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Entropy Data CLI

CI PyPI Python

The entropy-data CLI lets you manage your Entropy Data platform from the command line.

You can manage data products, data contracts, access agreements, teams, source systems, definitions, certifications, and more — directly from your terminal or CI/CD pipeline.

Install

Requires Python >= 3.11.

uv tool install entropy-data
entropy-data --help

Or with pip:

pip install entropy-data
entropy-data --help

Docker

docker run --rm entropydata/entropy-data-cli --help

Getting Started

1. Configure a connection

Generate an API key in the Entropy Data UI under organization settings, then:

entropy-data connection add prod
# prompts for API key and host

2. Explore your data platform

# List teams
entropy-data teams list

# Get a specific data product
entropy-data dataproducts get my-data-product

# List data contracts as JSON
entropy-data datacontracts list --output json

3. Manage resources

# Create or update a team from a YAML file
entropy-data teams put marketing --file team.yaml

# Show the team roles configuration, or switch to a custom role catalog
entropy-data settings team-roles get
entropy-data settings team-roles put --file team-roles.yaml

# Approve an access agreement
entropy-data access approve 640864de-83d4-4619-afba-ccea8037ed3a

# Search across all resources
entropy-data search query "customer orders"

Commands

entropy-data [--version] [--connection NAME] [--output table|json|yaml] [--debug]

  connection      list | get | add | remove | set-default | test
  dataproducts    list | get | put | delete | import-from-git | star | unstar | star-status | stargazers | gitconnection ...
  datacontracts   list | get | put | test | delete | yaml | generate | import-from-git | gitconnection ...
  access          list | get | put | delete | approve | reject | cancel | request
  teams           list | get | put | delete | git-credentials ... | notifications ...
  sourcesystems   list | get | put | delete
  definitions     list | get | put | delete
  certifications  list | get | put | delete
  classifications list | get | put | delete
  policies        list | get | put | delete
  example-data    list | get | put | delete
  test-results    list | get | publish | delete
  costs           list | add | delete
  assets          list | get | put | delete | tags ...
  tags            list | get | put | delete
  api-keys        create | delete
  connectors      list | get | put | delete
  integrations    list | get | runs | runs-get | runs-latest | run | cancel
  organization    get | members ... | git-credentials ...
  settings        get-customization | put-customization | get-scim-mapping | put-scim-mapping | team-roles ...
  events          poll
  lineage         list | submit | delete
  schemas         get
  search          query
  semantics       namespaces ... | concepts ... | relationships ... | search
  usage           list | submit | delete
  export          dir
  apply           dir [--include] [--exclude] [--prune] [--dry-run]
  import          zip
  sync            --source SRC --target TGT --include a,b [--exclude] [--prune] [--dry-run] [--keep DIR]

Syncing organization state between instances

sync copies the portable declarative state of an organization from one Entropy Data instance to another — for example to promote a test environment to prod. It exports the source and applies it to the target in one step (export dir + apply dir do the same in two). Only state reachable through the public /api/** API and portable across instances is copied (no secrets, telemetry, or environment-specific identity). Every write is an idempotent PUT-by-id, so runs converge and are safe to repeat.

sync copies nothing by default — name the resources to sync with --include.

Supported resources (in dependency order): teams, tags, definitions, policies, sourcesystems, certifications, classification-schemes, assets, datacontracts, dataproducts, example-data, access, semantic-namespaces, semantic-ontology, organization-features.

Not synced: users & team members, API keys, git credentials, integration and connector credentials, usage, costs, test results, events, and lineage (per-instance identity, secrets, or telemetry). Organization customization, SCIM mapping, team-roles configuration, notification channels, connectors, and integrations are not supported yet.

# Preview a test -> prod sync of selected resources without writing anything.
entropy-data sync --source test --target prod --include teams,policies,datacontracts,dataproducts --dry-run

# Sync those resources.
entropy-data sync --source test --target prod --include teams,policies,datacontracts,dataproducts

# Mirror: also delete target resources that are absent from the source.
entropy-data sync --source test --target prod --include datacontracts --prune

# The two-step equivalent, with a reviewable YAML tree in between.
entropy-data -c test export dir ./state
entropy-data -c prod apply dir ./state

apply dir — apply a local export tree

apply dir <path> reconciles a local export directory into the connected instance, in the spirit of kubectl apply -f <dir>. The tree follows a folder-as-kind convention: the directory name is the resource kind and each YAML file below it is one resource, addressed by the id in its body.

