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dewey

Data & analytics

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Updated 10-15 21:37

About this skill

What this skill carries — grep references/ for any subject the names below miss: !d=${CLAUDE_SKILL_DIR}; command -v skill-toc >/dev/null 2>&1 && exec skill-toc "$d"; s=$HOME/.claude/skills/plugin-utils/bin/skill-toc; [ -x "$s" ] && exec "$s" "$d"; echo "(skill-toc unavailable: references and scripts are NOT listed here — install the plugin-utils plugin, or start a new session so its bin/ reaches PATH)"

Contents

  • What Dewey Is
  • Credential Enforcement
  • Download Enforcement
  • Access Method Decision Table
  • Authentication
  • Quick Reference: Featured Datasets
  • SafeGraph Global Places Quick Reference
  • Additional Resources

What Dewey Is

Dewey Data is an academic data marketplace — one institutional Platform Subscription unlocks a catalog of ~300 datasets from ~40 providers (foot traffic, POI, mobility, consumer transactions, real estate, labor). UVA Library and NYU both hold the institutional subscription; SafeGraph and most providers are free under it.

Dewey is not a SQL warehouse like WRDS. Data is delivered as partitioned Parquet/CSV.gz files downloaded via an API key. You discover datasets, read metadata, sample, filter (by date partition + columns), then download. Think "S3 of presigned Parquet links," not "PostgreSQL."

WRDS Dewey
Data Finance/accounting POI, foot traffic, mobility, consumer, real estate
Access PostgreSQL / SAS on the grid File download (Parquet/CSV.gz) via API key
Query engine server-side SQL DuckDB over the files (local or remote presigned URLs)
Licensing per-vendor, negotiated one platform subscription unlocks the catalog
AI access none MCP server (api.deweydata.io/mcp)

Credential Enforcement

IRON LAW: NEVER GUESS, INVENT, OR HARDCODE THE API KEY

  • ALWAYS ask the user for the key before any real data pull. No exceptions.
  • NEVER write a placeholder like apikey = "your_api_key" and run it — it will 401 and waste a round trip. Read from DEWEY_API_KEY env var or a gitignored file (~/.config/dewey/apikey).
  • NEVER commit the key, echo it back, or paste it into a script that gets committed.

Guessing or hardcoding the key is NOT HELPFUL — every call 401s, and a committed key is a security incident the user must rotate.

Each product (dataset) has its own product path / project ID (prj_…), obtained from the dataset page: Get Data → (Skip filtering) → Connect to API / Bulk API → API URL. One API key, many product paths. If you don't have the product path, discover it via the MCP server (search_datasets) rather than guessing.

Download Enforcement

IRON LAW: NO BULK DOWNLOAD WITHOUT METADATA + SAMPLE + FILTER FIRST

Before downloading ANY Dewey dataset, you MUST:

  1. IDENTIFY the product path and what partitions/columns you actually need
  2. META — call get_meta (deweydatapy) / get_download_info (MCP) to learn partition columns, date range, file count, total size
  3. SAMPLE — pull 100 rows (read_sample / MCP sample_dataset) and INSPECT the schema before committing to a full pull
  4. FILTER — restrict by date partition (partition_key_after/before) AND columns; for selective pulls use DuckDB COPY TO over the presigned URLs, never download the whole catalog
  5. DOWNLOAD the filtered subset, then verify row counts / NULLs / date range on disk

This is not negotiable. Skipping the sample-and-filter step is NOT HELPFUL — Dewey datasets are routinely hundreds of GB to multiple TB; an unfiltered pull burns hours of bandwidth and disk for data you'll immediately throw away.

