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В октябре прошлого года на Хабре вышла статья «Как я писал свою звонилку для видеозвонков» — автор под ником CEOCTO за несколько вечеров написал P2P-видеозвонилку на WebRTC, потому что его достали обрывающиеся созвоны в мессенджерах. Я прочитал, улыбнулся, полез смотреть исходники на GitHub — и на этом всё. Как обычно бывает с чужими pet-проектами: оценил, закрыл вкладку, забыл

Объектное хранилище с типами, деревьями и настоящим SQL прямо в вашей PostgreSQL/MS SQL/SQLite. FK на объекты, EF и Dapper рядом. redb против Mongo и Raven.

Чтобы хранить объекты, графы и деревья с типами, индексами и полноценными запросами, вам не нужна ещё одна база данных. Нужна та, что у вас уже есть.

redb превращает PostgreSQL, MS SQL или SQLite в типизированное объектное хранилище, не отнимая ни SQL, ни EF Core, ни Dapper. Это принципиально другой разговор, чем «MongoDB против RavenDB»: там вы выбираете отдельный движок и живёте с ним отдельно; здесь объекты ложатся в базу, которая у вас уже крутится в проде. Ниже чем это выигрывает у документных баз, с кодом, и где у redb честные границы.

Чтобы не спорить с чучелами: MongoDB  зрелая серверная документная база с горизонтальным масштабированием и огромной экосистемой, и мультидокументные ACID-транзакции у неё есть с версии 4.0 (2018). RavenDB  .NET-native документная база, полностью ACID, с типизированным LINQ и автоиндексами. Обе хорошие продукты. redb просто играет на другом поле и на этом поле у него сильные карты.

И учить, по сути ...

Berlin to seek suspect’s extradition for 2022 explosions that damaged gas pipelines to Russia

A Ukrainian man has been arrested in Croatia as part of an investigation into the 2022 bombing of the Nord Stream gas pipelines between Germany and Russia.

Undersea explosions in September 2022, just months after Russia’s full-scale invasion of Ukraine, damaged three of the four pipelines built to carry Russian fossil gas to Germany under the Baltic Sea.

Hi, this is Gergely with a bonus, free issue of the Pragmatic Engineer Newsletter. In every issue, I cover Big Tech and startups through the lens of senior engineers and engineering leaders. Today, we cover one out of four topics from a previous The Pulse issue. Full subscribers received the article below four weeks ago. If you’ve been forwarded this email, you can subscribe here.

Last week, xAI (Elon Musk’s AI company, now part of SpaceX) released the Grok 4.5 model, built by Cursor (an acquisition), trained on SpaceX GPUs, and branded “Grok.” It’s a pretty good model; benchmarking as close in coding capability to Opus 4.8 and GPT 5.5 – while being 60-70% lower cost.

Grok 4.5 can be used via API, but is easiest used via the Grok Build coding CLI. So, that’s what many devs did. Some of them have noticed something really weird: the CLI is uploading all their local files in their working directories! Here’s an independent AI safety researcher known as ‘Cerblab’ documenting what is happening (emphasis mine):

“xAI’s official Grok Build coding CLI (grok), on a normal consumer login, does three things worth documenting precisely:It transmits the contents of files it reads — including a .env secrets file — to xAI, verbatim and unredacted. The secret appears in two channels: the live model turn (POST /v1/responses) and a session_state archive uploaded and accepted (HTTP 200) via POST /v1/storage — the endpoint the binary routes to the grok-code-session-traces GCS bucket (see section 5).It uploads the whole repository — every tracked file’s content plus git history — independent of what the agent reads. Grok packages the workspace and uploads it via POST /v1/storage. Proven directly: on a real codebase, with the prompt “reply OK, do not read any files”, Grok uploaded the entire repo as a git bundle (POST /v1/storage → 200); git cloning the captured bundle recovers a file the agent was told not to open — src/_probe/never_read_canary.txt — with its unique marker verbatim, plus the full git history (appendix uploaded_repo.bundle). And it scales: on a 12 GB repo of never-read random files, /v1/storage moved 5.10 GiB, all HTTP 200 (truncated mid-stream), while the model-turn channel moved just 192 KB — a ~27,800× ratio that pins the upload to the codebase, not to what was read. No storage upload failed; the only non-200s were a model-usage quota (402/429) on /v1/responses and one unrelated 404 — not a storage size cap.The storage destination is a Google Cloud Storage bucket, grok-code-session-traces (not AWS S3) — named verbatim in the binary and in a captured metadata.json (gs://grok-code-session-traces/…). I did not find this mechanism surfaced in the CLI’s install/quickstart materials (not an exhaustive docs audit — §7), it is active by default, and disabling “Improve the model” does not turn it off (/v1/settings still returned trace_upload_enabled: true; §6).

