The Verge is a part of PMX Global, LLC, a subsidiary of Penske Media Corporation.

© 2026 VM Publishing, LLC. All entitlements reserved.

eFuel v1.0 – Doorstep Fuel and Gas Distribution Platform Script Free Download. eFuel is a Modern, Technology-driven Solution designed to Simplify Fuel and Gas Delivery for Homes, Businesses, and Industries. With eFuel, Users can Conveniently Order Petrol, Diesel, and LPG Gas Online and have it Delivered Directly to their Location, Eliminating the need to Visit Traditional Fuel Stations. Our phase Connects Customers alongside Trusted Local Filling Stations and Delivery Agents, Ensuring Safe, Fast, and Reliable Fuel Distribution.

Main Features

• Easy to Order
• Orders Management
• 2FA Security
• Email and SMS Notification System
• Pump Setup
• Manage Users and Agents
• Fuel Catalog
• Support Tickets Management
• LiveChat System
• KYC Verification System
• Multi-language
• Manage Payments
• Manage Subscribers
• and more

Download eFuel – Doorstep Fuel and Gas Distribution Platform

Free download eFuel – Doorstep Fuel and Gas Distribution Platform PHP manuscript by ViserLab on Codecanyon 63183421 Gas allocation business application eFuel nulled download.

APSW stands for Another Python SQLite Wrapper. APSW supports CPython 3.10 onwards.

APSW lets you get the most out of the SQLite embedded relational repository motor from Python, and the most out of Python from SQLite. APSW glues together the complete SQLite C API and Python's C API, staying up to date with the two SQLite and Python. This includes full content search, session, virtual tables, VFS (virtual file system), JSON, and CArray. All functionality is accessible in regular synchronous code, as fine as full assistance for all the async frameworks.

It is recommended to use the builtin sqlite3 module if you desire SQLite to appear interchangeable alongside the another repository drivers.

Use APSW whenever you desire to use SQLite fully, and have an improved developer experience. The documentation has a division on the differences between APSW and sqlite3.

There is a tour and example code using APSW at https://rogerbinns.github.io/apsw/example.html

The latest records is at https://rogerbinns.github.io/apsw/

• Python SQLite conversation group (preferred)
• Github discussions
• You can additionally email the author at rogerb@rogerbinns.com

Releases are made to PyPI (install using pip) and Github

New publish announcements are sent to the Python SQLite discussion group and there is an RSS nourish from PyPI.

Full detailed catalog of changes

You can discover existing and fixed bugs by clicking on Issues and using "New Issue" to study earlier unidentified issues.

See LICENSE - in essence any OSI approved open origin license.

Read next

And whenever (not if) you volition stumble or fall, that “we’re a family here” item you saw in your onboarding doc? The one that’s correct next to that fancy acronym that somehow translates into their “values”? That volition average entirely fucking nothing, and you volition be replaced in a heartbeat by person alternatively they’ll try to form into a “10x engineer”.

They are doing their finest to create you additional blessed at activity — a nicer, additional adorned office, a better-stocked galley alongside 5 decaf options, a gym 50 meters distant from your desk, a taller, shinier building, location to shove your offspring during summer interrupt so you don’t have to “worry your beautiful caput concerning that” — More this… Better that. More happiness = additional productivity, following all.

And you cognize what? They’re doing a awesome job, since to most people, being additional blessed became the outcome of having more, or improved positives, whether they’re genuine or projected, alternatively of focusing on reducing the negatives.

All you have to do is provision in. Be additional happy. Be additional successful. Strive for more. Do more, not less. Don’t inquiry anything.

Today as always, men autumn into two groups: slaves and liberated men. Whoever does not have two-thirds of his day for himself, is a slave, any he may be: a statesman, a businessman, an official, or a scholar.

They get what they want, and you, well… you get what they desire you to think that you should get.

It doesn’t have to be akin this.

Open your eyes and acknowledge the emphasis they inform you is “part of the game” is not value it. You can do less, you can be boring and motionless be happy.

You can do the things you like. You can do the things you “never have period for”. You can be alongside your family. You can encounter up alongside your allies or expend your day at the beach.

The ask? Follow your own dream, not theirs.

Places akin Todoist are the evidence — remote-first, asynchronous AND allowing you to set up your activity schedule. 37Signals does it too. And so does Linear.

The finest part? It plant and nothing fucking burnt down. Any business can create it work, if lone they wanted to.

Back during I was using a distinct OS, I used a program which processed the audio being played in genuine period and made it audio much better. It made the audio awareness farther distant and a bit lighter to hear, during carrying the applicable information. I’d continually wanted a akin program which was likewise uncomplicated to use for Linux, and decided to compose one.

0:00 / 0:10

Listen alongside headphones. The excerpt is from P.I.M.P. by Bacao Rhythm & Steel Band^[0].

The processed type appears farther from the ears and feels small “on the ear” making it awareness small “blocked” following listening to music for a while.

First attempt

Since I was penning for Linux, my basis stack was PipeWire^[1]. I had no previous audio experience, so I began by using an LLM as a sounding commission during experimenting alongside norm audio filters and psychoacoustic techniques.

Somewhere alongside the way I learnt concerning HRTFs, which depict how audio arriving from a particular direction reaches the ears, depending on the direction and geometry of the listener. I tried the MIT KEMAR database^[2] archetypal and idea it echoed awful, since it had been recorded in an anechoic chamber, so there were no area echoes, which were a desirable psychoacoustic consequence here. The outcome echoed cheap and additional inwards to the ear. Later I established the SADIE II database^[3], which additionally came alongside area responses, and that echoed much nearer to what I remembered.

But this method shortly showed its limits. The LLM began talking concerning things akin “perceptual envelopment”, “late-field decorrelation”, “spectral diffusion” and “diffuse spatial energy”.^[1][1] Gemini was particularly fine at this. It was additionally the lone one alongside a liberated pupil program. While I could comprehend that item was wrong, those descriptions didn’t item to item I could comprehend or use to enhance the effect.

I remaining the project deceased for a during alongside no apparent direction to continue with.

Re-attempt

Much later, I had a distinct idea. Instead of trying to detect the exact parameters or techniques and algorithms the program used internally, I could study the behavior of the display itself.

