commoner-probe 0.6.1

Sousveillance infrastructure for state mandatory-disclosure portals — parliamentary questions, committee reports, budget data, and state assembly records.

commoner-probe

Sousveillance infrastructure for the state's mandatory disclosure systems.

A commoner probes the state's own paperwork — parliamentary questions, committee reports, state assembly records — and turns it into evidence. commoner-probe automates the acquisition so you can focus on the analysis.

pip install "commoner-probe[all]"
import commoner_probe as probe   # alias used throughout CommonerLLP toolchain

---

Why this exists

Parliamentary questions, committee reports, floor debates, bills, state assembly records, CSR exports, public mining-district disclosures, Union Budget files, and faculty-recruitment ads from public universities are mandatory or official public disclosures. The data exists. The problem is that it lives across undocumented portals with inconsistent APIs, no bulk export, and PDFs that require extraction to read programmatically.

commoner-probe handles the entire acquisition pipeline:

public disclosure portals  →  manifest.jsonl  →  files/PDFs  →  extracted records  →  your analysis
                               (metadata)        (raw source)      (structured text)

Classification, topic modelling, and dossier generation are intentionally out of scope. This library does one thing: acquire public disclosure data into provenance-rich, schema-validated JSONL and source files.

---

Install

pip install "commoner-probe[all]"          # requests + PDF extraction
pip install "commoner-probe[all,dev]"      # + schema validation and tests

---

Five-minute quickstart

Step 1 — Write a topic profile

{
  "name": "climate",
  "description": "Climate change and environmental policy",
  "search_groups": {
    "climate": ["climate change", "global warming", "net zero"],
    "air_quality": ["air pollution", "AQI", "particulate matter"]
  },
  "lok_sabha_ministries": ["ENVIRONMENT", "POWER", "PETROLEUM"],
  "rajya_sabha_ministry_likes": ["ENVIRONMENT", "POWER", "PETROLEUM"]
}

Step 2 — Probe parliamentary questions

commoner-probe sansad \
  --topic topic.json \
  --out data/climate \
  --house both \
  --from-date 2019-01-01

Writes data/climate/manifest.jsonl — one record per question from both houses.

Step 3 — Probe committee reports

commoner-probe committees \
  --topic topic.json \
  --out data/climate-committees \
  --house both

One record per standing committee report (LS and RS DRSCs).

Step 4 — Extract text from PDFs

commoner-probe extract-answers --out data/climate
commoner-probe extract-answers --out data/climate-committees

Parses downloaded PDFs into answers.jsonl: Q/A pairs, committee recommendations, and government responses.

Step 5 — Load in Python

import commoner_probe as probe

c = probe.Corpus("data/climate")

for r in c.manifest_qa():
    print(r.date, r.house, r.ministry, r.title)

for pair in c.join_qa():
    if pair.answers:
        print(pair.manifest.title)
        print(pair.answers[0].question_text[:200])

---

What you can study

Parliamentary questions (Lok Sabha + Rajya Sabha)

Each record carries who asked (MP name, party, state), which ministry answered, question number, type (starred / unstarred), date, session, and the full PDF. After extract-answers — extracted question and answer text.

Typical research questions: ministry responsiveness rates, which MPs ask the most questions by topic, how the same policy question evolves across sessions, party-level questioning patterns.

import commoner_probe as probe
from collections import Counter

c = probe.Corpus("data/climate")
ministry_counts = Counter(r.ministry for r in c.manifest_qa())
for ministry, n in ministry_counts.most_common(10):
    print(f"{ministry}: {n}")

Standing committee reports (LS + RS DRSCs)

Committee reports come in four shapes:

report_type	What it is
demands_for_grants	Annual budget scrutiny — the committee dissects ministry spending
bill	The committee's examination of a pending bill before it passes
subject	Own-initiative policy investigation — deepest substantive record
action_taken	The government's formal response to the committee's recommendations

Action Taken Reports (ATRs) are the government's formal written responses to committee recommendations. The atr-linkage command connects each ATR back to the original report, enabling lifecycle analysis: recommendation → government rejection/acceptance → follow-up.

import commoner_probe as probe

c = probe.Corpus("data/climate-committees")

for chain in c.join_atr_chain():
    print(f"Report: {chain.original and chain.original.title}")
    print(f"  Recommendations: {len(chain.original_observations)}")
    print(f"  Government responses: {len(chain.atr_answers)}")