None of this proves xAI trains on the data — that is a policy question addressed in [section] 6. What is proven is transmission, acceptance, and storage.”

There’s so much wrong with this approach! To name a few:

• Sending your codebase over the context window is not normal. All AI agents send over their context window to the server that runs the LLM. That’s where tokenization happens and the context is appended to the session. This means that other AI agents send over some part of the code that they read in their context window.
• No need to send over the source code to index it. Indexing the codebase is important for efficient code lookup, and we covered how Cursor does this in a privacy-conscious way by indexing a user’s codebase locally, creating embeddings, and sending those embeddings to the server. Cursor’s server does not store any of the user’s codebase though. Except that Grok CLI transferred all users’ codebases to a cloud bucket! Given Cursor and Grok are now combined as part of SpaceX, it’s a real head scratcher why the Grok CLI isn’t doing what Cursor always has.
• Sending over unencrypted .env files is reckless. Local .env files store secrets, database access tokens, service access tokens, and more. These are sensitive pieces of information that need to be handled with care. If transmitted, they should be encrypted at the very least. Grok / SpaceX storing them on the GCP storage bucket – likely unencrypted – is flat-out unacceptable and reason enough for any sensible company to ban usage of Grok CLI.
• No good reason to upload git history. Sure, seeing Git history could be helpful when training an AI model.
• It’s malicious to not tell devs anything about it. Developers using Grok CLI haven’t been asked to opt into this data upload, nor notified of it. Most evidently had no idea this has been happening, and are understandably furious after Cerblab’s writeup went viral.

SpaceX throws devs “under the bus”

Caught red-handed, Grok CLI disabled file uploads with a remote feature flag. AWS engineer Wes Eklund started tracking upload functionality with the CLI, finding that the uploads suddenly stopped due to a feature flag being flipped by the Grok team, pausing data collection.

But the code functionality to stream all local files to the server, unencrypted, remained present in the CLI, even in later updates. Read an in-depth analysis by Wes.

SpaceX’s official response was pretty laughable, not explaining why .env files and .git history were uploaded, and adding that enterprise customers with zero data retention (ZDR) enabled were the only ones unaffected by underhanded, secret uploading of users’ local files:

My initial reaction is what a condescending response by SpaceX, swiftly followed by the question: does Grok CLI even have enterprise customers? It might be few, given how reckless the team evidently is by uploading unencrypted secrets! SpaceX CEO Elon Musk chimed in with a post that seemed to be almost trolling angry users. He wrote:

“SpaceX policy regarding data retention.

It is actually helpful for debugging issues if we can retain some amount of data, so allowing this would be appreciated, but your privacy settings are always respected.”

This makes it worse because SpaceX has been secretly uploading far more data than is “useful for debugging!” Uploading the git history and sensitive .env files is not, in any way, useful for debugging. Also, Grok/SpaceX did not upload “some amount of data”; it uploaded every last file it could find in your local folder.

The developer community is justifiably upset to read SpaceX and Musk pretending that Grok has only uploaded scraps of data purely for debugging purposes. This time, even fans of SpaceX and Grok are speaking out against Musk and his company’s behavior. AWS engineer Wes Eklund:

“Elon, firstly, huge fan of everything you work on. Completely understand the need for some trace data to improve customer experiences.

From what I’ve researched, it seems to be much more than just trace debugging issues. It seems to be entire code repos with sensitive information just collected entirely.

Your Google Cloud blob storage must have petabytes of code repos from us.

Not ideal.”

