Motivation for the company_dns

To enable a more automated approach to gathering information about companies company_dns was created. This release enables the synthesis of data from the SEC EDGAR repository and Wikipedia. A Medium article entitled "A case for API based open company firmographics" is available discussing the process and motivation behind the creation of this service.

Web Application Documentation

The embedded web interface is a modern single-page application for exploring SEC EDGAR filings and industry classifications. For detailed documentation on features, architecture, and usage, see html/README.md.

V4.0.0-pre (pre-release)

A Rust rewrite of the service, V4.0.0-pre, is being prepared and runs in a staging environment. V3 (described in the rest of this file) is still the live service. V4 answers the same URLs (its /V3.0/ and /V2.0/ paths return V3's shapes, with one additive field, a top-level total), and adds semantic and hybrid industry-code search, an experimental SQL endpoint, and built-in API documentation (/docs, /redoc) and web UI (/ui/). It is faster than V3 on 26 of the 28 checks compared (docs/results/). The documents say "V4.0.0-pre" until it is released; the code reports 4.0.0.

• Start here: v4/README.md (running it, the settings, the endpoints, how it is deployed).
• Moving from V3: docs/migrating-to-v4.md and the using-the-API guide docs/using-the-api.md.
• What changed: CHANGELOG.md. Plans: docs/plans/README.md.
• Integrations: Zetaris AI Data Harness (loading the US SIC, EU NACE and Japan SIC classifications as SQL tables).
• Data sources and terms: see Data sources and terms below, including a pending permission for the ISIC data.

Changes

Introducing V3.3.0

The V3.3.0 release is a substantial performance pass across the whole service, covering the companies DB cache, request concurrency, replica capacity, comparison tooling, EDGAR connection reuse, and — the largest single win — a rewritten Wikipedia backend. See docs/plans/performance-improvements.md for the full investigation, findings, and measured before/after numbers behind each item below.

1. companies DB full-table-scan fix: filters to 10-% filing forms at ingest time instead of querying a ~2M-row unfiltered table, fixing a hidden bottleneck behind edgar_ciks/edgar_detail that had nothing to do with live SEC calls.
2. Blocking I/O moved off the event loop: handler objects are now constructed fresh per request (fixing a latent shared-singleton correctness risk) and blocking query methods run via run_in_threadpool, so requests actually execute concurrently instead of serializing on a single event loop.
3. Replica count bumped to 4 (from 2), multiplying the throughput gained from item 2 — the service now handles concurrency=16 cleanly where it previously crashed at that level on 2 replicas.
4. Before/after comparison tooling (perf_tests/baseline.py, perf_tests/compare.py): measures sequential and concurrent latency against the live deployment and flags regressions/improvements, so every change above was verified with real numbers rather than assumed.
5. HTTP connection reuse to SEC EDGAR: a shared requests.Session() instead of a new connection per call.
6. Wikipedia backend rewritten (lib/wikipedia_v2.py): replaces wptools with narrowed, direct MediaWiki/Wikidata HTTP requests (no more fetching entire parse trees or the full multi-hop wikidata-label cascade wptools triggered internally), plus a real, ToS-compliant User-Agent and 429/503 retry handling wptools never had. Validated against production with perf_tests/shadow_compare.py over multiple days before cutover. Now the default backend for the wikipedia/merged endpoints — median latency down 80% for both (wikipedia_firmographics: 3851ms → 773ms; merged_firmographics: 6095ms → 1199ms). The old wptools-based backend is still reachable at /V3.0/global/company/wikipedia/v1/firmographics/{company_name} and /V3.0/global/company/merged/v1/firmographics/{company_name} for reference/rollback.

Previous Releases

For release notes prior to V3.3.0 (including V3.2.0, V3.1.0, and V3.0.0), see the consolidated changelog: CHANGELOG.md.

Installation & Setup

The install and setup process is either for users or developers. Instructions for both are provided below.

For users via docker

New from V3.0.0 are automated docker builds providing a fresh image on a monthly basis. There are three reasons for this:

1. Gets the latest information from EDGAR such that when the service is queried the user can access the latest quarterly and yearly filings.
2. As the code progresses, and is checked into main, users will automatically get the latest improvements and fixes.
3. Creates images for both x86 and ARM architectures.