Floor debates (Lok Sabha)

debates acquires the Lok Sabha "text of debate" record: one PDF transcript per sitting day. It enumerates sitting dates per Lok Sabha / session, then fetches each day's transcript (optionally downloading the PDF with a SHA-256). It is a day-by-day document acquisition — verbatim text and per-speaker segmentation are left to a downstream extraction step. The richest longitudinal record of what is said on the floor.

commoner-probe debates \
  --out data/debates \
  --loksabhas 18 \
  --download

Bills and legislation

bills fetches the sansad.in legislation catalog — every bill with its introduction date, stage dates, and status — deduplicated by a stable key (no topic profile needed; the bill list is an exhaustive catalog). Enables tracking legislative velocity, committee-scrutiny rates, and private-member-bill outcomes.

commoner-probe bills \
  --out data/bills \
  --house both \
  --bill-type "Private Member"

State assembly records (NeVA portals)

From 2020, sub-national governments have been adopting NIC's NeVA (National e-Vidhan Application) infrastructure under a centrally sponsored scheme run by the Ministry of Parliamentary Affairs. Most state assemblies are onboarding, though coverage varies. The state-assembly command probes any NeVA portal:

commoner-probe state-assembly \
  --portal gujarat \
  --state GJ \
  --out data/gujarat-assembly \
  --assemblies 15

MCA CSR company-spend exports

The Ministry of Corporate Affairs CDM CSR data page exposes downloadable CSV exports by financial year. These records compare reporting/spending companies and project-sector amounts. They do not identify CSR consultants or implementing agencies unless MCA publishes that in the source export.

commoner-probe mca-csr \
  --out data/mca-csr \
  --years 2022-23,2021-22

import commoner_probe as probe

c = probe.Corpus("data/mca-csr")
for r in c.manifest_mca_csr():
    print(r.financial_year, r.status, r.filename)

Mines DMFT / PMKKKY disclosures

mines-dmft acquires raw Ministry of Mines and Odisha DMFT public disclosure files. Ministry CSVs are current cumulative snapshots timestamped by the source; treat them as snapshots, not fiscal-year series.

commoner-probe mines-dmft \
  --out data/mines-dmft \
  --sources mines-gov-in,odisha

Pair the executive disclosure snapshots with Sansad oversight records without flattening the source families:

commoner-probe evidence dmft \
  --mines-dmft-dir data/mines-dmft \
  --sansad-dir data/sansad/mines-dmft-pmkkky \
  --out data/evidence/dmft.json

Union Budget & RBI State-Finances

budget acquires fiscal source files: Union Budget SBE (Statement of Budget Estimates) spreadsheets — a static table of per-fiscal-year URL templates expanded across the requested demand numbers — and RBI State-Finances documents discovered from the RBI publication page. Each file is downloaded with existence-skip and a SHA-256, one budget_source_file record per file. Acquisition only: the spreadsheet→rows parsing stays downstream (it needs pandas).

commoner-probe budget \
  --out data/budget \
  --sources union-budget,rbi-state-finances \
  --demands 101,1,33

Academic faculty-recruitment ads

academic-jobs crawls Indian higher-education-institution (HEI) career pages for faculty-recruitment advertisements, driven by a bundled institution registry. Each ad becomes one academic_job_posting record; fetch/parse failures and empty-result cases are recorded so coverage gaps are visible rather than silent. (Migrated from the academiaindia project.)

commoner-probe academic-jobs \
  --out data/academic-jobs \
  --institutions iit-kharagpur,iit-bombay

---

All commands

commoner-probe sansad — parliamentary questions

commoner-probe sansad \
  --topic topic.json \
  --out data/climate \
  --house both \
  --from-date 2019-01-01 \
  --to-date 2026-01-01

Flag	Default	What it does
--topic	required	Path to topic profile JSON
--out	required	Output corpus directory
--house	both	ls, rs, or both
--from-date	—	Earliest question date (YYYY-MM-DD)
--to-date	—	Latest question date
--qtype	both	starred, unstarred, or both
--sessions	1-267	Rajya Sabha session range
--no-download	off	Skip PDF downloads; metadata only
--with-entities	off	Resolve asker names to stable entity IDs
--max-records N	—	Stop after N new records per house (smoke-test)
--max-buckets N	—	Only run the first N search/ministry combos
--reset	off	Wipe existing manifest and start fresh

commoner-probe committees — standing committee reports

commoner-probe committees \
  --topic topic.json \
  --out data/committees \
  --house both \
  --committees finance,education

