Add pwgen-fr entrypoint

Still problems with other forms

data/raw/.gitignore

@@ -1 +1,2 @@
 Lexique383
+Morphalou3.1_formatTEI

data/raw/README.md

@@ -0,0 +1,29 @@
+# Versions réduites de jeux de données
+
+Les fichiers dans ce dossier sont des versions réduites de jeux de données
+tiers.
+
+Veillez à respecter les licences respectives de ces ressources dans les usages
+que vous en faites.
+
+## Lexique
+
+La base de données Lexique (http://www.lexique.org/) est le travail, entre
+autres contributeurs et contributrices, de  Boris New et Christophe Pallier,
+sous licence CC BY-NC
+
+Le fichier présent ici est une version tronquée de la v3.83. Il ne conserve que
+la partie utile au présent logiciel. Le jeu de données entier est disponible
+sur leur site.
+
+## Morphalou
+
+La base de données Morphalou
+(https://www.ortolang.fr/market/lexicons/morphalou/v3.1) est le travail, entre
+autres contributeurs et contributrices, de Sandrine Ollinger, Christophe
+Benzitoun, Evelyne Jacquey, Ulrike Fleury, Etienne Petitjean et Marie
+Tonnelier. Sa version 3.1 est distribuée sous licence LGPL-LR.
+
+Le fichier présent ici est une version tronquée de la v3.1. Il ne conserve que
+la partie utile au présent logiciel. Le jeu de données entier est disponible
+sur leur site.

pwgen_fr/entrypoints.py

@@ -0,0 +1,22 @@
+import argparse
+import typing as t
+
+from . import generate
+
+
+def pwgen_fr():
+    choices_map: dict[str, t.Callable[[], str]] = {
+        "phrase4": generate.gen_phrase4,
+        "phrase6": generate.gen_phrase6,
+        "rand4": lambda: generate.gen_rand(n=4),
+        "rand6": lambda: generate.gen_rand(n=4),
+    }
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "mode", choices=choices_map.keys(), help="Select the generation procedure used"
+    )
+
+    args = parser.parse_args()
+
+    print(choices_map[args.mode]())

pwgen_fr/generate.py

@@ -1,37 +1,72 @@
 import secrets
 
-from . import lexique
+from . import word_db
 
-lex = lexique.Lexique.parse()
+wdb = word_db.WordDb.autoload()
 
 
-def gen_phrase4():
+def gen_phrase4() -> str:
-    out = []
+    """Generates a sentence with four words, of structure Adjective Noun Verb Adverb"""
-    out.append(secrets.choice(lex.most_common(lexique.CatGram.ADJECTIF)))
+    nombre = word_db.Nombre.pick()
-    out.append(secrets.choice(lex.most_common(lexique.CatGram.NOM)))
+    temps = word_db.Temps.pick()
-    out.append(secrets.choice(lex.most_common(lexique.CatGram.VERBE)))
+
-    out.append(secrets.choice(lex.most_common(lexique.CatGram.NOM)))
+    adj = secrets.choice(wdb.adjectifs)
-    return " ".join(map(lambda x: x.word, out))
+    nom = secrets.choice(wdb.noms)
+    verbe = secrets.choice(wdb.verbes)
+    adverbe = secrets.choice(wdb.adverbes)
+
+    return " ".join(
+        [
+            adj.accord(nom.genre_or_pick, nombre),
+            nom.accord(nombre),
+            verbe.accord(temps, nombre),
+            adverbe.accord(),
+        ]
+    )
 
