# http://pyrocko.org - GPLv3
#
# The Pyrocko Developers, 21st Century
# ---|P------/S----------~Lg----------
from __future__ import absolute_import, print_function
import sys
import os
import re
import math
import threading
import sqlite3
import logging
from collections import defaultdict
from pyrocko.io_common import FileLoadError
from pyrocko.guts import Object, Int, List, Tuple, String, Timestamp, Dict
from pyrocko import util
from pyrocko.progress import progress
from . import model, io, cache
from .model import to_kind_id, to_kind, separator, WaveformOrder
from .client import fdsn, catalog
from . import client, environment, error, pile
logger = logging.getLogger('pyrocko.squirrel.base')
guts_prefix = 'pf'
class GeneratorWithLen(object):
def __init__(self, gen, length):
self.gen = gen
self.length = length
def __len__(self):
return self.length
def __iter__(self):
return self.gen
def make_task(*args, **kwargs):
kwargs['logger'] = logger
return progress.task(*args, **kwargs)
def lpick(condition, seq):
ft = [], []
for ele in seq:
ft[int(bool(condition(ele)))].append(ele)
return ft
def execute_get1(connection, sql, args):
return list(connection.execute(sql, args))[0]
g_icount = 0
g_lock = threading.Lock()
def make_unique_name():
with g_lock:
global g_icount
name = '%i_%i' % (os.getpid(), g_icount)
g_icount += 1
return name
def codes_fill(n, codes):
return codes[:n] + ('*',) * (n-len(codes))
c_kind_to_ncodes = {
'station': 4,
'channel': 5,
'response': 5,
'waveform': 6,
'event': 1,
'waveform_promise': 6,
'undefined': 1}
c_inflated = ['', '*', '*', '*', '*', '*']
c_offsets = [0, 2, 1, 1, 1, 1, 0]
def codes_inflate(codes):
codes = codes[:6]
inflated = list(c_inflated)
ncodes = len(codes)
offset = c_offsets[ncodes]
inflated[offset:offset+ncodes] = codes
return inflated
def codes_patterns_for_kind(kind, codes):
if not codes:
return []
if kind in ('event', 'undefined'):
return [codes]
cfill = codes_inflate(codes)[:c_kind_to_ncodes[kind]]
if kind == 'station':
cfill2 = list(cfill)
cfill2[3] = '[*]'
return [cfill, cfill2]
return [cfill]
def group_channels(channels):
groups = defaultdict(list)
for channel in channels:
codes = channel.codes
gcodes = codes[:-1] + (codes[-1][:-1],)
groups[gcodes].append(channel)
return groups
def pyrocko_station_from_channel_group(group, extra_args):
list_of_args = [channel._get_pyrocko_station_args() for channel in group]
args = util.consistency_merge(list_of_args + extra_args)
from pyrocko import model as pmodel
return pmodel.Station(
network=args[0],
station=args[1],
location=args[2],
lat=args[3],
lon=args[4],
elevation=args[5],
depth=args[6],
channels=[ch.get_pyrocko_channel() for ch in group])
def blocks(tmin, tmax, deltat, nsamples_block=100000):
tblock = deltat * nsamples_block
iblock_min = int(math.floor(tmin / tblock))
iblock_max = int(math.ceil(tmax / tblock))
for iblock in range(iblock_min, iblock_max):
yield iblock * tblock, (iblock+1) * tblock
def gaps(avail, tmin, tmax):
assert tmin < tmax
data = [(tmax, 1), (tmin, -1)]
for (tmin_a, tmax_a) in avail:
assert tmin_a < tmax_a
data.append((tmin_a, 1))
data.append((tmax_a, -1))
data.sort()
s = 1
gaps = []
tmin_g = None
for t, x in data:
if s == 1 and x == -1:
tmin_g = t
elif s == 0 and x == 1 and tmin_g is not None:
tmax_g = t
if tmin_g != tmax_g:
gaps.append((tmin_g, tmax_g))
s += x
return gaps
def order_key(order):
return (order.codes, order.tmin, order.tmax)
[docs]class Selection(object):
'''
Database backed file selection (base class for :py:class:`Squirrel`).
:param database:
Database instance or file path to database.
:type database:
:py:class:`Database` or :py:class:`str`
:param persistent:
If given a name, create a persistent selection.
:type persistent:
:py:class:`str`
In the Squirrel framework, a selection is conceptually a list of files to
be made available in the application. Instead of using
:py:class:`Selection` directly, user applications should usually use its
subclass :py:class:`Squirrel` which adds content indices to the selection
and provides high level data querying.
By default, a temporary table in the database is created to hold the names
of the files in the selection. This table is only visible inside the
application which created it. If a name is given to ``persistent``, a named
selection is created, which is visible also in other applications using the
same database.
Besides the filename references, desired content kind masks and file format
indications are stored in the selection's database table to make the user
choice regarding these options persistent on a per-file basis. Book-keeping
on whether files are unknown, known or if modification checks are forced is
also handled in the selection's file-state table.
Paths of files can be added to the selection using the :py:meth:`add`
method and removed with :py:meth:`remove`. :py:meth:`undig_grouped` can be
used to iterate over all content known to the selection.