state/
  teams/                          # folder name = resource kind
    marketing.yaml                # one file per resource (filename is cosmetic)
  policies/
    pii-policy.yaml
  datacontracts/
    orders-1-orders.yaml
  semantic-ontology/
    main.yaml                     # document resources: one YAML doc per namespace
  organization-features/
    organization-features.yaml    # singleton: <name>/<name>.yaml

Unlike kubectl, the files carry no kind: field — the enclosing folder is authoritative, so a file only means what its folder says. Folders that are not a known resource kind are ignored. Unlike sync, apply dir applies the whole tree by default (the directory is your selection); use --include/--exclude to narrow it, --dry-run to preview, and --prune to also delete instance resources absent from the tree. This layout matches the app's own organization export, so an export dir tree and an in-app export zip interchange.

Useful options:

  • --include a,b — narrow the apply to these resources (names from the supported list above). Optional; the whole tree is applied when omitted.
  • --exclude a,b — drop resources from the applied set.
  • --prune — after upserts, delete target resources absent from the directory, in reverse dependency order. Guarded by a confirmation prompt unless --yes is passed.
  • --dry-run — print per-resource create/update/(prune) counts; no writes.

Notes:

  • Team members are stripped on import (users are per-instance identities); the export keeps them so the artifact is a faithful snapshot.
  • The semantics graph is copied as one OSI ontology YAML document per namespace (semantic-ontology/<namespace>.yaml) via the app's .../{ns}/ontology.yaml endpoint, which imports it in the correct internal dependency order and provisions the namespace from the metadata (display name, read-only flag, owning team) carried in the document's root custom_properties — so there is no separate namespace artifact. Requires that endpoint on the target instance. A tree exported by an older version that still carries a semantic-namespaces/ folder is applied as before.
  • The organization feature configuration is an org-level singleton (organization-features/organization-features.yaml), applied last and never pruned. It requires the app's GET/PUT /api/organization/features endpoint (entropy-data#1521), which must be merged and deployed to the target instance first.

Connection Management

Connections are stored in ~/.entropy-data/config.toml:

default_connection_name = "prod"

[connections.prod]
api_key = "ed_abc123..."
host = "https://api.entropy-data.com"

[connections.dev]
api_key = "ed_xyz789..."
host = "https://localhost:8080"

You can also use environment variables (ENTROPY_DATA_API_KEY, ENTROPY_DATA_HOST) or CLI options (--api-key, --host).

.env File Support

The CLI automatically loads a .env file from the current working directory. This is useful for project-specific configuration:

# .env
ENTROPY_DATA_API_KEY=ed_abc123...
ENTROPY_DATA_HOST=https://api.entropy-data.com

Values from .env are loaded as environment variables and do not override already-set environment variables.

Resolution precedence: CLI options > environment variables / .env > config file.

TLS behind a corporate proxy or internal CA

By default the CLI verifies TLS certificates against the bundled CA certificates (certifi). In a corporate network with a TLS-inspecting proxy or an internal certificate authority, this can fail with CERTIFICATE_VERIFY_FAILED: unable to get local issuer certificate, because the root CA is installed in the operating system's trust store but not in the bundled list.

Use the global --system-truststore option to verify against the operating system's trust store (macOS Keychain, Windows certificate store, or the system CA certificates on Linux) instead:

entropy-data --system-truststore datacontracts list

You can also enable it for every invocation by exporting an environment variable:

export ENTROPY_DATA_SYSTEM_TRUSTSTORE=1

This keeps certificate verification on while trusting the corporate root CA, and applies to every command that makes HTTPS requests.

Development

git clone https://github.com/entropy-data/entropy-data-cli
cd entropy-data-cli
uv sync --dev
uv run pytest
uv run ruff check .

Release

  1. Update the version in pyproject.toml
  2. Update CHANGELOG.md with a ## [X.Y.Z] section
  3. Commit, tag, and push:
git add pyproject.toml CHANGELOG.md
git commit -m "Bump version to X.Y.Z"
git tag vX.Y.Z
git push origin main --tags

The release workflow will automatically run tests, publish to PyPI, create a GitHub Release, and push a Docker image to Docker Hub.

About

Claude Code and Codex love this CLI tool to interface with Entropy Data

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