 
-def gen_rand(n=4):
+def gen_phrase6() -> str:
+    """Generates a sentence with six words, of structure Adjective Noun Verb Adjective
+    Noun Adverb"""
+    nombres = [word_db.Nombre.pick() for _ in range(2)]
+    temps = word_db.Temps.pick()
+
+    adj0 = secrets.choice(wdb.adjectifs)
+    nom0 = secrets.choice(wdb.noms)
+    verbe = secrets.choice(wdb.verbes)
+    adj1 = secrets.choice(wdb.adjectifs)
+    nom1 = secrets.choice(wdb.noms)
+    adverbe = secrets.choice(wdb.adverbes)
+
+    return " ".join(
+        [
+            adj0.accord(nom0.genre_or_pick, nombres[0]),
+            nom0.accord(nombres[0]),
+            verbe.accord(temps, nombres[0]),
+            adj1.accord(nom1.genre_or_pick, nombres[1]),
+            nom1.accord(nombres[1]),
+            adverbe.accord(),
+        ]
+    )
+
+
+def gen_rand(n=4) -> str:
+    """Generates a fully random sequence of n words, without grammatical consistency"""
     out = []
     for _ in range(n):
-        cat = secrets.choice(
+        word_cat = secrets.choice(list(wdb.CATEGORY_TO_ATTR))
-            (
+        if word_cat == word_db.Nom:
-                lexique.CatGram.ADJECTIF,
+            nombre = word_db.Nombre.pick()
-                lexique.CatGram.NOM,
+            out.append(secrets.choice(wdb.noms).accord(nombre))
-                lexique.CatGram.VERBE,
+        elif word_cat == word_db.Adjectif:
-                lexique.CatGram.ADVERBE,
+            genre = word_db.Genre.pick()
-            )
+            nombre = word_db.Nombre.pick()
-        )
+            out.append(secrets.choice(wdb.adjectifs).accord(genre, nombre))
-        out.append(secrets.choice(lex.most_common(cat)))
+        elif word_cat == word_db.Verbe:
-    return " ".join(map(lambda x: x.word, out))
+            temps = word_db.Temps.pick()
+            nombre = word_db.Nombre.pick()
+            out.append(secrets.choice(wdb.verbes).accord(temps, nombre))
+        elif word_cat == word_db.Adverbe:
+            out.append(secrets.choice(wdb.adverbes).accord())
 
-
+    return " ".join(out)
-def gen_nom(n=4):
-    out = []
-    for _ in range(n):
-        cat = lexique.CatGram.NOM
-        out.append(secrets.choice(lex.most_common(cat)))
-    return " ".join(map(lambda x: x.word, out))

pwgen_fr/lexique.py

@@ -1,9 +1,13 @@
 import csv
+import itertools
+from dataclasses import dataclass, field
 import logging
 import subprocess
 import typing as t
+from bisect import bisect_left
 import enum
 from pathlib import Path
+from .word_db import Genre, Nombre, Temps, Nom, Adjectif, Verbe, Adverbe, WordDb
 
 logger = logging.getLogger(__name__)
 
@@ -27,13 +31,25 @@ class CatGram(enum.Enum):
         base = val.split(":", maxsplit=1)[0]
         return cls(base)
 
+    def __lt__(self, oth):
+        return self.value < oth.value
 
-class Word(t.NamedTuple):
+
-    word: str
+def match_enum_or_all(val: str, enum_mapper, enum_cls) -> list:
-    lemme: str  # canonical form
+    """The value of the enum corresponding if any; else, all terms of the enum"""
+    if val in enum_mapper:
+        return [enum_mapper[val]]
+    return list(enum_cls)
+
+
+@dataclass
+class Mot:
+    mot: str
+    lemme: str
     cat_gram: CatGram
-    freq_lem: float  # occurrences of the canonical form, in films, by million words
+    freq: float  # occurrences of the canonical form by million words
-    freq: float  # occurrences of this exact form, in films, by million words
+    variantes: dict[tuple, str] = field(default_factory=dict)
+    genre: t.Optional[Genre] = None
 
 
 class Lexique:
@@ -47,10 +63,38 @@ class Lexique:
         CatGram.ADVERBE: 10000,
     }
 
-    dataset: list[Word]
+    class Parsers:
+        """Datatables to help parse the original data"""
 
-    def __init__(self, dataset):
+        genre: dict[str, Genre] = {
+            "m": Genre.MASC,
+            "f": Genre.FEM,
+        }
+        rev_genre: dict[t.Optional[Genre], str] = {
+            None: "",
+            Genre.MASC: "m",
+            Genre.FEM: "f",
+        }
+        nombre: dict[str, Nombre] = {
+            "s": Nombre.SING,
+            "p": Nombre.PLUR,
+        }
+        verbe_temps: dict[str, Temps] = {
+            "ind:pre": Temps.PRESENT,
+            "ind:fut": Temps.FUTUR,
+            "ind:imp": Temps.IMPARFAIT,
+        }
+        verbe_personne: dict[str, Nombre] = {
+            "3s": Nombre.SING,
+            "3p": Nombre.PLUR,
+        }
+
+    dataset: list[Mot]
+    lemfreq: dict[str, float]
+
+    def __init__(self, dataset, lemfreq):
         self.dataset = dataset
+        self.lemfreq = lemfreq
 
