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I'll be in my office

Blog #logger

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80s Log Truck 80s Log Truck with industrial enviroment

#Logger #Road #Log #Car #Tool #Truck #Logs #Pbr #Vehicle #Sleeper #Traffic

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#MissKittyPolitics
The other shoe is going to drop.
Fucking making me think of the one that leaked out of state troopers throwing ballot boxes into the #Everglades. Disappeared quickly.
#Logger boots with the tree climbing shit. #Kevlar. Licensed #open #carry. You are ready to #vote in 2026.

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I couldn't find a logging library that worked for my library, so I made one When I started building Fedify, an ActivityPub server framework, I ran into a problem that surprised me: I couldn't figure out how to add logging. Not because logging is hard—there are dozens of mature logging libraries for JavaScript. The problem was that they're primarily designed for _applications_ , not for libraries that want to stay unobtrusive. I wrote about this a few months ago, and the response was modest—some interest, some skepticism, and quite a bit of debate about whether the post was AI-generated. I'll be honest: English isn't my first language, so I use LLMs to polish my writing. But the ideas and technical content are mine. Several readers wanted to see a real-world example rather than theory. ## The problem: existing loggers assume you're building an app Fedify helps developers build federated social applications using the ActivityPub protocol. If you've ever worked with federation, you know debugging can be painful. When an activity fails to deliver, you need to answer questions like: * Did the HTTP request actually go out? * Was the signature generated correctly? * Did the remote server reject it? Why? * Was there a problem parsing the response? These questions span multiple subsystems: HTTP handling, cryptographic signatures, JSON-LD processing, queue management, and more. Without good logging, debugging turns into guesswork. But here's the dilemma I faced as a library author: if I add verbose logging to help with debugging, I risk annoying users who don't want their console cluttered with Fedify's internal chatter. If I stay silent, users struggle to diagnose issues. I looked at the existing options. With winston or Pino, I would have to either: * Configure a logger inside Fedify (imposing my choices on users), or * Ask users to pass a logger instance to Fedify (adding boilerplate) There's also `debug`, which is designed for this use case. But it doesn't give you structured, level-based logs that ops teams expect—and it relies on environment variables, which some runtimes like Deno restrict by default for security reasons. None of these felt right. So I built LogTape—a logging library designed from the ground up for library authors. And Fedify became its first real user. ## The solution: hierarchical categories with zero default output The key insight was simple: a library should be able to log without producing any output unless the _application_ developer explicitly enables it. Fedify uses LogTape's hierarchical category system to give users fine-grained control over what they see. Here's how the categories are organized: Category | What it logs ---|--- `["fedify"]` | Everything from the library `["fedify", "federation", "inbox"]` | Incoming activities `["fedify", "federation", "outbox"]` | Outgoing activities `["fedify", "federation", "http"]` | HTTP requests and responses `["fedify", "sig", "http"]` | HTTP Signature operations `["fedify", "sig", "ld"]` | Linked Data Signature operations `["fedify", "sig", "key"]` | Key generation and retrieval `["fedify", "runtime", "docloader"]` | JSON-LD document loading `["fedify", "webfinger", "lookup"]` | WebFinger resource lookups …and about a dozen more. Each category corresponds to a distinct subsystem. This means a user can configure logging like this: await configure({ sinks: { console: getConsoleSink() }, loggers: [ // Show errors from all of Fedify { category: "fedify", sinks: ["console"], lowestLevel: "error" }, // But show debug info for inbox processing specifically { category: ["fedify", "federation", "inbox"], sinks: ["console"], lowestLevel: "debug" }, ], }); When something goes wrong with incoming activities, they get detailed logs for that subsystem while keeping everything else quiet. No code changes required—just configuration. ## Request tracing with implicit contexts The hierarchical categories solved the filtering problem, but there was another challenge: correlating logs across async boundaries. In a federated system, a single user action might trigger a cascade of operations: fetch a remote actor, verify their signature, process the activity, fan out to followers, and so on. When something fails, you need to correlate all the log entries for that specific request. Fedify uses LogTape's implicit context feature to automatically tag every log entry with a `requestId`: await configure({ sinks: { file: getFileSink("fedify.jsonl", { formatter: jsonLinesFormatter }) }, loggers: [ { category: "fedify", sinks: ["file"], lowestLevel: "info" }, ], contextLocalStorage: new AsyncLocalStorage(), // Enables implicit contexts }); With this configuration, every log entry automatically includes a `requestId` property. When you need to debug a specific request, you can filter your logs: jq 'select(.properties.requestId == "abc-123")' fedify.jsonl And you'll see every log entry from that request—across all subsystems, all in order. No manual correlation needed. The `requestId` is derived from standard headers when available (`X-Request-Id`, `Traceparent`, etc.), so it integrates naturally with existing observability infrastructure. ## What users actually see So what does all this configuration actually mean for someone using Fedify? If a Fedify user doesn't configure LogTape at all, they see nothing. No warnings about missing configuration, no default output, and minimal performance overhead—the logging calls are essentially no-ops. For basic visibility, they can enable error-level logging for all of Fedify with three lines of configuration. When debugging a specific issue, they can enable debug-level logging for just the relevant subsystem. And if they're running in production with serious observability requirements, they can pipe structured JSON logs to their monitoring system with request correlation built in. The same library code supports all these scenarios—whether the user is running on Node.js, Deno, Bun, or edge functions, without extra polyfills or shims. The user decides what they need. ## Lessons learned Building Fedify with LogTape taught me a few things: **Design your categories early.** The hierarchical structure should reflect how users will actually want to filter logs. I organized Fedify's categories around subsystems that users might need to debug independently. **Use structured logging.** Properties like `requestId`, `activityId`, and `actorId` are far more useful than string interpolation when you need to analyze logs programmatically. **Implicit contexts turned out to be more useful than I expected.** Being able to correlate logs across async boundaries without passing context manually made debugging distributed operations much easier. When a user reports that activity delivery failed, I can give them a single `jq` command to extract everything relevant. **Trust your users.** Some library authors worry about exposing too much internal detail through logs. I've found the opposite—users appreciate being able to see what's happening when they need to. The key is making it opt-in. ## Try it yourself If you're building a library and struggling with the logging question—how much to log, how to give users control, how to avoid being noisy—I'd encourage you to look at how Fedify does it. The Fedify logging documentation explains everything in detail. And if you want to understand the philosophy behind LogTape's design, my earlier post covers that. LogTape isn't trying to replace winston or Pino for application developers who are happy with those tools. It fills a different gap: logging for libraries that want to stay out of the way until users need them. If that's what you're looking for, it might be a better fit than the usual app-centric loggers.
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“Train Dreams”

(USA)

Web (traindreamsfilm.com/home/)

Trailer (youtu.be/HyRdazbYKgY)

Review (brentmarchant.com/quick-cuts/t...)

