BitSquare

@bitsquare/nopy (1.0.0-alpha5-main.13.g6ecb2c3)

Published 2026-07-28 12:19:03 +02:00 by benjamie in BitSquare/ansiblings

Installation

@bitsquare:registry=https://gitea.bitsquare.dev/api/packages/BitSquare/npm/
npm install @bitsquare/nopy@1.0.0-alpha5-main.13.g6ecb2c3
"@bitsquare/nopy": "1.0.0-alpha5-main.13.g6ecb2c3"

About this package

Nopy

A CLI tool that simplifies pyinfra script management and execution, providing an interactive workflow for deploying infrastructure configurations ("cubes") to remote hosts.

Overview

Nopy wraps pyinfra with structure, validation, and an interactive experience for managing complex infrastructure deployments. It organizes deployments into self-contained "cubes" with dependency management, schema validation, and lifecycle hooks.

Features

  • Dependency resolution with topological sorting
  • Before/after hooks for multi-cube orchestration
  • SSH key or password authentication
  • Default values with optional customization via manifest env
  • Schema validation using Zod
  • Recursive cube directory discovery
  • Dry-run mode for previewing deployments
  • JSON output for CI/CD integration
  • Session history with replay capability

Workflow

  1. Load cubes - Discovers and validates cubes from configured directories
  2. Interactive prompts - Select cubes, target host, and authentication method
  3. Dependency resolution - Topologically sorts cubes based on dependencies
  4. Variable assignment - Validates and collects configuration with schema validation
  5. Execute hooks - Runs before/after hooks for orchestration
  6. Deploy - Sequentially executes pyinfra commands

Core Concepts

Cubes

A cube is a directory containing two files:

  • JavaScript manifest: manifest.mjs defining schema, dependencies, defaults, secrets, and hooks
  • Python deployment script: deploy.py, a plain pyinfra script

Configuration variables are declared in the manifest and validated with Zod schemas before the deployment script runs.

cubes/
├── .npcubes
└── apt/
    └── install/
        ├── manifest.mjs
        └── deploy.py

Any directory holding both files is treated as a cube, so cubes can be nested as deeply as you like to group them by topic. Discovery is recursive; directories starting with . and node_modules are skipped. Additional files in the cube directory (a README.md, config templates, and so on) are ignored by the loader and can be referenced from the deploy script — the script runs with its cube directory as the working directory.

The prefixed forms <cube-name>.manifest.mjs and <cube-name>.deploy.py are also still recognized, but plain manifest.mjs / deploy.py is the current convention.

A cube's identity comes from the manifest's id field (see below). If id is omitted, nopy falls back to an [id] prefix in the manifest name, and finally to the directory's own name. Note that the id does not have to mirror the folder path — cubes/network/tailscale declares id: 'net:tailscale'.

Cube Manifest

import { z } from 'zod'
import { cubes } from '@bitsquare/nopy'

export default cubes.Manifest({
    id: 'apt:install',
    name: 'Install packages with apt',
    dependencies: () => [],
    schema: z.object({
        UPDATE: z.boolean().describe('Update package cache').default(false),
        PACKAGES: z.string().describe('Space-separated list of packages').default('vim htop'),
    })
})

Deployment Script

The matching deploy.py is a plain pyinfra script. Nopy passes each schema variable to pyinfra as --data KEY=value, so they are available on host.data:

from pyinfra import host
from pyinfra.operations import apt

UPDATE = host.data.UPDATE
PACKAGES = str(host.data.PACKAGES).split(' ')

apt.packages(
    name='Install essential packages',
    packages=['ca-certificates', 'gnupg', 'lsb-release'],
    update=UPDATE,
    _sudo=True,
)

apt.packages(
    name='Install custom packages',
    packages=[p.strip() for p in PACKAGES if p],
    update=UPDATE,
    _sudo=True,
)

Every key defined in the manifest schema is guaranteed to be present on host.data — either from the Zod .default(), from .nopyrc.json, from a recorded session, from a dependency, or from a user prompt.

Value types: pyinfra parses --data values before your script sees them. "true" / "false" become booleans, numeric strings become int, valid JSON becomes the parsed structure, and everything else stays a string. This is why UPDATE can be handed straight to pyinfra's update= argument, while PACKAGES is wrapped in str(...) before splitting.