'''
def __init__(self, database, persistent=None):
self._conn = None
if not isinstance(database, Database):
database = get_database(database)
if persistent is not None:
assert isinstance(persistent, str)
if not re.match(r'^[a-zA-Z_][a-zA-Z0-9_]*$', persistent):
raise error.SquirrelError(
'invalid persistent selection name: %s' % persistent)
self.name = 'psel_' + persistent
else:
self.name = 'sel_' + make_unique_name()
self._persistent = persistent is not None
self._database = database
self._conn = self._database.get_connection()
self._sources = []
self._names = {
'db': 'main' if self._persistent else 'temp',
'file_states': self.name + '_file_states',
'bulkinsert': self.name + '_bulkinsert'}
self._conn.execute(self._register_table(self._sql(
'''
CREATE TABLE IF NOT EXISTS %(db)s.%(file_states)s (
file_id integer PRIMARY KEY,
file_state integer,
kind_mask integer,
format text)
''')))
self._conn.execute(self._sql(
'''
CREATE INDEX
IF NOT EXISTS %(db)s.%(file_states)s_index_file_state
ON %(file_states)s (file_state)
'''))
def __del__(self):
if hasattr(self, '_conn') and self._conn:
if not self._persistent:
self._delete()
else:
self._conn.commit()
def _register_table(self, s):
return self._database._register_table(s)
def _sql(self, s):
return s % self._names
[docs] def get_database(self):
'''
Get the database to which this selection belongs.
:returns: :py:class:`Database` object
'''
return self._database
def _delete(self):
'''
Destroy the tables assoctiated with this selection.
'''
self._conn.execute(self._sql(
'DROP TABLE %(db)s.%(file_states)s'))
self._conn.commit()
[docs] def add(
self,
paths,
kind_mask=model.g_kind_mask_all,
format='detect'):
'''
Add files to the selection.
:param paths:
Paths to files to be added to the selection.
:type paths:
iterator yielding :py:class:`str` objects
'''
if isinstance(paths, str):
paths = [paths]
task = make_task('Gathering file names')
paths = task(paths)
paths = util.short_to_list(200, paths)
if isinstance(paths, list) and len(paths) <= 200:
# short non-iterator paths: can do without temp table
self._conn.executemany(
'''
INSERT OR IGNORE INTO files
VALUES (NULL, ?, NULL, NULL, NULL)
''', ((x,) for x in paths))
task = make_task('Preparing database', 3)
task.update(0, condition='pruning stale information')
self._conn.executemany(self._sql(
'''
DELETE FROM %(db)s.%(file_states)s
WHERE file_id IN (
SELECT files.file_id
FROM files
WHERE files.path == ? )
AND kind_mask != ? OR format != ?
'''), (
(path, kind_mask, format) for path in paths))
task.update(1, condition='adding file names to selection')
self._conn.executemany(self._sql(
'''
INSERT OR IGNORE INTO %(db)s.%(file_states)s
SELECT files.file_id, 0, ?, ?
FROM files
WHERE files.path = ?
'''), ((kind_mask, format, path) for path in paths))
task.update(2, condition='updating file states')
self._conn.executemany(self._sql(
'''
UPDATE %(db)s.%(file_states)s
SET file_state = 1
WHERE file_id IN (
SELECT files.file_id
FROM files
WHERE files.path == ? )
AND file_state != 0
'''), ((path,) for path in paths))
task.update(3)
task.done()
else:
self._conn.execute(self._sql(
'''
CREATE TEMP TABLE temp.%(bulkinsert)s
(path text)
'''))
self._conn.executemany(self._sql(
'INSERT INTO temp.%(bulkinsert)s VALUES (?)'),
((x,) for x in paths))
task = make_task('Preparing database', 5)
task.update(0, condition='adding file names to database')
self._conn.execute(self._sql(
'''
INSERT OR IGNORE INTO files
SELECT NULL, path, NULL, NULL, NULL
FROM temp.%(bulkinsert)s
'''))
task.update(1, condition='pruning stale information')
self._conn.execute(self._sql(
'''
DELETE FROM %(db)s.%(file_states)s
WHERE file_id IN (
SELECT files.file_id
FROM temp.%(bulkinsert)s
INNER JOIN files
ON temp.%(bulkinsert)s.path == files.path)
AND kind_mask != ? OR format != ?
'''), (kind_mask, format))
task.update(2, condition='adding file names to selection')
self._conn.execute(self._sql(
'''
INSERT OR IGNORE INTO %(db)s.%(file_states)s
SELECT files.file_id, 0, ?, ?
FROM temp.%(bulkinsert)s
INNER JOIN files
ON temp.%(bulkinsert)s.path == files.path
'''), (kind_mask, format))
task.update(3, condition='updating file states')
self._conn.execute(self._sql(
'''
UPDATE %(db)s.%(file_states)s
SET file_state = 1
WHERE file_id IN (
SELECT files.file_id
FROM temp.%(bulkinsert)s
INNER JOIN files
ON temp.%(bulkinsert)s.path == files.path)
AND file_state != 0
'''))
task.update(4, condition='dropping temporary data')
self._conn.execute(self._sql(
'DROP TABLE temp.%(bulkinsert)s'))
task.update(5)
task.done()
[docs] def remove(self, paths):
'''
Remove files from the selection.
:param paths:
Paths to files to be removed from the selection.
:type paths:
:py:class:`list` of :py:class:`str`
'''
if isinstance(paths, str):
paths = [paths]
self._conn.executemany(self._sql(
'''
DELETE FROM %(db)s.%(file_states)s
WHERE %(db)s.%(file_states)s.file_id IN
(SELECT files.file_id
FROM files
WHERE files.path == ?)
'''), ((path,) for path in paths))
[docs] def iter_paths(self):
'''
Iterate over all file paths currently belonging to the selection.
:returns: Iterator yielding file paths.