Metacritic (5/10), Letterboxd (2.5/5), Imdb (5/10), TMDB (5/10)

#BrentMarchant #TrainDreams #JoelEdgerton #FelicityJones #WilliamHMacy #KerryCondon #logger #Idaho

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#TrainDreams #Review #Film #Movie #FilmReview #MovieReview #Drama #Historical #20thCentury #America #Railroad #Train #Logger #BookAdaptation #FilmCritique #CinematicJourney #TrainDreamsReview #MustWatchMovies #ClintBentley #JoelEdgerton #FelicityJones #WilliamHMacy #KerryCondon

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How did I learn all these skills?

#forest #forestry #forester #woods #work #nature #outdoor #outdoors #maple #sugaring #logging #logger #author #life #lesson #love #vermont

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univold.com/fluke-1748-t...
Fluke PWR QUALITY LOGGER W/24IN /60CM 3000A IFLEX EUS VERSION FLUKE-1748/30/EUS @FlukeNetworks.bsky.social @univold.bsky.social #power #qaulity #logger #24inc #60cm #3000a #iflex

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Arduino: Reloj calendario con RTC DS1307 i2C Este ejemplo es básicamente el mismo que el anterior post "arduino: reloj calendario sin rtc" pero esta vez con un RTC (Real Time Clock).

Un reloj con módulo RTC #ds1307 ideal para sistemas que necesiten #logger o #Backups en la plataforma #arduino o #esp32

www.infotronikblog.com/2015/05/ardu...

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Fact Or Fiction? The Real Elizabeth Of York Behind The White Princess (And What The Show Got Wrong) | Flipboard talesofthemiddleages.com - I love it when TV shows shine the spotlight on women in history, especially the ones that are often overshadowed by their more famous counterparts. …

what did The White Princess get right about Elizabeth of York, and what did they get wrong? I’ve done my research and I have ten facts, some true, some complete and utter….garbage! flip.it/0T8cq6 #history #tudors #thetudors #england #englishistory #flipboardusergroup #medieval #middleages #logger

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Kalispell woman breaks world record in women’s standing block chop Laruen Bergman’s competitive logging journey started at Flathead Valley Community College, after her brother encouraged her to join the college’s logging sports team.

Kalispell Montana woman breaks world record in standing block chop #logging #logger #sports #lumberjill #lumberjack

dailyinterlake.com/news/2025/au...

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In this week's ADMIN Update newsletter, @jefflayton.bsky.social looks at how the Linux logger tool can be helpful for HPC admins
www.admin-magazine.com/Articles/Log...
#HPC #admin #logger #Linux #grep #scripts

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Morning training

www.instagram.com/reel/DLZY5q1...

