fix(api): blank-name GIAS sentinel codes map to empty string, not Unknown(n) #27
@@ -78,6 +78,7 @@ OFFICIAL_SIXTH_FORM: dict[int, str] = {
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0: "Not applicable",
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1: "Has a sixth form",
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2: "Does not have a sixth form",
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9: "",
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}
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RELIGIOUS_CHARACTER: dict[int, str] = {
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@@ -128,12 +129,14 @@ RELIGIOUS_CHARACTER: dict[int, str] = {
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47: "Reformed Baptist",
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48: "Roman Catholic/Anglican",
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49: "Sunni Deobandi",
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99: "",
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}
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ADMISSIONS_POLICY: dict[int, str] = {
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0: "Not applicable",
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2: "Selective",
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4: "Non-selective",
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9: "",
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}
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@@ -81,3 +81,15 @@ def test_seed_matches_dictionaries():
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for row in csv.DictReader(fh):
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seed[row["field"]][int(row["code"])] = row["name"]
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assert seed == fields
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def test_blank_name_sentinel_codes_map_to_empty_string():
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"""GIAS carries codes whose (name) column is blank — e.g. ReligiousCharacter
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99 (~4k schools) and AdmissionsPolicy 9 (~5.6k schools). The old name
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pipeline served these as empty strings; the dictionaries must reproduce
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that ("" is falsy, so UI tag heuristics stay silent) rather than letting
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them hit the "Unknown (<code>)" path meant for genuinely new codes."""
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assert RELIGIOUS_CHARACTER[99] == ""
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assert ADMISSIONS_POLICY[9] == ""
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assert translate(99, RELIGIOUS_CHARACTER) == ""
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assert translate(9, ADMISSIONS_POLICY) == ""
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@@ -94,13 +94,23 @@ def main() -> None:
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for code_col, name_col, dict_name, field_key in FIELDS:
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pairs = (
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df[[code_col, name_col]]
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.loc[lambda d: (d[code_col] != "") & (d[name_col] != "")]
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.loc[lambda d: d[code_col] != ""]
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.drop_duplicates()
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)
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mapping = sorted((int(c), n) for c, n in pairs.itertuples(index=False))
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dupes = len(mapping) - len({c for c, _ in mapping})
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if dupes:
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sys.exit(f"{code_col}: {dupes} codes map to multiple names — investigate before generating")
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by_code: dict[int, set] = {}
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for c, n in pairs.itertuples(index=False):
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by_code.setdefault(int(c), set()).add(n)
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mapping = []
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for code, names in sorted(by_code.items()):
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named = sorted(n for n in names if n != "")
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if len(named) > 1:
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sys.exit(f"{code_col}: code {code} maps to multiple names {named} — investigate before generating")
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# Codes that only ever appear with a blank (name) are GIAS
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# "not recorded" sentinels (e.g. ReligiousCharacter 99,
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# AdmissionsPolicy 9). Map them to "" so the API serves the same
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# empty string the old name pipeline did — the "Unknown (<code>)"
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# path is reserved for genuinely new codes.
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mapping.append((code, named[0] if named else ""))
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lines = [f"{dict_name}: dict[int, str] = {{"]
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for code, name in mapping:
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escaped = name.replace('"', '\\"')
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@@ -78,6 +78,7 @@ OFFICIAL_SIXTH_FORM: dict[int, str] = {
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0: "Not applicable",
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1: "Has a sixth form",
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2: "Does not have a sixth form",
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9: "",
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}
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RELIGIOUS_CHARACTER: dict[int, str] = {
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@@ -128,12 +129,14 @@ RELIGIOUS_CHARACTER: dict[int, str] = {
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47: "Reformed Baptist",
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48: "Roman Catholic/Anglican",
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49: "Sunni Deobandi",
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99: "",
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}
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ADMISSIONS_POLICY: dict[int, str] = {
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0: "Not applicable",
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2: "Selective",
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4: "Non-selective",
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9: "",
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}
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@@ -42,12 +42,12 @@ models:
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tests:
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- accepted_values:
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severity: warn
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values: [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 26, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49]
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values: [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 26, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 99]
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- name: admissions_policy_code
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tests:
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- accepted_values:
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severity: warn
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values: [0, 2, 4]
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values: [0, 2, 4, 9]
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- name: dim_location
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description: School location dimension with PostGIS geometry
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@@ -53,6 +53,7 @@ phase_of_education,7,All-through
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official_sixth_form,0,Not applicable
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official_sixth_form,1,Has a sixth form
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official_sixth_form,2,Does not have a sixth form
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official_sixth_form,9,
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religious_character,0,Does not apply
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religious_character,2,Church of England
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religious_character,3,Roman Catholic
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@@ -100,6 +101,8 @@ religious_character,46,Protestant/Evangelical
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religious_character,47,Reformed Baptist
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religious_character,48,Roman Catholic/Anglican
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religious_character,49,Sunni Deobandi
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religious_character,99,
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admissions_policy,0,Not applicable
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admissions_policy,2,Selective
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admissions_policy,4,Non-selective
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admissions_policy,9,
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