'''
sql = self._sql('''
SELECT
files.path
FROM %(db)s.%(file_states)s
INNER JOIN files
ON files.file_id = %(db)s.%(file_states)s.file_id
ORDER BY %(db)s.%(file_states)s.file_id
''')
for values in self._conn.execute(sql):
yield values[0]
[docs] def get_paths(self):
'''
Get all file paths currently belonging to the selection.
:returns: List of file paths.
'''
return list(self.iter_paths())
def _set_file_states_known(self):
'''
Set file states to "known" (2).
'''
self._conn.execute(self._sql(
'''
UPDATE %(db)s.%(file_states)s
SET file_state = 2
WHERE file_state < 2
'''))
def _set_file_states_force_check(self):
'''
Set file states to "request force check" (1).
'''
self._conn.execute(self._sql(
'''
UPDATE %(db)s.%(file_states)s
SET file_state = 1
'''))
[docs] def undig_grouped(self, skip_unchanged=False):
'''
Get inventory of cached content for all files in the selection.
:param:
skip_unchanged: if ``True`` only inventory of modified files is
yielded (:py:meth:`flag_modified` must be called beforehand).
This generator yields tuples ``((format, path), nuts)`` where ``path``
is the path to the file, ``format`` is the format assignation or
``'detect'`` and ``nuts`` is a list of
:py:class:`~pyrocko.squirrel.Nut` objects representing the contents of
the file.
'''
if skip_unchanged:
where = '''
WHERE %(db)s.%(file_states)s.file_state == 0
'''
else:
where = ''
nfiles = execute_get1(self._conn, self._sql('''
SELECT
COUNT()
FROM %(db)s.%(file_states)s
''' + where), ())[0]
def gen():
sql = self._sql('''
SELECT
%(db)s.%(file_states)s.format,
files.path,
files.format,
files.mtime,
files.size,
nuts.file_segment,
nuts.file_element,
kind_codes.kind_id,
kind_codes.codes,
nuts.tmin_seconds,
nuts.tmin_offset,
nuts.tmax_seconds,
nuts.tmax_offset,
kind_codes.deltat
FROM %(db)s.%(file_states)s
LEFT OUTER JOIN files
ON %(db)s.%(file_states)s.file_id = files.file_id
LEFT OUTER JOIN nuts
ON files.file_id = nuts.file_id
LEFT OUTER JOIN kind_codes
ON nuts.kind_codes_id == kind_codes.kind_codes_id
''' + where + '''
ORDER BY %(db)s.%(file_states)s.file_id
''')
nuts = []
format_path = None
for values in self._conn.execute(sql):
if format_path is not None and values[1] != format_path[1]:
yield format_path, nuts
nuts = []
if values[2] is not None:
nuts.append(model.Nut(values_nocheck=values[1:]))
format_path = values[:2]
if format_path is not None:
yield format_path, nuts
return GeneratorWithLen(gen(), nfiles)
[docs] def flag_modified(self, check=True):
'''
Mark files which have been modified.
:param check:
If ``True`` query modification times of known files on disk. If
``False``, only flag unknown files.
Assumes file state is 0 for newly added files, 1 for files added again
to the selection (forces check), or 2 for all others (no checking is
done for those).
Sets file state to 0 for unknown or modified files, 2 for known and not
modified files.
'''
sql = self._sql('''
UPDATE %(db)s.%(file_states)s
SET file_state = 0
WHERE (
SELECT mtime
FROM files
WHERE files.file_id == %(db)s.%(file_states)s.file_id) IS NULL
AND file_state == 1
''')
self._conn.execute(sql)
if not check:
sql = self._sql('''
UPDATE %(db)s.%(file_states)s
SET file_state = 2
WHERE file_state == 1
''')
self._conn.execute(sql)
return
def iter_file_states():
sql = self._sql('''
SELECT
files.file_id,
files.path,
files.format,
files.mtime,
files.size
FROM %(db)s.%(file_states)s
INNER JOIN files
ON %(db)s.%(file_states)s.file_id == files.file_id
WHERE %(db)s.%(file_states)s.file_state == 1
ORDER BY %(db)s.%(file_states)s.file_id
''')
for (file_id, path, fmt, mtime_db,
size_db) in self._conn.execute(sql):
try:
mod = io.get_backend(fmt)
file_stats = mod.get_stats(path)
except FileLoadError:
yield 0, file_id
continue
except io.UnknownFormat:
continue
if (mtime_db, size_db) != file_stats:
yield 0, file_id
else:
yield 2, file_id
# could better use callback function here...
sql = self._sql('''
UPDATE %(db)s.%(file_states)s
SET file_state = ?
WHERE file_id = ?
''')
self._conn.executemany(sql, iter_file_states())
[docs]class SquirrelStats(Object):
'''
Container to hold statistics about contents available from a Squirrel.
See also :py:meth:`Squirrel.get_stats`.