#logger #paddleboarding #sup #suprace

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If you're building a JavaScript library and need logging, you'll probably love LogTape Building a JavaScript library is a delicate balance. You want to provide useful functionality while being respectful of your users' choices and constraints. When it comes to logging—something many libraries need for debugging, monitoring, and user support—this balance becomes particularly challenging. The JavaScript ecosystem has evolved various approaches to this challenge, each with its own trade-offs. LogTape offers a different path, one that's specifically designed with library authors in mind. ## The current state of library logging If you've built libraries before, you've probably encountered the logging dilemma. Your library would benefit from logging—perhaps to help users debug integration issues, trace internal state changes, or provide insights into performance bottlenecks. But how do you add this capability responsibly? Currently, popular libraries handle this challenge in several ways: The debug approach Libraries like Express and Socket.IO use the lightweight `debug` package, which allows users to enable logging through environment variables (`DEBUG=express:*`). This works well but creates a separate logging system that doesn't integrate with users' existing logging infrastructure. Custom logging systems Libraries like Mongoose and Prisma have built their own logging mechanisms. Mongoose offers `mongoose.set('debug', true)` while Prisma uses its own logging configuration. These approaches work, but each library creates its own logging API that users must learn separately. Application-focused libraries winston, Pino, and Bunyan are powerful logging solutions, but they're primarily designed for applications rather than libraries. Using them in a library means imposing significant dependencies and potentially conflicting with users' existing logging choices. No logging at all Many library authors avoid the complexity entirely, leaving their libraries silent and making debugging more challenging for everyone involved. Dependency injection Some libraries adopt a more sophisticated approach by accepting a logger instance from the application through their configuration or constructor parameters. This maintains clean separation of concerns and allows libraries to use whatever logging system the application has chosen. However, this pattern requires more complex APIs and places additional burden on library users to understand and configure logging dependencies. Each approach represents a reasonable solution to a genuine problem, but none fully addresses the core tension: how do you provide valuable diagnostic capabilities without imposing choices on your users? ## The fragmentation problem There's another challenge that emerges when libraries each solve logging in their own way: fragmentation. Consider a typical Node.js application that might use Express for the web framework, Socket.IO for real-time communication, Axios for HTTP requests, Mongoose for database access, and several other specialized libraries. Each library potentially has its own logging approach: * Express uses `DEBUG=express:*` * Socket.IO uses `DEBUG=socket.io:*` * Mongoose uses `mongoose.set('debug', true)` * Axios might use `axios-logger` or similar packages * Redis clients have their own debug configurations * Authentication libraries often include their own logging mechanisms From an application developer's perspective, this creates a management challenge. They must learn and configure multiple different logging systems, each with its own syntax, capabilities, and quirks. Logs are scattered across different outputs with inconsistent formats, making it difficult to get a unified view of what's happening in their application. The lack of integration also means that powerful features like structured logging, log correlation, and centralized log management become much harder to implement consistently across all the libraries in use. ## LogTape's approach LogTape attempts to address these challenges with what might be called a “library-first design.” The core principle is simple but potentially powerful: _if logging isn't configured, nothing happens_. No output, no errors, no side effects—just complete transparency. This approach allows you to add comprehensive logging to your library without any impact on users who don't want it. When a user imports your library and runs their code, LogTape's logging calls are essentially no-ops until someone explicitly configures logging. Users who want insights into your library's behavior can opt in; those who don't are completely unaffected. More importantly, when users do choose to configure logging, all LogTape-enabled libraries can be managed through a single, unified configuration system. This means one consistent API, one log format, and one destination for all library logs while still allowing fine-grained control over what gets logged from which libraries. Note This approach isn't entirely novel—it draws inspiration from Python's standard `logging` library, which has successfully created a unified logging ecosystem. In Python, libraries like Requests, SQLAlchemy, and Django components all use the standard logging framework, allowing developers to configure all library logging through a single, consistent system. This has proven to be both practical and powerful, enabling rich diagnostic capabilities across the entire Python ecosystem while maintaining simplicity for application developers. // In your library code - completely safe to include import { getLogger } from "@logtape/logtape"; const logger = getLogger(["my-awesome-lib", "database"]); export function connectToDatabase(config) { logger.debug("Attempting database connection", { config }); // ... your logic logger.info("Database connection established"); } ## The dependency consideration Modern JavaScript development involves careful consideration of dependencies. While popular logging libraries like winston and Pino are well-maintained and widely trusted, they do come with their own dependency trees. winston, for example, includes 17 dependencies, while Pino includes 1. For library authors, this creates a consideration: every dependency you add becomes a dependency for your users, whether they want it or not. This isn't necessarily problematic (many excellent libraries have dependencies), but it does represent a choice you're making on behalf of your users. LogTape takes a different approach with zero dependencies. This isn't just a philosophical choice—it has practical implications for your library's users. They won't see additional packages in their _node_modules_ , won't need to worry about supply chain considerations for logging-related dependencies, and won't face potential version conflicts between your logging choice and theirs. At just 5.3KB minified and gzipped, LogTape adds minimal weight to their bundles. The installation process becomes faster, the dependency tree stays cleaner, and security audits remain focused on the dependencies that directly serve your library's core functionality. ## Breaking the compatibility chain Here's a challenge that might be familiar: you want your library to support both ESM and CommonJS environments. Perhaps some of your users are working with legacy Node.js projects that rely on CommonJS, while others are using modern ESM setups or building for browsers. The challenge becomes apparent when you have dependencies. While ESM modules can import CommonJS modules without issues, the reverse isn't true—CommonJS modules cannot require ESM-only packages (at least not until the experimental features in Node.js 22+ become stable). This creates an asymmetric compatibility constraint. If your library depends on any ESM-only packages, your library effectively becomes