     @classmethod
     def _ensure_uncompressed(cls):
@@ -83,32 +127,117 @@ class Lexique:
                 f"Uncompressed dataset still missing at {cls.LEXIQUE_DIR_PATH} after extraction"
             )
 
+    @classmethod
+    def _find_word_key(cls, mot: Mot):
+        return (mot.lemme, mot.cat_gram, cls.Parsers.rev_genre[mot.genre])
+
+    @classmethod
+    def _find_word(cls, dataset: list[Mot], row: dict) -> t.Optional[Mot]:
+        str_lemme = row["lemme"]
+        cat_gram = CatGram.parse(row["cgram"])
+        genre = row["genre"] if cat_gram == CatGram.NOM else ""
+        row_key = (
+            str_lemme,
+            cat_gram,
+            genre,
+        )
+        lemme_pos = bisect_left(
+            dataset,
+            row_key,
+            key=cls._find_word_key,
+        )
+        if lemme_pos >= len(dataset):
+            return None
+        out = dataset[lemme_pos]
+        if row_key != cls._find_word_key(out):
+            return None
+        return dataset[lemme_pos]
+
     @classmethod
     def parse(cls) -> "Lexique":
         out = []
+        rows = []
+        lemfreq: dict[str, float] = {}
+
         with cls.LEXIQUE_PATH.open("r") as h:
             reader = csv.DictReader(h, dialect="excel-tab")
             for row in reader:
                 if not row["cgram"]:
                     continue
-                try:
+                rows.append(row)
-                    out.append(
+
-                        Word(
+        # First pass: generate canonical forms (lemmes)
-                            word=row["ortho"],
+        for row in rows:
-                            lemme=row["lemme"],
+            cat_gram = CatGram.parse(row["cgram"])
-                            cat_gram=CatGram.parse(row["cgram"]),
+            if (row["lemme"] != row["ortho"]) and not (
-                            freq_lem=float(row["freqlemlivres"]),
+                cat_gram == CatGram.NOM and row["genre"] == "f" and row["nombre"] == "s"
-                            freq=float(row["freqlivres"]),
+            ):
-                        )
+                # Un nom singulier féminin est considéré comme forme canonique
-                    )
+                continue
-                except ValueError as exn:
+
-                    print(row)
+            genre: t.Optional[Genre] = None
-                    raise exn from exn
+            if cat_gram == CatGram.NOM:
-        return cls(out)
+                genre = cls.Parsers.genre.get(row["genre"], None)
+            out.append(
+                Mot(
+                    mot=row["ortho"],
+                    lemme=row["lemme"],
+                    cat_gram=cat_gram,
+                    freq=float(row["freqlemlivres"]),
+                    genre=genre,
+                )
+            )
+
+        out.sort(key=cls._find_word_key)  # We need to bisect on this.
+
+        # Second pass: populate variants
+        for row in rows:
+            # Populate lemfreq
+            old_freq = lemfreq.get(row["ortho"], 0.0)
+            lemfreq[row["ortho"]] = max(
+                old_freq,
+                float(row["freqlemlivres"]),
+                float(row["freqlemfilms2"]),
+            )
+
+            lemme = cls._find_word(out, row)
+            if lemme is None:
+                continue
+
+            if lemme.cat_gram == CatGram.NOM:
+                nombres = match_enum_or_all(row["nombre"], cls.Parsers.nombre, Nombre)
+                for nombre in nombres:
+                    lemme.variantes[(nombre,)] = row["ortho"]
+
+            elif lemme.cat_gram == CatGram.VERBE:
+                infover = row["infover"].split(";")
+                for raw_ver in infover:
+                    ver = raw_ver.split(":")
+
+                    temps = None
+                    personne = None
+                    temps_select = ":".join(ver[0:2])
+                    if temps_select not in Temps:
+                        continue
+                    temps = Temps(temps_select)
+                    personne = cls.Parsers.verbe_personne.get(ver[2], None)
+                    if personne is None:
+                        continue  # we're not interested in all conj. persons
+
+                    lemme.variantes[(temps, personne)] = row["ortho"]
+
+            elif lemme.cat_gram == CatGram.ADJECTIF:
+                genres = match_enum_or_all(row["genre"], cls.Parsers.genre, Genre)
+                nombres = match_enum_or_all(row["nombre"], cls.Parsers.nombre, Nombre)
+                for genre, nombre in itertools.product(genres, nombres):
+                    lemme.variantes[(genre, nombre)] = row["ortho"]
+
+            # No need to match adverbs (invariant)
+        return cls(out, lemfreq)
 
