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feat(Database): Aggregate SQLAlchemy-based DB management in wordprofi…
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,192 @@ | ||
| import logging | ||
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| from pathlib import Path | ||
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| import sqlalchemy as sq | ||
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| from sqlalchemy import Column, Enum, MetaData, Table, text, types | ||
| from sqlalchemy.engine import Connection | ||
| from sqlalchemy.sql import func | ||
| from sqlalchemy.sql.schema import Index | ||
|
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| import wordprofile.config as config | ||
| from wordprofile.extract import relation_types, word_classes | ||
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| logger = logging.getLogger(__name__) | ||
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| FORM_TYPE = types.VARCHAR(config.max_form_length) | ||
| CORPUS_FILE_TYPE = types.Integer | ||
| RELATION_TYPE = Enum(relation_types) | ||
| TAG_TYPE = Enum(word_classes) | ||
|
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| meta = MetaData() | ||
| corpus_files = Table( | ||
| "corpus_files", | ||
| meta, | ||
| Column("id", CORPUS_FILE_TYPE), | ||
| Column("corpus", types.VARCHAR(50)), | ||
| Column("file", types.VARCHAR(200)), | ||
| Column("orig", types.Text), | ||
| Column("date", types.DateTime), | ||
| Column("available", types.Text), | ||
| mysql_engine="Aria", | ||
| ) | ||
| concord_sentences = Table( | ||
| "concord_sentences", | ||
| meta, | ||
| Column("corpus_file_id", CORPUS_FILE_TYPE), | ||
| Column("sentence_id", types.Integer), | ||
| Column("sentence", types.Text), | ||
| Column("random_val", types.Float, server_default=func.rand()), | ||
| mysql_engine="Aria", | ||
| ) | ||
| matches = Table( | ||
| "matches", | ||
| meta, | ||
| Column("id", types.Integer), | ||
| Column("collocation_id", types.Integer), | ||
| Column("head_surface", FORM_TYPE), | ||
| Column("dep_surface", FORM_TYPE), | ||
| Column("head_position", types.Integer), | ||
| Column("dep_position", types.Integer), | ||
| Column("prep_position", types.Text), | ||
| Column("corpus_file_id", CORPUS_FILE_TYPE), | ||
| Column("sentence_id", types.Integer), | ||
| mysql_engine="Aria", | ||
| ) | ||
| collocations = Table( | ||
| "collocations", | ||
| meta, | ||
| Column("id", types.Integer), | ||
| Column("label", RELATION_TYPE), | ||
| Column("lemma1", FORM_TYPE), | ||
| Column("lemma2", FORM_TYPE), | ||
| Column("lemma1_tag", TAG_TYPE), | ||
| Column("lemma2_tag", TAG_TYPE), | ||
| Column("preposition", FORM_TYPE), | ||
| Column("inv", types.Boolean, default=0), | ||
| Column("frequency", types.Integer, default=1), | ||
| Column("score", types.Float), | ||
| mysql_engine="Aria", | ||
| ) | ||
| mwe = Table( | ||
| "mwe", | ||
| meta, | ||
| Column("id", types.Integer), | ||
| Column("collocation1_id", types.Integer), | ||
| Column("collocation2_id", types.Integer), | ||
| Column("label", RELATION_TYPE), | ||
| Column("lemma", FORM_TYPE), | ||
| Column("lemma_tag", TAG_TYPE), | ||
| Column("inv", types.Boolean, default=0), | ||
| Column("frequency", types.Integer, default=1), | ||
| Column("score", types.Float), | ||
| mysql_engine="Aria", | ||
| ) | ||
| mwe_match = Table( | ||
| "mwe_match", | ||
| meta, | ||
| Column("mwe_id", types.Integer), | ||
| Column("match1_id", types.Integer), | ||
| Column("match2_id", types.Integer), | ||
| mysql_engine="Aria", | ||
| ) | ||
| corpus_freqs = Table( | ||
| "corpus_freqs", | ||
| meta, | ||
| Column("label", RELATION_TYPE), | ||
| Column("freq", types.Integer), | ||