ESM-only as well, since CommonJS environments won't be able to use it. This means that even one ESM-only dependency in your chain can prevent you from supporting CommonJS users. LogTape supports both ESM and CommonJS completely, meaning it won't be the weak link that forces this limitation. Whether your users are working with legacy Node.js projects, cutting-edge ESM applications, or hybrid environments, LogTape adapts seamlessly to their setup. More importantly, when LogTape provides native ESM support (rather than just being importable as CommonJS), it enables tree shaking in modern bundlers. Tree shaking allows bundlers to eliminate unused code during the build process, but it requires the static `import`/`export` structure that only ESM provides. While CommonJS modules can be imported into ESM projects, they're often treated as opaque blocks that can't be optimized, potentially including unused code in the final bundle. For a logging library that aims to have minimal impact, this optimization capability can be meaningful, especially for applications where bundle size matters. ## Universal runtime support The JavaScript ecosystem spans an impressive range of runtime environments today. Your library might run in Node.js servers, Deno scripts, Bun applications, web browsers, or edge functions. LogTape works identically across all of these environments without requiring polyfills, compatibility layers, or runtime-specific code. This universality means you can focus on your library's core functionality rather than worrying about whether your logging choice will work in every environment your users might encounter. Whether someone imports your library into a Cloudflare Worker, a Next.js application, or a Deno CLI tool, the logging behavior remains consistent and reliable. ## Performance without compromise One concern library authors often have about logging is performance impact. What if your users import your library into a high-performance application? What if they're running in a memory-constrained environment? LogTape addresses this with remarkable efficiency when logging is disabled. The overhead of an unconfigured LogTape call is virtually zero—among the lowest of any logging solution available. This means you can add detailed logging throughout your library for development and debugging purposes without worrying about performance impact on users who don't enable it. When logging is enabled, LogTape consistently outperforms other libraries, particularly for console output—often the most common logging destination during development. ## Avoiding namespace collisions Libraries sharing the same application can create logging chaos when they all output to the same namespace. LogTape's hierarchical category system elegantly solves this by encouraging libraries to use their own namespaces. Your library might use categories like `["my-awesome-lib", "database"]` or `["my-awesome-lib", "validation"]`, ensuring that your logs are clearly separated from other libraries and the main application. Users who configure LogTape can then control logging levels independently for different libraries and different components within those libraries. ## Developer experience that just works LogTape is built with TypeScript from the ground up, meaning your TypeScript-based library gets full type safety without additional dependencies or type packages. The API feels natural and modern, supporting both template literals and structured logging patterns that integrate well with contemporary JavaScript development practices. // Template literal style - feels natural logger.info`User ${userId} performed action ${action}`; // Structured logging - great for monitoring logger.info("User action completed", { userId, action, duration }); ## Practical integration Actually using LogTape in your library is refreshingly straightforward. You simply import the logger, create appropriately namespaced categories, and log where it makes sense. No configuration, no setup, no complex initialization sequences. import { getLogger } from "@logtape/logtape"; const logger = getLogger(["my-lib", "api"]); export async function fetchUserData(userId) { logger.debug("Fetching user data", { userId }); try { const response = await api.get(`/users/${userId}`); logger.info("User data retrieved successfully", { userId, status: response.status }); return response.data; } catch (error) { logger.error("Failed to fetch user data", { userId, error }); throw error; } } For users who want to see these logs, configuration is equally simple: import { configure, getConsoleSink } from "@logtape/logtape"; await configure({ sinks: { console: getConsoleSink() }, loggers: [ { category: ["my-lib"], lowestLevel: "info", sinks: ["console"] } ] }); ## Bridging the transition If your potential users are already invested in other logging systems, LogTape provides adapters for popular libraries like winston and Pino. This allows LogTape-enabled libraries to integrate with existing logging infrastructure, routing their logs through whatever system applications are already using. The existence of these adapters reveals an honest truth: LogTape isn't yet a widely-adopted standard in the JavaScript ecosystem. Most applications are still built around established logging libraries, and asking users to completely restructure their logging approach would be unrealistic. The adapters represent a practical compromise—they allow library authors to take advantage of LogTape's library-friendly design while respecting users' existing investments and preferences. This approach reduces friction for adoption while still providing library authors with a modern, zero-dependency logging API. Perhaps over time, as more libraries adopt this pattern and more developers experience its benefits, the need for such adapters might diminish. But for now, they serve as a pragmatic bridge between LogTape's vision and the current reality of the ecosystem. ## A choice worth considering Ultimately, choosing LogTape for your library represents a particular philosophy about the relationship between libraries and applications. It's about providing capabilities while preserving choice, offering insights while avoiding imposition. The traditional approaches—whether using `debug` packages, application-focused loggers, or custom solutions—each have their merits and have served the community well. LogTape simply offers another option: one designed specifically for the unique position libraries occupy in the JavaScript ecosystem. For library authors, this approach might offer several practical benefits. Your library gets detailed logging for development, debugging, and user support, while your users retain complete autonomy over whether and how to use those capabilities. The broader benefit might be a more cohesive logging experience across the JavaScript ecosystem—one where libraries can provide rich diagnostic information that integrates seamlessly with whatever logging strategy applications choose to employ. In a world where every dependency decision has implications, LogTape offers an approach worth considering: a way to enhance your library's capabilities while respecting your users' preferences and existing choices.