Variable Defaults

Variable defaults are defined directly in the Zod schema using .default(). This ensures that every cube has a predictable starting state and provides type-safe default values.

A variable can be set from several places in one run. Every assignment is kept, tagged with where it came from — its origin — and the highest-ranked origin wins.

Origins, lowest to highest:

Origin Set by
default the Zod schema's .default()
env the env block of .nopyrc.json
session a value recorded in a session file or history entry
prompt what the user typed
param a dependency spec or a before/after hook

This allows cubes to ship with reasonable defaults while still allowing users to override them globally via .nopyrc.json or interactively during deployment. Because env outranks the schema, .nopyrc.json is also what steers a run started with --use-defaults, which never prompts.

prompt and param rarely compete: a key a dependency supplies is left out of the prompt entirely, so the user is only ever asked about the keys nothing else has set.

Ranking by origin rather than by arrival order is what makes replay work: a recorded value is applied before the cube would be prompted for, and prompting can still override it, but a --data value pushed in by a dependency is never clobbered by a stale recording.

A field declared without .default() has no default origin to fall back on. It is prompted for like any other, with an empty initial value — but a run that cannot prompt (--use-defaults) fails on it unless env or a dependency provides it.

Secrets

A manifest can name schema keys that hold sensitive values:

export default cubes.Manifest({
    id: 'user:add',
    name: 'Add a user account',
    secrets: ['PASSWORD'],
    schema: z.object({
        USERNAME: z.string().describe('Username for the new account').default('deploy'),
        PASSWORD: z.string().describe('Password for the new user account').default('changeme'),
    })
})

Every entry must be a key of schema; naming anything else is a manifest error and aborts the run, so a typo fails loudly instead of silently leaving a value unprotected.

Declaring a key a secret changes three things:

  • It is never written to a session file or to the history. Everything else the run settled on is recorded — including values that came from a .default() — but declared secrets are left out.
  • It is masked wherever a command or a plan is printed--dry-run, --print-only, and the debug log all show ******** in place of the value, in the variable list and in the pyinfra command line above it. The SSH password passed via --password is masked the same way, whether or not any cube declares secrets.
  • It is re-prompted on replay, since there is nothing recorded to replay from (see Session Recording and Replay).

Nopy does not guess. A key called PASSWORD in a manifest that declares no secrets is treated as an ordinary variable — recorded, and printed in the clear.

Three limits are worth knowing, because secrets keeps a value out of the files nopy writes and nothing more:

  • It is on the command line. pyinfra takes its data as --data KEY=value, so the real value is visible in ps for as long as the deployment runs. Masking covers nopy's own output, not the process table.
  • The prompt shows it. The variable form displays and pre-fills what it is asking about, so a secret is on screen while it is being entered or confirmed.
  • A .default() is not protected. A default lives in the manifest, in plain text, wherever the manifest is checked in. Give a secret a placeholder default like changeme if it needs one at all, never a real credential.

Configuration

Uses .nopyrc.json files (project-level or home directory) containing:

{
  "hosts": ["host1.example.com", "host2.example.com"],
  "cubeDirs": ["./cubes", "../shared-cubes"],
  "cubePackages": ["@bitsquare/cubes-core"],
  "env": {
    "SHARED_VAR": "value"
  },
  "log": {
    "verbosity": "info",
    "debug": false
  },
  "history": {
    "maxSessions": 10,
    "autoSave": true
  },
  "execution": {
    "continueOnError": false
  }
}

history controls automatic session recording (see Deployment History), and execution.continueOnError sets the default for --continue-on-error.

cubeDirs holds paths, cubePackages holds installed npm packages that ship cubes — see Cube Discovery below and CUBE-BUNDLES.md for publishing your own. Both are additive, and both resolve relative to the config file that named them, not to the working directory: a .nopyrc.json two levels up may name a package that only exists in its node_modules.

