deta
AI Cost Tracking
- 🤖 LLM usage: $1.9600 (56 commits)
- 👤 Human dev: ~$2057 (20.6h @ $100/h, 30min dedup)
Generated on 2026-07-06 using openrouter/qwen/qwen3-coder-next
Infrastructure anomaly detection and monitoring tool for development environments.
Features
- Manifest Scanning: Scans docker-compose, OpenAPI, package.json, and pyproject.toml files up to 3 layers deep
- Environment Interpolation: Full
${VAR:-default}support with.envfile layering and compose override merging - Port Parsing: Resolves host/container port mappings with protocol and host-bind support
- Topology Building: Builds service dependency graphs with cycle detection and hub analysis
- Anomaly Detection: Detects missing healthchecks, port conflicts, dependency cycles, and hardcoded secrets
- Real-time Monitoring: Watches for config changes, probes HTTP/TCP health checks with concurrent probing
- Web Dashboard: Real-time FastAPI/WebSocket dashboard with topology visualization and event stream
- DSL Change Tracking: Structured change commands for service/port/probe state transitions
- Topology Caching: mtime-based cache with configurable TTL to avoid redundant rescans
- Multi-format Output: JSON, YAML graph, Mermaid, PNG (graphviz), and Semcod toon format
- CLI Interface:
scan,monitor,diff, andwebcommands via argparse
Installation
pip install deta
With optional dependencies:
# web dashboard (FastAPI + uvicorn + WebSocket)
pip install 'deta[web]'
# all extras
pip install deta[docker,toml,web]
Usage
Scan infrastructure
deta scan /path/to/project --depth 3 --output infra-map.json
Generate graph outputs (YAML / Mermaid / PNG)
# text graph + mermaid + json
deta scan /path/to/project --formats json,yaml,mermaid
# include online checks (localhost probes)
deta scan /path/to/project --formats json,yaml,mermaid --online
# try PNG (requires graphviz python package + graphviz binary)
deta scan /path/to/project --formats png
Generated files (configurable in deta.yaml):
infra-map.jsoninfra-graph.yamlinfra-graph.mmdinfra-graph.pnginfra.toon.yaml
Monitor in real-time
deta monitor /path/to/project --interval 30 --depth 3
deta monitor . --interval 30 --depth 3
# realtime watch from scan command (regenerates outputs on each change)
deta scan /path/to/project --watch --formats json,yaml,mermaid --online
Web Dashboard
deta web /path/to/project --depth 3 --host 127.0.0.1 --port 8765
Open http://127.0.0.1:8765 — real-time topology view with WebSocket event push (service up/down, port changes).
Configuration in deta.yaml:
web:
enabled: true
host: 127.0.0.1
port: 8765
refresh_seconds: 5
cache_ttl_seconds: 30.0
debounce_seconds: 0.5
push_events:
- service_added
- service_removed
- service_up
- service_down
Compare with baseline
deta diff --baseline infra-map.json /path/to/project
Example Workflow (e.g., for c2004 project)
Here is a complete example of how to use deta to scan, monitor, and visualize the c2004 project:
- Scan and export topology:
deta scan ../maskservice/c2004 --output infra-map.json
- Detect changes against the baseline:
deta diff --baseline infra-map.json ../maskservice/c2004
- Monitor infrastructure in real-time:
deta monitor ../maskservice/c2004 --interval 5
- Launch the interactive Web Dashboard:
# Ensure the web extra is installed: pip install '.[web]' deta web ../maskservice/c2004 --host 127.0.0.1 --port 8765
Python API
from pathlib import Path
from deta import build_topology, scan_compose, scan_openapi, probe_all
# Build topology from manifests
topology = build_topology(Path("/path/to/project"), max_depth=3)
# Detect anomalies
anomalies = topology.detect_anomalies()
for anomaly in anomalies:
print(f"{anomaly['severity']}: {anomaly['type']}")