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Announcing LogTape 1.0.0 ## What is LogTape? LogTape is a logging library designed specifically for the modern JavaScript ecosystem. It stands out with its zero-dependency architecture, universal runtime support across Node.js, Deno, Bun, browsers, and edge functions, and a library-first design philosophy that allows library authors to add logging without imposing any burden on their users. When LogTape isn't configured, logging calls have virtually no performance impact, making it the only truly unobtrusive logging solution available. For a comprehensive overview of LogTape's capabilities and philosophy, see our introduction guide. ## Milestone achievement We're excited to announce LogTape 1.0.0, marking a significant milestone in the library's development. This release represents our commitment to API stability and long-term support. The 1.0.0 designation signals that LogTape's core APIs are now stable and ready for production use, with any future breaking changes following semantic versioning principles. This milestone builds upon months of refinement, community feedback, and real-world usage, establishing LogTape as a mature and reliable logging solution for JavaScript applications and libraries. ## Major new features ### High-performance logging infrastructure LogTape 1.0.0 introduces several performance-oriented features designed for high-throughput production environments. The new non-blocking sink option allows console, stream, and file sinks to buffer log records and flush them asynchronously, preventing logging operations from blocking your application's main thread. import { configure, getConsoleSink } from "@logtape/logtape"; await configure({ sinks: { console: getConsoleSink({ nonBlocking: { bufferSize: 1000, flushInterval: 50 } }) }, // ... }); The new `fromAsyncSink()` function provides a clean way to integrate asynchronous logging operations while maintaining LogTape's synchronous sink interface. This enables scenarios like sending logs to remote servers or databases without blocking your application. import { fromAsyncSink } from "@logtape/logtape"; const webhookSink = fromAsyncSink(async (record) => { await fetch("https://logs.example.com", { method: "POST", body: JSON.stringify(record) }); }); For file operations specifically, the new `getStreamFileSink()` function in the @logtape/file package leverages Node.js PassThrough streams to deliver optimal I/O performance with automatic backpressure management. ### New sink integrations This release significantly expands LogTape's integration capabilities with two major new sink packages. The @logtape/cloudwatch-logs package enables direct integration with AWS CloudWatch Logs, featuring intelligent batching, exponential backoff retry strategies, and support for structured logging through JSON Lines formatting. import { getCloudWatchLogsSink } from "@logtape/cloudwatch-logs"; const sink = getCloudWatchLogsSink({ logGroupName: "/aws/lambda/my-function", logStreamName: "my-stream", region: "us-east-1" }); The @logtape/windows-eventlog package brings native Windows Event Log support with cross-runtime compatibility across Deno, Node.js, and Bun. This integration uses runtime-optimized FFI implementations for maximum performance while maintaining proper error handling and resource cleanup. ### Beautiful development experience The new @logtape/pretty package transforms console logging into a visually appealing experience designed specifically for local development. Inspired by Signale, it features colorful emojis for each log level, smart category truncation that preserves important context, and perfect column alignment that makes logs easy to scan. import { configure, getConsoleSink } from "@logtape/logtape"; import { prettyFormatter } from "@logtape/pretty"; await configure({ sinks: { console: getConsoleSink({ formatter: prettyFormatter }) }, // ... }); As shown above, the pretty formatter supports true color terminals with rich color schemes, configurable icons, and intelligent word wrapping that maintains visual consistency even for long messages. ### Ecosystem integration Perhaps most significantly, LogTape 1.0.0 introduces adapter packages that bridge the gap between LogTape's library-friendly design and existing logging infrastructure. The @logtape/adaptor-winston and @logtape/adaptor-pino packages allow applications using these established logging libraries to seamlessly integrate LogTape-enabled libraries without changing their existing setup. // Quick setup with winston import "@logtape/adaptor-winston/install"; // Or with custom configuration import { install } from "@logtape/adaptor-winston"; import winston from "winston"; const logger = winston.createLogger({/* your config */}); install(logger); These adapters preserve LogTape's structured logging capabilities while routing everything through your preferred logging system, making adoption of LogTape-enabled libraries frictionless for existing applications. ## Developer experience enhancements This release includes several quality-of-life improvements for developers working with LogTape. The new `getLogLevels()` function provides programmatic access to all available log levels, while the `LogMethod` type offers better type inference for logging methods. Browser compatibility has been improved, particularly for the @logtape/otel package, which previously had issues in browser environments due to Node.js-specific imports. The package now works seamlessly across all JavaScript runtimes without throwing module resolution errors. ## Breaking changes and migration guide LogTape 1.0.0 includes one notable breaking change: the removal of the deprecated `LoggerConfig.level` property. This property was deprecated in version 0.8.0 in favor of the more descriptive `LoggerConfig.lowestLevel` property. If your configuration still uses the old property, simply rename it: // Before (deprecated) { category: ["app"], level: "info", sinks: ["console"] } // After { category: ["app"], lowestLevel: "info", sinks: ["console"] } For more complex filtering requirements, consider using the `LoggerConfig.filters` option instead, which provides more flexibility and supports inheritance from parent loggers. ## Complete package ecosystem LogTape 1.0.0 represents the culmination of a comprehensive package ecosystem, now consisting of 11 specialized packages that address different aspects of logging infrastructure. This modular approach allows you to install only the packages you need, keeping your dependency footprint minimal while accessing powerful logging capabilities when required. Package | JSR | npm | Description ---|---|---|--- @logtape/logtape | JSR | npm | Core logging functionality @logtape/adaptor-pino | JSR | npm | Pino adapter @logtape/adaptor-winston | JSR | npm | winston adapter @logtape/cloudwatch-logs | JSR | npm | AWS CloudWatch Logs sink @logtape/file | JSR | npm | File sinks @logtape/otel | JSR | npm | OpenTelemetry sink @logtape/pretty | JSR | npm | Beautiful text formatter @logtape/redaction | JSR | npm | Data redaction @logtape/sentry | JSR | npm | Sentry sink @logtape/syslog | JSR | npm | Syslog sink @logtape/windows-eventlog | JSR | npm | Windows Event Log sink ## Getting started Whether you're new to LogTape or upgrading from a previous version, getting started with 1.0.0 is straightforward. For new projects, begin with a simple configuration and gradually add the packages and features you need: import { configure, getConsoleSink } from "@logtape/logtape"; await configure({ sinks: { console: getConsoleSink() }, loggers: [ { category: "my-app", lowestLevel: "info", sinks: ["console"] } ] }); Existing applications using winston or Pino can immediately benefit from LogTape-enabled libraries by installing the appropriate adapter. For comprehensive migration guidance and detailed feature documentation, visit our documentation site. The 1.0.0 release represents not just a version number, but a commitment to the stability and maturity that production applications require. We're excited to see what you'll build with LogTape.