Logging Configuration

Control pyinfra output verbosity and debug information using the log configuration object:

log.verbosity - Controls the level of information printed during execution:

Verbosity PyInfra Flag Description Use Case
"silent" (none) Minimal output (default) Production deployments, clean output
"info" -v Print meta information See what operations are running
"verbose" -vv Include input data Debug parameters and configuration
"trace" -vvv Full command output See all command outputs and details

log.debug - Enables pyinfra's internal debug logging:

Value PyInfra Flag Description Use Case
false (none) No debug logs (default) Normal operation
true --debug Enable pyinfra debug logs Deep debugging of pyinfra internals

Recommendation: Start with "info" for typical troubleshooting, use "trace" when investigating command failures, and enable debug: true only when debugging pyinfra itself.

Session Recording and Replay

Nopy supports recording deployment sessions to JSON files for later replay. This is useful for:

  • Repeatable deployments
  • CI/CD pipelines
  • Documentation and auditing
  • Sharing configurations across teams

Session File Format

Sessions are stored in .nopysession.json files with the following structure:

{
  "version": "1.0.0",
  "name": "My Deployment Session",
  "timestamp": "2025-10-13T10:30:00Z",
  "cubes": [
    {
      "key": "apt:essentials",
      "variables": {
        "UPDATE": true
      }
    },
    {
      "key": "apt-more",
      "variables": {
        "SOME_VAR": "value"
      }
    }
  ],
  "hosts": [
    "@docker/nopy-test-container"
  ],
  "env": {
    "KEY_DIR": "../../vault/tmp"
  },
  "auth": {
    "method": "ssh-key",
    "username": "root"
  }
}

Structure Details:

  • cubes: Array of cubes with the variable values that cube ran with
  • env: The env block of .nopyrc.json as it stood at record time, kept for reference
  • hosts: Array of target hosts
  • auth: Authentication configuration (passwords are never stored)

What is recorded: every value each cube settled on, regardless of where it came from — a value the user typed, one inherited from .nopyrc.json env, one a dependency supplied, and one that fell through to the schema's .default() are all written out the same way. A session is therefore a full snapshot rather than a diff, and a --use-defaults run produces a session with real values in it instead of an empty one.

The consequence is that replay is faithful rather than re-derived: the recorded value outranks the current .nopyrc.json env and the current schema default, so editing either one does not silently change what a replay does. To pick up a new default, record a fresh session.

Security Note: Passwords are never stored in session files. This covers both the SSH password — a session records the auth method and username, never the credential — and any schema key a cube's manifest lists under secrets. Both are re-prompted on replay.

Recording a Session

# Run deployment interactively and save the session
nopy install --save-session my-deployment.nopysession.json

# With defaults (no prompts for variables)
nopy install -D --save-session automated-deployment.nopysession.json

Replaying a Session

# Load and execute a saved session
nopy install --load-session my-deployment.nopysession.json

# Session replay uses the exact cubes, variables, and hosts from the file
# Only password authentication will prompt for credentials

A replay runs straight through without asking anything, with three exceptions. Password authentication always re-prompts. A session with no recorded host falls back to the host picker. And a cube is re-prompted for its declared secrets, plus for any required variable the session has no value for — which happens when the cube's schema has gained a field since the session was written.

Those re-prompts are what a session cannot supply, so --use-defaults cannot paper over them: combining -D with a replay that needs either fails with a message naming the keys rather than deploying with a placeholder. Put the values under env in .nopyrc.json to make such a replay unattended.

Cube Discovery

Nopy searches for cubes in:

  1. Directories specified in .nopyrc.json cubeDirs
  2. Cube directories of every package listed in .nopyrc.json cubePackages
  3. Directories containing a .npcubes marker file (searching upwards from current directory)

All three are unioned and scanned the same way. A directory is a cube when it holds both a manifest (manifest.mjs or *.manifest.mjs) and a deploy script (deploy.py or *.deploy.py); dotted directories and node_modules are skipped during the scan.

Cube packages

A cube package is an ordinary npm package that ships cube directories and points at them from its own package.json:

{
  "name": "@bitsquare/cubes-core",
  "nopy": { "cubes": ["./cubes"] }
}

Install it and name it — nothing needs linking or copying:

pnpm add -D @bitsquare/cubes-core
{ "cubePackages": ["@bitsquare/cubes-core"] }

Naming a package is a statement that cubes are expected from it, so anything wrong is an error that aborts the run rather than a silent skip: the package is not installed, it declares no nopy.cubes, or an entry points at a directory that does not exist or lies outside the package.