     def most_common(
         self, cat_gram: CatGram, threshold: t.Optional[int] = None
-    ) -> list[Word]:
+    ) -> list[Mot]:
         if threshold is None:
             try:
                 threshold = self.PRESET_THRESHOLD_BY_CAT[cat_gram]
@@ -120,3 +249,52 @@ class Lexique:
         out = list(filter(lambda word: word.cat_gram == cat_gram, self.dataset))
         out.sort(key=lambda word: word.freq, reverse=True)
         return out[:threshold]
+
+    def word_db(self, thresholds: t.Optional[dict[CatGram, int]] = None) -> WordDb:
+        """Convert to a WordDb"""
+        thresholds = thresholds or {}
+
+        noms = self.most_common(CatGram.NOM, thresholds.get(CatGram.NOM, None))
+        db_noms = [
+            Nom(
+                genre=t.cast(Genre, nom.genre),  # not None for noms
+                sing=nom.variantes[(Nombre.SING,)],
+                plur=nom.variantes[(Nombre.PLUR,)],
+            )
+            for nom in noms
+        ]
+
+        adjectifs = self.most_common(
+            CatGram.ADJECTIF, thresholds.get(CatGram.ADJECTIF, None)
+        )
+        db_adjectifs = [
+            Adjectif(
+                masc_sing=adj.variantes[(Genre.MASC, Nombre.SING)],
+                masc_plur=adj.variantes[(Genre.MASC, Nombre.PLUR)],
+                fem_sing=adj.variantes[(Genre.FEM, Nombre.SING)],
+                fem_plur=adj.variantes[(Genre.FEM, Nombre.PLUR)],
+            )
+            for adj in adjectifs
+        ]
+
+        verbes = self.most_common(CatGram.VERBE, thresholds.get(CatGram.VERBE, None))
+        db_verbes = [
+            Verbe(
+                present_sing=verbe.variantes[(Temps.PRESENT, Nombre.SING)],
+                present_plur=verbe.variantes[(Temps.PRESENT, Nombre.PLUR)],
+                futur_sing=verbe.variantes[(Temps.FUTUR, Nombre.SING)],
+                futur_plur=verbe.variantes[(Temps.FUTUR, Nombre.PLUR)],
+                imparfait_sing=verbe.variantes[(Temps.IMPARFAIT, Nombre.SING)],
+                imparfait_plur=verbe.variantes[(Temps.IMPARFAIT, Nombre.PLUR)],
+            )
+            for verbe in verbes
+        ]
+
+        adverbes = self.most_common(
+            CatGram.ADVERBE, thresholds.get(CatGram.ADVERBE, None)
+        )
+        db_adverbes = [Adverbe(adv=adv.mot) for adv in adverbes]
+
+        return WordDb(
+            noms=db_noms, adjectifs=db_adjectifs, verbes=db_verbes, adverbes=db_adverbes
+        )