| Index("label_index", "label"), | ||
| mysql_engine="Aria", | ||
| ) | ||
| token_freqs = Table( | ||
| "token_freqs", | ||
| meta, | ||
| Column("lemma", FORM_TYPE), | ||
| Column("tag", TAG_TYPE), | ||
| Column("freq", types.Integer), | ||
| Column("surface", FORM_TYPE), | ||
| Column("surface_freq", types.Integer), | ||
| mysql_engine="Aria", | ||
| ) | ||
|
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||
| indices = ( | ||
| Index("corpus_index", corpus_files.c.id, unique=True), | ||
| Index("concord_corpus_index", concord_sentences.c.corpus_file_id), | ||
| Index("concord_corpus_sentence_index", concord_sentences.c.corpus_file_id, concord_sentences.c.sentence_id), | ||
| Index("rand_val", concord_sentences.c.random_val), | ||
| Index("matches_index", matches.c.id, unique=True), | ||
| Index("matches_corpus_index", matches.c.corpus_file_id), | ||
| Index("matches_corpus_sentence_index", matches.c.corpus_file_id, matches.c.sentence_id), | ||
| Index("matches_relation_label_index", matches.c.collocation_id), | ||
| Index("mwe_index", mwe.c.id, unique=True), | ||
| Index("mwe_collocation1_index", mwe.c.collocation1_id), | ||
| Index("mwe_match_index", mwe_match.c.mwe_id), | ||
| Index("colloc_id", collocations.c.id, unique=True), | ||
| Index("colloc_lemma1_index", collocations.c.lemma1), | ||
| Index("colloc_lemma1_tag_index", collocations.c.lemma1, collocations.c.lemma1_tag), | ||
| Index("colloc_lemma2_tag_index", collocations.c.lemma2, collocations.c.lemma2_tag), | ||
| Index("colloc_lemma_index", collocations.c.lemma1, collocations.c.lemma2), | ||
| Index("token_freq_lemma", token_freqs.c.lemma), | ||
| Index("token_freq_lemma_tag", token_freqs.c.lemma, token_freqs.c.tag) | ||
| ) | ||
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| def open_db(create_schema=True, clear=False, **args): | ||
| url = "mysql+pymysql://{}:{}@{}/{}?charset=utf8mb4&local_infile=1".format( | ||
| config.DB_USER, config.DB_PASSWORD, config.DB_HOST, config.DB_NAME | ||
| ) | ||
| db = sq.create_engine(url, **args) | ||
| logger.info("Opening '%s'" % db) | ||
| if clear: | ||
| logger.info("Clearing '%s'" % db) | ||
| with db.connect() as c: | ||
| meta.drop_all(c) | ||
| if create_schema: | ||
| logger.info("Initializing '%s'" % db) | ||
| with db.connect() as c: | ||
| meta.create_all(c) | ||
| return db | ||
|
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| loaded_tables = ( | ||
| "corpus_files", | ||
| "concord_sentences", | ||
| "collocations", | ||
| "token_freqs", | ||
| "matches", | ||
| "mwe", | ||
| "mwe_match" | ||
| ) | ||
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| def load_db(db, data_dir): | ||
| data_dir = Path(data_dir) | ||
| logger.info("Loading '%s'" % data_dir) | ||
| with db.connect() as c: | ||
| logger.info("Dropping indices") | ||
| for index in indices: | ||
| index.drop(c) | ||
| for table in loaded_tables: | ||
| table_file = data_dir / table | ||
| if not table_file.exists(): | ||
| logger.warning("Local file '%s' does not exist." % table_file) | ||
| continue | ||
| logger.info("Loading table '%s'" % table) | ||
| sql = f"LOAD DATA LOCAL INFILE '{table_file}' INTO TABLE {table}" | ||
| if table == "concord_sentences": | ||
| sql += " (corpus_file_id, sentence_id, sentence)" | ||
| sql += ";" | ||
| c.execute(text(sql)) | ||
| logger.info("Creating corpus frequency statistics") | ||
| c.execute(text( | ||
| """ | ||
| INSERT INTO corpus_freqs (label, freq) | ||
| SELECT label, SUM(frequency) as freq | ||
| FROM collocations c | ||
| GROUP BY label | ||
| """ | ||
| )) | ||
| logger.info("Creating indices") | ||
| for index in indices: | ||
| index.create(c) |
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