Ids are claimed globally

A cube id such as apt:essentials is claimed across every source at once, not per directory or per package. Two cubes with the same id abort the run with an error naming both and where each came from. There is no precedence rule and no shadowing — a local cube does not quietly win over a packaged one, in either direction. Prefix your own cubes distinctly if you point cubeDirs at a local tree alongside an installed bundle.

Writing cubes to publish is covered in CUBE-BUNDLES.md.

Command Line Usage

Installation

This package is part of a yarn workspace monorepo. Install from the repository root:

# From repository root (/ansiblings)
yarn install
yarn workspace @bitsquare/nopy build

To use the nopy command globally, you can:

  1. Use yarn workspace command:

    yarn workspace @bitsquare/nopy nopy
    
  2. Link the package globally:

    cd packages/nopy
    npm link
    # Now you can use 'nopy' from anywhere
    nopy install
    
  3. Use via npm scripts (from packages/nopy directory):

    yarn nopy
    

Basic Commands

Install cubes (default command):

nopy install
# or simply
nopy

Install with defaults (no prompts for customization):

nopy install --use-defaults
# or
nopy install -D

Skips the per-cube variable form. Every variable is taken from the sources that need no interaction — the Zod .default(), env in .nopyrc.json, and values handed over by a dependency or a hook — which is what makes .nopyrc.json the place to configure an unattended run.

Cube selection, host and authentication are still asked for; there is nowhere else for them to come from. Pair -D with -K to skip the auth question too, or with -R / -H / -l, which supply all three from the recorded session.

A cube whose schema declares a field with no .default() cannot be filled in this way, so the run stops before anything is deployed rather than passing the variable as empty:

Error: Cube "net:wifi:connection" cannot run with --use-defaults: SSID, PASSWORD
have no default values. Set them under "env" in .nopyrc.json, pass them from a
dependency, or drop --use-defaults to be prompted.

Pairing -D with a replay fails the same way when the replay would have to ask something — a declared secret, which is never recorded, or a required variable the session has no value for. Both are the sources -D has no substitute for, so it stops rather than deploying a placeholder:

Error: Cube "user:add" cannot be replayed with --use-defaults: PASSWORD would
have to be entered. Secrets are never recorded in a session. Replay without
--use-defaults, or set the values under "env" in .nopyrc.json.

Use SSH key authentication:

nopy install --auth-method-key
# or
nopy install -K

Repeat last run:

nopy install --repeat-last
# or
nopy install -R

Every deployment is automatically recorded to a .nopy.history.json file in the current working directory, so the last run is always available to -R without having to pass --save-session first. The default retention is the 10 most recent sessions (configurable via history.maxSessions); use nopy history to list them and nopy install -H <id> to replay any one of them — see Deployment History.

The recording happens before the deploy commands run, so a failed deployment is recorded too — -R is the quick way to retry one after fixing the cause. Replaying a session with -R or -H does not itself create a new entry, so repeating never pushes the original run out of the list.

A run is not recorded when:

  • --dry-run or --no-history is passed
  • No cubes were selected, so there was nothing to deploy
  • history.autoSave is set to false in .nopyrc.json

Because the history file is resolved against the current working directory, each project keeps its own history — running nopy from a different directory will not find the previous run. As with session files, passwords are never stored and are re-prompted on replay.

Save session for replay:

nopy install --save-session my-deployment.nopysession.json
# or
nopy install -s my-deployment.nopysession.json

Load and replay session:

nopy install --load-session my-deployment.nopysession.json
# or
nopy install -l my-deployment.nopysession.json

Combined options:

nopy install -D -K  # Use defaults + SSH key auth
nopy install -D -s session.nopysession.json  # Use defaults and save session

Advanced Options

Dry run (preview without executing):

nopy install --dry-run

Shows the execution plan including commands, environment variables, and targets without running anything. Sensitive data is masked in output.

JSON output (for CI/CD):

nopy install --json
nopy history --json

Machine-readable JSON output for scripting and CI/CD integration.