pwgen_fr/morphalou.py

@@ -0,0 +1,256 @@
+""" Reads the Morphalou dataset, in its TSV form """
+
+import itertools
+import logging
+import subprocess
+import typing as t
+from pathlib import Path
+
+from lxml import etree
+
+from .word_db import Adjectif, Adverbe, Genre, Nom, Nombre, Temps, Verbe, WordDb
+
+TSV_NS = {
+    "tsv": "http://www.tei-c.org/ns/1.0",
+    "xml": "http://www.w3.org/XML/1998/namespace",
+}
+
+logger = logging.getLogger(__name__)
+
+
+class MorphalouSet:
+    MORPHALOU_DIR_PATH = (
+        Path(__file__).parent.parent / "data/raw/Morphalou3.1_formatTEI"
+    )
+    MORPHALOU_FILENAME_TEMPLATE = "{cat_name}_Morphalou3.1_TEI.xml"
+
+    CAT_MAPPING: dict[t.Type[t.NamedTuple], str] = {
+        Nom: "commonNoun",
+        Adjectif: "adjective",
+        Verbe: "verb",
+        Adverbe: "adverb",
+    }
+
+    word_db: WordDb
+
+    def __init__(self):
+        self.word_db = WordDb()
+
+    @classmethod
+    def _ensure_uncompressed(cls):
+        """Ensures the dataset is uncompressed"""
+        if cls.MORPHALOU_DIR_PATH.exists():
+            return
+
+        lexique_archive = cls.MORPHALOU_DIR_PATH.with_suffix(".tar.xz")
+        if not lexique_archive.exists():
+            logger.error("Missing compressed dataset at %s", lexique_archive)
+            raise Exception(f"Missing compressed dataset at {lexique_archive}")
+
+        logger.info("Uncompressing dataset")
+        subprocess.check_call(
+            [
+                "tar",
+                "-xJf",
+                lexique_archive.as_posix(),
+                "-C",
+                lexique_archive.parent.as_posix(),
+            ]
+        )
+
+        if not cls.MORPHALOU_DIR_PATH.exists():
+            logger.error(
+                "Uncompressed dataset still missing at %s after extraction",
+                cls.MORPHALOU_DIR_PATH,
+            )
+            raise Exception(
+                f"Uncompressed dataset still missing at {cls.MORPHALOU_DIR_PATH} after extraction"
+            )
+
+    def parse(self):
+        """Parses the dataset"""
+        self.__class__._ensure_uncompressed()
+
+        for cat, cat_file in self.__class__.CAT_MAPPING.items():
+            word_db_elt = WordDb.CATEGORY_TO_ATTR[cat]
+            logging.info("Parsing %s...", word_db_elt)
+            setattr(
+                self.word_db,
+                word_db_elt,
+                getattr(self, f"_parse_{word_db_elt}")(
+                    self.__class__.MORPHALOU_DIR_PATH
+                    / self.__class__.MORPHALOU_FILENAME_TEMPLATE.format(
+                        cat_name=cat_file
+                    )
+                ),
+            )
+
+    def _tsv_elems(self, tsv_path: Path):
+        """Opens a TSV file, and returns the <body> node, direct parent of all the
+        relevant nodes"""
+        with tsv_path.open("r") as h:
+            tree = etree.parse(h)
+        root = tree.getroot()
+        body = root.find("./tsv:text/tsv:body", TSV_NS)
+        return body
+
+    def _parse_noms(self, tsv_path: Path) -> list[Nom]:
+        """Parse the nouns"""
+        root = self._tsv_elems(tsv_path)
+        out: list[Nom] = []
+
+        for entry in root.iterfind("./tsv:entry", TSV_NS):
+            try:
+                genre = self._genre(
+                    entry.find(
+                        "./tsv:form[@type='lemma']/tsv:gramGrp/tsv:gen", TSV_NS
+                    ).text
+                )
+            except AttributeError:
+                continue  # some nouns don't have a gender defined, somehow -- ignore
+
+            forms = {}
+            for inflected in entry.iterfind("./tsv:form[@type='inflected']", TSV_NS):
+                orth = inflected.find("./tsv:orth", TSV_NS).text
+                nombres = self._nombre_set(
+                    inflected.find("./tsv:gramGrp/tsv:number", TSV_NS).text
+                )
+                for form in nombres:
+                    forms[form] = orth
+            try:
+                out.append(
+                    Nom(
+                        genre=genre,
+                        sing=forms[Nombre.SING],
+                        plur=forms[Nombre.PLUR],
+                    )
+                )
+            except KeyError:
+                continue  # cannot be inflected to all required forms: skip
+
+        return out
+
+    def _parse_adjectifs(self, tsv_path: Path) -> list[Adjectif]:
+        """Parse the adjectives"""
+        root = self._tsv_elems(tsv_path)
+        out: list[Adjectif] = []
+
