iacore
19b62c9c87
fix translation: compassion→care, making a living→survival-level, 生生增上 life-after-life, 因病返贫 remove 'back'
128 lines
4.1 KiB
Markdown
128 lines
4.1 KiB
Markdown
# Termbase Rebuild (from absorbed termbase-management)
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How to rebuild the terms DuckDB from source spreadsheets. This is the full pipeline from the now-archived `termbase-management` skill.
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## Prerequisites
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```bash
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pip install openpyxl odfpy pyyaml duckdb
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```
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## Step 1: Inspect spreadsheet structure
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```python
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from openpyxl import load_workbook
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wb = load_workbook(path, read_only=True, data_only=True)
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for sn in wb.sheetnames:
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ws = wb[sn]
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rows = [list(r) for r in ws.iter_rows(min_row=1, max_row=6, values_only=True)]
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print(f"[{sn}] {sum(1 for _ in ws.iter_rows())} rows, cols: {len(rows[0]) if rows else 0}")
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for r in rows[:5]: print(f" {r}")
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```
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For ODS files, use odfpy:
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```python
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from odf.opendocument import load as odf_load
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from odf.table import Table, TableRow, TableCell
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from odf.text import P
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doc = odf_load(path)
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for table in doc.getElementsByType(Table):
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for row in table.getElementsByType(TableRow):
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cells = row.getElementsByType(TableCell)
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vals = []
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for cell in cells:
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text = ''
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for p in cell.getElementsByType(P):
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for node in p.childNodes:
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if node.nodeType == node.TEXT_NODE:
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text += node.data
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vals.append(text.strip() if text else None)
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```
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## Step 2: Convert to CSV + YAML
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### Cleaning
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- Strip trailing None/empty values from each row: `while row and not row[-1]: row.pop()`
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- Skip entirely empty rows
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- Pad all rows to the max column count
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### Duplicate header handling
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Some sheets have duplicate column names (e.g., two `英文` columns in paired layout). Deduplicate with suffixes:
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```python
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from collections import Counter
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def dedup_headers(headers):
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seen = Counter()
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result = []
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for h in headers:
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s = str(h) if h else ''
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if s in seen:
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seen[s] += 1
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result.append(f"{s}_{seen[s]}")
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else:
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seen[s] = 1
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result.append(s)
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return result
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```
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### Output formats
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- **CSV**: `csv.writer` — column-major, preserves all raw data
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- **YAML**: `yaml.dump(data, allow_unicode=True, default_flow_style=False, sort_keys=False, width=200)` — list of dicts
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## Step 3: Load into DuckDB
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```python
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import duckdb
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con = duckdb.connect('termlib.duckdb')
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# Simple CSVs work with auto-detect:
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con.execute("""
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CREATE TABLE table_name AS
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SELECT * FROM read_csv_auto('file.csv', header=true, all_varchar=true)
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""")
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```
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### Pitfall: Multiline CSV fields
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CSV files with embedded newlines (common in glossary example-sentence columns) break DuckDB's auto-sniffer. Fall back to Python csv.reader:
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```python
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import csv
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with open(path, 'r', encoding='utf-8') as f:
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rows = list(csv.reader(f))
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headers = rows[0]
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data = rows[1:]
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col_defs = ', '.join(f'"{h}" VARCHAR' for h in cleaned_headers)
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con.execute(f'CREATE TABLE "{table}" ({col_defs})')
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batch_size = 500
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for i in range(0, len(data), batch_size):
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batch = data[i:i+batch_size]
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placeholders = ', '.join(['(' + ', '.join(['?' for _ in headers]) + ')' for _ in batch])
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flat = [v for row in batch for v in row]
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con.execute(f'INSERT INTO "{table}" VALUES {placeholders}', flat)
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```
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### Pitfall: DuckDB CLI opens in-memory by default
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Running plain `duckdb` gives an empty database. Always pass the file path:
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```
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duckdb path/to/termlib.duckdb
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```
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## Step 4: Create unified views
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See `references/unified-view.sql` for the pattern. Key patterns:
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- `UNION ALL` across all source tables
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- Normalize column names to `zh`, `en`, `loc` (出处), `source`
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- For paired-column sheets (e.g., `中文/英文` + `补充内容/英文_1`), emit two UNION branches
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- Filter out rows where zh or en is NULL/empty
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## Pitfalls
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- **ODS reading**: Must traverse `odf.text.P` child elements, not direct text nodes
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- **Duplicate headers**: JSON/YAML dict silently overwrites duplicate keys — always deduplicate
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- **Multiline CSV + DuckDB**: `read_csv_auto` fails on CSVs with quoted newlines — use Python csv.reader
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- **DuckDB path**: Always explicit file path; `duckdb` alone is in-memory
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- **`execute_code` sandbox**: Does NOT share pip-installed packages — use `terminal` for Python scripts
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