build_BDD.py 23.9 KB
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#!/usr/bin/env python
# -*- coding: utf-8 -*-

"""This script inspect a SPASE dataset folder (containing Granules, NumericalData, Instrument and
Observatory folders), then generate a SQL script which insert all the granules in a database,
formatted as epn-tap parameters.

See
http://spase-group.org/data/reference/spase-2_2_6/ for more information about spase specification,
and https://voparis-confluence.obspm.fr/display/VES/EPN-TAP+V2.0+parameters for more information
about epn-tap-v2 specification."""

import math
import re
import xml.etree.ElementTree as ElTr
import os.path as op
from os import walk
from datetime import datetime, timedelta
from typing import Tuple, List, Dict, Optional
import sys

# Type aliases
SQLDic = Dict[str, object]
SpaseDic = Dict[str, List[ElTr.Element]]

# Paths
WORKING_DIR = op.dirname(op.abspath(__file__))  # parent directory
OUTPUT_SQL_FILE_PATH = op.join(WORKING_DIR, 'DaCHS', 'amdadb_db.sql')
SPASE_DIR = op.join(WORKING_DIR, 'DATA')
LOG_FILE_PATH = op.join(WORKING_DIR, 'log', 'build_granules.log')  # Set to None if you want to log in stdout instead of a file

# XML and SQL formats
XMLNS = 'http://www.spase-group.org/data/schema'
XML_DATE_FORMAT = '%Y-%m-%dT%H:%M:%SZ'
SQL_DATE_FORMAT = '%Y-%m-%d'
SEP = '#'

# Dictionaries of values
DATAPRODUCT_TYPE_DIC = {'Image': 'im', 'Plasmagram': 'ds', 'Spectrogram': 'ds', 'StackPlot': 'ts',
                        'TimeSeries': 'ts', 'time_series': 'ts', 'WaveForm': 'ts'}

PROCESSING_LEVEL_DIC = {'Calibrated': 3, 'Raw': 1, 'Uncalibrated': 5}

# Based on http://spase-group.org/
TARGET_CLASS_DIC = {'Heliosphere': 'interplanetary_medium', 'Interstellar': 'galaxy',
                    'Earth': 'planet', 'Saturn': 'planet', 'Mercury': 'planet', 'Uranus': 'planet',
                    'Mars': 'planet', 'Neptune': 'planet', 'Jupiter': 'planet', 'Venus': 'planet',
                    'Moon': 'satellite', 'Callisto': 'satellite', 'Europa': 'satellite',
                    'Ganymede': 'satellite', 'Dione': 'satellite', 'Enceladus': 'satellite',
                    'Mimas': 'satellite', 'Miranda': 'satellite', 'Phobos': 'satellite',
                    'Iapetus': 'satellite', 'Titania': 'satellite', 'Oberon': 'satellite',
                    'Puck': 'satellite', 'Deimos': 'satellite', 'Ariel': 'satellite',
                    'Umbriel': 'satellite', 'Rhea': 'satellite', 'Tethys': 'satellite',
                    'Titan': 'satellite', 'Io': 'satellite',
                    'Pluto': 'dwarf_planet',
                    'Comet': 'comet'
                    }

MIME_TYPE_LIST = {'AVI': 'video/x-msvideo',
                  'Binary': 'application/octet-stream',
                  'CDF': 'application/x-cdf-istp',
                  'CEF': 'application/x-cef1',
                  'CEF1': 'application/x-cef1',
                  'CEF2': 'application/x-cef2',
                  'Excel': 'application/vnd.ms-excel',
                  'FITS': 'application/x-fits-bintable',
                  'GIF': 'image/gif',
                  'HDF': 'application/x-hdf',
                  'HDF4': 'application/x-hdf',
                  'HDF5': 'application/x-hdf',
                  'HTML': 'text/html',
                  'Hardcopy': None,
                  'Hardcopy.Film': None,
                  'Hardcopy.Microfiche': None,
                  'Hardcopy.Microfilm': None,
                  'Hardcopy.Photograph': None,
                  'Hardcopy.PhotographicPlate': None,
                  'Hardcopy.Print': None,
                  'IDFS': None,
                  'IDL': 'application/octet-stream',
                  'JPEG': 'image/jpeg ',
                  'MATLAB_4': 'application/octet-stream',
                  'MATLAB_6': 'application/octet-stream',
                  'MATLAB_7': 'application/octet-stream',
                  'MPEG': 'video/mpeg',
                  'NCAR': None,
                  'NetCDF': 'application/x-netcdf',
                  'PDF': 'application/pdf',
                  'PNG': 'image/png',
                  'Postscript': 'application/postscript',
                  'QuickTime': 'video/quicktime',
                  'TIFF': 'image/tiff',
                  'Text': 'text/plain',
                  'Text.ASCII': 'text/plain',
                  'Text.Unicode': 'text/plain',
                  'UDF': None,
                  'VOTable': 'application/x-votable+xml',
                  'XML': 'text/xml'}