# Cycle & hub analysis
cycles = topology.detect_cycles()
hubs = topology.find_hubs(min_degree=3)
# Export to JSON
import json
output = json.loads(topology.to_json())
# Probe services
results = probe_all(topology.services, max_concurrency=20)
Architecture
deta/
├── scanner/ # Manifest parsing
│ ├── compose.py # docker-compose.yml (with override merging)
│ ├── openapi.py # OpenAPI specs
│ ├── npm.py # package.json
│ ├── python.py # pyproject.toml & requirements.txt
│ ├── env.py # .env file loading & interpolation
│ └── ports.py # Port binding parsing & resolution
├── builder/ # Topology construction
│ ├── topology.py # Graph, anomaly detection, cycles, hubs
│ └── cache.py # mtime-based topology cache
├── monitor/ # Real-time monitoring
│ ├── watcher.py # File change polling
│ ├── prober.py # HTTP/TCP health checks (concurrent)
│ └── alerter.py # Rich console output
├── formatter/ # Output formats
│ ├── graph.py # YAML graph, Mermaid, PNG
│ └── toon.py # Semcod toon format
├── dsl/ # Change tracking DSL
│ └── commands.py # service_up/down, port_added/removed
├── web/ # Real-time dashboard
│ └── app.py # FastAPI + WebSocket (topology, probes, events)
├── integration/ # Ecosystem hooks
│ └── semcod.py # sumd, pyqual, vallm, pre_deploy_check
├── config.py # deta.yaml configuration (Pydantic models)
├── core.py # Base Wup class
└── cli.py # CLI entry point (scan, monitor, diff, web)
Configuration
Place deta.yaml in your project root. See deta.yaml.example for all options:
- scan — depth, include/exclude patterns
- watch — file monitoring paths and patterns
- anomaly — toggle checks, secret patterns, severity levels
- monitor — interval, probe timeout/retries, concurrency
- output — formats and file paths
- alert — console colors, min severity
- web — dashboard host/port, refresh, cache TTL, push events
Semcod Integration
deta integrates with the Semcod ecosystem:
from pathlib import Path
from deta.integration import generate_for_sumd, generate_for_pyqual, generate_for_vallm, pre_deploy_check
# Generate toon for sumd
generate_for_sumd(Path("."), output=Path("infra.toon.yaml"))
# Quality analysis for pyqual
generate_for_pyqual(Path("."), depth=3)
# Validation for vallm
generate_for_vallm(Path("."), depth=3)
# Pre-deployment validation
passed, issues = pre_deploy_check(Path("."))
if not passed:
print("Deployment blocked:", issues)
Tests
pytest tests/ -v
Test coverage: cache invalidation, compose env interpolation, DSL commands, .env parsing, port parsing, monitor port display.
License
Licensed under Apache-2.0.
Metadata
Release files for deta 0.2.54
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| deta-0.2.54.tar.gz | 67.8 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| deta-0.2.54-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 133.5 kB
Release files / deta-0.2.54.tar.gz
| Download URL | deta-0.2.54.tar.gz |
|---|---|
| Size | 67.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
d1515aa7997ccb29724481366cc6d1b276830340aed3734bb41e3a1ae577d42a
|
|
BLAKE2b-256 checksum How to use checksums |
ddb77db9236ff4568cb8f05cee26ef6249f9593781cfb333dc956edc19d8c5ed
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.7
|
Release files / deta-0.2.54-py3-none-any.whl
| Download URL | deta-0.2.54-py3-none-any.whl |
|---|---|
| Size | 65.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
3dcfd2f1c6c4a5a7c23e0f9a675addcd0435003af1bcd2251f5f8dde83a37a62
|
|
BLAKE2b-256 checksum How to use checksums |
e73964d53b46b5540e606d0a91194da0d5eae81c5f1e7c9767a3181ab44e2010
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.7
|
Security for deta 0.2.54
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.