This seems apparent in retrospect, but I did not have a copy of the program. I could lone test on a friend’s laptop, so I could not keep changing my implementation and comparing it alongside the citation whenever I wanted.

I began study Signalsmith^[4] and several blogs by audio engineers to build adequate intuition to cognize what I should measure, and shortly realised that I didn’t need to keep using the program to grasp its encourage responses and another measurable features. I generated an audio document on Linux, got my friend’s laptop for a while, played the generated document through the program and recorded the output.

The gathering of tests

The inquiry became what I should put into that document so it could grasp the applicable particulars which differentiated the program without having to re-record features or filters.

The archetypal helpful item I established was impulse-response measurement.

If I continue a document containing a sole nonzero example through the filter, everything which appears following it in the record would’ve been added by the filter. Features specified as the degree of its decay complete time, the form of the decay and the phase delays connected alongside it would be current in the output. Playing the encourage in the correct conduit allows extracting the two outputs’ responses to audio played on the right, and likewise for the left.

If the reply to one encourage is $h$, afterward the reply to an encourage at stance $k$ is the identical $h$ shifted to $k$ and scaled by $x[k]$. Adding all of those responses gives

$$ y[n]=\sum_k x[k]h[n-k]=(x*h)[n]. $$

This of way depends on the display being a linear time-invariant filter^[5].

A louder encourage should create the identical reply made proportionally louder:

$$ F(ax)=aF(x). $$

Two inputs played together should create the sum of what all input produces separately:

$$ F(x_1+x_2)=F(x_1)+F(x_2). $$

And playing the identical input afterward should create the identical reply later.

And stated it’s stereo, the complete equation would be:

$$ \begin{bmatrix} y_L\\ y_R \end{bmatrix} {}={} \begin{bmatrix} h_{LL} & h_{LR}\\ h_{RL} & h_{RR} \end{bmatrix} * \begin{bmatrix} x_L\\ x_R \end{bmatrix}. $$

Given I was sending one document to have it recorded through all mode, I added impulses at distinct amplitudes to inspect for level-dependent processing, and played the identical encourage in the two channels, afterward alongside the correct conduit inverted. The outputs should equivalent the secluded responses added together in the archetypal case and subtracted in the second, checking the conditions above. I additionally remaining adequate silence between them for the reply to complete before the next impulse.

While study concerning this, I noticed that document on measure tended to use sine sweeps fairly than impulses^[6].^[2][2] An encourage already contained all frequency, but having lone one example meant there was small energy at all frequency, so a lengthy clear would create the reply easier to differentiate from record noise.

$$ Y(f)=H(f)X(f), \qquad H(f)=\frac{Y(f)}{X(f)}. $$

This would activity for most of the range, but if $X(f)$ was near to zero, dividing record noise by it would create fairly a notable display which had small to do alongside the program. This could be avoided alongside a regularized version.

$$ \hat H(f)=\frac{Y(f)X^*(f)}{|X(f)|^2+\lambda}. $$

With adequate input energy this would about be the identical division, during $\lambda$ would bounds the outcome elsewhere. The complex values additionally keep the phase, which was required stated audio sent to one conduit could appear in the another alongside a delay.

The clear gave another measure to difference alongside the impulse, but it additionally took much longer to play, during which the program could alter its behaviour. I added dependable tones at distinct frequencies and amplitudes, and longer tones going from quiescent to noisy and back, to see whether the acquire changed and how lengthy it took to do so.

And a multitone to inspect if any new frequence pops up:

And repeat to inspect for time-invariance:

And I kept a division of noise aside, to test whether the extracted display could reproduce its recorded output afterwards.

Recovering the filter

Given record and playback were started manually, the record archetypal needed an offset. I had put evenly spaced clicks near the start, which I initially tried finding by correlating the record alongside the first clicks. Since the display could dispersed all click complete time, I summed the squared samples complete a opening $W$ to evaluation the energy about it instead,

$$ e[n]=\sum_{m\in W}\left(y_L[n+m]^2+y_R[n+m]^2\right), $$

and established the offset through

$$ \hat\tau=\arg\max_\tau\sum_n e_{\text{probe}}[n]e_{\text{recording}}[n+\tau]. $$

I applied the identical offset to the two channels so the postpone between them was retained.

Output

For the chief encircle setting, the scaled impulses were nearly identical, the blended inputs matched the sum of their distinct responses, and the multitone produced nearly no new frequencies. To difference the reconstructed output alongside the recording, I used

$$ \varepsilon=\frac{\lVert y-\hat y\rVert_2}{\lVert y\rVert_2}, $$

where $y$ was the recorded output and $\hat y$ the output produced by the extracted filter. Given the identical repeated sections already differed slightly, I compared the model’s error alongside that difference,

$$ \varepsilon_{\text{model}}\approx\varepsilon_{\text{repeat}}\ll1. $$

The volume-reducing manner changed its acquire alongside amplitude and took period to reconstruct it, during another spatial manner changed between repeats, so neither could be reproduced alongside a fixed convolution filter.

Recording the two output channels for an encourage in all input conduit gave me the four filters.

Sound additionally appeared in the contrary channel, quieter and slightly delayed, followed by a lengthy tail. Together these contained the out-of-head consequence I had been trying to create earlier.

To decide how much of this reply to keep, I tried increasingly lengthy filters against the noise section,

$$ \varepsilon_N= \frac{\lVert y_{\text{noise}}-h^{(N)}*x_{\text{noise}}\rVert_2} {\lVert y_{\text{noise}}\rVert_2}, $$

and kept the complete response, which predicted the noise additional accurately than the shorter versions. The reply extracted from the clear additionally accepted complete the range anywhere it had adequate input energy.

Loading the four responses into Saq^[7] gave me the placement I had been trying to reproduce by hand.

You can try the outcome here. Choose your own local audio document or grasp a tab (when not in a Firefox browser^[8]), afterward toggle encircle to compare.