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LogTape 0.12.0 Release Notes LogTape is a zero-dependency logging library for JavaScript and TypeScript that provides a simple yet flexible logging system. It supports multiple JavaScript runtimes (Deno, Node.js, Bun, browsers, and edge functions), features hierarchical categories, structured logging, and offers seamless integration for both applications and libraries. ## What's New in 0.12.0 ### Trace Log Level LogTape now includes a `trace` severity level, which sits below `debug` in the verbosity hierarchy. This addition provides finer-grained control over logging output, particularly useful for detailed execution flow tracking during development and debugging. * Added `"trace"` to the `LogLevel` union type * Added `Logger.trace()` method for logging trace-level messages * The complete severity hierarchy is now: `trace` < `debug` < `info` < `warning` < `error` < `fatal` ### Enhanced File Sink Performance File sinks now support configurable buffering, significantly improving write performance for high-volume logging scenarios. * Added `bufferSize` option (default: 8192 characters) to control write buffering behavior * Added `flushInterval` option (default: 5000ms) for automatic time-based buffer flushing * Set `bufferSize` to 0 for immediate writes without buffering * Set `flushInterval` to 0 to disable time-based flushing * Buffer contents are automatically flushed when the sink is disposed These options are available for both `getFileSink()` and `getRotatingFileSink()` functions. ### Syslog Support The new _@logtape/syslog_ package enables sending log messages to syslog servers using the RFC 5424 format. * Support for both UDP and TCP protocols * All standard RFC 5424 facilities (`kern`, `user`, `mail`, `daemon`, `local0`–`7`, etc.) * Automatic priority calculation based on log levels * Structured data support for log record properties * Cross-runtime compatibility with Deno, Node.js, and Bun * Configurable connection timeouts, custom hostnames, and application names ### Logger Method Alias Added `Logger.warning()` as an alias for `Logger.warn()` to ensure consistency with the `LogLevel` type definition. This change addresses the naming mismatch where the `LogLevel` union type uses `"warning"` while the logger method was named `warn()`, making metaprogramming and dynamic method invocation more straightforward. ### Unified Package Releases Starting with version 0.12.0, all LogTape packages including _@logtape/otel_, _@logtape/sentry_, and _@logtape/syslog_ share the same version number and are released together. This ensures compatibility between packages and simplifies version management for users. ### Improved Build Infrastructure LogTape has migrated from dnt to tsdown for npm package bundling. tsdown is a library-focused bundler built on top of Rolldown, a Rust-based bundler that powers the next generation of Vite. Unlike general-purpose bundlers, tsdown is specifically optimized for building TypeScript and JavaScript libraries with minimal configuration. This change brings several benefits: * Elimination of bundler warnings in Webpack, Vite, and other build tools * Improved compatibility with modern JavaScript toolchains * Better tree-shaking support * Cleaner package output * Faster build times through Rust-based performance optimizations ## Migration Guide ### Updating to Trace Level If you have code that relies on `debug` being the lowest severity level, you may need to update your log level configurations: // Before { lowestLevel: "debug" } // This was the most verbose setting // After { lowestLevel: "trace" } // Now includes trace messages ### Leveraging Buffer Configuration To optimize file sink performance in high-throughput scenarios: getFileSink("app.log", { bufferSize: 16384, // Larger buffer for better performance flushInterval: 10_000 // Flush every 10 seconds }) ## Installation LogTape 0.12.0 is available on JSR and npm: deno add jsr:@logtape/logtape # Deno npm add @logtape/logtape # npm pnpm add @logtape/logtape # pnpm yarn add @logtape/logtape # yarn bun add @logtape/logtape # Bun For the syslog sink: deno add jsr:@logtape/syslog # Deno npm add @logtape/syslog # npm pnpm add @logtape/syslog # pnpm yarn add @logtape/syslog # yarn bun add @logtape/syslog # Bun ## Acknowledgments We thank all contributors who helped make this release possible, including those who reported issues, submitted pull requests, and provided feedback. For the complete list of changes, please refer to the changelog.
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LogTape 0.11.0 release notes LogTape is a zero-dependency logging library for JavaScript and TypeScript that works across all runtimes. We're excited to announce the release of LogTape 0.11.0, which introduces significant enhancements to structured logging capabilities and adds a new JSON Lines formatter for better log processing. ## New features and enhancements ### Enhanced structured logging LogTape 0.11.0 brings major improvements to structured logging, making it easier and more flexible to work with structured data in your logs. #### Direct object logging You can now log structured data directly by passing an object as the first argument to any log method: logger.info({ userId: 123456, username: "johndoe", loginTime: new Date(), }); This creates a log entry with the object properties as structured fields, making your logs more machine-readable and searchable. #### Universal property interpolation with `{*}` A new special placeholder `{*}` allows you to interpolate all properties from your structured data at once: logger.info("User logged in with properties {*}", { userId: 123456, username: "johndoe", loginTime: new Date(), }); This is particularly useful when you want to include all available context without explicitly naming each property in your message template. #### Streamlined logging methods All logging methods (`debug`, `info`, `warn`, `error`, `fatal`) now support the new object-first syntax as a convenient shorthand for structured logging with the `{*}` placeholder. ### JSON Lines formatter LogTape now includes built-in support for JSON Lines (also known as JSONL or NDJSON) format, a popular choice for structured logging in modern applications: import { jsonLinesFormatter } from "@logtape/logtape"; import { getFileSink } from "@logtape/file"; await configure({ sinks: { jsonl: getFileSink("app.jsonl", { formatter: jsonLinesFormatter }), }, // ... rest of configuration }); The JSON Lines formatter outputs each log record as a JSON object on a separate line, making it ideal for log aggregation systems and analysis tools. #### Customizable JSON Lines options The new `getJsonLinesFormatter()` function provides several customization options: * _Category separator_ : Control how hierarchical categories are joined * _Message format_ : Choose between raw templates or rendered messages * _Properties handling_ : Flatten properties, nest them, or prepend with custom prefixes ## Backward compatibility All existing logging patterns continue to work exactly as before. The new features are additive and don't break any existing code. ## Why this matters These enhancements make LogTape even more powerful for modern application logging: * _Better observability_ : Structured data makes logs more searchable and analyzable * _Improved developer experience_ : Less boilerplate when logging complex objects * _Industry standard formats_ : JSON Lines support for better integration with log management systems * _Flexible formatting_ : Customize output to match your infrastructure needs ## Installation LogTape 0.11.0 is available on both JSR and npm: deno add jsr:@logtape/logtape@0.11.0 npm add @logtape/logtape@0.11.0 pnpm add @logtape/logtape@0.11.0 yarn add @logtape/logtape@0.11.0 bun add @logtape/logtape@0.11.0 ## Learn more * Structured logging guide * Text formatters docs * Complete changelog We hope these new features enhance your logging experience. As always, LogTape remains zero-dependency and works across all JavaScript runtimes. Happy logging!
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GitHub - winstonjs/winston: A logger for just about everything. A logger for just about everything. Contribute to winstonjs/winston development by creating an account on GitHub.