Dewey Facts

  • SafeGraph Patterns is multi-TB; "download everything and filter in pandas" fills the disk before the filter ever runs — counterproductive on its own terms. Use DuckDB COPY TO with a WHERE clause on the remote parquet to pull only the rows/columns you need.
  • Column names differ by provider and release (naics_code vs NAICS_CODE; opened_on may not exist at all). A full pull against guessed columns is the exact incompetence the sample step exists to prevent — read_sample(nrows=100) BEFORE the full pull.
  • Most datasets are date-partitioned weekly; "all of it" means every weekly file ever shipped. Set partition_key_after/before to the study window.
  • Presigned links expire in 24h (download_files0). For large multi-day pulls use download_files1 (page-by-page, refreshes links) — a long job on download_files0 dies mid-pull.
  • A wrong prj_ product path 404s or returns someone else's data. Get the path from Connect to API or MCP search_datasets; hardcoding a guessed path is an unverified claim presented as fact.
  • Use deweypy.get_dataset_files, not deweydatapy.get_meta/get_file_list — the latter's external-api/v3 endpoint is dead (returns non-JSON / 500 → JSONDecodeError), confirmed 2026-06-10. See references/deweypy-client.md.
  • The download service throws transient HTTP 500s on individual presigned URLs, and one bad file aborts a whole-batch DuckDB COPY read_csv([...]). For filtered pulls: chunk (~20 files), retry per chunk re-minting fresh URLs, fall back to per-file skip; restartable via per-chunk parquet. Set SET http_timeout=120000; SET http_retries=3;. Worked example in references/deweypy-client.md.
  • Some providers gate access behind extra terms (e.g. ConsumerEdge): the web "Get Data" flow shows an "I acknowledge…additional terms" modal you must accept once before the dataset is usable / its prj_ path mints. Don't auto-accept a provider license without the user's OK.
  • MCP tools load only at session start. After claude mcp add … dewey-prod, the search_datasets/sample_dataset/etc. tools are NOT available in the current session — start a new session to use them.

Red Flags — STOP Immediately If You're About To:

  • Call download_files* without first calling get_meta + read_sample → STOP. Meta + sample first.
  • Download a dataset with no start_date/end_date / partition filter → STOP. Scope the date range.
  • Load a whole remote dataset into a DataFrame → STOP. Use DuckDB COPY TO … (FORMAT PARQUET, PARTITION_BY …) to persist a filtered subset to disk.
  • Run a pull with apikey="your_api_key" or any guessed key → STOP. Ask the user; read from env/file.
  • Write the API key into a script you'll commit → STOP. Env var or gitignored file only.

Access Method Decision Table

Need Method Reference
Discover/search datasets, check schema, sample — from inside Claude MCP server (api.deweydata.io/mcp) references/mcp.md
Scripted Python bulk download deweypy (recommended) or deweydatapy (legacy, product_path API) references/deweypy-client.md
Selective pull — specific columns/rows from huge datasets DuckDB over presigned URLs (read_parquet($urls) + COPY TO) references/duckdb.md
R workflow deweyr (download_dewey()) references/deweypy-client.md
One-off, dataset < 2.0 GB UI CSV download (platform → project) references/access-options.md
Analyze data already on disk DuckDB / pandas / polars over *.parquet or *.csv.gz references/access-options.md

Authentication

Get the key once from app.deweydata.io → Connections → Add Connection → API Key. Store it out of source control:

mkdir -p ~/.config/dewey && echo 'YOUR_KEY' > ~/.config/dewey/apikey && chmod 600 ~/.config/dewey/apikey
# or: export DEWEY_API_KEY=...   (add to .envrc, which should be gitignored)

import os, pathlib
apikey = os.environ.get("DEWEY_API_KEY") or pathlib.Path("~/.config/dewey/apikey").expanduser().read_text().strip()

Institutional login (to browse the catalog / create the key) is via UVA NetBadge (use your UVA email) or NYU SSO. The Platform Subscription is what makes SafeGraph etc. free — see references/datasets.md.

Quick Reference: Featured Datasets

Provider Dataset(s) What it is
SafeGraph Global Places (POI), Geometry, Spend, Patterns POI master, building footprints, card spend, foot-traffic visit patterns
Advan Research Monthly/Weekly Patterns, Home Panel Foot traffic aggregated to place & census-block
dataplor POI Global POI, strong emerging-markets coverage
Veraset Movement Device-level mobility (institutional license only)
PassBy Foot Traffic Per-POI foot-traffic analytics
Consumer Edge / PDI Spend / transactions Card & product-level purchasing
GovFiles US Business Entity All 50 Secretary of State registries — 84.4M entities incl. dissolved (OpenCorporates alternative)
Exchange Data International Global Equity Corporate Actions (WCA/RCAN) Dividends, splits, mergers, tenders — 2001→, global, w/ CUSIP/SEDOL/ISIN/FIGI bridges
LinkUp Job postings Labor-market activity, scraped from employer career sites (2007→)
ATTOM / Dwellsy / RentHub Real estate Property records, rentals

Full catalog (all ~250 datasets): references/catalog.md — every dataset grouped by category with time coverage, row count, size, and download access (machine-readable: references/catalog.csv). Featured-dataset detail + discovery workflow: references/datasets.md.