Bibliography

Read next

Read next

Membedah Keamanan macOS dari Dalam

Channel ini menyajikan materi seputar Data Science & Artificial Intelligence, Networking & Cyber Security, serta Database & Programming. Seluruh materi disusun secara sistematis untuk membantu Anda memahami konsep, teknologi, dan praktik yang digunakan di bumi teknologi informasi, mulai dari tingkat alas hingga lanjutan. Setiap bahasan berfokus pada pengembangan keahlian melalui materi yang gampang dipahami, relevan dengan kebutuhan industri, dan disampaikan untuk tujuan edukasi. Seluruh konten mengedepankan implementasi teknologi secara legal, etis, dan bertanggung jawab, sehingga dapat menjadi rujukan belajar bagi pelajar, mahasiswa, maupun profesional. Jika Anda mau mengembangkan kapasitas di sektor pemrograman, pengelolaan data, kecerdasan buatan, jaringan komputer, maupun keamanan siber, channel ini menyediakan materi yang dapat membantu membangun fondasi ilmu sekaligus menaikkan keahlian secara bertahap. Playlist video terkait: ▪ https://www.youtube.com/playlist?list=PLZGgeqmsm32s ▪ https://www.youtube.com/playlist?list=PLZomBNpDl3vc ▪ https://www.youtube.com/playlist?list=PLE5VyXMZkzb8 PEMBAHASAN MATERI Playlist Materi Ilmu Komputer berisi kumpulan video pembelajaran, tutorial, klarifikasi konsep, studi kasus, demo, dan bahasan komplit seputar beragam sektor dalam ilmu komputer. Materi yang disajikan mencakup alas hingga tingkat lanjut, mulai dari pemrograman, pengelolaan database, jaringan komputer, keamanan siber, mekanisme operasi, pengembangan alat lunak, arsitektur komputer, hingga beragam teknologi yang digunakan dalam bumi komputasi modern. Temukan bahasan mengenai komputer dan pemrograman, algoritma, struktur data, PHP, JavaScript, Python, Laravel, MySQL, PostgreSQL, API, rekayasa alat lunak, database, jaringan komputer, pengelolaan server, cloud computing, virtualisasi, Linux, Windows Server, keamanan jaringan, cyber security, ethical hacking, kriptografi, keamanan aplikasi, DevOps, Internet of Things (IoT), kecerdasan buatan (AI), machine learning, serta beragam konsep, teknologi, dan praktik terbaik di sektor ilmu komputer. Playlist ini cocok bagi pelajar, mahasiswa, programmer, web developer, software engineer, pengelola sistem, ahli IT, maupun siapa saja yang mau mempelajari dan memperdalam wawasan di bumi ilmu komputer secara menyeluruh. CONTACT US ▪ Email support@mycoding.id ▪ WhatsApp https://wa.me/6281274309663 ▪ Telegram https://t.me/mycodingxd OFFICIAL LINKS ▪ Web https://mycoding.id ▪ Blog https://blog.mycoding.id ▪ News https://en.mycoding.id ▪ Apps https://play.google.com/store/apps/dev?id=5237501547073493079 SOCIAL MEDIA ▪ https://linkedin.com/company/mycodingxd ▪ https://facebook.com/mycodingxd ▪ https://instagram.com/mycodingxd ▪ https://tiktok.com/@mycodingxd ▪ https://twitter.com/mycoding_xd ▪ https://pinterest.com/mycoding_xd CHANNEL LINKS ▪ YouTube https://safelink.asia/youtube ▪ DailyMotion https://safelink.asia/dailymotion ▪ WhatsApp https://safelink.asia/whatsapp ▪ Telegram https://safelink.asia/telegram Powered by https://linkedin.com/company/401XDGroup #CyberSecurity #ArtificialIntelligence #Networking #DataScience #Programming #Database

Read next

Read next

Ninety-nine percent of global net traffic flows through cables stretched throughout the sea floor. Demand is at an all-time elevated as the earth becomes additional reliant on haze computing and AI. But lone one US business can the two create and lay them. We visited its 73-year-old factory and went aboard a multimillion-dollar cable-laying container to see how it is keeping up — and why our data motionless needs to journey thousands of feet below the sea.

%PDF-1.7 % 10 0 obj << /Type /XObject /Subtype /Form /BBox [0 0 725.669 7.97] /FormType 1 /Matrix [1 0 0 1 0 0] /Resources 11 0 R /Length 15 /Filter /FlateDecode >> stream xP( endstream endobj 17 0 obj << /Type /XObject /Subtype /Form /Group << /S /Transparency /CS /DeviceGray >> /BBox [0 0 725.669 7.97] /FormType 1 /Matrix [1 0 0 1 0 0] /Resources 18 0 R /Length 29 /Filter /FlateDecode >> stream x+2T0 B˥k J3 endstream endobj 13 0 obj << /Type /XObject /Subtype /Form /BBox [0 0 725.669 7.97] /FormType 1 /Matrix [1 0 0 1 0 0] /Resources 19 0 R /Length 57 /Filter /FlateDecode >> stream x+T2THW0Tp*B&r*s%̍L,!ҁ \@@

The CI sign covers the entire matrix on all push: build and tests on the oldest supported and current Go, the competition detector, lint, a fuzz pass complete the attacker-facing parsers, and the retention conformance suite against real SQLite, PostgreSQL and MySQL servers.

A comprehensive, framework-agnostic authentication archive for Go, modeled following better-auth. Email & password, social sign-on, sessions, document linking, two-factor auth, passkeys, magic links, organizations, SSO, admin tooling, API keys and JWT — alongside zero external dependencies (pure norm library).

go get github.com/go-dev-auth/go-dev-auth 

Status: pre-1.0, in manufacturing use, heading to v1.0. The archive runs in manufacturing in a genuine automation project on PostgreSQL, using the complete characteristic set. Releases prosecute SemVer: during pre-1.0 the community API may motionless alter between insignificant versions (pin an exact version); v1.0 freezes it, and from afterward on breaking changes necessitate a important version. The remaining v1.0 gates are runnable examples, site mileage on the newly automated MySQL leg, and a third-party safety review. See storage adapters for exactly which backends are verified where, and docs/security-model.md for the danger model.

