kna 0.4.1

Comprehensive CLI for the Korean National Assembly: bills, lifecycle, votes, ideal points, and bill texts

kna - Korean National Assembly CLI

Comprehensive CLI and master database for the Korean National Assembly. Integrates 8 Open Assembly API endpoints into a single queryable interface covering six assembly terms (17th-22nd, 2004-2026).

Installation

Step 1: Install the CLI

pip install kna

If you see a PATH warning like:

WARNING: The script kna is installed in '/Users/you/Library/Python/3.x/bin' which is not on PATH.

Add it to your shell:

# Find where pip installed it
python3 -c "import site; print(site.getusersitepackages().replace('lib/python/site-packages','bin'))"

# Add to PATH (adjust the path from above)
echo 'export PATH="$HOME/Library/Python/3.9/bin:$PATH"' >> ~/.zshrc
source ~/.zshrc

Or use pipx install kna which handles PATH automatically.

Step 2: Get the data

The CLI needs the parquet data files. The repository uses Git LFS for large files.

# Install Git LFS first (required, one-time)
brew install git-lfs    # macOS
# or: sudo apt install git-lfs    # Ubuntu/Debian

git lfs install         # one-time setup

# Clone with data
git clone https://github.com/kyusik-yang/kna.git
cd kna

If you already cloned without LFS, the parquet files will be tiny pointer files and kna info will fail. Fix it:

cd kna
git lfs install
git lfs pull            # downloads actual data files (~500MB)

Step 3: Point the CLI to the data

# Set the environment variable
export KBL_DATA=~/kna/data/processed

# Make it permanent
echo 'export KBL_DATA="$HOME/kna/data/processed"' >> ~/.zshrc
source ~/.zshrc

# Verify
kna info

Troubleshooting

Problem	Cause	Fix
kna: command not found	pip bin dir not in PATH	Add pip's bin directory to ~/.zshrc PATH (see Step 1)
ArrowInvalid: Parquet magic bytes not found	Git LFS not installed; parquet files are pointer files	brew install git-lfs && git lfs install && git lfs pull
Cannot find data directory	KBL_DATA not set and not running from repo root	export KBL_DATA=~/kna/data/processed
No master file for Nth assembly	Data files missing for that assembly	Check ls $KBL_DATA/master_bills_*.parquet
ERROR: requires Python >=3.9	Python too old	python3 --version - need 3.9+
ModuleNotFoundError: No module named 'kna'	Installed to wrong Python	pip3 install --user kna or use the same python3 -m pip install kna

Requirements

• Python 3.9+
• Git LFS (for data files)
• ~500MB disk space (data files)

Interactive Explorer | Uijeong Jido 의정지도 | Tutorial | PyPI

Key Statistics

Total Bills	110,778 (17-22nd, full lifecycle)
Roll Call Votes	2,425,113 member-level records
DW-NOMINATE	936 legislator-terms (20-22nd, cross-assembly aligned)
Committee Meetings	572,127 records
Members	1,933 member-terms (17-22nd, party/district/committee)
Asset Disclosures	2,928 member-year rows (19-22nd, wealth panel)
Bill Texts	60,925 propose-reason texts (20-22nd)
Date Range	2004 - 2026

CLI Usage

# Database overview
kna info

# Search bills by title
kna search "인공지능" --assembly 22 --status enacted

# Full-text search in propose-reason texts
kna text "기후변화" --assembly 22

# Bill lifecycle timeline (proposal → promulgation)
kna show 2217673

# Legislator profile with DW-NOMINATE ideal point
kna legislator 이재명 --assembly 22

# Legislative funnel
kna stats funnel --assembly 22

# Passage rate trend across assemblies
kna stats passage-rate

# Export to CSV or Parquet
kna export health.csv --assembly 22 --committee 보건복지 --status enacted

Python API

from kna.data import BillDB

db = BillDB()

