feat: GIAS code->name dictionaries generated from live bulk CSV

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
This commit is contained in:
Tudor
2026-07-09 10:38:19 +01:00
co-authored by Claude Fable 5
parent 08bd86db05
commit e188c2ff4b
5 changed files with 626 additions and 0 deletions
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"""Generate GIAS code->name dictionaries from the live bulk CSV.
Writes:
- backend/gias_codes.py (canonical Python module)
- pipeline/scripts/gias_codes.py (byte-identical copy)
- pipeline/transform/seeds/gias_code_names.csv (dbt seed for drift test)
Run from the repo root whenever the dbt drift test warns that DfE
added/renamed a value: python pipeline/scripts/generate_gias_codes.py
"""
from __future__ import annotations
import io
import sys
from datetime import date, timedelta
from pathlib import Path
import pandas as pd
import requests
GIAS_URL = (
"https://ea-edubase-api-prod.azurewebsites.net"
"/edubase/downloads/public/edubasealldata{date}.csv"
)
# (CSV code column, CSV name column, python dict name, seed field key)
FIELDS = [
("TypeOfEstablishment (code)", "TypeOfEstablishment (name)", "SCHOOL_TYPE", "school_type"),
("EstablishmentStatus (code)", "EstablishmentStatus (name)", "ESTABLISHMENT_STATUS", "establishment_status"),
("PhaseOfEducation (code)", "PhaseOfEducation (name)", "PHASE_OF_EDUCATION", "phase_of_education"),
("OfficialSixthForm (code)", "OfficialSixthForm (name)", "OFFICIAL_SIXTH_FORM", "official_sixth_form"),
("ReligiousCharacter (code)", "ReligiousCharacter (name)", "RELIGIOUS_CHARACTER", "religious_character"),
("AdmissionsPolicy (code)", "AdmissionsPolicy (name)", "ADMISSIONS_POLICY", "admissions_policy"),
]
MODULE_HEADER = '''"""GIAS code -> name dictionaries.
GENERATED by pipeline/scripts/generate_gias_codes.py from the GIAS bulk CSV
— do not edit by hand; rerun the script when the dbt drift test warns.
The canonical file is backend/gias_codes.py; pipeline/scripts/gias_codes.py
must be byte-identical (enforced by backend/tests/test_gias_codes.py).
"""
from __future__ import annotations
import logging
import math
logger = logging.getLogger(__name__)
'''
MODULE_FOOTER = '''
def translate(code, mapping: dict[int, str]) -> str | None:
"""Translate a GIAS code to its display name.
None/NaN -> None (column absent or suppressed). Unknown codes degrade to
"Unknown (<code>)" with a warning so a new DfE value never blanks the UI.
"""
if code is None or (isinstance(code, float) and math.isnan(code)):
return None
code = int(code)
if code not in mapping:
logger.warning("Unknown GIAS code %s (not in dictionary)", code)
return f"Unknown ({code})"
return mapping[code]
'''
def download_csv() -> pd.DataFrame:
for day in (date.today(), date.today() - timedelta(days=1)):
url = GIAS_URL.format(date=day.strftime("%Y%m%d"))
print(f"Downloading {url}")
resp = requests.get(url, timeout=300)
if resp.status_code == 404:
continue
resp.raise_for_status()
return pd.read_csv(
io.StringIO(resp.content.decode("latin-1")),
dtype=str, keep_default_na=False,
)
sys.exit("GIAS CSV not available for today or yesterday")
def main() -> None:
repo = Path(__file__).resolve().parents[2]
df = download_csv()
module_parts = [MODULE_HEADER]
seed_rows: list[tuple[str, int, str]] = []
for code_col, name_col, dict_name, field_key in FIELDS:
pairs = (
df[[code_col, name_col]]
.loc[lambda d: (d[code_col] != "") & (d[name_col] != "")]
.drop_duplicates()
)
mapping = sorted((int(c), n) for c, n in pairs.itertuples(index=False))
dupes = len(mapping) - len({c for c, _ in mapping})
if dupes:
sys.exit(f"{code_col}: {dupes} codes map to multiple names — investigate before generating")
lines = [f"{dict_name}: dict[int, str] = {{"]
for code, name in mapping:
escaped = name.replace('"', '\\"')
lines.append(f' {code}: "{escaped}",')
lines.append("}\n")
module_parts.append("\n".join(lines))
seed_rows += [(field_key, code, name) for code, name in mapping]
module = "\n".join(module_parts) + MODULE_FOOTER
(repo / "backend" / "gias_codes.py").write_text(module)
(repo / "pipeline" / "scripts" / "gias_codes.py").write_text(module)
seed_path = repo / "pipeline" / "transform" / "seeds" / "gias_code_names.csv"
with open(seed_path, "w", newline="") as fh:
import csv
w = csv.writer(fh)
w.writerow(["field", "code", "name"])
w.writerows(seed_rows)
print(f"Wrote backend/gias_codes.py, pipeline/scripts/gias_codes.py, {seed_path.name}")
print("\nKey codes for the dbt work (Task 3):")
for field in ("establishment_status", "phase_of_education", "official_sixth_form"):
print(f" {field}:")
for f, code, name in seed_rows:
if f == field:
print(f" {code} = {name}")
if __name__ == "__main__":
main()
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"""GIAS code -> name dictionaries.