'''
nfiles = Int.T(
help='Number of files in selection.')
nnuts = Int.T(
help='Number of index nuts in selection.')
codes = List.T(
Tuple.T(content_t=String.T()),
help='Available code sequences in selection, e.g. '
'(agency, network, station, location) for stations nuts.')
kinds = List.T(
String.T(),
help='Available content types in selection.')
total_size = Int.T(
help='Aggregated file size of files is selection.')
counts = Dict.T(
String.T(), Dict.T(Tuple.T(content_t=String.T()), Int.T()),
help='Breakdown of how many nuts of any content type and code '
'sequence are available in selection, ``counts[kind][codes]``.')
tmin = Timestamp.T(
optional=True,
help='Earliest start time of all nuts in selection.')
tmax = Timestamp.T(
optional=True,
help='Latest end time of all nuts in selection.')
def __str__(self):
kind_counts = dict(
(kind, sum(self.counts[kind].values())) for kind in self.kinds)
codes = ['.'.join(x) for x in self.codes]
if len(codes) > 20:
scodes = '\n' + util.ewrap(codes[:10], indent=' ') \
+ '\n [%i more]\n' % (len(codes) - 20) \
+ util.ewrap(codes[-10:], indent=' ')
else:
scodes = '\n' + util.ewrap(codes, indent=' ') \
if codes else '<none>'
stmin = util.tts(self.tmin) if self.tmin is not None else '<none>'
stmax = util.tts(self.tmax) if self.tmax is not None else '<none>'
s = '''
Available codes: %s
Number of files: %i
Total size of known files: %s
Number of index nuts: %i
Available content kinds: %s
Time span of indexed contents: %s - %s''' % (
scodes,
self.nfiles,
util.human_bytesize(self.total_size),
self.nnuts,
', '.join('%s: %i' % (
kind, kind_counts[kind]) for kind in sorted(self.kinds)),
stmin, stmax)
return s
[docs]class Squirrel(Selection):
'''
Prompt, lazy, indexing, caching, dynamic seismological dataset access.
:param env:
Squirrel environment instance or directory path to use as starting
point for its detection. By default, the current directory is used as
starting point. When searching for a usable environment the directory
``'.squirrel'`` or ``'squirrel'`` in the current (or starting point)
directory is used if it exists, otherwise the parent directories are
search upwards for the existence of such a directory. If no such
directory is found, the user's global Squirrel environment
``'$HOME/.pyrocko/squirrel'`` is used.
:type env:
:py:class:`SquirrelEnvironment` or :py:class:`str`
:param database:
Database instance or path to database. By default the
database found in the detected Squirrel environment is used.
:type database:
:py:class:`Database` or :py:class:`str`
:param cache_path:
Directory path to use for data caching. By default, the ``'cache'``
directory in the detected Squirrel environment is used.
:type cache_path:
:py:class:`str`
:param persistent:
If given a name, create a persistent selection.
:type persistent:
:py:class:`str`
Provides a unified interface to query seismic waveforms, station and sensor
metadata, and event information from local file collections and remote data
sources. Query results are promptly returned, even for very large
collections, thanks to a highly optimized database setup working behind the
scenes. Assemblage of a data selection is very fast for known files as all
content indices are cached in a database. Unknown files are automatically
indexed when added to the selection.
Features
- Efficient[1] lookup of data relevant for a selected time window.
- Metadata caching and indexing.
- Modified files are re-indexed as needed.
- SQL database (sqlite) is used behind the scenes.
- Can handle selections with millions of files.
- Data can be added and removed at run-time, efficiently[1].
- Just-in-time download of missing data.
- Disk-cache of meta-data query results with expiration time.
- Efficient event catalog synchronization.
- Always-up-to-date data coverage indices.
- Always-up-to-date indices of available station/channel codes.
[1] O log N performance, where N is the number of data entities (nuts).
Queries are restricted to the contents offered by the files which have
been added to the Squirrel (which usually is a subset of the information
collected in the attached global file meta-information database).
By default, temporary tables are created in the attached database to hold
the names of the files in the selection as well as various indices and
counters. These tables are only visible inside the application which
created it. If a name is given to ``persistent``, a named selection is
created, which is visible also in other applications using the same
database.
Paths of files can be added to the selection using the
:py:meth:`add` method.
'''
def __init__(
self, env=None, database=None, cache_path=None, persistent=None):
if not isinstance(env, environment.SquirrelEnvironment):
env = environment.get_environment(env)
if database is None:
database = env.database_path
if cache_path is None:
cache_path = env.cache_path
if persistent is None:
persistent = env.persistent
Selection.__init__(self, database=database, persistent=persistent)
c = self._conn
self._content_caches = {
'waveform': cache.ContentCache(),
'default': cache.ContentCache()}
self._cache_path = cache_path
self._pile = None