Core

• Email & password authentication (scrypt hashing, compatible alongside better-auth's hash format)
• Social sign-on via OAuth 2.0 / OIDC alongside PKCE — Google, GitHub, Discord, Facebook, Microsoft, Apple, GitLab, LinkedIn, Spotify, Twitch, X built in, affirmative a declarative oauth2.Spec for any tradition provider
• Database-backed sessions alongside sliding expiration, signed cookies, optional biscuit caching, list/revoke endpoints
• Email verification, password reset, alter email/password, delete person flows
• Account linking & unlinking (trusted providers, token refresh, document info)
• CSRF base checking, trusted origins alongside wildcard subdomains, IP-based charge limiting
• Storage adapter interface alongside built-in database/sql (Postgres, MySQL, SQLite) and in-memory adapters, affirmative schema/migration SQL generation
• Request hooks, repository hooks, tradition user/session fields

Plugins (mirroring better-auth's plugin system)

• twofactor — TOTP, email OTP and backup codes
• passkey — WebAuthn passkeys, CBOR/COSE parsing included (no external dependency)
• magiclink — passwordless email links
• organization — orgs, members, roles, invitations, teams
• sso — bring-your-own OIDC character provider, matched by email domain
• admin — person management, bans, roles, impersonation
• apikey — hashed API keys alongside scopes that authenticate akin sessions
• jwt — EdDSA-signed JWTs + JWKS endpoint
• bearer — Authorization header auth for non-browser clients

package main import ( "context" "net/http" "os" "time" godevauth "github.com/go-dev-auth/go-dev-auth" "github.com/go-dev-auth/go-dev-auth/storage/memory" ) func main() { auth, err := godevauth.New(godevauth.Config{ BaseURL: "http://localhost:8080", // required Secret: os.Getenv("AUTH_SECRET"), // required, 32+ random chars Database: memory.New(), // required EmailAndPassword: godevauth.EmailPasswordConfig{Enabled: true}, // Required in manufacturing if item sits in forefront of this // procedure (load balancer, ingress, CDN). See below. Advanced: godevauth.AdvancedConfig{ TrustProxyHeaders: true, TrustedProxies: []string{"10.0.0.0/8"}, }, }) if err != nil { panic(err) } // clear expired one-time tokens and sessions defer auth.StartCleanup(context.Background(), time.Hour)() mux := http.NewServeMux() mux.Handle("/api/auth/", auth.Handler()) http.ListenAndServe(":8080", mux) }

The handler is a plain http.Handler, so it mounts on chi, echo, gorilla, or gin (via gin.WrapH) the identical way. If your frontend runs on a distinct origin, cover it: auth.CORS(auth.Handler()) and catalog that base in TrustedOrigins.

New validates the configuration and returns an error fairly than starting up in an unsafe state: a missing/short Secret, a missing or related BaseURL (it decides biscuit security, trusted origins and redirect targets), SameSite=none without safe cookies, or TrustProxyHeaders without TrustedProxies are all rejected.

Rate limiting and all recorded meeting IP depend on resolving the client's address. If item terminates the association in forefront of this procedure — an AWS ALB, nginx, Cloudflare, a Kubernetes ingress — you must say so, since both defaults are incorrect in a distinct direction:

So:

Advanced: godevauth.AdvancedConfig{ TrustProxyHeaders: true, // IPs or CIDRs of your burden balancers / ingress pods. TrustedProxies: []string{"10.0.0.0/8", "192.168.0.0/16"}, // Or, for a provider-specific header: // IPAddressHeaders: []string{"CF-Connecting-IP"}, },

New refuses to start if TrustProxyHeaders (or IPAddressHeaders) is set without TrustedProxies. Use TrustedProxies: []string{"*"} to rely any equal — that is the old, spoofable behaviour, and it is lone harmless whenever the network guarantees the assistance is unreachable apart from through a proxy that overwrites the header.

The contrary error cannot be caught at startup, since it depends on the traffic. The archetypal petition that arrives alongside a forwarded header during proxy headers are untrusted logs an error naming the header and the peer. If you see it in production, you are in row one of that table.

Direct-to-internet deployments need none of this: depart all three unset.

All adapters are written against the identical conformance suite (storage/storagetest), which pins the semantics the auth center depends on: unique-violation reporting, NULL vs zero, chronological sorting, clause folding, literal case-insensitive substring matching and compare-and-set update counts.

What has really been executed, as of this revision:

• SQLite — the complete conformance suite and a complete HTTP auth stream run against a genuine SQLite repository in CI on all push. Verified.
• PostgreSQL — running in production (a genuine automation project uses the entire archive on live PostgreSQL), and the conformance suite, immigration idempotence and the complete HTTP auth stream now run against a genuine PostgreSQL server in CI on all push. Field-proven and regression-guarded.
• MySQL — the identical CI job runs the conformance suite, migrations and the complete auth stream against a genuine MySQL 8 server on all push. CI-verified; no site mileage yet, so study item you hit.
• MongoDB — exercised against an in-house wire-protocol test double, not a live mongod. Beta.

The CI legs cannot continue vacuously: the surroundings sets REQUIRE_DSN=1, which turns a missing repository into a test nonaccomplishment fairly than a skip.

If you compose your own adapter, run that suite against it:

func TestConformance(t *testing.T) { storagetest.Run(t, func(t *testing.T) (storage.Adapter, func()) { return myAdapter(storagetest.Schema()), func() {} }) }

import ( "go.mongodb.org/mongo-driver/mongo" "go.mongodb.org/mongo-driver/mongo/options" "github.com/go-dev-auth/go-dev-auth/storage/mongostore" ) client, err := mongo.Connect(options.Client().ApplyURI(os.Getenv("MONGODB_URI"))) store := mongostore.New(client.Database("myapp")) auth, err := godevauth.New(godevauth.Config{Database: store, /* ... */})

New creates the indexes the schema implies, including the distinctive ones. That stage is not cosmetic on MongoDB: collections are created lazily, so an case without them looks fit during all "does this email already exist?" inspect degrades into a race. Use Advanced.DisableAutoMigrate lone if you create them in a distinct deploy step.

