Wrds Download

WRDS Data Download (Python)

You help users download data from the Wharton Research Data Services (WRDS) PostgreSQL database using the wrds-dl Python CLI tool (via uv).

Prerequisites

The user must have:

• uv installed (https://docs.astral.sh/uv/)
• WRDS credentials configured via one of:
• Environment variables: PGUSER and PGPASSWORD
• Saved credentials at ~/.config/wrds-dl/credentials
• Standard ~/.pgpass file

Run the CLI with uv run wrds-dl from the python/ directory of the wrds-download repo, or wrds-dl if installed via uv tool install.

If wrds-dl is not found and uv is available, install it:

uv tool install wrds-dl --from /path/to/wrds-download/python

Workflow

Follow these steps for every download request:

Step 1: Identify the table

Parse the user's request to determine the WRDS schema and table. Common mappings:

| Dataset | Schema | Key Tables | |---------|--------|------------| | CRSP daily stock | crsp | dsf (daily), msf (monthly), dsi (index) | | CRSP events | crsp | dsedelist, stocknames | | Compustat annual | comp | funda | | Compustat quarterly | comp | fundq | | Compustat global | comp_global_daily | g_funda, g_fundq | | IBES | ibes | statsum_epsus, actu_epsus | | OptionMetrics | optionm | opprcd (prices), secprd (security) | | TAQ | taqmsec | ctm_YYYYMMDD | | CRSP/Compustat merged | crsp | ccmxpf_linktable | | BoardEx | boardex | na_wrds_company_profile | | Institutional (13F) | tfn | s34 | | Audit Analytics | audit | auditnonreli | | Ravenpack | ravenpack | rpa_djnw | | Bank Regulatory | bank | call_schedule_rc, bhck |

If unsure which table, ask the user or use wrds-dl info to explore.

Step 2: Inspect the table

Always run wrds-dl info first to understand the table structure:

wrds-dl info --schema  --table 

Use the output to:

• Confirm the table exists and has the expected columns
• Note column names for the user's requested variables
• Check the estimated row count to warn about large downloads

For JSON output (useful for parsing): wrds-dl info --schema --table --json

Step 3: Dry run

For tables with more than 1 million estimated rows, or when a WHERE clause is involved, always do a dry run first:

wrds-dl download --schema  --table  \
  --columns "" --where "" --dry-run

Show the user the row count and sample rows. Ask for confirmation before proceeding if the row count is very large (>10M rows).

Step 4: Download

Build and run the download command:

wrds-dl download \
  --schema  \
  --table  \
  --columns "" \
  --where "" \
  --out  \
  --format 

Defaults and conventions

• Format: Use Parquet unless the user asks for CSV. Parquet is smaller and faster.
• Output path: Name the file descriptively, e.g., crsp_dsf_2020.parquet or comp_funda_2010_2023.parquet.
• Columns: Select only the columns the user needs. Don't use * on wide tables — ask what variables they need.
• Limit: Use --limit for testing. Suggest --limit 1000 if the user is exploring.

Common filters

• Date ranges: `--where "date >= '2020-01-01' AND date = 2010 AND fyear

## Error handling

- **Authentication errors**: Remind the user to set `PGUSER`/`PGPASSWORD` or configure `~/.config/wrds-dl/credentials`.
- **Table not found**: Use `wrds-dl info` to check schema/table names. WRDS schemas and table names are lowercase.
- **Timeout on large tables**: Suggest adding a `--where` filter or `--limit` to reduce the result set.
- **Duo 2FA prompt**: The connection triggers a Duo push. Tell the user to approve it on their phone.

## Example interactions

**User**: "Download CRSP daily stock data for 2020"
-> `wrds-dl info --schema crsp --table dsf`
-> `wrds-dl download --schema crsp --table dsf --where "date >= '2020-01-01' AND date  `wrds-dl info --schema comp --table funda`
-> `wrds-dl download --schema comp --table funda --columns "gvkey,datadate,sale" --out comp_funda.parquet`

**User**: "I need IBES analyst estimates"
-> `wrds-dl info --schema ibes --table statsum_epsus`
-> Ask what date range and variables they need, then download.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [LouLouLibs](https://github.com/LouLouLibs)
- **Source:** [LouLouLibs/claude-skills](https://github.com/LouLouLibs/claude-skills)
- **License:** MIT

Install and usage instructions live in the source repository linked above.