The image can be pulled using docker pull ghcr.io/miha42-github/company_dns/company_dns:latest. With the image pulled you can run it using docker run -m 1G -p 8000:8000 company_dns:latest which will run the image in the foreground, and running the image in the background docker run -d -m 1G -p 8000:8000 company_dns:latest. GitHub's container registry is used to store the images, and more information on this package can be found at company_dns/company_dns.

For developers via GitHub with docker and without docker

Assuming you have setup access to GitHub and a Linux or MacOS system of some kind, you'll need to get the repository.

1. Create a directory that will contain the code: mkdir ~/dev
2. Enter the directory: cd ~/dev/
3. Clone the repository: git clone [email protected]:miha42-github/company_dns.git

With docker

Since the docker build process takes care of data cache creation, Python requirements installation and other items getting company_dns running is relatively straight forward. To simplify the process further the svc_ctl.sh script is provided.

Service Control Script

svc_ctl.sh automates build/run/log tasks for company_dns. Common workflows:

1. From ~/dev/company_dns: ./svc_ctl.sh build then ./svc_ctl.sh start (background) or ./svc_ctl.sh foreground (interactive).
2. Watch logs: ./svc_ctl.sh tail.
3. Stop or kill: ./svc_ctl.sh stop (graceful) or ./svc_ctl.sh kill (forceful).
4. Rebuild and restart: ./svc_ctl.sh rebuild.
5. Check status or dependencies: ./svc_ctl.sh status or ./svc_ctl.sh check-deps.
6. Cleanup stopped containers/images: ./svc_ctl.sh cleanup.

Service control usage information

NAME:
    ./svc_ctl.sh <sub-command>

COMMANDS:
    help         - Display help
    check-deps   - Validate docker and required files
    start        - Start the service in the background
    stop         - Stop the running container gracefully
    kill         - Forcefully stop the running container
    build        - Build the Docker image
    rebuild      - Rebuild image and restart the service
    foreground   - Run the service in the foreground
    tail         - View logs of the running container
    status       - Check container status and port
    cleanup      - Remove stopped containers and dangling images

Without docker

Depending upon the intention for getting the code it could be running in a Python virtual environment or in a vanilla file system. Regardless the steps below can be followed to get the service up and running.

Pre-execution

Before you get started it is important to install all prequisites and then create the cache database.

1. Enter the directory with the service bits (assuming you're using ~/dev): cd ~/dev/company_dns/company_dns
2. Install all prerequsites: pip3 install -r ./requirements.txt
3. Create the database cache python3 ./makedb.py

Execution

If everything above completed successfully then running company_dns can be performed via python3 ./company_dns.py this will run the service in the foreground.

On-prem Kubernetes (how the live deployment actually runs)

The live service at company-dns.mediumroast.io runs on an on-prem MicroK8s HA cluster (it previously ran as an Azure Container App). This is a maintainer-facing deployment path, not required for local development — see k8s/README.md for the manifest layout, first-time cutover steps, and routine redeploy instructions, and docs/plans/onprem-k8s-migration.md for the full migration rationale. Routine redeploys are a single command from a workstation with cluster access:

./scripts/build-and-deploy.sh

which builds the image, pushes it to GHCR, and rolls it out via kubectl (requires a .env file with GITHUB_PAT set — see .env.template).

V4 (pre-release) on Kubernetes

V4 is deployed with scripts/build-and-deploy-v4.sh and k8s/staging/. Those scripts and manifests are maintainer-focused today: they assume this project's registry and namespace, Traefik, cert-manager with a named issuer, SealedSecrets and its host names. The application and the container image are general (run the image with docker run; see v4/README.md), the manifests are a usable reference, and making the scripts generic is planned work, listed with the rest of the debt in v4/README.md.

Verify that the service is working

Regardless of the approach taken to run the company_dns checking to see if it is operating is important. A quick way to check on service availability when running on localhost is to follow this link: http://localhost:8000/. If this is successful the embedded web interface will display (see screenshot below) describing core capabilities and function, examples with curl, and some helpful links to the company_dns GitHub repository.

Checkout a live system

A live system is available for Mediuroast efforts and for anyone to try out, running on an on-prem MicroK8s cluster (see k8s/README.md). Relevant links are below.

