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from contextlib import contextmanager |
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from sqlalchemy import create_engine, text |
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from sqlalchemy.orm import sessionmaker |
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import pandas as pd |
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import geopandas as gpd |
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from egon.data import config |
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def credentials(): |
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"""Return local database connection parameters. |
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Returns |
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------- |
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dict |
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Complete DB connection information |
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""" |
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translated = { |
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"--database-name": "POSTGRES_DB", |
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"--database-password": "POSTGRES_PASSWORD", |
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"--database-host": "HOST", |
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"--database-port": "PORT", |
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"--database-user": "POSTGRES_USER", |
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} |
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configuration = config.settings()["egon-data"] |
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update = { |
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translated[flag]: configuration[flag] |
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for flag in configuration |
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if flag in translated |
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} |
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configuration.update(update) |
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return configuration |
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def engine(): |
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"""Engine for local database.""" |
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db_config = credentials() |
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return create_engine( |
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f"postgresql+psycopg2://{db_config['POSTGRES_USER']}:" |
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f"{db_config['POSTGRES_PASSWORD']}@{db_config['HOST']}:" |
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f"{db_config['PORT']}/{db_config['POSTGRES_DB']}", |
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echo=False, |
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) |
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def execute_sql(sql_string): |
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"""Execute a SQL expression given as string. |
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The SQL expression passed as plain string is convert to a |
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`sqlalchemy.sql.expression.TextClause`. |
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Parameters |
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---------- |
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sql_string : str |
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SQL expression |
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""" |
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engine_local = engine() |
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with engine_local.connect().execution_options(autocommit=True) as con: |
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con.execute(text(sql_string)) |
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def submit_comment(json, schema, table): |
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"""Add comment to table. |
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We use `Open Energy Metadata <https://github.com/OpenEnergyPlatform/ |
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oemetadata/blob/develop/metadata/v140/metadata_key_description.md>`_ |
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standard for describging our data. Metadata is stored as JSON in the table |
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comment. |
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Parameters |
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---------- |
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json : str |
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JSON string reflecting comment |
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schema : str |
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The target table's database schema |
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table : str |
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Database table on which to put the given comment |
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""" |
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prefix_str = "COMMENT ON TABLE {0}.{1} IS ".format(schema, table) |
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check_json_str = ( |
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"SELECT obj_description('{0}.{1}'::regclass)::json".format( |
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schema, table |
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) |
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) |
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execute_sql(prefix_str + json + ";") |
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# Query table comment and cast it into JSON |
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# The query throws an error if JSON is invalid |
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execute_sql(check_json_str) |
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@contextmanager |
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def session_scope(): |
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"""Provide a transactional scope around a series of operations.""" |
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Session = sessionmaker(bind=engine()) |
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session = Session() |
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try: |
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yield session |
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session.commit() |
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except: |
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session.rollback() |
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raise |
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finally: |
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session.close() |
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def select_dataframe(sql, index_col=None): |
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""" Select data from local database as pandas.DataFrame |
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Parameters |
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---------- |
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sql : str |
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SQL query to be executed. |
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index_col : str, optional |
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Column(s) to set as index(MultiIndex). The default is None. |
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Returns |
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------- |
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df : pandas.DataFrame |
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Data returned from SQL statement. |
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""" |
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df = pd.read_sql(sql, engine(), index_col=index_col) |
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if df.size == 0: |
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print(f"WARNING: No data returned by statement: \n {sql}") |
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return df |
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def select_geodataframe(sql, index_col=None, geom_col='geom', epsg=3035): |
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""" Select data from local database as geopandas.GeoDataFrame |
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Parameters |
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---------- |
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sql : str |
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SQL query to be executed. |
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index_col : str, optional |
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Column(s) to set as index(MultiIndex). The default is None. |
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geom_col : str, optional |
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column name to convert to shapely geometries. The default is 'geom'. |
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epsg : int, optional |
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EPSG code specifying output projection. The default is 3035. |
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150
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Returns |
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------- |
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gdf : pandas.DataFrame |
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Data returned from SQL statement. |
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""" |
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gdf = gpd.read_postgis( |
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sql, engine(), index_col=index_col, geom_col=geom_col |
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).to_crs(epsg=epsg) |
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if gdf.size == 0: |
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print(f"WARNING: No data returned by statement: \n {sql}") |
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return gdf |
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openego /
eGon-data
