ae8292d68d
Seule 'Sans objet' est considérée négative parmi les marchés renseignés, cohérent avec le reste des traitements. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
181 lines
6.1 KiB
Python
181 lines
6.1 KiB
Python
import polars as pl
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def _make_lff(rows):
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return pl.LazyFrame(rows)
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def test_compute_considerations_stats_basic():
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from src.figures import compute_considerations_stats
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lff = _make_lff(
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[
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# uid u1 : social oui (Clause), env non (Sans objet)
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{
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"uid": "u1",
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"considerationsSociales": "Clause sociale",
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"considerationsEnvironnementales": "Sans objet",
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},
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# uid u2 : social non (Sans objet), env oui (Critère)
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{
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"uid": "u2",
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"considerationsSociales": "Sans objet",
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"considerationsEnvironnementales": "Critère environnemental",
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},
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# uid u3 : social oui (Marché réservé compte), env null
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{
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"uid": "u3",
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"considerationsSociales": "Marché réservé",
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"considerationsEnvironnementales": None,
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},
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# uid u4 : aucune considération
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{
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"uid": "u4",
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"considerationsSociales": "Pas de considération sociale",
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"considerationsEnvironnementales": "Sans objet",
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},
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]
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)
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stats = compute_considerations_stats(lff)
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# 4 marchés au total. Social : u1, u3 -> 2/4 = 50%. Env : u2 -> 1/4 = 25%.
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assert stats["sociales"] == (2, 50)
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assert stats["environnementales"] == (1, 25)
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# Renseignées : dénominateur = non-null ; numérateur = non-null ET != "Sans objet".
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# Social : 4 non-null, 3 != "Sans objet" (u1/u3/u4) -> (4, 75%).
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# Env : 3 non-null, 1 != "Sans objet" (u2) -> (3, 33%).
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assert stats["sociales_renseignees"] == (4, 75)
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assert stats["environnementales_renseignees"] == (3, 33)
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def test_compute_considerations_stats_dedup_per_uid():
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from src.figures import compute_considerations_stats
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lff = _make_lff(
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[
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# uid u1 présent 2 fois (2 titulaires) -> compté une seule fois
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{
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"uid": "u1",
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"considerationsSociales": "Clause sociale",
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"considerationsEnvironnementales": "Sans objet",
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},
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{
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"uid": "u1",
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"considerationsSociales": "Clause sociale",
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"considerationsEnvironnementales": "Sans objet",
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},
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{
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"uid": "u2",
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"considerationsSociales": "Sans objet",
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"considerationsEnvironnementales": "Sans objet",
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},
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]
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)
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stats = compute_considerations_stats(lff)
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# 2 marchés distincts. Social : u1 -> 1/2 = 50%.
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assert stats["sociales"] == (1, 50)
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assert stats["environnementales"] == (0, 0)
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# Social : 2 non-null, 1 positif -> (2, 50%). Env : 2 non-null, 0 positif -> (2, 0%).
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assert stats["sociales_renseignees"] == (2, 50)
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assert stats["environnementales_renseignees"] == (2, 0)
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def test_compute_considerations_stats_missing_column():
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from src.figures import compute_considerations_stats
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lff = _make_lff(
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[
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{"uid": "u1", "considerationsSociales": "Clause sociale"},
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{"uid": "u2", "considerationsSociales": "Sans objet"},
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]
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)
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stats = compute_considerations_stats(lff)
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# Colonne env absente -> (0, 0) sans exception. Social : 1/2 = 50%.
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assert stats["sociales"] == (1, 50)
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assert stats["environnementales"] == (0, 0)
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# Social : 2 non-null, 1 positif -> (2, 50%). Env absente -> (0, 0).
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assert stats["sociales_renseignees"] == (2, 50)
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assert stats["environnementales_renseignees"] == (0, 0)
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def test_compute_considerations_stats_empty():
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from src.figures import compute_considerations_stats
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lff = pl.LazyFrame(
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{
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"uid": pl.Series([], dtype=pl.String),
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"considerationsSociales": pl.Series([], dtype=pl.String),
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"considerationsEnvironnementales": pl.Series([], dtype=pl.String),
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}
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)
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stats = compute_considerations_stats(lff)
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assert stats["sociales"] == (0, 0)
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assert stats["environnementales"] == (0, 0)
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assert stats["sociales_renseignees"] == (0, 0)
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assert stats["environnementales_renseignees"] == (0, 0)
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def test_get_considerations_card_content_returns_four_progress_bars():
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import dash_bootstrap_components as dbc
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from dash import html
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from src.figures import get_considerations_card_content
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lff = pl.LazyFrame(
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[
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{
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"uid": "u1",
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"considerationsSociales": "Clause sociale",
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"considerationsEnvironnementales": "Sans objet",
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},
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{
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"uid": "u2",
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"considerationsSociales": "Sans objet",
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"considerationsEnvironnementales": "Critère environnemental",
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},
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]
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)
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div = get_considerations_card_content(lff)
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assert isinstance(div, html.Div)
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def find_progress(component, found):
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if isinstance(component, dbc.Progress):
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found.append(component)
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children = getattr(component, "children", None)
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if isinstance(children, (list, tuple)):
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for c in children:
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find_progress(c, found)
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elif children is not None and not isinstance(children, str):
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find_progress(children, found)
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return found
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all_bars = find_progress(div, [])
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inner_bars = [b for b in all_bars if getattr(b, "bar", False)]
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# 4 barres internes : 2 positives + 2 renseignées
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assert len(inner_bars) == 4
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social_pos, social_ren, env_pos, env_ren = inner_bars
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# Sociales positives : u1 -> 1/2 = 50%
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assert social_pos.value == 50
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assert social_pos.color == "#CC6677"
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assert social_pos.style["color"] == "white"
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# Sociales renseignées : 2 non-null, 1 positif (u1) -> 50%
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assert social_ren.value == 50
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assert social_ren.color == "#E5B2BB"
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# Environnementales positives : u2 -> 1/2 = 50%
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assert env_pos.value == 50
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assert env_pos.color == "#117733"
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assert env_pos.style["color"] == "white"
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# Environnementales renseignées : 2 non-null (u1 "Sans objet", u2), 1 positif (u2) -> 50%
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assert env_ren.value == 50
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assert env_ren.color == "#88BB99"
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