Sam Altman pushes Grok to open source Grok CLI

OpenAI CEO, Sam Altman, also posted, using a term Musk often employs when commenting on things he disapproves of in society, and hinting at the benefits of Codex which doesn’t upload your whole local filesystem, or mess with .env files and the git history. The Codex harness is open source, so secretive file-upload functionality would be visible in the source code:

Musk clearly read it and responded a few hours later:

A day later, (15 July), SpaceX did indeed open source Grok CLI. Altman’s comment seemingly hit home. Also, SpaceX has stated it is deleting data from its servers, writing:

“We disabled default retention for all Grok Build users starting on July 12th. Additionally, we are deleting all coding data that was previously retained, ensuring every user’s preferences are respected. With these steps, Grok Build goes beyond other major coding products to protect user privacy.”

The open sourced repo is rushed, unsurprisingly. Kernel engineer Elliot Arledge used the repo and reported what he found:

“Out of the box, `cargo test --workspace` doesn’t compile. 190+ errors, all one bug class: cross-crate test helpers hidden behind #[cfg(test)], which Bazel’s per-target test builds tolerate but Cargo doesn’t, because a dependency is never compiled in test mode. The default-bazel feature is declared in ~20 manifests and wired to nothing. Ungating the benign helpers and putting the signing-key test seam behind a dev-dependency-only feature gets the suite running for the first time on the published tree: 24,663 passed, 28 failed, and every one of the 28 is a pre-existing bug the broken build had been hiding (tests reading your real ~/.claude/settings.json, a tool missing from the registry, macOS /var symlink breakage, one Theme::current() race).

Questions for the team:

Did anyone try downloading this repo and running it before publishing?”

In fairness, it’s clear from the outside that the dev team was instructed to open source the repo ASAP, and did just that. I would expect improvements to allow the developer community to compile the repo and run tests will come later.

On a side note, I wonder what the mood within Grok is. A mandate to open source the product – that was not built to be open sourced! – and doing it in a couple of hours hints what it’s like to work there. Some folks doubtless would find it thrilling and a big challenge, while others likely find it pretty stressful having the “Eye of Sauron” (the CEO) upon them!

Can companies trust Grok now?

To hand it to Grok/SpaceX, the last 24 hours of this incident saw some impressive execution. In contrast, everything that took place beforehand screams “amateur hour”:

• Did no one in teams that wrote the functionality to upload the complete local codebase raise concerns that this would be unacceptable to devs?
• How did uploading secrets without encryption not raise alarm bells?
• Why greenlight any of it without opt-in and do it in a secretive manner?

For sensible companies generating revenue with software, vendors who are allowed to access their codebase are limited to those that can be trusted. Grok has demonstrated it is unprepared to handle codebases with security fundamentals in mind.

There’s now frantic backpedaling and rapid open sourcing, but my impression is that this is simply because Grok/SpaceX was caught red-handed, and understands the risk of losing enterprise contracts caused by this flagrant breach of trust. This is why SpaceX’s communication mentioned that enterprise customers with zero data retention have not been impacted!

Trust is earned in drops and lost in buckets; SpaceX/Grok will likely learn this. By secretly uploading codebases and secrets, Grok CLI revealed itself as an untrustworthy coding agent that’s a risk to use. Meanwhile, all the major competitors – Claude Code, Codex, OpenCode, Gemini CLI – have never violated user trust this way.

Grok CLI can rebuild trust, but it’ll likely take years of no security-related incidents to prove they are an open source-first product (that they were not, just a day ago!), and also demonstrate that they care about “normal” developers, and not just enterprise clients with ZDR turned on.

This incident is a good reminder of why planning and process can slow shipping speed, but increase revenue generation. I would wager that the Grok team has shrunk SpaceX’s enterprise subscription prospects for the foreseeable, in the name of saving a few hours on security reviews, learning what other coding harnesses do with codebase uploads, or even just asking the Cursor team!

I predict Grok/SpaceX will have to offer very high usage limits inside the Grok CLI to convince devs to take a risk on running this software on their system. And they will have to undercut OpenAI and Anthropic API pricing massively for any security team to greenlight use of a CLI that just last week was sending .env secrets unencrypted to their GCP buckets.