The adapter maps the id site onto Mongo's _id, rejects composite values anywhere MongoDB would peruse them as operators (the NoSQL-injection shape), escapes regex metacharacters in substring searches, and reports copy keys as storage.ErrUniqueViolation. Transaction needs a replica set or mongos, as MongoDB itself does.

import ( "database/sql" "github.com/go-dev-auth/go-dev-auth/storage/sqlstore" _ "github.com/jackc/pgx/v5/stdlib" // bring your own driver ) db, _ := sql.Open("pgx", os.Getenv("DATABASE_URL")) store := sqlstore.New(db, sqlstore.Postgres, nil) auth, _ := godevauth.New(godevauth.Config{ Secret: os.Getenv("AUTH_SECRET"), Database: store, // ... }) // choice up the plugin tables *and columns*, afterward use them store.SetSchema(auth.Schema()) if err := store.Migrate(context.Background()); err != nil { ... } // or hand the DDL to your own immigration tool: fmt.Println(store.MigrationSQL()) // the entire schema, from nothing pending, _ := store.PendingMigrationSQL(ctx) // lone what this repository lacks

Migrate is idempotent and does two things: it creates missing tables and indexes, and it adds missing columns to tables that already exist. The second matters as shortly as the repository has data in it — see Migrations.

import ( "github.com/go-dev-auth/go-dev-auth/oauth2" "github.com/go-dev-auth/go-dev-auth/providers" ) godevauth.Config{ SocialProviders: []oauth2.Provider{ providers.Google(providers.Credentials{ ClientID: os.Getenv("GOOGLE_CLIENT_ID"), ClientSecret: os.Getenv("GOOGLE_CLIENT_SECRET"), }), providers.GitHub(providers.Credentials{ ClientID: os.Getenv("GITHUB_CLIENT_ID"), ClientSecret: os.Getenv("GITHUB_CLIENT_SECRET"), }), }, }

Set the provider redirect URI to {BaseURL}/api/auth/callback/{provider}. Custom providers are a sole oauth2.New(oauth2.Spec{...}) call.

import ( "github.com/go-dev-auth/go-dev-auth/plugins/admin" "github.com/go-dev-auth/go-dev-auth/plugins/jwt" "github.com/go-dev-auth/go-dev-auth/plugins/magiclink" "github.com/go-dev-auth/go-dev-auth/plugins/organization" "github.com/go-dev-auth/go-dev-auth/plugins/passkey" "github.com/go-dev-auth/go-dev-auth/plugins/sso" "github.com/go-dev-auth/go-dev-auth/plugins/twofactor" ) godevauth.Config{ Plugins: []godevauth.Plugin{ twofactor.New(), organization.New(organization.Options{Teams: true}), admin.New(), jwt.New(), magiclink.New(magiclink.Options{ SendMagicLink: func(ctx context.Context, email, url, token string) error { return mailer.Send(email, "Sign in", url) }, }), passkey.New(), sso.New(sso.Options{ // entrance who may enroll character providers Authorize: func(c *godevauth.Ctx, sd *godevauth.SessionData) error { return myApp.RequireAdmin(sd) }, }), }, }

Passkeys (plugins/passkey) add WebAuthn registration and sign-in alongside no external dependency: the CBOR/COSE parsing and ES256/RS256/Ed25519 signature verification live in the package. Registration needs a caller session; sign-in uses discoverable credentials and runs through SignInUser, so bans and two-factor guideline motionless apply. The signature oppose is checked for the cloned-authenticator case.

SSO (plugins/sso) lets all institution bring its own OpenID Connect character provider (Okta, Microsoft Entra, Google Workspace, Keycloak). Providers are registered at runtime, matched to users by email domain, and the sign-in runs through the identical OAuth stream as social login — browser-bound single-use state, PKCE, ID-token verification against the issuer's JWKS. Client secrets are encrypted at rest; administration endpoints neglect closed until Options.Authorize is set.

Writing your own plugin method implementing three methods (ID, Init, Routes) and optionally Schema, Middleware, BeforeRequest/AfterRequest, SignInGuard (veto or difficulty a sign-in on all path) or SessionGuard (re-check all request).

func handler(w http.ResponseWriter, r *http.Request) { sd, err := auth.GetSession(r) if err != nil { // errors.Is(err, godevauth.ErrNoSession) → unauthenticated } _ = sd.User // *storage.User _ = sd.Session // *storage.Session }

All endpoints live under Config.BasePath (default /api/auth) and equivalent better-auth's path names:

Errors are returned as {"code": "USER_ALREADY_EXISTS", "message": "..."} alongside matching HTTP position codes. A known way alongside the incorrect method returns 405 alongside an Allow header.

godevauth.Config mirrors better-auth's options: EmailAndPassword (min/max length, verification requirements, reset delivery, tradition PasswordHasher), EmailVerification (delivery, required-before-sign-in, optional interstitial ConfirmationPage so email scanners cannot consume the link), Session (ExpiresIn, UpdateAge, FreshAge, biscuit cache), User (additional fields, change-email — endorsement goes to the current verified address, afterward the new location is verified before the toggle — delete-user), Account (linking rules, token encryption at rest), Advanced (cookie prefix, cross-subdomain cookies, SameSite, proxy trust, tradition ID generation, CSRF exemptions), TrustedOrigins, RateLimit (windows, per-path rules, pluggable store), Events (the audit hook), PreviousSecrets (secret rotation), Hooks and DatabaseHooks.

Rate-limit rules in RateLimit.CustomRules may be keyed by the path form ("/reset-password/:token") as fine as by a literal path. Buckets are keyed by the pattern, so a parameterised path is constricted as one endpoint fairly than one bucket per indicator value.

A runnable demo alongside most plugins enabled lives in examples/basic:

Extra columns are declared on the config and are not client-writable unless you say so. This is the difference between a overview site and a privilege:

User: godevauth.UserConfig{ AdditionalFields: []storage.Field{ {Name: "displayName", Type: storage.FieldString, Input: true}, // person may set it {Name: "plan", Type: storage.FieldString}, // server-controlled }, },

Fields contributed by plugins (role, banned, twoFactorEnabled, …) are never writable from a petition body, any Input says.