Continue on error:

nopy install --continue-on-error
# or
nopy install -c

Continue deploying remaining cubes even if one fails.

Default behaviour (fail-fast): without this flag, nopy stops at the first cube that fails. Cubes are deployed sequentially in dependency order, so the failing cube's output is the last thing you see — every cube still queued behind it is skipped entirely and is never attempted.

This is deliberate: because cubes are topologically sorted, a cube that fails is often a dependency of the ones after it, and continuing would deploy them onto a half-configured host.

Two consequences worth knowing:

  • Cubes that already succeeded are not rolled back. The host is left in a partial state — the cubes before the failure are applied, the rest are not. Fix the cause and re-run; well-written cubes are idempotent, so re-applying the earlier ones is normally harmless.
  • Skipped cubes are not reported as failed. They are simply absent from the results, so a summary of "3 successful, 1 failed" out of 6 cubes means the remaining 2 were never run.

Either way, the command exits with code 1 if any cube failed, which is what CI picks up. Use --continue-on-error when your cubes are genuinely independent and you would rather collect every failure in one run than stop at the first.

The default can be flipped for a project by setting execution.continueOnError in .nopyrc.json; the CLI flag takes precedence over it.

Deployment History

nopy history              # List recent deployments
nopy history --json       # Same list as JSON, including each recorded session
nopy install -H <id>      # Replay a specific deployment by ID
nopy clear-history        # Delete all recorded sessions

History is what makes Repeat last run work, but it holds more than just the last deployment: every recorded run stays replayable until newer runs push it out. nopy history (alias nopy h) lists them newest first, with marking the entry that -R would replay:

Session History:

  → [1] 07/26/2026, 14:32 - apt:install, net:tailscale → root@web-01
       ID: mdk3n1qx4a2fh
    [2] 07/26/2026, 09:05 - apt:install → root@web-01
       ID: mdk0zzp8b71cq

Total: 2 session(s)

Each entry records the selected cubes together with every variable value they ran with, the target hosts, the authentication method, and the username — never the password, and never a key the manifest declared a secret. Pass an ID to -H to run that exact combination again:

nopy install -H mdk0zzp8b71cq

A replay is non-interactive: cube selection, host, and variable values all come from the entry, so nopy runs straight through without asking anything. It asks only for what the entry cannot hold — the password under password authentication, and any declared secret — plus the host picker when the entry recorded none.

Two things are worth knowing before relying on an older entry:

  • Recorded values win over the current configuration. The entry is a snapshot of everything the run settled on, so editing a cube's .default() or the env block of .nopyrc.json afterwards does not change what the replay does. A variable the schema has gained since the entry was written has nothing recorded: if it has a .default() the replay quietly takes it, and if it is required the replay prompts for it.
  • A replay fails if a cube no longer exists. Renaming or deleting a cube id makes every history entry that referenced it unreplayable: nopy logs Cube from session not found and then aborts with Cube not found: <id>.

The history lives in .nopy.history.json in the working directory and uses the same structure as a session file, so trimming the array by hand is a perfectly good way to prune it. It does contain the variable values a run used, which is why it is listed in this repository's .gitignore — treat it like any other file holding deployment configuration. A corrupt or unreadable history file is treated as empty rather than raising an error, which looks exactly like a project that has never been deployed from.

For a run you want to keep indefinitely, don't rely on history — it rotates. Use --save-session to write it to a file you control (see Session Recording and Replay).

Development

Run without building:

npm run nopy

Debug:

npm run debug

Documentation

Resources

Dependencies

Dependencies

ID Version
@bitsquare/nopy-cube 1.0.0-alpha0-main.13.g6ecb2c3
@logtape/logtape ^2.2.4
commander ^15.0.0
enquirer ^2.4.1
execa ^10.0.0
fuzzy ^0.1.3
inquirer ^14.0.2
zod ^4.4.3
zx ^8.8.5

Development Dependencies

ID Version
@types/node ^26.1.1
@vitest/coverage-v8 ^4.1.10
tsx ^4.23.1
typescript ^7.0.2
vitest ^4.1.10

Keywords

pyinfra deployment cli infrastructure
Details
npm
2026-07-28 12:19:03 +02:00
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bitsquare
MIT
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