Of course, SpaceX/Grok will be just fine as it has the capital to fix things. It will now just be a lot more expensive and time-consuming to fix something that was likely caused by a few engineers wanting to make debugging easier!

Read the full The Pulse issue, or check out this week’s The Pulse. The full issue additionally covers:

1. New trend: concern about massive increase in code review load. Top of mind for engineering leaders: what to do about the ever-growing code review load, and how devs are starting to review code less thoroughly than before? Many questions, but few proven solutions. Send comments about what you see working.
2. Are more devs at enterprises upset about enterprise pricing by AI labs – and does it matter? I got a message from a reader baffled to learn their company pays 20-30x the price for tokens than their own $20/month Claude Code / Codex subscription. It may show how valuable AI coding tools are.
3. Linux creator: AI “clearly useful.” Inside the Linux kernel maintainers group, the discussion veered onto whether Linux should consider banning AI contributions, similar to how some FOSS projects have done so. Linus Torvalds weighed in and made it clear that AI is useful, everyone should decide whether to use it, but no one is allowed to tell others what tools to use. Given AI is an increasingly capable tool, it would be foolish to not use it as such.

Read the full The Pulse

The Normandy beach town of Trouville-sur-Mer is a two-hour train ride from Paris, but feels a world away, with English Channel breezes and the sound of seagulls screeching through the cobbled streets.

Here’s what professionals have to say about good workout etiquette, from using equipment to being on your phone

I like to think of myself as a fairly laid-back person. Other people’s behavior is not my business. There is one notable exception: my gym nemesis.

He brings his computer to the gym and takes work conference calls at full volume. He has four to six pairs of dumbbells around him at all times – then doesn’t put them away. Intellectually I understand he is a fragile, flawed human like the rest of us, but in my gut I sometimes wonder if he arrived here from another galaxy.

Recycling system in Cambridgeshire that could save thousands of litres a day is deemed not in line with rules

The largest water reuse system in the UK, which could save thousands of litres of water a day for people living in one of the driest regions of the country, is not allowed to be switched on because of drinking water regulations.

As water supplies in England reach critical levels, the Guardian can reveal that a model water recycling system within an urban housing development in Cambridgeshire has not been switched on since it was made ready in 2021.

Firefighters describe being pushed to limit by a brutal wildfire season, with key leadership roles going unfilled

The US has faced a critical shortage of firefighters at the US Forest Service (USFS) this summer as thousands of fires erupted across the country.

Despite officials’ claims that the firefighting workforce was stronger than ever, the agency has failed to keep pace with escalating conditions and the catastrophic fires fueled by them, according to nine firefighters who spoke to the Guardian anonymously, because they are barred from disclosing the information to the public.

If elected, Guyanese politician Carolyn Rodrigues-Birkett wants to prioritise climate issues and ensure the United Nations remains a force for good

• Don’t already get The Long Wave in your inbox? Sign up here

As the Guardian’s Caribbean correspondent, I sometimes encounter stories that everyone is talking about in the region, but are not on the radar of the international media. Today, I’m taking over the Long Wave to bring you one of those stories. This summer, Guyanese ambassador Carolyn Rodrigues-Birkett has made history as the first Caribbean candidate for the prestigious post of United Nations secretary general. If successful, she will be the first woman to hold the position too. I spoke to her about the value of the UN, and what a Caribbean leader could bring to the role.

Carolyn Rodrigues-Birkett started life in the remote Indigenous village of Santa Rosa, in the interior of the Caribbean and South American nation of Guyana.

As her supergroup with Neko Case and Laura Veirs celebrates the 10th anniversary of its sublime album, the Ingénue herself will answer your questions

A decade ago, three of the finest voices in Americana got together to make a sublime supergroup record. Case/Lang/Veirs, in case the title didn’t make it plain, brought together Neko Case of the New Pornographers, stalwart Portland songwriter Laura Veirs and kd lang, the Grammy-winning Canadian country icon. Sadly, that glorious album has remained a one-off – though a new anniversary release includes a gorgeous never-before-heard song, Accidental Tattoo – but happily, lang is joining the Guardian for a very rare interview to answer your questions.