+        for entry in root.iterfind("./tsv:entry", TSV_NS):
+            forms = {}
+            for inflected in entry.iterfind("./tsv:form[@type='inflected']", TSV_NS):
+                orth = inflected.find("./tsv:orth", TSV_NS).text
+                gram_grp = inflected.find("./tsv:gramGrp", TSV_NS)
+                genres = self._genre_set(gram_grp.find("./tsv:gen", TSV_NS).text)
+                nombres = self._nombre_set(gram_grp.find("./tsv:number", TSV_NS).text)
+
+                for form in itertools.product(genres, nombres):
+                    forms[form] = orth
+            try:
+                out.append(
+                    Adjectif(
+                        masc_sing=forms[Genre.MASC, Nombre.SING],
+                        masc_plur=forms[Genre.MASC, Nombre.PLUR],
+                        fem_sing=forms[Genre.FEM, Nombre.SING],
+                        fem_plur=forms[Genre.FEM, Nombre.PLUR],
+                    )
+                )
+            except KeyError:
+                continue  # cannot be inflected to all required forms: skip
+
+        return out
+
+    def _parse_verbes(self, tsv_path: Path) -> list[Verbe]:
+        """Parse the verbs"""
+        root = self._tsv_elems(tsv_path)
+        out: list[Verbe] = []
+
+        for entry in root.iterfind("./tsv:entry", TSV_NS):
+            forms = {}
+            for inflected in entry.iterfind("./tsv:form[@type='inflected']", TSV_NS):
+                gram_grp = inflected.find("./tsv:gramGrp", TSV_NS)
+
+                # Order of tests is important! If mood == 'participle', there is no
+                # 'person' defined.
+                if (
+                    gram_grp.find("./tsv:mood", TSV_NS).text != "indicative"
+                    or gram_grp.find("./tsv:per", TSV_NS).text != "thirdPerson"
+                ):
+                    continue  # irrelevant for us
+
+                temps = self._tense(gram_grp.find("./tsv:tns", TSV_NS).text)
+                if temps is None:
+                    continue  # irrelevant for us
+
+                nombres = self._nombre_set(gram_grp.find("./tsv:number", TSV_NS).text)
+
+                orth = inflected.find("./tsv:orth", TSV_NS).text
+                for nombre in nombres:
+                    forms[(temps, nombre)] = orth
+            try:
+                out.append(
+                    Verbe(
+                        present_sing=forms[Temps.PRESENT, Nombre.SING],
+                        present_plur=forms[Temps.PRESENT, Nombre.PLUR],
+                        futur_sing=forms[Temps.FUTUR, Nombre.SING],
+                        futur_plur=forms[Temps.FUTUR, Nombre.PLUR],
+                        imparfait_sing=forms[Temps.IMPARFAIT, Nombre.SING],
+                        imparfait_plur=forms[Temps.IMPARFAIT, Nombre.PLUR],
+                    )
+                )
+            except KeyError:
+                continue  # cannot be inflected to all required forms: skip
+
+        return out
+
+    def _parse_adverbes(self, tsv_path: Path) -> list[Adverbe]:
+        """Parse the adverbs"""
+        root = self._tsv_elems(tsv_path)
+        out: list[Adverbe] = []
+
+        for entry in root.iterfind("./tsv:entry", TSV_NS):
+            # We're only interested in the lemma form
+            orth = entry.find("./tsv:form[@type='lemma']/tsv:orth", TSV_NS)
+            assert orth is not None
+            adv = orth.text
+            out.append(Adverbe(adv=adv))
+
+        return out
+
+    @staticmethod
+    def _genre_set(genre: str) -> list[Genre]:
+        return {
+            "masculine": [Genre.MASC],
+            "feminine": [Genre.FEM],
+            "invariable": [Genre.MASC, Genre.FEM],
+        }[genre]
+
+    @staticmethod
+    def _genre(genre: str) -> Genre:
+        return {
+            "masculine": Genre.MASC,
+            "feminine": Genre.FEM,
+            "invariable": Genre.INV,
+        }[genre]
+
+    @staticmethod
+    def _nombre(nombre: str) -> Nombre:
+        return {
+            "singular": Nombre.SING,
+            "plural": Nombre.PLUR,
+        }[nombre]
+
+    @staticmethod
+    def _nombre_set(nombre: str) -> list[Nombre]:
+        return {
+            "singular": [Nombre.SING],
+            "plural": [Nombre.PLUR],
+            "invariable": [Nombre.SING, Nombre.PLUR],
+        }[nombre]
+
+    @staticmethod
+    def _tense(tense: str) -> t.Optional[Temps]:
+        return {
+            "present": Temps.PRESENT,
+            "imperfect": Temps.IMPARFAIT,
+            "future": Temps.FUTUR,
+        }.get(tense, None)