winston - A logger for just about everything.

- github.com/winstonjs/wi...

#logger #nodejs #denojs #javascript #typescript

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LogTape 0.10.0 Released We're pleased to announce the release of LogTape 0.10.0 today. This version introduces several significant enhancements to improve security, flexibility, and usability. What is LogTape? LogTape is a simple, zero-dependency logging library for JavaScript with support for multiple runtimes (Node.js, Deno, Bun, browsers, and edge functions). It features structured logging, hierarchical categories, template literals, and is designed to be used in both applications and libraries. ## Key Highlights ### New Data Redaction Package The most notable addition in this release is the new _@logtape/redaction_ package, designed to help protect sensitive information in your logs. This package provides two complementary approaches to redaction: * Pattern-based redaction: Uses regular expressions to identify and redact sensitive patterns like credit card numbers, email addresses, and tokens in formatted log output. * Field-based redaction: Identifies and redacts sensitive fields by their names in structured log data. The package includes several built-in patterns for common sensitive data types: * Credit card numbers * Email addresses * JSON Web Tokens (JWTs) * U.S. Social Security numbers * South Korean resident registration numbers Both approaches can be used independently or combined for maximum security. Comprehensive documentation for these features is available in the _Data redaction_ section of the manual. ### Timestamp Formatting Improvements Text formatters now support omitting timestamps entirely from formatted messages. The `TextFormatterOptions.timestamp` option has been extended to include `"none"` and `"disabled"` values, giving you more control over log output format. ### Lazy File Sink Option A new `FileSinkOptions.lazy` option has been added, allowing file sinks to open files only when actually needed, which can improve resource utilization. ### Config Error Detection The `configure()` and `configureSync()` functions now check for duplicate logger configurations with the same category and throw a `ConfigError` when detected. This prevents unintended overriding of logger configurations. ## Acknowledgments We'd like to thank our external contributors who helped make this release possible: * Ooker for implementing the ability to omit timestamps from formatted messages (#35) * Rickey Ward for adding the lazy file sink option (#38, #39) We encourage all users to upgrade to this version to take advantage of these improvements. As always, we welcome your feedback and contributions. * * * For more details on these changes, see the full changelog.
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Why LogTape Should Be Your Go-To Logging Library for JavaScript/TypeScript In the diverse and ever-evolving JavaScript ecosystem, logging remains a critical component for development, debugging, and monitoring applications. While numerous logging libraries exist, LogTape stands out with its unique combination of simplicity, flexibility, and cross-runtime compatibility. Let's explore why LogTape deserves consideration for your next JavaScript or TypeScript project—whether you're building an application or a library. ## Zero Dependencies: A Lightweight Footprint One of LogTape's most compelling features is its complete absence of dependencies. In an era where “dependency hell” plagues many JavaScript projects, LogTape offers a refreshing alternative: // No additional packages to install beyond LogTape itself import { configure, getConsoleSink, getLogger } from "@logtape/logtape"; This zero-dependency approach provides several advantages: Reduced bundle size No transitive dependencies means smaller packages Enhanced stability No risk of breaking changes from upstream dependencies Simplified security Fewer potential vulnerabilities from third-party code Lower integration overhead Particularly valuable for library authors who don't want to burden users with additional dependencies ## Runtime Diversity: Write Once, Log Everywhere While many popular logging libraries focus primarily on Node.js, LogTape provides seamless support across diverse JavaScript runtimes: * Node.js * Deno * Bun * Web browsers * Edge functions (e.g., Cloudflare Workers) This runtime flexibility means you can use consistent logging patterns regardless of your deployment environment: // Same API works seamlessly across all JavaScript runtimes import { getLogger } from "@logtape/logtape"; const logger = getLogger(["my-service", "user-management"]); // Works in Node.js, Deno, Bun, browsers, or edge functions logger.info`User ${userId} logged in successfully`; For teams working across multiple platforms or projects transitioning between runtimes, this consistency is invaluable. No need to learn different logging libraries or approaches—LogTape works the same way everywhere. ## Hierarchical Categories: Fine-Grained Control LogTape's hierarchical category system represents a standout feature that's surprisingly rare among JavaScript logging libraries. Categories allow you to organize logs in a tree-like structure: // Parent category const appLogger = getLogger(["my-app"]); // Child category inherits settings from parent const dbLogger = getLogger(["my-app", "database"]); // Grandchild category const queryLogger = getLogger(["my-app", "database", "queries"]); // Alternative approach using getChild() const userLogger = appLogger.getChild("users"); const authLogger = userLogger.getChild("auth"); This hierarchical approach offers powerful benefits: Targeted filtering Configure different log levels for different parts of your application Inheritance Child loggers inherit settings from parents, reducing configuration overhead Organizational clarity Logs naturally follow your application's module structure Here's how you might configure logging levels for different categories: await configure({ sinks: { console: getConsoleSink(), file: getFileSink("app.log"), }, loggers: [ // Base configuration for all app logs { category: ["my-app"], lowestLevel: "info", sinks: ["console", "file"] }, // More verbose logging just for database components { category: ["my-app", "database"], lowestLevel: "debug", sinks: ["file"] } ] }); With this configuration, all application logs at "info" level and above go to both console and file, while database-specific logs include more detailed "debug" level information, but only in the log file. ## Structured Logging: Beyond Simple Text Modern logging goes beyond simple text strings. LogTape embraces structured logging, which treats log entries as data objects rather than plain text: logger.info("User logged in", { userId: 123456, username: "johndoe", loginTime: new Date(), ipAddress: "192.168.1.1" }); LogTape also supports placeholders in messages, connecting structured data with human-readable text: logger.info("User {username} (ID: {userId}) logged in from {ipAddress}", { userId: 123456, username: "johndoe", ipAddress: "192.168.1.1" }); Structured logging offers substantial benefits: Improved searchability Search for specific field values instead of parsing text Better analysis Perform data analysis on structured fields Consistent format Enforce standardized log formats Machine-readable Easier processing by log management systems For performance-conscious applications, LogTape offers lazy evaluation of structured data: logger.debug("Performance metrics", () => ({ memoryUsage: process.memoryUsage(), cpuUsage: process.cpuUsage(), timestamp: performance.now() })); The function is only evaluated if the debug level is enabled, preventing unnecessary computation for suppressed log levels. ## Extremely Simple Sinks and Filters: Minimal Boilerplate LogTape's approach to extensibility is remarkably straightforward. Creating custom sinks (output destinations) and filters requires minimal boilerplate code. ### Dead Simple Sinks A sink in LogTape is just a function that receives a log record: // Creating a custom sink is as simple as defining a