandboxing python within python is nontrivial to impossible; consts might help a bit - https://mail.python.org/pipermail/python-dev/2016-April/143958.html - "Proposal to add const-ness type hints to PEP-484" https://mail.python.org/archives/list/python-ideas@python.org/thread/OVPF5I6IOVF6G… - https://github.com/python/typing/issues/242 - "Final names and attributes" https://github.com/python/mypy/pull/5522 This is where `typing.Final` comes from. - "[Python-ideas] "Immutable Builder" Pattern and Operator" https://mail.python.org/pipermail/python-ideas/2017-January/044374.html - [pyrsistent] and "fn.py [do] immutables: https://github.com/kachayev/fn.py/blob/master/README.rst#persistent-data-structures " - "[Python-ideas] Add recordlcass to collections module" https://groups.google.com/g/python-ideas/c/9crHfcCBgYs/m/6_EEaWJAAgAJ - ORMs (e.g. Django, SQLAlchemy) require "dirty state" checking to know which object attributes have changed and need an SQL statement to be executed to synchronize the state; this is relevant because when we're asking for mutable namedtuple we're often trying to do exactly this pattern. - "[Python-ideas] Suggestions: dict.flow_update and dict.__add__" https://www.google.com/search?q=%22%5BPython-ideas%5D+Suggestions%3A+dict.flow_upd… > dicttoolz has functions for working with these objects; including dicttoolz.merge (which returns a reference to the merged dicts but does not mutate the arguments passed). > > https://toolz.readthedocs.io/en/latest/api.html#dicttoolz > https://toolz.readthedocs.io/en/latest/api.html#toolz.dicttoolz.merge > > pyrsistent has a PRecord class with invariants and type checking that precedes dataclasses. pyrsistent also has 'freeze' and 'thaw' functions for immutability. PRecord extends PMap, which implements __add__ as self.update(arg) (which does not mutate self) https://github.com/tobgu/pyrsistent/blob/master/README.rst#precord > > https://github.com/tobgu/pyrsistent/blob/master/pyrsistent/_pmap.py - "[Python-ideas] How to prevent shared memory from being corrupted ?" https://www.google.com/search?q=%22How+to+prevent+shared+memory+from+being+corrupt… > PyArrow Plasma object ids, "sealing" makes an object immutable, pyristent > > https://arrow.apache.org/docs/python/plasma.html#object-ids > https://arrow.apache.org/docs/python/plasma.html#creating-an-object-buffer > > Objects are created in Plasma in two stages. First, they are created, which allocates a buffer for the object. At this point, the client can write to the buffer and construct the object within the allocated buffer. [...] - [Python-ideas] Experimenting with dict performance, and an immutable dict https://mail.python.org/archives/list/python-ideas@python.org/message/DNBGUJHDH4UT… > https://pyrsistent.readthedocs.io/en/latest/intro.html#pyrsistent : > >> Pyrsistent is a number of persistent collections (by some referred to as functional data structures). Persistent in the sense that they are immutable. >> >> All methods on a data structure that would normally mutate it instead return a new copy of the structure containing the requested updates. The original structure is left untouched. >> >> This will simplify the reasoning about what a program does since no hidden side effects ever can take place to these data structures. You can rest assured that the object you hold a reference to will remain the same throughout its lifetime and need not worry that somewhere five stack levels below you in the darkest corner of your application someone has decided to remove that element that you expected to be there. >> >> Pyrsistent is influenced by persistent data structures such as those found in the standard library of Clojure. The data structures are designed to share common elements through path copying. It aims at taking these concepts and make them as pythonic as possible so that they can be easily integrated into any python program without hassle. > What would be the advantage of such a declaration? Constants don't need to be locked or unlocked; which is advantageous for parallelism and reasoning about program correctness. True consts (wherein everything referred to in that object is 'frozen' and immutable or at least only modifiable with e.g. copy-on-write) wouldn't require locks, which would be post-GIL advantageous. You could do consts by never releasing a threading.Lock (or similar): - https://docs.python.org/3/library/asyncio-sync.html#locks - https://docs.python.org/3/library/threading.html#lock-objects - This from https://docs.python.org/2/library/sets.html?highlight=immutable#immutable-transforms re ImmutableSet/FrozenSet is not present in the python 3 docs: https://docs.python.org/3/library/stdtypes.html#set-types-set-frozenset Though - even if Python enforced normal consts in the language - all of the other code objects would still be mutable, so you still have the impossibility of sandboxing python. Functional and contracts coding styles rely upon invariance; which can be accomplished with various third-party packages that enforce const-ness throughout what may be an object tree behind that reference that would otherwise need to be copy.deepcopy()'d. ## pyrsistent Src: https://github.com/tobgu/pyrsistent > - PVector, similar to a python list > - PMap, similar to dict > - PSet, similar to set > - PRecord, a PMap on steroids with fixed fields, optional type and invariant checking and much more > - PClass, a Python class fixed fields, optional type and invariant checking and much more > - Checked collections, PVector, PMap and PSet with optional type and invariance checks and more > - PBag, similar to collections.Counter > - PList, a classic singly linked list > - PDeque, similar to collections.deque > - Immutable object type (immutable) built on the named tuple > - freeze and thaw functions to convert between python standard collections and pyrsistent collections. > - Flexible transformations of arbitrarily complex structures built from PMaps and PVectors. ## icontract Src: https://github.com/Parquery/icontract > icontract provides design-by-contract to Python3 with informative violation messages and inheritance. > > It also gives a base for a flourishing of a wider ecosystem: > > - A linter pyicontract-lint, > - A sphinx plug-in sphinx-icontract, > - A tool icontract-hypothesis for automated testing and ghostwriting test files which infers Hypothesis strategies based on the contracts, together with IDE integrations such as icontract-hypothesis-vim, icontract-hypothesis-pycharm, and icontract-hypothesis-vscode, > - Directly integrated into CrossHair, a tool for automatic verification of Python programs, together with IDE integrations such as crosshair-pycharm and crosshair-vscode, and > - An integration with FastAPI through fastapi-icontract to enforce contracts on your HTTP API and display them in OpenAPI 3 schema and Swagger UI. https://en.wikipedia.org/wiki/Design_by_contract https://en.wikipedia.org/wiki/Invariant_(mathematics)#Invari... [ https://en.wikipedia.org/wiki/Class_invariant ] > What is the difference between "invariant" and "constant" and "final"?
In A “frozen” dictionary for Python
I find Bertrand Meyer's Effiel System very compelling. The design by contract methodology is baked into the language. I did try a DBC library [1] for Python but eventually gave up trying to build it into my work. Not because there is anything wrong with that library, but the extra syntax "mess" that results from the bolt on nature that the library provides to Python in order to work became too much for me in the end. [1] https://github.com/Parquery/icontract
In Oxygene: A modern language built on the foundation of Object Pascal
JSONLD types are specified with @type, and the range of a @type attribute includes rdfs:Class. icontract and pycontracts (Design-by-Contract programming) have runtime type and constraint checking; data validation. Preconditions, Command, Postconditions (assertions, assertions of invariance after command C_funcname executed) https://github.com/Parquery/icontract pydantic_schemaorg: https://github.com/lexiq-legal/pydantic_schemaorg > Pydantic_schemaorg contains all the models defined by schema.org. The pydantic classes are auto-generated from the schema.org model definitions that can be found on https://schema.org/version/latest/schemaorg-current-https.js... [ https://github.com/schemaorg/schemaorg/tree/main/data/releas... ]
In Show HN: Mathesar – open-source collaborative UI for Postgres databases

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