Flag	Default	What it does
--committees	all	Comma-separated committee slugs
--lok-sabha-no	18	LS number for LS reports
--from-date / --to-date	—	Date range filter
--no-download	off	Skip PDF downloads

Available LS committees (16 DRSCs): agriculture, chemicals, coal, communications, consumer_affairs, defence, energy, external_affairs, finance, housing, labour, petroleum, railways, rural_development, social_justice, water_resources

Available RS committees (8 DRSCs): commerce, education, health, home_affairs, industry, personnel, science, transport

commoner-probe extract-answers — PDF text extraction

commoner-probe extract-answers --out data/climate
commoner-probe extract-answers --out data/climate --refresh

Reads manifest.jsonl and downloaded PDFs; writes answers.jsonl with:

• qa_response — (question_text, answer_text) pairs from Q/A PDFs
• atr_response — (recommendation_no, recommendation_text, response_text) triples from ATR PDFs
• dfg_recommendation — numbered observation paragraphs from DFG/Bill/Subject PDFs

Requires pip install "commoner-probe[pdf]".

commoner-probe atr-linkage — ATR → original report

commoner-probe atr-linkage --out data/committees

Writes atr_linkage.jsonl — each ATR linked back to the report it responds to. Safe to re-run (idempotent overwrite).

commoner-probe state-assembly — state legislature records

commoner-probe state-assembly \
  --portal gujarat \
  --state GJ \
  --out data/gujarat \
  --assemblies 15

commoner-probe mca-csr — MCA CSR company-spend exports

commoner-probe mca-csr \
  --out data/mca-csr \
  --years 2022-23

Downloads CSV exports from the MCA CDM CSR data page and writes one manifest.jsonl record per financial year. Use --dry-run to print manifest records without opening a network session.

commoner-probe mines-dmft — Ministry of Mines / DMFT files

commoner-probe mines-dmft \
  --out data/mines-dmft \
  --sources mines-gov-in,odisha

Downloads raw Ministry of Mines static CSV snapshots and Odisha DMFT public JSON/report surfaces. Use --dry-run to print manifest records without opening network sessions.

commoner-probe bills — bills & legislation catalog

commoner-probe bills \
  --out data/bills \
  --house both

Flag	Default	What it does
--out	required	Output corpus directory
--house	both	ls, rs, or both (the endpoint lives under api_rs for both)
--bill-type	all types	Filter by bill type, e.g. Government or Private Member
--max-records	—	Stop after N new records per house (smoke-test brake)
--dry-run	off	Emit one planning record per house without fetching

commoner-probe debates — Lok Sabha floor-debate transcripts

commoner-probe debates \
  --out data/debates \
  --loksabhas 18 \
  --download

Flag	Default	What it does
--out	required	Output corpus directory
--loksabhas	18	Comma-separated Lok Sabha numbers, e.g. 17,18
--sessions	all	Comma-separated session numbers to limit to
--from-date / --to-date	—	ISO date bounds (YYYY-MM-DD)
--max-records	—	Stop after N new records per Lok Sabha
--download	off	Download each day's transcript PDF (+ sha256)
--dry-run	off	List candidate sitting dates without fetching PDFs

commoner-probe budget — Union Budget & RBI State-Finances files

commoner-probe budget \
  --out data/budget \
  --sources union-budget \
  --demands 101

Flag	Default	What it does
--out	required	Output directory
--sources	union-budget	Comma-separated: union-budget, rbi-state-finances
--demands	101	Comma-separated Union Budget demand numbers, e.g. 101,1,33
--rbi-url	RBI default	RBI State-Finances publication page to discover documents from
--dry-run	off	Print manifest records without writing (offline for union-budget)

commoner-probe academic-jobs — HEI faculty-recruitment ads

commoner-probe academic-jobs \
  --out data/academic-jobs \
  --institutions iit-kharagpur

