pitindex 0.2.1

Point-in-time constituents of major equity indices, from free public sources.

pitindex

Point-in-time constituents of major equity indices, derived from free public sources, shipped as a small Python package.

The S&P 1500 family is supported, with per-index PIT coverage dictated by what the free sources can honestly reconstruct:

Index	Key	Coverage from
S&P 500	sp500 (default)	2005-01-03
S&P 400 MidCap	sp400	2011-11-20
S&P 600 SmallCap	sp600	2021-03-26
S&P 1500 (virtual composite)	sp1500	2021-03-26 (max of the three)

import pitindex

# Membership snapshot at a point in time:
df = pitindex.get_constituents("2020-12-22")
# -> DataFrame[ticker, name, cik, gics_sector, gics_sub_industry]

# Other indices of the family:
mid = pitindex.get_constituents("2023-06-30", index="sp400")
broad = pitindex.get_constituents("2023-06-30", index="sp1500")
# sp1500 adds an `index` column telling which sub-index each ticker is in.

# Sparse history: one snapshot per change date in [start, end]:
hist = pitindex.get_constituents_history("2020-01-01", "2020-12-31")

# Build metadata (sources, sizes, last refresh):
pitindex.info()                # sp500
pitindex.info(index="sp600")

# Refresh the local cache from upstream sources (requires the [build] extra):
pitindex.update()

Install

pip install pitindex            # runtime only
pip install "pitindex[build]"   # adds the build pipeline (used by update())

The package ships with a pre-built dataset, so the runtime has no network dependencies. pitindex.update() is an optional escape hatch for users who need data fresher than the most recent release.

API

get_constituents(as_of, index="sp500")

Returns the index membership at the end of the given date.

• as_of accepts datetime.date, datetime.datetime, or an ISO-format string "YYYY-MM-DD".
• index is one of sp500, sp400, sp600, sp1500.
• Output columns: ticker, name, cik, gics_sector, gics_sub_industry (plus index for the sp1500 composite).
• cik and the GICS columns are populated for tickers that are still index members today; for delisted constituents only what was preserved upstream is returned (typically the company name).
• Weekend / holiday dates simply return the last preceding event-driven membership state — no calendar interpolation is required.
• The as_of value is also exposed via df.attrs["as_of"].

get_constituents_history(start, end, index="sp500")

Returns one snapshot per change date in [start, end] plus a snapshot at start. The output adds an as_of column to the schema above.

This is intentionally sparse to avoid the huge cartesian product of a fully-densified daily history. To obtain a per-trading-day view, iterate get_constituents over your trading calendar.

update(force=False)

Re-runs the build pipeline against current upstream sources and writes the result into ~/.cache/pitindex/, taking precedence over the bundled data on subsequent calls. Pass force=True to bypass the 24-hour cache freshness check.

info()

Returns a dict of metadata about the loaded dataset: build timestamp, source URLs, roster sizes, reconciliation diff ratio, plus data_age_days, stale_threshold_days, and is_stale.

Staying fresh

The package ships a snapshot of the dataset built at release time. The upstream Wikipedia roster does change (a few times a year), so the library has two complementary mechanisms to keep you current:

• Weekly cron in this repo. A GitHub Actions workflow rebuilds the data every Monday morning UTC and commits any drift back to main. Releases get cut from those refreshed commits, so a normal pip install -U pitindex pulls in the latest weekly snapshot. This is free CI on public repositories.

• Runtime staleness reminder. When the loaded dataset is older than the freshness threshold (default 14 days), the first call into the library emits a pitindex.StaleDataWarning telling you to upgrade or call update(). Configure with:

  export PITINDEX_STALE_DAYS=30   # custom threshold
  export PITINDEX_STALE_DAYS=0    # opt out entirely
  

  Or programmatically:

  import warnings, pitindex
  warnings.filterwarnings("ignore", category=pitindex.StaleDataWarning)
  

Together they cover the two failure modes: the maintainer-side ("did the cron run?") and the user-side ("did the user remember to upgrade?").

How the data is built

The build pipeline (python -m scripts.build_dataset) combines free public sources, in order of trust. See DESIGN.md for the full rationale behind each choice.