self._names.update({
'nuts': self.name + '_nuts',
'kind_codes_count': self.name + '_kind_codes_count',
'coverage': self.name + '_coverage'})
c.execute(self._register_table(self._sql(
'''
CREATE TABLE IF NOT EXISTS %(db)s.%(nuts)s (
nut_id integer PRIMARY KEY,
file_id integer,
file_segment integer,
file_element integer,
kind_id integer,
kind_codes_id integer,
tmin_seconds integer,
tmin_offset integer,
tmax_seconds integer,
tmax_offset integer,
kscale integer)
''')))
c.execute(self._register_table(self._sql(
'''
CREATE TABLE IF NOT EXISTS %(db)s.%(kind_codes_count)s (
kind_codes_id integer PRIMARY KEY,
count integer)
''')))
c.execute(self._sql(
'''
CREATE UNIQUE INDEX IF NOT EXISTS %(db)s.%(nuts)s_file_element
ON %(nuts)s (file_id, file_segment, file_element)
'''))
c.execute(self._sql(
'''
CREATE INDEX IF NOT EXISTS %(db)s.%(nuts)s_index_file_id
ON %(nuts)s (file_id)
'''))
c.execute(self._sql(
'''
CREATE INDEX IF NOT EXISTS %(db)s.%(nuts)s_index_tmin_seconds
ON %(nuts)s (tmin_seconds)
'''))
c.execute(self._sql(
'''
CREATE INDEX IF NOT EXISTS %(db)s.%(nuts)s_index_tmax_seconds
ON %(nuts)s (tmax_seconds)
'''))
c.execute(self._sql(
'''
CREATE INDEX IF NOT EXISTS %(db)s.%(nuts)s_index_kscale
ON %(nuts)s (kind_id, kscale, tmin_seconds)
'''))
c.execute(self._sql(
'''
CREATE TRIGGER IF NOT EXISTS %(db)s.%(nuts)s_delete_nuts
BEFORE DELETE ON main.files FOR EACH ROW
BEGIN
DELETE FROM %(nuts)s WHERE file_id == old.file_id;
END
'''))
# trigger only on size to make silent update of mtime possible
c.execute(self._sql(
'''
CREATE TRIGGER IF NOT EXISTS %(db)s.%(nuts)s_delete_nuts2
BEFORE UPDATE OF size ON main.files FOR EACH ROW
BEGIN
DELETE FROM %(nuts)s WHERE file_id == old.file_id;
END
'''))
c.execute(self._sql(
'''
CREATE TRIGGER IF NOT EXISTS
%(db)s.%(file_states)s_delete_files
BEFORE DELETE ON %(db)s.%(file_states)s FOR EACH ROW
BEGIN
DELETE FROM %(nuts)s WHERE file_id == old.file_id;
END
'''))
c.execute(self._sql(
'''
CREATE TRIGGER IF NOT EXISTS %(db)s.%(nuts)s_inc_kind_codes
BEFORE INSERT ON %(nuts)s FOR EACH ROW
BEGIN
INSERT OR IGNORE INTO %(kind_codes_count)s VALUES
(new.kind_codes_id, 0);
UPDATE %(kind_codes_count)s
SET count = count + 1
WHERE new.kind_codes_id
== %(kind_codes_count)s.kind_codes_id;
END
'''))
c.execute(self._sql(
'''
CREATE TRIGGER IF NOT EXISTS %(db)s.%(nuts)s_dec_kind_codes
BEFORE DELETE ON %(nuts)s FOR EACH ROW
BEGIN
UPDATE %(kind_codes_count)s
SET count = count - 1
WHERE old.kind_codes_id
== %(kind_codes_count)s.kind_codes_id;
END
'''))
c.execute(self._register_table(self._sql(
'''
CREATE TABLE IF NOT EXISTS %(db)s.%(coverage)s (
kind_codes_id integer,
time_seconds integer,
time_offset integer,
step integer)
''')))
c.execute(self._sql(
'''
CREATE UNIQUE INDEX IF NOT EXISTS %(db)s.%(coverage)s_time
ON %(coverage)s (kind_codes_id, time_seconds, time_offset)
'''))
c.execute(self._sql(
'''
CREATE TRIGGER IF NOT EXISTS %(db)s.%(nuts)s_add_coverage
AFTER INSERT ON %(nuts)s FOR EACH ROW
BEGIN
INSERT OR IGNORE INTO %(coverage)s VALUES
(new.kind_codes_id, new.tmin_seconds, new.tmin_offset, 0)
;
UPDATE %(coverage)s
SET step = step + 1
WHERE new.kind_codes_id == %(coverage)s.kind_codes_id
AND new.tmin_seconds == %(coverage)s.time_seconds
AND new.tmin_offset == %(coverage)s.time_offset
;
INSERT OR IGNORE INTO %(coverage)s VALUES
(new.kind_codes_id, new.tmax_seconds, new.tmax_offset, 0)
;
UPDATE %(coverage)s
SET step = step - 1
WHERE new.kind_codes_id == %(coverage)s.kind_codes_id
AND new.tmax_seconds == %(coverage)s.time_seconds
AND new.tmax_offset == %(coverage)s.time_offset
;
DELETE FROM %(coverage)s
WHERE new.kind_codes_id == %(coverage)s.kind_codes_id
AND new.tmin_seconds == %(coverage)s.time_seconds
AND new.tmin_offset == %(coverage)s.time_offset
AND step == 0
;
DELETE FROM %(coverage)s
WHERE new.kind_codes_id == %(coverage)s.kind_codes_id
AND new.tmax_seconds == %(coverage)s.time_seconds
AND new.tmax_offset == %(coverage)s.time_offset
AND step == 0
;
END
'''))
c.execute(self._sql(
'''
CREATE TRIGGER IF NOT EXISTS %(db)s.%(nuts)s_remove_coverage
BEFORE DELETE ON %(nuts)s FOR EACH ROW
BEGIN
INSERT OR IGNORE INTO %(coverage)s VALUES
(old.kind_codes_id, old.tmin_seconds, old.tmin_offset, 0)
;
UPDATE %(coverage)s
SET step = step - 1
WHERE old.kind_codes_id == %(coverage)s.kind_codes_id
AND old.tmin_seconds == %(coverage)s.time_seconds
AND old.tmin_offset == %(coverage)s.time_offset
;
INSERT OR IGNORE INTO %(coverage)s VALUES
(old.kind_codes_id, old.tmax_seconds, old.tmax_offset, 0)
;
UPDATE %(coverage)s
SET step = step + 1
WHERE old.kind_codes_id == %(coverage)s.kind_codes_id
AND old.tmax_seconds == %(coverage)s.time_seconds
AND old.tmax_offset == %(coverage)s.time_offset
;
DELETE FROM %(coverage)s
WHERE old.kind_codes_id == %(coverage)s.kind_codes_id
AND old.tmin_seconds == %(coverage)s.time_seconds
AND old.tmin_offset == %(coverage)s.time_offset
AND step == 0
;
DELETE FROM %(coverage)s
WHERE old.kind_codes_id == %(coverage)s.kind_codes_id
AND old.tmax_seconds == %(coverage)s.time_seconds
AND old.tmax_offset == %(coverage)s.time_offset
AND step == 0
;
END
'''))
def _delete(self):
'''Delete database tables associated with this Squirrel.'''