Maybe you’d like to know secrets from behind the scenes of making this record in lang’s loft and Veirs’ dining room, or about lang’s relationship with the late, great Tony Bennett, her animal rights advocacy, what the Edmonton country-swing scene was like in the mid-80s before lang became a country star and later mainstream icon, or what she and Cindy Crawford talked about when they posed for quite possibly the greatest magazine photoshoot of all time. What was Roy Orbison like to work with, is new music on the horizon, or what her contemporary constant cravings are? Or anything else indeed.

ABC and its corporate parent, The Walt Disney Co., filed a lawsuit against the FCC Tuesday, accusing the agency of violating its First Amendment rights.

Пять месяцев назад я начал делать игровой движок Neotolis Engine на C17. Хотел глубже погрузиться в рендер и собрать для себя движок, с которым мне было бы легко и приятно работать. Сейчас в нём уже достаточно фич, чтобы делать игру. Я делаю 3D-инкременталку про проблему вагонетки Not a Trolley Problem.

В статье рассказываю, какие принципы я заложил в движок, как использую Claude и Codex и почему важно делать игры, а не только движок.

Michael Caruso, once praised by Ron DeSantis, removed from Palm Beach county civic official roles after arrest

Florida’s Republican governor, Ron DeSantis, has suspended a former close ally and senior civic official who was arrested on felony child sexual abuse charges.

Michael Caruso, who was removed as clerk of court and comptroller for Palm Beach county on Tuesday, was a vocal supporter of a law signed by DeSantis in 2023 that allowed the death penalty for anybody convicted of the sexual battery of a child under 12.

Firefighters describe being pushed to limit by a brutal wildfire season, with key leadership roles going unfilled

The US has faced a critical shortage of firefighters at the US Forest Service (USFS) this summer as thousands of fires erupted across the country.

Despite officials’ claims that the firefighting workforce was stronger than ever, the agency has failed to keep pace with escalating conditions and the catastrophic fires fueled by them, according to nine firefighters who spoke to the Guardian anonymously, because they are barred from disclosing the information to the public.

Recycling system in Cambridgeshire that could save thousands of litres a day is deemed not in line with rules

The largest water reuse system in the UK, which could save thousands of litres of water a day for people living in one of the driest regions of the country, is not allowed to be switched on because of drinking water regulations.

As water supplies in England reach critical levels, the Guardian can reveal that a model water recycling system within an urban housing development in Cambridgeshire has not been switched on since it was made ready in 2021.

Как с Windows только не изгалялись: сколько для неё было сделано модификаций, оболочек и скинов за последние лет 20 — подсчитать, наверное, невозможно. Но мода «накатывать красоту» поверх обыкновенных “Окон” началась, на самом деле, даже не в нулевых.

Привет, это команда Яндекс Практикума. Приём документов на поступление в 2026 году закончится меньше, чем через неделю, но вы ещё можете успеть поступить в онлайн-магистратуру «Специалист по работе с данными и применению ИИ» НИЯУ МИФИ в партнёрстве с Практикумом. В статье мы расскажем, что входит в программу и как на неё поступить.

Compton’s Cafeteria is one of the earliest examples of LGBTQ+ resistance. Today, a prison company occupies the site

One of the earliest documented examples of LGBTQ+ resistance against police happened on a hot summer night 60 years ago this month. It started not with the throwing of a brick, as it did in New York City’s 1969 Stonewall riots, but with the throwing of a coffee cup inside Compton’s Cafeteria in San Francisco.

When police attempted to raid Compton’s – a hub for the drag performers, trans people and sex workers in the city’s Tenderloin neighborhood – hundreds of people in the community fought back. A drag queen threw a coffee mug at a police officer; others threw dishes and chairs outside. It was the culmination of years of police harassment, arrests and violence against the community and the beginning of the city’s trans movement.

Across the PyCharm 2026.2 release line, we shipped 263 fixes and improvements. Many improve Python code insight directly, with more precise type inference, fewer false positives, smarter completion and imports, and more reliable refactoring. Here are some of the smaller changes you’re likely to notice in everyday Python development.

