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@studio/log

A tiny streaming ndJSON logger

latest
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npmnpm
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2.1.3
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Studio Log 2

👻 Log ndjson to an output stream, pretty print the output with emoji ✨

Note! Version 2 has significantly changed compared to the original announcement. Make sure to read the release notes for migration instructions!

Features

  • API designed to produce expressive source code.
  • Uses topics instead of log levels for more fine grained filtering.
  • Uses object streams to avoid serialize -> parse -> serialize when used in a command line application.
  • Disabled by default. If no output stream is specified, no logs are written.

Usage

Log output is disabled by default to ensure logs don't get in the way when writing unit tests. Therefore you want to set this up as the first thing in your main:

// Sending raw ndJSON logs to stdout, e.g. in a server application:
const Stringify = require('@studio/ndjson/stringify');
require('@studio/log')
  .pipe(new Stringify())
  .pipe(process.stdout);

// Sending fancy formatted logs to stdout, e.g. in a command line tool:
const Format = require('@studio/log-format/fancy');
require('@studio/log')
  .pipe(new Format())
  .pipe(process.stdout);

// Sending logs to console.log, e.g. in a browser:
const Format = require('@studio/log-format/console');
require('@studio/log')
  .pipe(new Format())

Next, create a logger instance in a module and start writing logs:

const logger = require('@studio/log');

const log = logger('app');

exports.startService = function (port) {
  log.launch('my service', { port: 433 });
};

In the server example above, this output is produced:

{"ts":1486630378584,"ns":"app","topic":"launch","msg":"my service","data":{"port":433}}

Send your logs to the emojilog CLI for pretty printing:

cat logs.ndjson | emojilog
09:52:58 🚀 app my service port=433

Install

❯ npm i @studio/log

Topics

Instead of log levels, this logger uses a set of topics. Unlike log levels, topics are not ordered by severity.

These topics are available: ok, warn, error, issue, ignore, input, output, send, receive, fetch, finish, launch, terminate, spawn, broadcast, disk, timing, money, numbers and wtf.

Topics and their mapping to emojis are defined in the Studio Log Topics project.

Log format

  • ns: The logger instance namespace.
  • ts: The timestamp as returned by Date.now().
  • topic: The topic name.
  • msg: The message.
  • data: The data.
  • stack: The stack of error object.
  • cause: The cause stack of error.cause object, if available.

API

Creating a logger

  • log = logger(ns[, data]): Creates a new logger with the given namespace. The namespace is added to each log entry as the ns property. If data is provided, it is added to each log entry. Multiple calls with the same ns property return the same logger instance while data is replaced.
  • log.child(ns[, data]): Creates a child logger of a log instance. The namespaces are joined with a blank and data is merged. Multiple calls with the same ns property return the same logger instance while data is replaced.

Log instance API

  • log.{topic}([message][, data][, error]): Create a new log entry with these behaviors:
    • The topic is added as the "topic".
    • If message is present, it's added as the "msg".
    • If data is present, it's added as the "data".
    • If error is present, the stack property of the error is added as the "stack". If no stack is present, the toString representation of the error is used.
    • If error.code is present, it is added to the "data" without modifying the original object.
    • If error.cause is present, the stack property of the cause is added as the "cause". If no stack is present, the toString representation of the cause is used.
    • If error.cause.code is present, a cause object is added to the "data" with { code: cause.code } and without modifying the original object.

Module API

  • logger.pipe(stream): Configure the output stream to write logs to. If not specified, no logs are written. Returns the stream.
  • logger.hasStream(): Whether a stream was set.
  • logger.reset(): Resets the internal state.

Transform streams

Transform streams can be used to alter the data before passing it on. For example, Studio Log X is a Transform stream that can remove confidential data from the log data and Studio Log Format project implements the basic, fancy and console pretty printers.

Format transforms are node transform streams in writableObjectMode. Here is an example implementation, similar to the ndjson stringify transform:

const { Transform } = require('stream');

const ndjson = new Transform({
  writableObjectMode: true,

  transform(entry, enc, callback) {
    const str = JSON.stringify(entry);
    callback(null, `${str}\n`);
  }
});

License

MIT

Made with ❤️ on 🌍

Keywords

log

FAQs

Package last updated on 31 Jan 2024

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