# All default SQL values for missing parameters in dataset
DEFAULT_DATASET_VALUES = {
                  'dataproduct_type': 'Unknown',
                  'target_name': 'Unknown',
                  'target_class': 'Unknown',
                  'target_region': None,
                  'spase_region': None,
                  'instrument_host_name': None,
                  'instrument_name': None,
                  'measurement_type': None,
                  'spatial_frame_type': None,
                  'processing_level': 0,
                  'time_sampling_step_min': None,
                  'time_sampling_step_max': None,
                  'time_exp_min': None,
                  'access_format': 'application/x-cdf-istp'
                  }

# All default SQL values for missing parameters in granule
DEFAULT_GRANULE_VALUES = {
                  # obs_id: if missing, the script exits directly.
                  'time_min': 0.0,
                  'time_max': 0.0,
                  'access_url': None,
                  'access_estsize': 0,
                  'release_date': '01-01-0001'
                  }

# SQL code
SQL_HEADER = '''-- Generated by build_BDD.py on %s.
-- SQL procedure to define amdadb data table. Other parameters comes in the epn_core view.
-- Name: amdadb; Type: SCHEMA; Schema: amdadb; Owner: postgres

DROP SCHEMA IF EXISTS amdadb cascade;
CREATE SCHEMA amdadb;
SET search_path = public, pg_catalog;
SET default_tablespace = '';
SET default_with_oids = false;
SET client_encoding = 'UTF8';

-- Name: data_table; Type: TABLE; Schema: amdadb; Owner: postgres; Tablespace:
CREATE TABLE amdadb.data_table (
  -- header parameters
  id SERIAL PRIMARY KEY,
  obs_id TEXT,
  dataproduct_type TEXT,
  target_name TEXT,
  time_min DOUBLE PRECISION, -- date as JD
  time_max DOUBLE PRECISION, -- date as JD
  -- important parameters
  access_url TEXT,
  target_class TEXT,
  target_region TEXT,
  spase_region TEXT,
  instrument_host_name TEXT,
  instrument_name TEXT,
  measurement_type TEXT,
  spase_measurement_type TEXT,
  spatial_frame_type TEXT,
  processing_level INTEGER,
  release_date DATE,
  access_estsize INTEGER,
  access_format TEXT,
  time_sampling_step_min DOUBLE PRECISION, -- duration in seconds
  time_sampling_step_max DOUBLE PRECISION, -- duration in seconds
  time_exp_min DOUBLE PRECISION -- duration in seconds
);

''' % datetime.now().strftime('%c')

SQL_ROW = 'INSERT INTO amdadb.data_table(%s) VALUES (%s);\n'

SQL_FOOTER = '''REVOKE ALL ON SCHEMA "amdadb" FROM PUBLIC;
REVOKE ALL ON SCHEMA "amdadb" FROM postgres;
GRANT ALL ON SCHEMA "amdadb" TO postgres;
GRANT ALL PRIVILEGES ON SCHEMA amdadb TO gavo WITH GRANT OPTION;
GRANT ALL PRIVILEGES ON SCHEMA amdadb TO gavoadmin WITH GRANT OPTION;
GRANT ALL PRIVILEGES ON amdadb.data_table TO gavo WITH GRANT OPTION;
GRANT ALL PRIVILEGES ON amdadb.data_table TO gavoadmin WITH GRANT OPTION;'''


def log(message: str) -> None:
    """Log a warning in a log file or the stdout.