SQLAlchemy 2.0 support

SQLAlchemy has been a long-standing source of false positives – enough that several duplicate tickets have accumulated over the years. This release resolves a batch of them for the 2.0 style.

String forward-references inside Mapped[...] resolve correctly:

posts: Mapped[list["Post"]] = relationship(back_populates="author")

# "Post" now resolves to the model class

PyCharm also correctly infers the mapped type returned by Session.get(), instead of treating the result as the model class itself:

report = session.get(Report, report_id)

reveal_type(report)  # was: type[Report] | None   now: Report | None

Modern hybrid_property setters written as @name.inplace.setter are recognized, so assigning to the property no longer produces a warning. Model class attributes defined via mixins are picked up again, too, clearing the old unexpected argument reports on model constructors.

(PY-78816, PY-65142, PY-59732, PY-51906, PY-28762)

Code insight and type inference

Control-flow narrowing and “unreachable code”

Several false This code is unreachable reports and instances of lost narrowing across loops have been fixed. The common issue: flow analysis either gave up or over-eagerly narrowed to Never in branches it should have kept alive.

isinstance on a numeric union no longer kills the else branch:

def foo(y: int | float) -> None:

    if isinstance(y, float):

        pass

    else:

        print(y)  # was flagged unreachable, y inferred as Never

Narrowing also survives a while loop, so re-narrowing an optional attribute inside the loop body no longer reports a bogus has no attribute error.

(PY-83206, PY-83354, PY-88265)

Strings inside type annotations

A string used as metadata inside Annotated[...] – a Pydantic discriminator field name, for instance – is no longer parsed as a forward reference and flagged as unresolved.

(PY-48749, PY-82245)

Iterable unpacking and star expressions

PyCharm’s analysis of tuple and star unpacking could lose type information and fall back to Any. Unpacking a starred value into a tuple lost its element types, *-expansion collapsed to Any, and several genuine errors went unreported. Starred expressions preserve their element types:

def a() -> tuple[int, int]:

    return 2, 3

def b() -> tuple[int, int, int]:

    return (1, *a())  # no more bogus "Expected tuple[int, int, int]"

(PY-12592, PY-27205, PY-43585, PY-90219)

Augmented assignment

A cluster of false positives came from augmented assignments being misanalyzed. A simple /= on an int produced the wrong type:

foo = 5

foo /= 2

reveal_type(foo)  # was: int   now: float | int

(PY-80622)

Self and constructor return types

Self binds correctly through classmethod parameters typed as type[Self]:

class A:

    @classmethod

    def bar(cls, y: type[Self]) -> Self: ...

x = A.bar(A)      # was a spurious "Expected type[A], got type[A]"

reveal_type(x)    # was: Any   now: A

Construction also respects __new__, __init__, and metaclass __call__. When __new__ returns something other than an instance, that’s the constructed type – even when an __init__ is present. The same fix covers explicitly parameterized calls like MyClass[int]() and __new__ assigned as a class attribute.

(PY-89296, PY-77611, PY-88644, PY-89571)

Enum members: Literal types for .value and .name

Reading an enum member’s .value or .name yields a precise Literal instead of a widened str or int, so assignments to Literal[...] target type-check. This matches mypy’s inference:

from enum import Enum

from typing import Literal

class E(Enum):

    a = "a"

b: Literal["a"] = E.a.value   # was: Expected 'Literal["a"]', got 'str'

n: Literal["a"] = E.a.name    # .name is a Literal too

(PY-61028, PY-79198)

Parameter types inferred from decorators

When a decorator constrains the callable it accepts, the decorated function’s parameters are inferred from that constraint instead of falling back to Any:

from typing import Callable

def d(fn: Callable[[int], str]): ...

@d

def f(a):

    reveal_type(a)   # was: Any   now: int

(PY-79204)

Also fixed

• Keyword arguments in a class header are validated against the base class’s __init_subclass__ signature, and offered in completion (PY-79173).
• An ellipsis in a Callable used as a PEP 695 type-parameter bound no longer reports a bogus Invalid type expression (PY-83570).
• Type-checker findings are split into granular suppression codes rather than a single PyTypeChecker id, and # noinspection directives accept a simplified name form. PyTypeChecker still works as a blanket ignore (PY-90265).