for s in '''
DROP TRIGGER %(db)s.%(nuts)s_delete_nuts;
DROP TRIGGER %(db)s.%(nuts)s_delete_nuts2;
DROP TRIGGER %(db)s.%(file_states)s_delete_files;
DROP TRIGGER %(db)s.%(nuts)s_inc_kind_codes;
DROP TRIGGER %(db)s.%(nuts)s_dec_kind_codes;
DROP TABLE %(db)s.%(nuts)s;
DROP TABLE %(db)s.%(kind_codes_count)s;
DROP TRIGGER IF EXISTS %(db)s.%(nuts)s_add_coverage;
DROP TRIGGER IF EXISTS %(db)s.%(nuts)s_remove_coverage;
DROP TABLE IF EXISTS %(db)s.%(coverage)s;
'''.strip().splitlines():
self._conn.execute(self._sql(s))
Selection._delete(self)
self._conn.commit()
[docs] def add(self,
paths,
kinds=None,
format='detect',
check=True,
progress_viewer='terminal'):
'''
Add files to the selection.
:param paths:
Iterator yielding paths to files or directories to be added to the
selection. Recurses into directories. If given a ``str``, it
is treated as a single path to be added.
:type paths:
:py:class:`list` of :py:class:`str`
:param kinds:
Content types to be made available through the Squirrel selection.
By default, all known content types are accepted.
:type kinds:
:py:class:`list` of :py:class:`str`
:param format:
File format identifier or ``'detect'`` to enable auto-detection.
:type format:
:py:class:`str`
Complexity: O(log N)
'''
if isinstance(kinds, str):
kinds = (kinds,)
if isinstance(paths, str):
paths = [paths]
kind_mask = model.to_kind_mask(kinds)
with progress.view(progress_viewer):
Selection.add(
self, util.iter_select_files(
paths,
show_progress=False,
pass_through=lambda path: path.startswith('virtual:')
), kind_mask, format)
self._load(check)
self._update_nuts()
[docs] def reload(self):
'''
Check for modifications and reindex modified files.
Based on file modification times.
'''
self._set_file_states_force_check()
self._load(check=True)
self._update_nuts()
[docs] def add_virtual(self, nuts, virtual_paths=None):
'''
Add content which is not backed by files.
:param nuts:
Content pieces to be added.
:type nuts:
iterator yielding :py:class:`~pyrocko.squirrel.Nut` objects
:param virtual_paths:
List of virtual paths to prevent creating a temporary list of the
nuts while aggregating the file paths for the selection.
:type virtual_paths:
:py:class:`list` of :py:class:`str`
Stores to the main database and the selection.
'''
if isinstance(virtual_paths, str):
virtual_paths = [virtual_paths]
if virtual_paths is None:
nuts_add = []
virtual_paths = set()
for nut in nuts:
virtual_paths.add(nut.file_path)
nuts_add.append(nut)
else:
nuts_add = nuts
Selection.add(self, virtual_paths)
self.get_database().dig(nuts_add)
self._update_nuts()
def _load(self, check):
for _ in io.iload(
self,
content=[],
skip_unchanged=True,
check=check):
pass
def _update_nuts(self):
task = make_task('Aggregating selection')
self._conn.set_progress_handler(task.update, 100000)
nrows = self._conn.execute(self._sql(
'''
INSERT INTO %(db)s.%(nuts)s
SELECT NULL,
nuts.file_id, nuts.file_segment, nuts.file_element,
nuts.kind_id, nuts.kind_codes_id,
nuts.tmin_seconds, nuts.tmin_offset,
nuts.tmax_seconds, nuts.tmax_offset,
nuts.kscale
FROM %(db)s.%(file_states)s
INNER JOIN nuts
ON %(db)s.%(file_states)s.file_id == nuts.file_id
INNER JOIN kind_codes
ON nuts.kind_codes_id ==
kind_codes.kind_codes_id
WHERE %(db)s.%(file_states)s.file_state != 2
AND (((1 << kind_codes.kind_id)
& %(db)s.%(file_states)s.kind_mask) != 0)
''')).rowcount
task.update(nrows)
self._set_file_states_known()
self._conn.set_progress_handler(None, 0)
task.done()
[docs] def add_source(self, source):
'''
Add remote resource.
:param source:
Remote data access client instance.
:type source:
subclass of :py:class:`~pyrocko.squirrel.Source`
'''
self._sources.append(source)
source.setup(self)
[docs] def add_fdsn(self, *args, **kwargs):
'''
Add FDSN site for transparent remote data access.
Arguments are passed to :py:class:`~pyrocko.squirrel.FDSNSource`.
'''
self.add_source(fdsn.FDSNSource(*args, **kwargs))
[docs] def add_catalog(self, *args, **kwargs):
'''
Add online catalog for transparent event data access.
Arguments are passed to :py:class:`~pyrocko.squirrel.CatalogSource`.
'''
self.add_source(catalog.CatalogSource(*args, **kwargs))
def _get_selection_args(
self, obj=None, tmin=None, tmax=None, time=None, codes=None):
if time is not None:
tmin = time
tmax = time
if obj is not None:
tmin = tmin if tmin is not None else obj.tmin
tmax = tmax if tmax is not None else obj.tmax
codes = codes if codes is not None else obj.codes
if isinstance(codes, str):
codes = tuple(codes.split('.'))
return tmin, tmax, codes
[docs] def iter_nuts(
self, kind=None, tmin=None, tmax=None, codes=None, naiv=False,
kind_codes_ids=None):
'''
Iterate content entities matching given constraints.