- ``message``: The message to display or to print in the log file.
"""

    if log_file:
        log_file.write(message + '\n')
    else:
        print(message)


def get_nb_files() -> int:
    """Get the number of files in the ``SPASE`` directory,
in order to be able to show a progress bar."""

    return sum([len(walker[2]) for walker in walk(SPASE_DIR)])


def get_spase() -> Optional[SpaseDic]:
    """Get all the spase files

- ``return``: a dictionary, where:

    - **key** = dataset type ('numerical_data', 'granules', etc) ;
    - **value** = A list of spase ElementTree nodes.
"""

    spase_dic = {}
    n_file = 0
    for dir_path, _, files in walk(SPASE_DIR):
        for file_path in [op.join(dir_path, file_name) for file_name in files]:
            try:
                root = ElTr.parse(file_path).getroot()
            except FileNotFoundError:
                print('\nThe spase file is not found on %s.\n' % file_path)
                with open(file_path) as spase_file:
                    print(spase_file.read())
                return
            for child in root:
                key = str(child.tag).split('}')[-1]
                if key != 'Version':
                    if key not in spase_dic:
                        spase_dic[key] = []

                    spase_dic[key].append(child)

            print('Parsed {:<23.23} {:<19.19} [{:<50.50}]'.format(
                  '%d/%d (%.2f%%)' % (n_file + 1, nb_files, 100 * float(n_file + 1) / nb_files),
                  op.splitext(op.basename(file_path))[0],
                  '.' * int((n_file + 1) / nb_files * 50)), end='\r')
            n_file += 1
    print()

    if not spase_dic:
        print('The SPASE dictionary is empty, please check the SPASE folder: %s.' % SPASE_DIR)
        return

    return spase_dic


def get_observatory(spase_dic: SpaseDic, observatory_id: str) -> ElTr.Element:
    """Given the ``observatory_id``, return the *observatory ElementTree node*
(by looking in the Observatory spase file).
"""

    obs_ids = [obs.find('{%s}ResourceID' % XMLNS).text for obs in spase_dic['Observatory']]
    return spase_dic['Observatory'][obs_ids.index(observatory_id)]


def get_instrument(spase_dic: SpaseDic, instrument_id: str) -> ElTr.Element:
    """Given the ``instrument_id``, return the *instrument ElementTree node*,
by looking in the Instrument spase file.
"""

    instru_ids = [instru.find('{%s}ResourceID' % XMLNS).text for instru in spase_dic['Instrument']]
    return spase_dic['Instrument'][instru_ids.index(instrument_id)]


def get_access_format(numerical_data_node: ElTr.Element) -> SQLDic:
    """Given the ``NumericalData`` node, return a dictionary containing the access format (mime-type)."""

    access_formats = set()
    for access_info in numerical_data_node.findall('{%s}AccessInformation' % XMLNS):
        spase_format_node = access_info.find('{%s}Format' % XMLNS)
        if spase_format_node and spase_format_node.text:
            access_formats.add(spase_format_node.text)

    access_format = SEP.join(access_formats)
    try:
        return {'access_format': MIME_TYPE_LIST[access_format]}
    except KeyError:
        return {'access_format': None}


def get_region_info(numerical_data_node: ElTr.Element) -> SQLDic:
    """Given the ``NumericalData`` node, return a dictionary containing:

- **target_class**: the ```target_class`` EPN-TAP parameter;
- **target_name**: the ```target_name`` EPN-TAP parameter;
- **target_region**: the ``target_region`` EPN-TAP parameter.
- **spase_region**: the ``spase_region`` parameter, added to the EPN-TAP parameters for the purposes of AMDA.
"""

    target_name = set()
    target_class = set()
    target_region = set()
    spase_region = set()
    obs_regions = numerical_data_node.findall('{%s}ObservedRegion' % XMLNS)
    for target in [o_reg.text.split('.') for o_reg in obs_regions if o_reg.text is not None]:
        offset = 1 if len(target) >= 2 and target[1] in TARGET_CLASS_DIC \
                      and TARGET_CLASS_DIC[target[1]] == 'satellite' else 0
        target_class.add(TARGET_CLASS_DIC[target[offset]])
        target_name.add(target[offset] if target[offset] != 'Heliosphere' else 'Sun')
        target_region.add('.'.join(target[offset + 1:]))
        spase_region.add('.'.join(target))
    return {'target_class': SEP.join(target_class) if target_class else None,
            'target_name': SEP.join(target_name) if target_name else None,
            'target_region': SEP.join(target_region) if target_region else None,
            'spase_region': SEP.join(spase_region) if spase_region else None}


def get_instru_name_and_host_name(spase_dic: SpaseDic, numerical_data_node: ElTr.Element) -> SQLDic:
    """Given the ``NumericalData`` node, return a dictionary containing:

- **instrument_name**: the ``instrument_name`` EPN-TAP parameter;
- **instrument_host_name**: the ``instrument_host_name`` EPN-TAP parameter.
"""

    instru_names = set()
    instru_host_names = set()
    for instru_id in [i.text for i in numerical_data_node.findall('{%s}InstrumentID' % XMLNS)]:
        instru = get_instrument(spase_dic, instru_id)
        instru_names.add(instru.find('{%s}ResourceHeader' % XMLNS).find('{%s}ResourceName' % XMLNS).text)
        observatory = get_observatory(spase_dic, instru.find('{%s}ObservatoryID' % XMLNS).text)
        instru_host_names.add(observatory.find('{%s}ResourceHeader' % XMLNS).find('{%s}ResourceName' % XMLNS).text)
    return {'instrument_name': SEP.join(instru_names) if instru_names else None,
            'instrument_host_name': SEP.join(instru_host_names) if instru_host_names else None}


def get_types(numerical_data_node: ElTr.Element) -> SQLDic:
    """Given the ``NumericalData`` node, return a dictionary containing:

- **dataproduct_type**: the ``dataproduct_type`` EPN-TAP parameter;
- **spatial_frame_type**: the ``spatial_frame_type`` EPN-TAP parameter;
- **measurement_type**: the ``measurement_type`` EPN-TAP parameter.
- **spase_measurement_type**: the ``spase_measurement_type`` parameter,
    added to the EPN-TAP parameters for the purposes of AMDA.
"""
    with open('log', 'w') as f_out:
        dataproduct_types = set()
        sp_frame_types = set()
        measurement_types = set()
        spase_measurement_type = getattr(numerical_data_node.find('{%s}MeasurementType' % XMLNS), 'text', None)
        for param in numerical_data_node.findall('{%s}Parameter' % XMLNS):
            hints = param.findall('{%s}RenderingHints' % XMLNS)
            dt_nodes = [hint.find('{%s}DisplayType' % XMLNS) for hint in hints]
            for display in [display.text for display in dt_nodes if display is not None and display.text is not None]:
                dataproduct_types.add(DATAPRODUCT_TYPE_DIC[display])
            coord_sys = param.find('{%s}CoordinateSystem' % XMLNS)
            if coord_sys is not None:
                sp_frame_types.add(coord_sys.find('{%s}CoordinateRepresentation' % XMLNS).text.lower())
            measurement_type = param.find('{%s}Ucd' % XMLNS)
            if measurement_type is not None and measurement_type.text is not None:
                f_out.write(measurement_type.text)
                measurement_types.add(measurement_type.text)
        return {'dataproduct_type': SEP.join(dataproduct_types) if dataproduct_types else None,
                'spatial_frame_type': SEP.join(sp_frame_types) if sp_frame_types else None,
                'measurement_type': SEP.join(measurement_types) if measurement_types else None,
                'spase_measurement_type': spase_measurement_type}


def get_times_min_max(numerical_data_node: ElTr.Element) -> SQLDic:
    """Given the ``NumericalData`` node, return a dictionary containing:

- **time_sampling_step_min**: the ``time_sampling_step_min`` EPN-TAP parameter;
- **time_sampling_step_max**: the ``time_sampling_step_max`` EPN-TAP parameter;
- **time_exp_min**: the ``time_exp_min`` EPN-TAP parameter.
"""

    temporal_description_node = numerical_data_node.find('{%s}TemporalDescription' % XMLNS)

    if temporal_description_node is None:
        return {'time_sampling_step_min': None, 'time_sampling_step_max': None, 'time_exp_min': None}

    return {'time_sampling_step_min': str(xml_duration_to_seconds(getattr(temporal_description_node.find(
        '{%s}%s' % (XMLNS, 'Cadence_Min')), 'text', None))),
        'time_sampling_step_max': str(xml_duration_to_seconds(getattr(temporal_description_node.find(
            '{%s}%s' % (XMLNS, 'Cadence_Max')), 'text', None))),
        'time_exp_min': str(xml_duration_to_seconds(getattr(temporal_description_node.find(
            '{%s}%s' % (XMLNS, 'Exposure')), 'text', None)))
    }


def get_processing_lvl(numerical_data_node: ElTr.Element) -> SQLDic:
    """Given the ``NumericalData`` node, return a dictionary containing:

- **processing_level**: the ``processing_level`` EPN-TAP parameter;
"""

    proc_lvl = getattr(numerical_data_node.find('{%s}ProcessingLevel' % XMLNS), 'text', None)
    return {'processing_level': PROCESSING_LEVEL_DIC.get(proc_lvl, None)}


def get_granule_and_parent(gr_node: ElTr.Element) -> Tuple[str, SQLDic]:
    """Given a Granule node, return a dictionary containing all the parameters inside it:

- **obs_id**: the ``obs_id`` EPN-TAP parameter;
- **creation_date**: the ``creation_date`` EPN-TAP parameter;
- **release_date**: the ``release_date`` EPN-TAP parameter;
- **time_min**: the ``time_min`` EPN-TAP parameter;
- **time_max**: the ``time_max`` EPN-TAP parameter;
- **access_url**: the ``access_url`` EPN-TAP parameter;
- **access_estsize**: the ``access_estsize`` EPN-TAP parameter.
"""

    parent_id = getattr(gr_node.find('{%s}ParentID' % XMLNS), 'text', None)
    obs_id = getattr(gr_node.find('{%s}ResourceID' % XMLNS), 'text', '').split('/')[-1]
    if not obs_id:
        print('Can not get the ResourceID content of a granule. Exiting here.')
        sys.exit()

    release_date = getattr(gr_node.find('{%s}ReleaseDate' % XMLNS), 'text', None)
    tim_min = xml_date_to_jd(getattr(gr_node.find('{%s}StartDate' % XMLNS), 'text', None))
    time_max = xml_date_to_jd(getattr(gr_node.find('{%s}StopDate' % XMLNS), 'text', None))
    src_n = gr_node.find('{%s}Source' % XMLNS)
    access_url = getattr(src_n.find('{%s}URL' % XMLNS), 'text', None) if src_n else None
    data_extent_node = src_n.find('{%s}DataExtent' % XMLNS) if src_n else None
    access_estsize = getattr(data_extent_node.find('{%s}Quantity' % XMLNS), 'text', None)

    return parent_id, {'obs_id': obs_id,
                       'release_date': release_date,
                       'time_min': tim_min,
                       'time_max': time_max,
                       'access_url': access_url,
                       'access_estsize': int(access_estsize) if access_estsize else None}


def xml_date_to_jd(xml_date: str) -> Optional[float]:
    """Convert a *XML date* to *Julian day*."""

    try:
        output_date = datetime.strptime(xml_date, XML_DATE_FORMAT)
    except ValueError:  # Date is not well formatted
        return None

    if output_date.month == 1 or output_date.month == 2:
        year_p = output_date.year - 1
        month_p = output_date.month + 12
    else:
        year_p = output_date.year
        month_p = output_date.month

    # this checks where we are in relation to October 15, 1582, the beginning
    # of the Gregorian calendar.
    if ((output_date.year < 1582) or
            (output_date.year == 1582 and output_date.month < 10) or
            (output_date.year == 1582 and output_date.month == 10 and output_date.day < 15)):
        j_day = 0
    else:
        j_day = 2 - math.trunc(year_p / 100.) + math.trunc(math.trunc(year_p / 100.) / 4.)

    j_day += math.trunc((365.25 * year_p) - 0.75) if year_p < 0 else math.trunc(365.25 * year_p)
    j_day += math.trunc(30.6001 * (month_p + 1)) + output_date.day + 1720994.5
    j_day += output_date.hour/24 + output_date.minute/1440 + output_date.second/86400

    return j_day


def xml_date_to_sql_date(xml_date: str) -> str:
    """Convert a *XML date* to a *SQL date*."""

    return datetime.strptime(xml_date, XML_DATE_FORMAT).strftime(SQL_DATE_FORMAT)


def xml_duration_to_seconds(xml_duration: str) -> int:
    """Convert a *XML duration* to seconds."""

    if not xml_duration:
        return 0

    regex = re.compile(r'(?P<sign>-?)P(?:(?P<years>\d+)Y)?(?:(?P<months>\d+)M)?(?:(?P<days>\d+)D)?' +
                       r'(?:T(?:(?P<hours>\d+)H)?(?:(?P<minutes>\d+)M)?(?:(?P<seconds>\d+)S)?)?')