pwgen_fr/morphalou_frequency.py

@@ -0,0 +1,74 @@
+""" Generates a worddb based on Morphalou, but limits to frequent words based on
+external sources (eg Lexique) """
+
+import logging
+import typing as t
+
+from . import lexique, morphalou
+from .word_db import Adjectif, Adverbe, Genre, Nom, Nombre, Temps, Verbe, WordDb
+
+logger = logging.getLogger(__name__)
+
+
+class MorphalouFreqSet:
+    morphalou_db: WordDb
+    lexique: lexique.Lexique
+    filtered_db: WordDb
+
+    def __init__(
+        self,
+        morphalou_db: t.Optional[WordDb] = None,
+        lexique: t.Optional[lexique.Lexique] = None,
+    ):
+        if not morphalou_db:
+            morphalou_set = morphalou.MorphalouSet()
+            morphalou_set.parse()
+            self.morphalou_db = morphalou_set.word_db
+        else:
+            self.morphalou_db = morphalou_db
+
+        if not lexique:
+            self.lexique = lexique.Lexique.parse()
+        else:
+            self.lexique = lexique
+
+        self.filtered_db = self._filter_lexique()
+
+    def _filter_nom(self, nom: Nom) -> bool:
+        freq = max(
+            self.lexique.lemfreq.get(nom.sing, 0.0),
+            self.lexique.lemfreq.get(nom.plur, 0.0),
+        )
+        return freq > 0
+
+    def _filter_adjectif(self, adjectif: Adjectif) -> bool:
+        freq = max(
+            self.lexique.lemfreq.get(adjectif.masc_sing, 0.0),
+            self.lexique.lemfreq.get(adjectif.fem_sing, 0.0),
+        )
+        return freq > 0
+
+    def _filter_verbe(self, verbe: Verbe) -> bool:
+        freq = max(
+            self.lexique.lemfreq.get(verbe.present_sing, 0.0),
+            self.lexique.lemfreq.get(verbe.futur_sing, 0.0),
+            self.lexique.lemfreq.get(verbe.imparfait_sing, 0.0),
+            self.lexique.lemfreq.get(verbe.present_plur, 0.0),
+            self.lexique.lemfreq.get(verbe.futur_plur, 0.0),
+            self.lexique.lemfreq.get(verbe.imparfait_plur, 0.0),
+        )
+        return freq > 0
+
+    def _filter_adverbe(self, adverbe: Adverbe) -> bool:
+        if " " in adverbe.adv:
+            return False
+        freq = self.lexique.lemfreq.get(adverbe.adv, 0.0)
+        return freq > 0
+
+    def _filter_lexique(self) -> WordDb:
+        out = WordDb()
+        out.noms = list(filter(self._filter_nom, self.morphalou_db.noms))
+        out.adjectifs = list(filter(self._filter_adjectif, self.morphalou_db.adjectifs))
+        out.verbes = list(filter(self._filter_verbe, self.morphalou_db.verbes))
+        out.adverbes = list(filter(self._filter_adverbe, self.morphalou_db.adverbes))
+        return out