:param kind:
Content kind (or kinds) to extract.
:type kind:
:py:class:`str`, :py:class:`list` of :py:class:`str`
:param tmin:
Start time of query interval.
:type tmin:
timestamp
:param tmax:
End time of query interval.
:type tmax:
timestamp
:param codes:
Pattern of content codes to be matched.
:type codes:
:py:class:`tuple` of :py:class:`str`
:param naiv:
Bypass time span lookup through indices (slow, for testing).
:type naiv:
:py:class:`bool`
:param kind_codes_ids:
Kind-codes IDs of contents to be retrieved (internal use).
:type kind_codes_ids:
:py:class:`list` of :py:class:`str`
Complexity: O(log N) for the time selection part due to heavy use of
database indices.
Yields :py:class:`~pyrocko.squirrel.Nut` objects representing the
intersecting content.
Query time span is treated as a half-open interval ``[tmin, tmax)``.
However, if ``tmin`` equals ``tmax``, the edge logics are modified to
closed-interval so that content intersecting with the time instant ``t
= tmin = tmax`` is returned (otherwise nothing would be returned as
``[t, t)`` never matches anything).
Time spans of content entities to be matched are also treated as half
open intervals, e.g. content span ``[0, 1)`` is matched by query span
``[0, 1)`` but not by ``[-1, 0)`` or ``[1, 2)``. Also here, logics are
modified to closed-interval when the content time span is an empty
interval, i.e. to indicate a time instant. E.g. time instant 0 is
matched by ``[0, 1)`` but not by ``[-1, 0)`` or ``[1, 2)``.
'''
if not isinstance(kind, str):
if kind is None:
kind = model.g_content_kinds
for kind_ in kind:
for nut in self.iter_nuts(kind_, tmin, tmax, codes):
yield nut
return
extra_cond = []
tmin_cond = []
args = []
if tmin is not None or tmax is not None:
assert kind is not None
if tmin is None:
tmin = self.get_time_span()[0]
if tmax is None:
tmax = self.get_time_span()[1] + 1.0
tmin_seconds, tmin_offset = model.tsplit(tmin)
tmax_seconds, tmax_offset = model.tsplit(tmax)
if naiv:
extra_cond.append('%(db)s.%(nuts)s.tmin_seconds <= ?')
args.append(tmax_seconds)
else:
tscale_edges = model.tscale_edges
for kscale in range(tscale_edges.size + 1):
if kscale != tscale_edges.size:
tscale = int(tscale_edges[kscale])
tmin_cond.append('''
(%(db)s.%(nuts)s.kind_id = ?
AND %(db)s.%(nuts)s.kscale == ?
AND %(db)s.%(nuts)s.tmin_seconds BETWEEN ? AND ?)
''')
args.extend(
(to_kind_id(kind), kscale,
tmin_seconds - tscale - 1, tmax_seconds + 1))
else:
tmin_cond.append('''
(%(db)s.%(nuts)s.kind_id == ?
AND %(db)s.%(nuts)s.kscale == ?
AND %(db)s.%(nuts)s.tmin_seconds <= ?)
''')
args.extend(
(to_kind_id(kind), kscale, tmax_seconds + 1))
extra_cond.append('%(db)s.%(nuts)s.tmax_seconds >= ?')
args.append(tmin_seconds)
elif kind is not None:
extra_cond.append('kind_codes.kind_id == ?')
args.append(to_kind_id(kind))
if codes is not None:
pats = codes_patterns_for_kind(kind, codes)
if pats:
extra_cond.append(
' ( %s ) ' % ' OR '.join(
('kind_codes.codes GLOB ?',) * len(pats)))
args.extend(separator.join(pat) for pat in pats)
if kind_codes_ids is not None:
extra_cond.append(
' ( kind_codes.kind_codes_id IN ( %s ) ) ' % ', '.join(
'?'*len(kind_codes_ids)))
args.extend(kind_codes_ids)
sql = ('''
SELECT
files.path,
files.format,
files.mtime,
files.size,
%(db)s.%(nuts)s.file_segment,
%(db)s.%(nuts)s.file_element,
kind_codes.kind_id,
kind_codes.codes,
%(db)s.%(nuts)s.tmin_seconds,
%(db)s.%(nuts)s.tmin_offset,
%(db)s.%(nuts)s.tmax_seconds,
%(db)s.%(nuts)s.tmax_offset,
kind_codes.deltat
FROM files
INNER JOIN %(db)s.%(nuts)s
ON files.file_id == %(db)s.%(nuts)s.file_id
INNER JOIN kind_codes
ON %(db)s.%(nuts)s.kind_codes_id == kind_codes.kind_codes_id
''')
cond = []
if tmin_cond:
cond.append(' ( ' + ' OR '.join(tmin_cond) + ' ) ')
cond.extend(extra_cond)
if cond:
sql += ''' WHERE ''' + ' AND '.join(cond)
sql = self._sql(sql)
if tmin is None and tmax is None:
for row in self._conn.execute(sql, args):
nut = model.Nut(values_nocheck=row)
yield nut
else:
assert tmin is not None and tmax is not None
if tmin == tmax:
for row in self._conn.execute(sql, args):
nut = model.Nut(values_nocheck=row)
if (nut.tmin <= tmin < nut.tmax) \
or (nut.tmin == nut.tmax and tmin == nut.tmin):
yield nut
else:
for row in self._conn.execute(sql, args):
nut = model.Nut(values_nocheck=row)
if (tmin < nut.tmax and nut.tmin < tmax) \
or (nut.tmin == nut.tmax
and tmin <= nut.tmin < tmax):
yield nut
[docs] def get_nuts(self, *args, **kwargs):
'''
Get content entities matching given constraints.