function const mySink = (record) => { const timestamp = new Date(record.timestamp).toISOString(); const level = record.level.toUpperCase(); const category = record.category.join('.'); // Send to your custom destination myCustomLogService.send({ time: timestamp, priority: level, component: category, message: record.message, ...record.properties }); }; // Use your custom sink in configuration await configure({ sinks: { console: getConsoleSink(), custom: mySink }, loggers: [ { category: ["my-app"], sinks: ["console", "custom"] } ] }); Compare this with other libraries that require extending classes, implementing multiple methods, or following specific patterns. LogTape's approach is refreshingly straightforward. ### Simple Filters Similarly, filters in LogTape are just functions that return a Boolean: // Filter that only passes high-priority or specific component logs const importantLogsFilter = (record) => { // Always include errors if (record.level === "error" || record.level === "fatal") { return true; } // Always include payment-related logs if (record.category.includes("payments")) { return true; } // Filter out other logs return false; }; await configure({ // ...sinks configuration filters: { important: importantLogsFilter }, loggers: [ { category: ["my-app"], sinks: ["alertSystem"], filters: ["important"] } ] }); LogTape also provides a convenient shorthand for level-based filtering: await configure({ // ...sinks configuration filters: { // This creates a filter for "warning" level and above warningAndAbove: "warning" }, loggers: [ { category: ["my-app"], sinks: ["console"], filters: ["warningAndAbove"] } ] }); ## Perfect for Library Authors LogTape is uniquely well-suited for library authors who want to incorporate logging without burdening their users. The core philosophy is simple: 1. Libraries provide logging output points 2. Applications configure how those logs are handled Here's how a library might implement LogTape: // my-awesome-lib/database.js import { getLogger } from "@logtape/logtape"; export class Database { private logger = getLogger(["my-awesome-lib", "database"]); constructor(host, port, user) { this.host = host; this.port = port; this.user = user; } connect() { this.logger.info("Connecting to database", { host: this.host, port: this.port, user: this.user }); // Connection logic... this.logger.debug("Connection established"); } query(sql) { this.logger.debug("Executing query", { sql }); // Query logic... } } The key point is that the library _never calls`configure()`_. Instead, it provides useful log output points with appropriate levels and contextual data. Applications using the library can then decide exactly how to handle these logs: // Application code import { configure, getConsoleSink } from "@logtape/logtape"; import { Database } from "my-awesome-lib"; // Configure how logs should be handled await configure({ sinks: { console: getConsoleSink(), file: getFileSink("app.log") }, loggers: [ // Handle all library logs { category: ["my-awesome-lib"], lowestLevel: "info", sinks: ["file"] }, // More verbose for database component during development { category: ["my-awesome-lib", "database"], lowestLevel: "debug", sinks: ["console", "file"] } ] }); // Use the library const db = new Database("localhost", 5432, "user"); db.connect(); This separation of concerns offers several benefits: 1. Library users have complete control over log handling 2. Libraries can provide rich logging without imposing implementation details 3. No risk of conflict with application logging configurations 4. Libraries can be "noisy" internally while allowing applications to filter as needed ## Contexts for Richer Logging LogTape provides context mechanisms for adding consistent properties across multiple log messages. This is particularly valuable for tracing requests through a system: ### Explicit Contexts const logger = getLogger(["my-app", "api"]); // Create a logger with context const requestLogger = logger.with({ requestId: "abc-123", userId: 42, endpoint: "/users" }); // All logs from this logger include the context properties requestLogger.info("Processing request"); requestLogger.debug("Validating input"); requestLogger.info("Request completed", { durationMs: 120 }); ### Implicit Contexts (v0.7.0+) For cases where you want context to apply across function calls without explicit passing: import { getLogger, withContext } from "@logtape/logtape"; function handleRequest(req, res) { withContext({ requestId: req.id, userId: req.user?.id }, () => { // All logs within this function and any functions it calls // will automatically include the context properties processRequest(req, res); }); } function processRequest(req, res) { // No need to pass context - it's automatically available getLogger(["my-app", "processor"]).info("Processing data"); // Call other functions that will also inherit the context validateInput(req.body); } function validateInput(data) { // This log also gets the requestId and userId getLogger(["my-app", "validator"]).debug("Validating input", { data }); } This implicit context capability is invaluable for tracing requests through multiple layers of code without manually threading context through every function call. ## When LogTape Might Not Be Your Best Choice While LogTape offers compelling advantages for many use cases, it's not universally the best choice: Extreme performance requirements If your application logs tens of thousands of entries per second and raw performance is the top priority, specialized high-performance libraries like Pino may be more suitable with their focus on optimized logging throughput. Extensive pre-built integrations If you need immediate integration with numerous specific systems (Elasticsearch, Graylog, etc.) without writing any custom code, Winston's rich ecosystem of transports might provide a faster starting point. Legacy systems with specific logging requirements If you're maintaining systems built around specific logging patterns from Java or other environments, purpose-built libraries like Log4js might offer more familiar APIs. Web browser-only applications with minimal logging needs For extremely simple web browser-only logging needs where you just want basic console output with levels, even simpler libraries like loglevel might be sufficient. ## Conclusion LogTape stands out in the crowded JavaScript logging landscape by offering a unique combination of features that address real-world development challenges: * _Zero dependencies_ for a lightweight, secure foundation * _Runtime diversity_ supporting Node.js, Deno, Bun, browsers, and edge functions * _Hierarchical categories_ for better log organization and filtering * _Structured logging_ for improved analysis and searchability * _Simple extension mechanisms_ with minimal boilerplate * _Library-friendly design_ that respects separation of concerns Whether you're building applications or libraries, working across multiple JavaScript runtimes, or simply seeking a clean, well-designed logging solution, LogTape deserves serious consideration. Its thoughtful design balances simplicity with powerful features, avoiding common pitfalls of JavaScript logging libraries. For more information and detailed documentation, visit LogTape's official website.
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Adafruit Weekly Editorial Round-Up: WLED Matrix Display with Sparkle Motion, PCM5122 is an I2S DA […]

[Original post on blog.adafruit.com]

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Adafruit Weekly Editorial Round-Up: WLED Matrix Display with Sparkle Motion, PCM5122 is an I2S DA […]

[Original post on blog.adafruit.com]

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Adafruit Weekly Editorial Round-Up: WLED Matrix Display with Sparkle Motion, PCM5122 is an I2S DA […]

[Original post on blog.adafruit.com]

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If yer gonna be loud and annoying. Atleast get some work done in the process. Nothin worse than more noise and less work! #logger #faller #husqvarna #evolve #bekind #chainsaw #love.

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