pwgen_fr/word_db.py

@@ -0,0 +1,206 @@
+""" A pre-processed database of words, independant of their source """
+
+import gzip
+import json
+import secrets
+import typing as t
+from enum import Enum
+from pathlib import Path
+
+
+class Genre(Enum):
+    MASC = "masculin"
+    FEM = "féminin"
+    INV = "invariable"  # pour les noms uniquement
+
+    @classmethod
+    def pick(cls) -> "Genre":
+        """random-pick (avoids inv)"""
+        return secrets.choice([cls.MASC, cls.FEM])
+
+
+class Nombre(Enum):
+    SING = "singulier"
+    PLUR = "pluriel"
+
+    @classmethod
+    def pick(cls) -> "Nombre":
+        """random-pick"""
+        return secrets.choice(list(cls))
+
+
+class Temps(Enum):
+    PRESENT = "present"
+    FUTUR = "futur"
+    IMPARFAIT = "imparfait"
+
+    @classmethod
+    def pick(cls) -> "Temps":
+        """random-pick"""
+        return secrets.choice(list(cls))
+
+
+class Nom(t.NamedTuple):
+    """Nom commun"""
+
+    genre: Genre
+    sing: str
+    plur: str
+
+    def __str__(self) -> str:
+        return f"{self.sing}"
+
+    def accord(self, nombre: Nombre) -> str:
+        """Accorde en nombre"""
+        return getattr(self, nombre.name.lower())
+
+    @property
+    def genre_or_pick(self) -> Genre:
+        """Genre of the noun, or random-pick if invariable"""
+        if self.genre == Genre.INV:
+            return Genre.pick()
+        return self.genre
+
+    @property
+    def serialized(self):
+        return {"genre": self.genre.name, "sing": self.sing, "plur": self.plur}
+
+    @classmethod
+    def unserialized(cls, kwargs):
+        genre = Genre[kwargs.pop("genre")]
+        return cls(**kwargs, genre=genre)
+
+
+class Adjectif(t.NamedTuple):
+    masc_sing: str
+    masc_plur: str
+    fem_sing: str
+    fem_plur: str
+
+    def __str__(self) -> str:
+        return f"{self.masc_sing}/{self.fem_sing}"
+
+    def accord(self, genre: Genre, nombre: Nombre) -> str:
+        """Accorde en genre et en nombre"""
+        return getattr(self, f"{genre.name.lower()}_{nombre.name.lower()}")
+
+    @property
+    def serialized(self):
+        return self._asdict()
+
+    @classmethod
+    def unserialized(cls, kwargs):
+        return cls(**kwargs)
+
+
+class Verbe(t.NamedTuple):
+    present_sing: str
+    present_plur: str
+    futur_sing: str
+    futur_plur: str
+    imparfait_sing: str
+    imparfait_plur: str
+
+    def __str__(self) -> str:
+        return f"{self.present_sing}"
+
+    def accord(self, temps: Temps, nombre: Nombre) -> str:
+        """Accorde en temps et en nombre (seule la 3è pers. est utilisée)"""
+        return getattr(self, f"{temps.name.lower()}_{nombre.name.lower()}")
+
+    @property
+    def serialized(self):
+        return self._asdict()
+
+    @classmethod
+    def unserialized(cls, kwargs):
+        return cls(**kwargs)
+
+
+class Adverbe(t.NamedTuple):
+    """Packed as named tuple for consistence"""
+
+    adv: str
+
+    def __str__(self) -> str:
+        return self.adv
+
+    def accord(self) -> str:
+        """for consistence"""
+        return self.adv
+
+    @property
+    def serialized(self):
+        return self._asdict()
+
+    @classmethod
+    def unserialized(cls, kwargs):
+        return cls(**kwargs)
+
+
+class WordDb:
+    """Base de donnée de mots, sérialisable"""
+
+    SERIALIZED_GZ_LOCATION = Path(__file__).parent.parent / "morphalou.json.gz"
+
+    _serialize_data: dict[str, t.Type[t.NamedTuple]] = {
+        "noms": Nom,
+        "adjectifs": Adjectif,
+        "verbes": Verbe,
+        "adverbes": Adverbe,
+    }
+
+    CATEGORY_TO_ATTR: dict = {
+        Nom: "noms",
+        Adjectif: "adjectifs",
+        Verbe: "verbes",
+        Adverbe: "adverbes",
+    }
+
+    noms: list[Nom]
+    adjectifs: list[Adjectif]
+    verbes: list[Verbe]
+    adverbes: list[Adverbe]
+
+    def __init__(
+        self,
+        noms: t.Optional[list[Nom]] = None,
+        adjectifs: t.Optional[list[Adjectif]] = None,
+        verbes: t.Optional[list[Verbe]] = None,
+        adverbes: t.Optional[list[Adverbe]] = None,
+    ):
+        self.noms = noms or []
+        self.adjectifs = adjectifs or []
+        self.verbes = verbes or []
+        self.adverbes = adverbes or []
+
+    def serialize(self) -> dict:
+        """Serialize to plain dictionary (no classes)"""
+        return {
+            attr: [x.serialized for x in getattr(self, attr)]
+            for attr in self.__class__._serialize_data
+        }
+
+    def save(self, fd):
+        """Serialize to this stream"""
+        json.dump(self.serialize(), fd)
+
+    @classmethod
+    @t.no_type_check  # serialization is messy
+    def unserialize(cls, data: dict) -> "WordDb":
+        """Reverses :serialize:"""
+        parsed = {}
+        for attr, attr_cls in cls._serialize_data.items():
+            parsed[attr] = list(map(attr_cls.unserialized, data[attr]))
+        return cls(**parsed)
+
+    @classmethod
+    def load(cls, fd) -> "WordDb":
+        """Unserialize from this stream"""
+        return cls.unserialize(json.load(fd))
+
+    @classmethod
+    def autoload(cls) -> "WordDb":
+        """Unserialize from default source"""
+        with gzip.open(cls.SERIALIZED_GZ_LOCATION) as h:
+            return cls.load(h)

setup.py

@@ -25,9 +25,7 @@ setup(
     install_requires=parse_requirements(),
     entry_points={
         "console_scripts": [
-            #            (
+            ("pwgen-fr = pwgen_fr.entrypoints:pwgen_fr",),
-            #                "proxmox-snapshot-review = proxmox_scripts.snapshots:review_snapshots",
-            #            ),
         ]
     },
 )