Completion and auto-import

Smarter auto-import 

Auto-import is now noticeably less noisy. Previously, if a module was already imported, PyCharm would offer to add a second, redundant import instead of qualifying through the one you already had. The quick-fix – and the completion popup – prefer to reuse the existing import.

Given pkg/src.py containing MyClass, and a file that already imports the module, Alt+Enter produces this:

from pkg import src  # no longer flagged as unused

src.MyClass

instead of adding from pkg.src import MyClass. The same reuse logic applies to plain import pkg.src, and to the auto-import completion on a second Ctrl+Space.

Nested classes can be auto-imported too, which is something PyCharm didn’t previously support:

# mod.py

class Outer:

    class Inner:

        pass

# main.py – Alt+Enter on Inner now offers "Import Outer from mod"

from mod import Outer

value = Outer.Inner()

(PY-87970, PY-87971, PY-87972, PY-88009, PY-88016)

Completion for unittest.mock.patch() targets

Patching by string target previously offered no code assistance, so dotted paths had to be entered manually. The string argument to mock.patch(...) gets code completion for modules, classes, and their attributes, and it no longer suggests the invalid as keyword mid-path:

from unittest import mock

# sample.py defines: class Foo: my_attr = 42

with mock.patch("sample.Foo.my_attr", 14):

    ...

# completion now offers `sample`, `Foo`, and `my_attr`

(PY-89189, PY-89191, PY-89192)

Typed signatures when overriding built-in methods

Completing an override of a dunder or built-in method fills in the full annotated signature – and auto-imports the types it needs – instead of bare parameters:

from types import TracebackType

class A:

    def __exit__(self, exc_type: type[BaseException] | None,

                 exc_val: BaseException | None,

                 exc_tb: TracebackType | None): ...

# was: def __exit__(self, exc_type, exc_val, exc_tb):

(PY-79218)

Editor and inspections

Type inlay hints

Inferred type arguments are shown inline at the call site, so you can see what a generic resolved to without hovering over it:

class A[T]:

    def __init__(self, t: T): ...

A[int](1)     # [int] shown as an inlay hint

Type names rendered inside inlay hints – return types and solved arguments alike – are also clickable, so you can jump straight to a type’s definition from the hint.

(PY-90411, PY-90293)

f-string format-spec validation

PyCharm already validated the str.format() mini-language. Those checks apply to f-strings too, and PyCharm flags formatting a type that doesn’t implement __format__:

data = 1

f"{data:.2f}"   # ok

f"{data:.2q}"   # now flagged: unsupported format spec

class A: ...

f"{A():d}"      # now flagged: A doesn't support the 'd' format

(PY-51322, PY-89760)

Refactoring

The Rename refactoring also updates references to a module when the module itself is renamed. Previously, the renaming left importing sites pointing at the old name:

# rename provider/provider_module.py → some_module.py

from ..provider import provider_module  # this reference is updated too

(PY-53274)

The Refactor | Field action is now Attribute, and the documentation says “instance attributes” to match Python terminology (PY-85828).

Conclusion

Taken together, these changes make PyCharm’s understanding of Python more precise and predictable: fewer false positives, better type inference, smarter completion, and less time spent working around cases where the IDE gets valid code wrong.

Many of these improvements started with real-world examples reported by users. If PyCharm still misunderstands a typing pattern, framework API, or other valid Python code in your project, let us know in YouTrack – a small reproducer can help us turn that friction into the next fix.

Try PyCharm 2026.2 and let us know which improvements make the biggest difference for your workflow.

Thank you for using PyCharm!

Еще недавно ИИ в работе с данными использовали как вспомогательный инструмент. Нейросеть помогала написать запрос, найти информацию или подготовить отдельный документ. Теперь ей можно передать целый набор повторяющихся задач и подключить к корпоративным системам, каталогам и инструментам разработки. Часть работы выполняет агент, а специалист определяет правила, проверяет результат и принимает верхнеуровневые решения.

Как меняется работа с корпоративными данными под влиянием ИИ, рассказали эксперты на седьмом MWS Meetup.

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