GENERATED by pipeline/scripts/generate_gias_codes.py from the GIAS bulk CSV
— do not edit by hand; rerun the script when the dbt drift test warns.
The canonical file is backend/gias_codes.py; pipeline/scripts/gias_codes.py
must be byte-identical (enforced by backend/tests/test_gias_codes.py).
"""
from __future__ import annotations
import logging
import math
logger = logging.getLogger(__name__)
SCHOOL_TYPE: dict[int, str] = {
1: "Community school",
2: "Voluntary aided school",
3: "Voluntary controlled school",
5: "Foundation school",
6: "City technology college",
7: "Community special school",
8: "Non-maintained special school",
10: "Other independent special school",
11: "Other independent school",
12: "Foundation special school",
14: "Pupil referral unit",
15: "Local authority nursery school",
18: "Further education",
24: "Secure units",
25: "Offshore schools",
26: "Service children's education",
27: "Miscellaneous",
28: "Academy sponsor led",
29: "Higher education institutions",
30: "Welsh establishment",
31: "Sixth form centres",
32: "Special post 16 institution",
33: "Academy special sponsor led",
34: "Academy converter",
35: "Free schools",
36: "Free schools special",
37: "British schools overseas",
38: "Free schools alternative provision",
39: "Free schools 16 to 19",
40: "University technical college",
41: "Studio schools",
42: "Academy alternative provision converter",
43: "Academy alternative provision sponsor led",
44: "Academy special converter",
45: "Academy 16-19 converter",
46: "Academy 16 to 19 sponsor led",
49: "Online provider",
56: "Institution funded by other government department",
57: "Academy secure 16 to 19",
}
ESTABLISHMENT_STATUS: dict[int, str] = {
1: "Open",
2: "Closed",
3: "Open, but proposed to close",
4: "Proposed to open",
}
PHASE_OF_EDUCATION: dict[int, str] = {
0: "Not applicable",
1: "Nursery",
2: "Primary",
3: "Middle deemed primary",
4: "Secondary",
5: "Middle deemed secondary",
6: "16 plus",
7: "All-through",
}
OFFICIAL_SIXTH_FORM: dict[int, str] = {
0: "Not applicable",
1: "Has a sixth form",
2: "Does not have a sixth form",
}
RELIGIOUS_CHARACTER: dict[int, str] = {
0: "Does not apply",
2: "Church of England",
3: "Roman Catholic",
4: "Methodist",
5: "Jewish",
6: "None",
7: "Muslim",
8: "Seventh Day Adventist",
9: "Church of England/Methodist",
10: "Methodist/Church of England",
11: "Church of England/Roman Catholic",
12: "Church of England/United Reformed Church",
13: "Roman Catholic/Church of England",
14: "Quaker",
15: "Christian",
16: "United Reformed Church",
17: "Congregational Church",
18: "Free Church",
19: "Church of England/Free Church",
20: "Church of England/Christian",
21: "Sikh",
22: "Greek Orthodox",
24: "Buddhist",
25: "Hindu",
26: "Moravian",
28: "Inter- / non- denominational",
29: "Multi-faith",
30: "Church of England/Methodist/United Reform Church/Baptist",
31: "Anglican",
32: "Anglican/Christian",
33: "Anglican/Evangelical",
34: "Anglican/Church of England",
35: "Catholic",
36: "Charadi Jewish",
37: "Christian/Evangelical",
38: "Christian Science",
39: "Christian/Methodist",
40: "Christian/non-denominational",
41: "Church of England/Evangelical",
42: "Islam",
43: "Orthodox Jewish",
44: "Plymouth Brethren Christian Church",
45: "Protestant",
46: "Protestant/Evangelical",
47: "Reformed Baptist",
48: "Roman Catholic/Anglican",
49: "Sunni Deobandi",
}
ADMISSIONS_POLICY: dict[int, str] = {
0: "Not applicable",
2: "Selective",
4: "Non-selective",
}
def translate(code, mapping: dict[int, str]) -> str | None:
"""Translate a GIAS code to its display name.
None/NaN -> None (column absent or suppressed). Unknown codes degrade to
"Unknown (<code>)" with a warning so a new DfE value never blanks the UI.
"""
if code is None or (isinstance(code, float) and math.isnan(code)):
return None
code = int(code)
if code not in mapping:
logger.warning("Unknown GIAS code %s (not in dictionary)", code)
return f"Unknown ({code})"
return mapping[code]