SafeGraph Global Places Quick Reference

Core POI schema — columns are UPPERCASE, NAICS_CODE is a string, BRANDS is a JSON-array string (extract with json_extract_string(BRANDS,'$[0].safegraph_brand_name')). Always sample before filtering.

Column Meaning
PLACEKEY Stable unique POI id (join key across SafeGraph products)
LOCATION_NAME POI name
BRANDS JSON array: [{"safegraph_brand_name":"…"}] — not plain text
STREET_ADDRESS,CITY,REGION,POSTAL_CODE,ISO_COUNTRY_CODE Address (REGION=US state)
LATITUDE,LONGITUDE Coordinates
NAICS_CODE,NAICS_CODE_2022 6-digit NAICS (string)
TOP_CATEGORY,SUB_CATEGORY Category labels
OPENED_ON,CLOSED_ON,TRACKING_CLOSED_SINCE Open/close dates (exist but sparsely populated — NULL for BTMs)

Resolved empirically: crypto/Bitcoin ATMs do exist as standalone POIs under NAICS_CODE='522320'; all major operators are present. But OPENED_ON/CLOSED_ON are NULL for BTMs in the current release → it's a cross-section, not a time series. Full details, the 7 BTM operators, and the worked example: references/safegraph-places.md and examples/btm_safegraph_pull.py.

Additional Resources

Reference Files

  • references/access-options.md — all download methods (UI, deweypy, deweydatapy, DuckDB, MCP, R), 24h link expiry, partitioning, reading data on disk
  • references/deweypy-client.md — deweypy (modern CLI + auth/download) and deweydatapy (get_meta, get_file_list, read_sample, download_files0/1) function reference; deweyr for R
  • references/duckdb.md — selective remote-Parquet pulls, COPY TO … PARTITION_BY pattern, querying downloaded files
  • references/govfiles-business-entity.md — GovFiles US business-entity registry: all 7 table schemas w/ fill rates, the SEC CIK / LEI / FEIN bridge in Identifiers, the missing officers/parties table, the ungraphable Relationships table (1% counterparty key), FILED_ON sentinel dates, launched Jun 2026 / empty changelog — which sparse fields may backfill and which won't, worked DuckDB join
  • references/linkup-job-postings.md — LinkUp: 12 tables across 2 products (incl. Extracted Salary, Job Descriptions, Structured Fields, Remote Tag — added Jun 2026, NOT in the stale catalog.csv), join keys (COMPANY_ID/JOB_HASH/BASE_HASH/REQID), salary top-coding at 12k/1M, point-in-time ticker joins, the scrape-log structural-break trap, worked firm-quarter vacancy panel
  • references/edi-corporate-actions.md — EDI WCA/RCAN corporate actions: event grain (options=ORs, serials=ANDs), identifier hierarchy + outturn ids, generic label/value slots, future-dated rows, Notes-table coverage gap, worked dividend/CUSIP query + EVENTCD enumeration
  • references/mcp.md — Dewey MCP server URL, JSON config, the 9 tools, discovery → schema → sample workflow
  • references/datasets.md — featured-dataset catalog, UVA NetBadge / NYU institutional access, discovery workflow
  • references/catalog.md + catalog.csv — full enumerated catalog (~250 datasets / 39 partners) by category, with coverage / rows / column count / size / access
  • references/schemas.json — full column schemas for all ~250 datasets (keyed by slug → columns[] with name/type/description; 11,264 columns). Look up a dataset's columns here before pulling, instead of a live get_dataset_schema call
  • references/linkage.md — cross-dataset join-key map (placekey, ticker, cusip/cik, domain, person id, lat/long, fips, zip…) — which datasets combine and on what spine
  • references/safegraph-places.md — Global Places schema, NAICS 522320, BTM operator brands, opened_on/closed_on, the Bitcoin-ATM worked example

Example Files

  • examples/btm_safegraph_pull.py — acceptance test: filter SafeGraph Global Places to the 7 BTM operator brands + NAICS 522320, verify standalone-POI / open-close coverage, export the US subset to ~/projects/batm/