S&P 500:

1. Seed snapshot dataset — the community-maintained fja05680/sp500 repository provides daily-resolution membership snapshots from 1996 through roughly 2019. We compute event diffs between consecutive snapshots to obtain the bulk of the historical event log, which is more complete than any single curated source. The seed is the primary source for everything within its coverage window.

2. Wikipedia "List of S&P 500 companies" — used for (a) the current roster (with GICS sector and CIK), and (b) the change events for the period after the seed dataset's coverage ends. Wikipedia's "Selected changes" table is not exhaustive (it omits many 2008-financial-crisis exits, for example), so we deliberately defer to the seed where they overlap.

S&P 400 / S&P 600 (no fja05680 equivalent exists):

1. Wikipedia "changes" table — the precise-dated event source, but measurably incomplete for these pages (mostly missing removals).
2. Page revision history — the seed roster comes from the oldest reliable page revision, and fill events are derived from diffs between monthly-sampled revisions (the same snapshot-diff technique, applied to Wikipedia's own history). Fill events are dated at the revision timestamp — the first date the information was demonstrably public — and carry revid provenance in their reason field. A per-index sanity band on parsed roster sizes rejects corrupt revisions (the pre-2021 S&P 600 page carried ~1000 names). The derived baseline is committed under data/{key}_revision_events.csv and only its tail is extended on weekly rebuilds.

All indices — curated overrides, two CSVs in data/ that close gaps no upstream source captures:

• data/ticker_renames.csv: index members whose ticker changed (FB → META, BBT → TFC, BK → BNY, …). The file is global: a rename is applied only in the index whose roster holds the old ticker on the rename date, and no-ops silently elsewhere.
• data/manual_events.csv: explicit added/removed events (with an index column) that correct known errors or omissions in the upstream data (e.g. the period-correct LEH ticker for Lehman Brothers, where the seed uses the post-bankruptcy notation LEHMQ throughout).

Every build runs a per-index reconciliation gate: the seed roster is walked forward through the merged event log and compared against the current Wikipedia roster. If the resulting diff exceeds 5% of the current roster, the build fails loud rather than shipping silently-corrupt data. The full reconciliation report lands in data/build_log.md.

Limitations

• Heterogeneous coverage floors. sp500 from 2005-01-03, sp400 from 2011-11-20, sp600 only from 2021-03-26 — before that date the S&P 600 Wikipedia page carried a wrong (~1000-name) roster and no free source for its membership exists. The sp1500 composite starts at the max of the floors. Pre-floor queries raise instead of extrapolating.
• Fill-event dates are upper bounds. For sp400/sp600, events recovered from revision diffs are dated at the revision timestamp (lag ≤ ~1 month vs the true effective date). Precisely-dated changes-table events are preferred wherever they exist. This is conservative in the no-look-ahead direction.
• Tickers for delisted constituents may be the upstream-encoded form. The seed dataset uses post-event tickers for some delisted companies (LEHMQ, WAMUQ, ABKFQ, …). We patch the most prominent ones via ticker_renames.csv but coverage is best-effort. PRs welcome.
• No CIK for sp400 members. The S&P 400 Wikipedia page does not publish a CIK column (the 500 and 600 pages do).
• No index weights. Weights require contemporaneous market-cap and float data that no truly-free source provides at PIT granularity. If you need weights, derive them from the constituent list plus your preferred price/shares-outstanding source.
• No corporate-action provenance. The change events carry a reason field where one was captured by the source, but the library is not a corporate-actions database.

Contributing

The most common contribution is adding a new ticker rename when an S&P 500 member changes its ticker. Append a row to data/ticker_renames.csv:

date,old_ticker,new_ticker,reason
2024-09-12,BLL,BALL,Ball Corporation ticker change.

Then re-run python -m scripts.build_dataset and commit the regenerated files in pitindex/data/. The same applies to data/manual_events.csv for genuine add/remove events that neither upstream captures.

License

MIT — see LICENSE.

The bundled data is derived from public sources: Wikipedia (CC BY-SA 4.0) and the fja05680/sp500 dataset (MIT). Factual data (membership, ticker symbols, dates) is not itself copyrightable; the curation in this repo is MIT.