    time = regex.match(xml_duration.upper()).groupdict(0)
    delta = timedelta(
        days=int(time['days']) + (int(time['months']) * 30) + (int(time['years']) * 365),
        hours=int(time['hours']),
        minutes=int(time['minutes']),
        seconds=int(time['seconds']))

    return (delta * -1 if time['sign'] == "-" else delta).total_seconds()


def get_parameters(spase_dic: SpaseDic) -> List[SQLDic]:
    """Get all the parameters of the entire dataset.
Return a list containing the granules, where each granule is a dictionary, with:

- **keys**: the EPN-TAP parameter name;
- **values**: the EPN-TAP value corresponding to the parameter name.
"""

    datasets = {}
    missing_parameters = {}
    nb_elements = len(spase_dic['NumericalData']) + len(spase_dic['NumericalOutput']) + len(spase_dic['Granule'])
    n_dataset = 0

    for numerical_data_node in spase_dic['NumericalData'] + spase_dic['NumericalOutput']:
        print('Dataset %d/%d' % (n_dataset, nb_elements), end=' ' * 99 + '\r')
        n_dataset += 1
        try:
            dataset_key = getattr(numerical_data_node.find('{%s}ResourceID' % XMLNS), 'text', None).split('/')[-1]
        except AttributeError:
            print('Can not get the ResourceID content of a dataset. Exiting here.')
            sys.exit()
        dataset = get_region_info(numerical_data_node)
        dataset.update(get_instru_name_and_host_name(spase_dic, numerical_data_node))
        dataset.update(get_types(numerical_data_node))
        dataset.update(get_access_format(numerical_data_node))
        dataset.update(get_times_min_max(numerical_data_node))
        dataset.update(get_processing_lvl(numerical_data_node))

        # Looking for None parameters in each dataset
        for parameter, default_value in DEFAULT_DATASET_VALUES.items():
            if not dataset[parameter]:
                dataset[parameter] = default_value
                if dataset_key not in missing_parameters:
                    missing_parameters[dataset_key] = set()
                missing_parameters[dataset_key].add(parameter)
        datasets[dataset_key] = dataset

    granules_list = []
    for granule_node in spase_dic['Granule']:
        parent_id, granule = get_granule_and_parent(granule_node)
        dataset_key = parent_id.split('/')[-1]

        print('Granule {:<23.23} {:<18.18} [{:<50.50}]'.format(
              '%d/%d (%.2f%%)' % (n_dataset + 1, nb_elements, 100 * float(n_dataset + 1) / nb_elements),
              dataset_key,
              '.' * int((n_dataset + 1) / nb_files * 50)), end='\r')

        # Looking for None parameters in each granule
        for parameter, default_value in DEFAULT_GRANULE_VALUES.items():
            if not granule[parameter]:
                granule[parameter] = default_value
                if dataset_key not in missing_parameters:
                    missing_parameters[dataset_key] = set()
                missing_parameters[dataset_key].add(parameter)

        try:
            granule.update(datasets[dataset_key])
        except KeyError:
            print('The parent id "%s" of the granule "%s" is not found in the dataset dictionary.'
                  % (parent_id, granule['access_url']))
        granules_list.append(granule)
        n_dataset += 1
    print()
    for bad_dataset, missings in missing_parameters.items():
        log('%s\tmissing %s' % (bad_dataset, ', '.join(missings)))
    return granules_list


def write_sql(granules_list):
    """Write a SQL script which insert all the granules in the database."""

    with open(OUTPUT_SQL_FILE_PATH, 'w') as sql_file:
        sql_file.write(SQL_HEADER)
        for gr in granules_list:
            keys = ', '.join(gr.keys())
            values = ', '.join(['NULL' if param is None else "'%s'" % param if isinstance(param, str) else
                               str(param) for param in gr.values()])
            sql_file.write(SQL_ROW % (keys, values))
        sql_file.write(SQL_FOOTER)


if __name__ == '__main__':
    log_file = open(LOG_FILE_PATH, 'w+') if LOG_FILE_PATH else None

    print('Getting number of files in %s...' % SPASE_DIR)
    nb_files = get_nb_files()

    print('Parsing %d files...' % nb_files)
    spase = get_spase()

    print('Done. Found these types of data: %s.' % ', '.join([key for (key, val) in spase.items()]))

    print('Loading numerical data...')
    granules = get_parameters(spase)

    print('Creating SQL script...')
    write_sql(granules)

    import subprocess

    subprocess.Popen(['notify-send', 'The SQL script %s has been generated.' % OUTPUT_SQL_FILE_PATH])