Flag	Default	What it does
--out	required	Output directory
--institutions	all in registry	Comma-separated institution ids (e.g. iit-kharagpur)
--registry	bundled	Path to an alternative institutions_registry.json
--no-download	off	Skip PDF download + text extraction (listing-page heuristics only)
--dry-run	off	List which institutions would be probed without fetching

commoner-probe evidence dmft — cross-source evidence bundle

commoner-probe evidence dmft \
  --mines-dmft-dir data/mines-dmft \
  --sansad-dir data/sansad/mines-dmft-pmkkky \
  --out data/evidence/dmft.json

Builds a JSON bundle with separate executive_disclosure and parliamentary_oversight sections. It does not merge unlike source families into one table.

commoner-probe stats — corpus health

commoner-probe stats --out data/climate
commoner-probe stats --out data/climate --json

commoner-probe validate — schema validation

commoner-probe validate --out data/climate

Validates every JSONL file against its JSON Schema. Exits 1 on errors. Requires [dev] extra.

---

Topic profile

Controls what the probe acquires:

{
  "name": "libraries",
  "description": "Public library infrastructure and policy",
  "search_groups": {
    "public_libraries": ["public library", "rural library"],
    "policy": ["National Mission on Libraries", "RRRLF"]
  },
  "lok_sabha_ministries": ["CULTURE", "EDUCATION"],
  "rajya_sabha_ministry_likes": ["CULTURE", "EDUCATION"]
}

• search_groups — keyword groups for LS full-text search. Each query runs independently; results are union-deduped on key.
• lok_sabha_ministries — exact ministry filter for LS (case-sensitive).
• rajya_sabha_ministry_likes — ministry LIKE filter for RS (prefix match).

See examples/topics/ for working examples.

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Output files

File	Contents
manifest.jsonl	One record per question or committee report
_runs.jsonl	Audit log: scope, topic hash, errors, per-bucket counts
answers.jsonl	Extracted Q/A and recommendation/response pairs
atr_linkage.jsonl	ATR → original report linkages
source CSV/JSON/HTML files	Raw source files for source-specific probes such as MCA CSR and DMFT
pdfs/ls/	Downloaded LS PDFs
pdfs/rs/	Downloaded RS PDFs
probe.log	Human-readable probe progress log

For complete field-level documentation see docs/SCHEMAS.md.

---

Entity resolution (--with-entities)

Pass --with-entities to commoner-probe sansad to resolve asker names to stable entity_id values. On first run the entity store is populated from the sansad.in MP roster; subsequent runs reuse the local cache.

Resolved entity IDs join across corpora and sessions — useful for studying the same MP's questioning behaviour over time or across houses.

---

Python API

import commoner_probe as probe

c = probe.Corpus("data/climate")

# Typed iterators
for r in c.manifest_qa():                 # ManifestQaRecord
    ...
for r in c.manifest_committee_reports():  # ManifestCommitteeReportRecord
    ...
for r in c.answers_qa():                  # AnswerQaResponse
    ...
for r in c.answers_atr():                 # AnswerAtrResponse
    ...
for r in c.answers_dfg():                 # AnswerDfgRecommendation
    ...
for r in c.atr_linkages():                # AtrLinkageRecord
    ...
for r in c.manifest_mca_csr():            # ManifestMcaCsrRecord
    ...
for r in c.manifest_mines_dmft():         # ManifestMinesDmftRecord
    ...
for r in c.runs():                        # RunRecord
    ...

# Join helpers
for pair in c.join_qa():                  # manifest + extracted answers
    ...
for chain in c.join_atr_chain():          # ATR + original report + observations
    ...

# pandas (pip install commoner-probe[pandas])
df = c.to_dataframe("manifest_committee_reports")

See examples/usage.py for a runnable walkthrough. See docs/ENDPOINTS.md for source-family endpoint notes.

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License

MIT License — see LICENSE.

commoner-probe is sousveillance infrastructure, built for the commons. It is released under the permissive MIT license so it can serve as a shared acquisition floor that any downstream project — including the other repos in the CommonerLLP federation, whatever their own licenses — can build on without copyleft friction.

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Upcoming

MP profiles and career timelines

Structured biographical data for each member: constituency, state, party, terms served, educational background, declared profession. Pairs with the Q/A corpus for studies of how MP background predicts parliamentary participation.