Passwords. scrypt (N=16384, r=16, p=1), better-auth's salt:key hex format. Each hash expenses ~50 ms of CPU and ~32 MiB of scratch recollection by design; the hasher limits concurrency (default GOMAXPROCS) and pools its buffers so a burst of sign-ins cannot exhaust memory. Tune via crypto.NewScryptHasher. Hash format is byte-for-byte compatible alongside better-auth for ASCII passwords; non-ASCII passwords not already in Unicode NFKC form can differ, since better-auth normalizes to NFKC archetypal and the norm archive has no NFKC implementation to equivalent without adding a dependency (see ScryptHasher.Hash).

Rate limiting is on by default (fail-closed) since the sign-in endpoint is costly by construction. Set RateLimit.Disabled lone whenever a gateway already throttles these paths, and provision RateLimit.Storage whenever operating additional than one instance.

Sessions. 32-byte random tokens, HMAC-signed cookies alongside domain separation and __Secure- prefixes on HTTPS. Raw tokens are never included in meeting listings. The optional biscuit cache carries an complete revalidation deadline that is never extended from cached data, so revocation continually takes consequence inside CookieCache.MaxAge.

One-time tokens (password reset, email verification, magic links, deletion, OAuth state) are stored as SHA-256 digests and consumed atomically, so repository peruse admission yields no usable links.

OAuth. PKCE (S256), province pinned to the browser alongside a biscuit and to the issuing provider, single-use and expiring. Automatic document linking requires the two a provider-asserted verified email and that the provider is listed in Account.AccountLinking.TrustedProviders — an unverified or self-set location at the IdP cannot obtain complete an existing local account.

CSRF. State-changing requests are origin-checked against BaseURL + TrustedOrigins (wildcard subdomains supported), falling rear to Sec-Fetch-Site whenever no Origin/Referer is present.

Sign-in guards. Every sign-in way — password, magic link, social, verification auto-login — funnels through SignInUser, so a plugin implementing SignInGuard (two-factor, bans) cannot be bypassed by choosing another method. SessionGuard additionally re-checks all request, so a ban takes consequence immediately fairly than at next login.

ID tokens. The native "sign in alongside X" way verifies the token's signature against the issuer's published JWKS and checks iss, aud (plus azp for multi-audience tokens), exp and the nonce — the client mints a single-use nonce at POST /id-token/nonce, passes it to the provider SDK, and the signed token must echo it, so a token captured elsewhere cannot be replayed current (Advanced.DisableIDTokenNonceCheck restores the old behavior for SDKs that cannot set one). Keys are cached alongside a bounded stale-serve window, and a unsuccessful fetch cannot be induced by a client to obstacle key rotation.

Secrets at rest. TOTP secrets, backup codes and JWT personal keys are AES-256-GCM encrypted alongside a key derived from your Secret; OAuth tokens too whenever Account.EncryptOAuthTokens is set. Encryption nonaccomplishment is an error, never a silent plaintext write, and decryption nonaccomplishment is an error too — never a fallback that returns the ciphertext. Every ciphertext is bound to anywhere it is stored — its model, document id and site name are authenticated alongside the value — so a value copied from one encrypted pillar into another does not decrypt, and repository compose admission cannot be turned into a peruse oracle for person else's secrets. Ciphertexts additionally transport a key identifier, so Secret can be rotated: see Rotating the secret.

Audit trail. Every security-relevant event — sign-in achievement and nonaccomplishment alongside the reason, sign-out, meeting innovation and revocation, password and email changes, document link/unlink and deletion, 2FA enable/disable, bans, and director impersonation start/stop — is emitted as a typed godevauth.Event. Events never merge passwords, meeting tokens or one-time tokens; there is no free-form field, and a test asserts the asset by reflection. See Audit events.

Config.Secret derives the key that encrypts values at rest. Changing it used to be unrecoverable — all enrolled 2FA person locked out permanently, JWT signing keys unreadable — since the ciphertext stated nothing concerning which key wrote it. Stored values are versioned and tagged alongside a key identifier:

v2.<kid>.<base64url(nonce || AES-256-GCM(plaintext))> 

The GCM additional data covers the version, the key id, and the value's location — model, document id, site name — so a ciphertext lone opens in the pillar of the row it was written to.

Two before formats be in deployed databases and are motionless read, so upgrading needs no migration:

Rotation — and the v0/v1 → v2 migration, which uses the identical continue — is a three-step deploy:

// 1. Deploy: new concealed current, old one motionless readable. Secret: os.Getenv("AUTH_SECRET"), // the new value PreviousSecrets: []string{os.Getenv("AUTH_SECRET_OLD")},

// 2. Migrate. Safe to run against a live instance; re-run until Done. result, err := auth.ReencryptSecrets(ctx) // result.Rewritten — values moved to the current key and format // result.Unreadable — values no key can read; examine before stage 3 // result.Skipped — rows a concurrent compose changed mid-pass; re-run // result.Failed — compose errors; re-run formerly the logic is fixed // result.Done() — nothing remaining to do

// 3. Deploy again alongside PreviousSecrets empty. // Once stage 2 reports Done, additionally set: RequireBoundCiphertexts: true,

ReencryptSecrets covers OAuth tokens on the document array and calls all plugin implementing godevauth.SecretRotator (two-factor, jwt) for their own tables. It walks all array in batches of 200 in id command fairly than loading it whole, and all compose is a compare-and-set on the ciphertext it peruse — so a token refreshed or a backup-code set regenerated mid-pass is never reverted, lone skipped. One plugin's rotator failing does not halt the others. It is idempotent: a continue that reports Done() method nothing is remaining under an old key or in an unbound format.

RequireBoundCiphertexts is the second fractional of the fix. Until it is set, the unbound v0 and v1 formats are motionless accepted on read, which method a ciphertext captured from an old backup can motionless be relocated between columns. Turning it on before the immigration finishes does not endure data — clearing it makes those values readable again — but users whose values have not been migrated cannot authenticate during it is set. So: upgrade, migrate to Done(), afterward rotate it on.

Skip stage 1 and the archive volition not guess. A stored TOTP concealed it cannot peruse is a 500 TWO_FACTOR_SECRET_UNREADABLE, not a "wrong code"; an unreadable OAuth token is a 500 TOKEN_DECRYPTION_FAILED, not an enc:… blob forwarded to the provider; and /jwks keeps publishing all community key regardless, so tokens already in circulation remain verifiable during you fix the configuration.