# Load bills (with column pruning)
bills = db.bills(assembly=22, columns=["bill_id", "bill_nm", "status", "ppsl_dt"])

# Ideal points (sign-flipped: negative = liberal, positive = conservative)
ip = db.ideal_points()

# Roll call votes
votes = db.roll_calls(assembly=22)

# Bill texts
texts = db.bill_texts()

# Member metadata (party, district, committee, gender)
members = db.members(assembly=22)  # 306 members

# Asset disclosures (net_worth, real estate, stocks, etc. in 천원)
assets = db.assets(assembly=22)  # member-year wealth panel

# Committee meetings
meetings = db.committee_meetings(assembly=22)

R

library(arrow)
library(dplyr)

master <- read_parquet("data/processed/master_bills_22.parquet")
laws <- master %>% filter(bill_kind == "법률안")

laws %>%
  group_by(ppsr_kind) %>%
  summarise(total = n(), enacted = sum(enacted)) %>%
  mutate(rate = enacted / total * 100)

Per-Assembly Breakdown

Assembly	Bills	Enacted	Rate	Committee Mtgs
17th (2004-08)	8,369	2,547	30.4%	20,044
18th (2008-12)	14,762	2,930	19.8%	57,003
19th (2012-16)	18,735	3,414	18.2%	78,115
20th (2016-20)	24,996	3,794	15.2%	107,933
21st (2020-24)	26,711	3,554	13.3%	200,283
22nd (2024-)	17,205	1,399	8.1%	108,749

Data Structure

master_bills (1 row = 1 bill, 49-55 columns)
├── Identifiers: bill_id, bill_no, age, bill_kind, bill_nm
├── Proposer: ppsr_kind, rst_proposer, rst_mona_cd, publ_mona_cd
├── Lifecycle: ppsl_dt → committee_dt → cmt_proc_dt → law_proc_dt → rgs_rsln_dt → prom_dt
├── Results: status, passed, enacted, proc_rslt
├── Votes: vote_yes, vote_no, vote_abstain
└── Derived: days_to_proc, days_to_committee

roll_calls_all (2.4M rows, member-level)
└── term, member_name, member_id, party, vote, bill_id, date

dw_ideal_points_20_22 (936 rows)
└── member_id, member_name, term, party, aligned, party_bloc

members_{age} (1,933 member-terms across 17-22nd)
└── mona_cd, member_name, party, district, committee, sex, birth_date, election_type, reelection

assets_wealth_panel (2,928 member-year rows, 19-22nd)
└── mona_cd, wealth_year, assembly, net_worth, total_realestate, total_stocks, total_deposits, ...

bill_texts_linked (60K rows)
└── BILL_ID, propose_reason, scrape_status

Documentation

Resource	Link
Tutorial	kyusik-yang.github.io/assembly-tutorial
Codebook	CODEBOOK.md
Data Availability	DATA_AVAILABILITY.md
Interactive Explorer	kyusik-yang.github.io/kna
Ideology Map	Uijeong Jido 의정지도

Companion Data

kna vs open-assembly-mcp: kna is an offline master database for statistical analysis in Python/R. For real-time lookups and exploratory queries via Claude, use open-assembly-mcp.

Dataset	Description
kr-hearings-data	9.9M speech-level records from 16,830 hearings (2000-2025)
open-assembly-mcp	MCP server for real-time API queries via Claude
assembly-explorer	Interactive Streamlit web app

Reproducing the Data

Data files are large and not included in the repo. To regenerate:

# Set API key (free from https://open.assembly.go.kr)
export ASSEMBLY_API_KEY=your_key

# Collect and build
python3 collect.py phase1 && python3 collect.py phase2
python3 integrate.py
python3 build_multi_assembly.py lite && python3 build_multi_assembly.py batch

# Roll call votes
python3 collect_roll_calls.py && python3 consolidate_votes.py

# Member metadata
python3 collect_members.py

# Rebuild interactive site
python3 build_site.py && python3 build_voteview.py

License

Data sourced from public government APIs. Code is MIT licensed.