• Embedded background - https://company-dns.mediumroast.io/
• Company search for IBM - https://company-dns.mediumroast.io/V3.0/global/company/merged/firmographics/IBM
• Standard industry code search for Oil - https://www.mediumroast.io/company_dns/V3.0/na/sic/description/oil

How can I contribute?

Bugs

If you encounter a problem with the company_dns please first review existing open issues, and if you find a match then please add a comment with any detail you might deem relevant. If you're unable to find an issue that matches the behavior you're seeing please open a new issue.

Tests

• V3: see perf_tests/ and the API tests in api_tests/.
• V4: cd v4 && cargo test --workspace; python3 api_tests/run.py against a running server (see v4/README.md); python3 scripts/test_v4_scripts.py for the deploy scripts; python3 scripts/check_hygiene.py for the open-source hygiene check (no addresses, internal names or secrets in the repository).

Improvements

We try to keep high level Todos and Improvements in a list contained in a section below, and as we begin to work on things we will create a corresponding issue, link to it, progress and close it. However, if there is a change in design, major improvement, and so on something may fall off the list below. If something isn't on the list then please create a new issue and we will evaluate. We'll let you know if we pick up your request and progress to working on it.

Future work/Todos

Here are the things that are likely to be worked but without any strict deadline:

1. Determine if feasible to talk to the companies house API for gathering data from the UK
   1. Initial feasibility has been checked, but the value of the data is still being evaluated
2. Evaluate if financial data can be added from EDGAR, Wikipedia and Companies House
3. Provide instructions/details for running on a Pi or Arm based system
   1. Since one of the target docker images is for ARM, the next logical step is to provide instructions for running on a Pi.

Data sources and terms

The classification data bundled with the service, and where it comes from. This is a summary of the published terms, not legal advice; follow the linked terms.

Data	Licence	Terms	Status
US SIC (Standard Industrial Classification)	Federal Government Works, Public Domain Policy	dol.gov copyright	Redistribution rights in hand
EU NACE Rev. 2	Creative Commons Attribution 4.0 International (CC BY 4.0)	Eurostat copyright notice	Redistribution rights in hand
Japan SIC (JSIC Rev. 13)	Creative Commons Attribution 4.0 International (CC BY 4.0)	e-Stat terms of use	Redistribution rights in hand
ISIC Rev. 4 (United Nations)	not yet confirmed		Permission requested from the UN; no answer yet
SEC EDGAR filings	public SEC data, read under the SEC's fair-access policy (an identifying User-Agent)	sec.gov	fetched at build time and live
Wikipedia and Wikidata	Wikipedia text CC BY-SA 4.0; Wikidata CC0; read under the Wikimedia User-Agent policy	wikimedia terms	read live

Attribution (CC BY 4.0). The EU NACE data contains information from Eurostat and the Japan SIC data contains information from e-Stat (Japan), both under CC BY 4.0. Mediumroast changed it: the classifications are flattened into one table per system and embedded (vectors added) for similarity search.

Risk: the ISIC data could be removed. A request to the United Nations for permission to redistribute ISIC has not been answered. If the answer is no, or never comes, the ISIC data will be taken out of the image and the service. What would stop working: the international ISIC lookups (/V4.0/international/... and their /V3.0/ aliases), ISIC rows in the global keyword search, and crosswalks to ISIC in company matching. The other systems are unaffected, and the server already starts without any one classification file (it warns and continues). Do not build on ISIC yet. Updates will be recorded here and in the CHANGELOG.

License

Since this code falls under a liberal Apache-V2 license it is provided as is, without warranty or guarantee of support. Feel free to fork the code, but please provide attribution to the authors.

Key Dependencies

• PyEdgar - used to interface with the SEC's EDGAR repository
• SQLite - helps all utilities and the RESTful service quickly and expressively respond to interactions with the other elements to find appropriate company data
• FastAPI - used to create the RESTful service
• Uvicorn - used to run the RESTful service
• GeoPy with ArcGIS - Enables proper address formatting and reporting of lat-long pairs for companies
• requests - direct MediaWiki/Wikidata HTTP calls power the default Wikipedia backend (lib/wikipedia_v2.py) as of V3.3.0
• wptools - powers the legacy /v1/ Wikipedia backend only, kept for reference/rollback; no longer used by the default endpoints