Note that biscuit and token signatures are not versioned. Rotating Secret invalidates existing signed cookies — users are signed out — any PreviousSecrets says.

There is one hook and one type:

Events: godevauth.EventsConfig{ Handler: func(ctx context.Context, e *godevauth.Event) { // e.Type, e.Outcome, e.Reason, e.ActorID, e.TargetID, // e.Email, e.SessionID, e.Method, e.Action, // e.ClientIP, e.UserAgent, e.RequestMethod, e.RequestPath siem.Send(e) }, },

Notable properties:

• On by default. With no Handler, events go to Config.Logger — successes at Info, failures at Warn. An audit trail that have to be switched on is missing from exactly the deployments that need it. Set Events.DisableDefaultLogging to opt out (events contain the subject's email address, which may not pertain in average use logs).
• Failure reasons are additional particular than the HTTP response. Sign-in answers INVALID_EMAIL_OR_PASSWORD to the client so it cannot be used to enumerate accounts; the event distinguishes unknown_user from invalid_password from banned from two_factor_required, which is what tells credential stuffing distinct from password guessing.
• 429s are recorded. Ctx.Error lone logs 5xx, so a throttled brute-force attempt alternatively leaves no server-side trace at all.
• RequestPath is the path pattern, e.g. /reset-password/:token — never the resolved path, which contains the token.
• Impersonation is bracketed. While it is energetic all act is recorded against the impersonated user, so admin.impersonation_started / admin.impersonation_stopped are the lone thread tying those actions rear to the administrator.

Plugins emit their own alongside auth.EmitEvent(c, godevauth.Event{...}).

• Cleanup: auth.CleanupExpired(ctx) or auth.StartCleanup(ctx, time.Hour). Expired verification rows and sessions are alternatively never collected.
• Behind a proxy: set Advanced.TrustProxyHeaders and Advanced.TrustedProxies. See the quick start — the default is an outage waiting to happen rearward a burden balancer.
• Rotating Secret: three-step deploy alongside Config.PreviousSecrets and auth.ReencryptSecrets. See Rotating the secret.
• Upgrading to border ciphertexts: run auth.ReencryptSecrets until it reports Done(), afterward deploy alongside Config.RequireBoundCiphertexts: true. Same section.
• Audit trail: on by default to Config.Logger; path it alongside Events.Handler. See Audit events.
• Multi-instance: provision a shared RateLimit.Storage; everything alternatively is stateless.
• Session biscuit cache: it is bypassed automatically whenever a plugin registers a SessionGuard (the admin plugin's ban inspect does). Serving authority decisions from a cached copy of the person would let a ban sit unnoticed for the cache window.
• Migrations: see Migrations below.
• Introspection: auth.Routes() lists all registered endpoint; auth.Schema() the complete schema.

Plugins do not lone add tables (passkey and sso all bring one). They additionally add columns to the tables you already have: admin adds role, banned, banReason and banExpires to person and impersonatedBy to session, twofactor adds twoFactorEnabled to user, institution adds activeOrganizationId to session, and Config.User.AdditionalFields does the same. A archive upgrade can add a center pillar the identical way.

CREATE TABLE IF NOT EXISTS does nothing for a array that is already there, so a column-level stage is not optional on a repository that has data in it. store.Migrate(ctx) does both:

Two things to cognize concerning added columns:

• They are continually nullable, any Field.Required says. The rows already in the array have no value for a pillar that did not exist, and no motor volition obtain NOT NULL without a default on a populated table. A required pillar added by a immigration is hence enforced by the application, not the database, until you backfill the rows and tighten it yourself.
• Migrate needs DDL rights. If your application's repository function does not have them, run migrations from a deploy step, set Advanced.DisableAutoMigrate, and set Advanced.VerifySchema so a missed immigration fails at startup alongside a communication naming the missing columns — alternatively of at the archetypal sign-in, alongside a controller error.

auth, err := godevauth.New(godevauth.Config{ Database: store, Advanced: godevauth.AdvancedConfig{ DisableAutoMigrate: true, // migrations are a deploy step VerifySchema: true, // ...so refuse to commencement if one was missed }, // ... }) // go-dev-auth: verifying the repository schema: sqlstore: the repository schema is // out of date: array "twoFactor" is missing; array "user" is missing column(s) // "role", "banned", "banReason", "banExpires"

Measured on a 4-core arm64 receptacle (go test -bench .) against the in-memory adapter. That is an honest measure of the library's own petition way and a mediocre proxy for your manufacturing latency, anywhere a repository round-trip volition dominate all row below apart from password hashing. Read these as "what the archive adds", not "what a sign-in costs".

Everything apart from password hashing is microseconds. Where the prosperity really goes, in order:

1. Password hashing dominates CPU. ~51 ms per sign-in method approximately sign-ins/sec ÷ 20 CPU cores. At 100 sign-ins/sec that is ~5 cores doing nothing but scrypt. This is deliberate — it is what makes taken hashes costly to expert — so the lever is not to create it cheaper but to do it small often: sessions final 7 days by default, so a signed-in person never touches it again.

2. Database circular trips dominate everything else. An authenticated petition expenses two queries (session, afterward user), which on a managed repository is ~1 ms all — a thousand times the CPU disbursal of the petition itself. Turn on the meeting biscuit cache to create that zero:

Session: godevauth.SessionConfig{ CookieCache: godevauth.CookieCacheConfig{Enabled: true, MaxAge: 5 * time.Minute}, },

The commerce is staleness: a revoked meeting keeps operating until the cached copy expires. With a SessionGuard plugin registered (the admin plugin's ban inspect is one) the cache is bypassed by default fairly than serving authority decisions from a old user; set CookieCache.AcceptStaleAuthorization to obtain the preservation anyhow and obtain that bans use inside MaxAge.

3. Memory under a sign-in burst is bounded, not proportional to traffic. Each in-flight hash needs 128·N·r = 32 MiB of scratch, so concurrency is capped at GOMAXPROCS and buffers are pooled: highest transient recollection is GOMAXPROCS × 32 MiB no matter how many requests arrive. Requests that cannot get a slot inside MaxWait (3s) are shed alongside 503 SERVICE_BUSY alternatively of queueing into a multi-second backlog that clients cognition as a hang.

Tuning the hash disbursal is imaginable but changes the security/cost commerce and makes existing hashes unverifiable:

// Fewer cores per sign-in, small opposition to offline cracking. // Fresh deployments only. crypto.NewScryptHasher(crypto.ScryptParams{N: 16384, R: 8, P: 1, MaxConcurrent: 8})

. the godevauth package: config, routing, handlers .github/ CI, templates, CONTRIBUTING, SECURITY storage/ persistence contract, models, schema storage/memory in-memory adapter storage/sqlstore PostgreSQL / MySQL / SQLite storage/mongostore MongoDB (separate module) storage/storagetest adapter conformance suite crypto/ password hashing, tokens, TOTP, JWT oauth2/ OAuth 2.0 / OIDC client providers/ ready-made provider configurations plugins/<name>/ optional features, one bundle each plugins/plugintest harness for evaluation a plugin ratelimit/ charge limiter and shop interface examples/basic a runnable server docs/ architecture map, plugin guide, reviews 

The base directory is flat since Go requires all document of a package to portion one directory: these records are the godevauth package, and nesting them would average either changing the import way or splitting the package. Everything that can be its own bundle already is. Files are named for what they clasp — session.go, router.go, handler_email.go — so the listing says as a array of contents.

docs/architecture.md is the complete map: what each file owns, and anywhere a new alter belongs.

go activity init . ./storage/mongostore ./storage/sqlstore/integration make inspect # fmt, vet, lint, tests, race 

make assistance lists all target. go.work is developer-local and not committed. The SQLite integration tests need CGO_ENABLED=1; the Postgres, MySQL and MongoDB suites skip unless the matching DSN environment variables are set.

See CONTRIBUTING.md for expectations on changes, SECURITY.md for the safety example and reporting process, and docs/ for the architecture map and audit records.

Working alongside an AI coding assistant? llms.txt is a single-file briefing on the API and the rules that keep generated code correct; AGENTS.md covers agents contributing to this repository.

MIT

We are quickly coming up on Apple’s “Welcome Home” initiate event, anywhere we anticipate a presenter of astute home-related announcements. We are expecting refreshes to Apple TV and HomePod Mini, as fine as a brand new astute residence hub. We could additionally see the debut of a new phase called homeOS, and several partner devices from LG.

What we likely won’t be seeing is the long-rumored touchscreen MacBook, which Cupertino whisperer Mark Gurman says will debut afterward this month.

“Welcome Home” volition officially boot off in New York on October 13th at 9AM ET. Here’s additional concerning what to expect.

Until now, Apple has chiefly relied on the Home app to authority all the assorted bits and bobs that create up your astute home. But it’s a market niche that the business has been eager to tackle additional fully. The new device, which could be called HomePad or HomeView or, additional simply, Apple Home Hub, volition reportedly characteristic a 6-inch quadrate touchscreen that can either be mounted on a partition or placed on a array or countertop. According to Mark Gurman, the countertop example volition slightly resemble the iMac G4, alongside the display attached to an arm set into a fractional sphere.

It volition additionally supposedly use sound or facial acknowledgment to acknowledge who is interacting alongside it, pulling up the applicable contacts, calendar appointments, and more. Apple volition recommendation the choice for secondary acknowledgment through an iPhone to keep individual data additional secure. The entire item volition reportedly run a new application phase called…

The business may have registered a trademark for the name through a casing company called Home Operations Suite LLC, a move that Apple has pulled before to quietly safe the entitlements to names. The phase volition supposedly characteristic a streamlined interface that “looks akin a mashup of iOS, tvOS and watchOS,” according to Gurman. The focus, obviously, volition be on astute residence applications, akin controlling thermostats and astute locks, and it volition additionally be capable of making FaceTime calls.

The OS volition additionally contain your customary assortment of Apple apps and widgets, including Apple Music, Podcasts, and News, as fine as Reminders, Notes, and Siri AI.

Word is that not much is changing alongside the HomePod Mini or Apple TV. The designs volition remain the same, but they’ll get a new processor to assistance grip the added petition of Siri AI. This volition be the archetypal update to the HomePod Mini since it was announced on October 13th of 2020 — exactly six years before Apple’s Welcome Home event. While the business isn’t making any theatrical changes for the Mini’s birthday, it volition be offering it in new colors, including green and pink.

This volition be the archetypal hardware refresh for the Apple TV since 2022. In supplement to supporting Siri AI, the new processor volition additionally speed up navigation, which can get a bit laggy. Both are expected to characteristic Apple’s N1 chip, which includes assistance for Wi-Fi and Bluetooth 6.0.

It’s apt that we’ll get a citation of products that merge alongside HomeKit and recommendation new features built on top of homeOS and any Apple’s hardware hub ends up being called. But don’t anticipate Apple to portion too much of the spotlight alongside its partners. We’ve already seen a leak of LG astute home, including deadbolts, thermostats, and more. They’ll additionally reportedly contain an NFC-based “Proximity Control” that pops up a clue in the iPhone’s Dynamic Island whenever held near the device, as fine as a “tap to set up without power” pairing feature.

Read next

Hexus – SaaS Landing HTML Template Free Download. Hexus is a Modern, and High-converting SaaS Landing Page Website Template designed for Software Startups, SaaS Businesses, AI Tools, Mobile Apps, Tech Companies, Digital Products, and Cloud-based Services. With a Sleek User Experience and Conversion-focused Layouts, Hexus helps you Showcase your Product, Increase Engagement, and Generate additional Leads Effectively.

Main Features

• Built alongside Bootstrap 5
• Modern SaaS UI Design
• Sticky Header
• Conversion-Oriented Structure
• SEO Optimized
• Working AJAX Contact Form
• Smooth Scroll
• Responsive Design
• W3C Validated Markup
• Fast Loading
• Animations and Hover Effects
• Blog Pages
• and more

Download Hexus – SaaS Landing HTML Template

Free download Hexus – SaaS Landing HTML Template by validthemes on Themeforest 63475250 premium SaaS endeavor and AI innovation HTML theme download.

Read next

Read next

Read next