Like :py:meth:`iter_nuts` but returns results as a list.
'''
return list(self.iter_nuts(*args, **kwargs))
def _split_nuts(
self, kind, tmin=None, tmax=None, codes=None, path=None):
tmin_seconds, tmin_offset = model.tsplit(tmin)
tmax_seconds, tmax_offset = model.tsplit(tmax)
tscale_edges = model.tscale_edges
tmin_cond = []
args = []
for kscale in range(tscale_edges.size + 1):
if kscale != tscale_edges.size:
tscale = int(tscale_edges[kscale])
tmin_cond.append('''
(%(db)s.%(nuts)s.kind_id = ?
AND %(db)s.%(nuts)s.kscale == ?
AND %(db)s.%(nuts)s.tmin_seconds BETWEEN ? AND ?)
''')
args.extend(
(to_kind_id(kind), kscale,
tmin_seconds - tscale - 1, tmax_seconds + 1))
else:
tmin_cond.append('''
(%(db)s.%(nuts)s.kind_id == ?
AND %(db)s.%(nuts)s.kscale == ?
AND %(db)s.%(nuts)s.tmin_seconds <= ?)
''')
args.extend(
(to_kind_id(kind), kscale, tmax_seconds + 1))
extra_cond = ['%(db)s.%(nuts)s.tmax_seconds >= ?']
args.append(tmin_seconds)
if codes is not None:
pats = codes_patterns_for_kind(kind, codes)
if pats:
extra_cond.append(
' ( %s ) ' % ' OR '.join(
('kind_codes.codes GLOB ?',) * len(pats)))
args.extend(separator.join(pat) for pat in pats)
if path is not None:
extra_cond.append('files.path == ?')
args.append(path)
sql = self._sql('''
SELECT
%(db)s.%(nuts)s.nut_id,
%(db)s.%(nuts)s.tmin_seconds,
%(db)s.%(nuts)s.tmin_offset,
%(db)s.%(nuts)s.tmax_seconds,
%(db)s.%(nuts)s.tmax_offset,
kind_codes.deltat
FROM files
INNER JOIN %(db)s.%(nuts)s
ON files.file_id == %(db)s.%(nuts)s.file_id
INNER JOIN kind_codes
ON %(db)s.%(nuts)s.kind_codes_id == kind_codes.kind_codes_id
WHERE ( ''' + ' OR '.join(tmin_cond) + ''' )
AND ''' + ' AND '.join(extra_cond))
insert = []
delete = []
for row in self._conn.execute(sql, args):
nut_id, nut_tmin_seconds, nut_tmin_offset, \
nut_tmax_seconds, nut_tmax_offset, nut_deltat = row
nut_tmin = model.tjoin(
nut_tmin_seconds, nut_tmin_offset, nut_deltat)
nut_tmax = model.tjoin(
nut_tmax_seconds, nut_tmax_offset, nut_deltat)
if nut_tmin < tmax and tmin < nut_tmax:
if nut_tmin < tmin:
insert.append((
nut_tmin_seconds, nut_tmin_offset,
tmin_seconds, tmin_offset,
model.tscale_to_kscale(
tmin_seconds - nut_tmin_seconds),
nut_id))
if tmax < nut_tmax:
insert.append((
tmax_seconds, tmax_offset,
nut_tmax_seconds, nut_tmax_offset,
model.tscale_to_kscale(
nut_tmax_seconds - tmax_seconds),
nut_id))
delete.append((nut_id,))
sql_add = '''
INSERT INTO %(db)s.%(nuts)s (
file_id, file_segment, file_element, kind_id,
kind_codes_id, tmin_seconds, tmin_offset,
tmax_seconds, tmax_offset, kscale )
SELECT
file_id, file_segment, file_element,
kind_id, kind_codes_id, ?, ?, ?, ?, ?
FROM %(db)s.%(nuts)s
WHERE nut_id == ?
'''
self._conn.executemany(self._sql(sql_add), insert)
sql_delete = '''DELETE FROM %(db)s.%(nuts)s WHERE nut_id == ?'''
self._conn.executemany(self._sql(sql_delete), delete)
[docs] def get_time_span(self):
'''
Get time interval over all content in selection.
Complexity O(1), independent of the number of nuts.
:returns: (tmin, tmax)
'''
sql = self._sql('''
SELECT MIN(tmin_seconds), MIN(tmin_offset)
FROM %(db)s.%(nuts)s WHERE
tmin_seconds == (SELECT MIN(tmin_seconds) FROM %(db)s.%(nuts)s)
''')
tmin = None
for tmin_seconds, tmin_offset in self._conn.execute(sql):
tmin = model.tjoin(tmin_seconds, tmin_offset, 0.0)
sql = self._sql('''
SELECT MAX(tmax_seconds), MAX(tmax_offset)
FROM %(db)s.%(nuts)s WHERE
tmax_seconds == (SELECT MAX(tmax_seconds) FROM %(db)s.%(nuts)s)
''')
tmax = None
for (tmax_seconds, tmax_offset) in self._conn.execute(sql):
tmax = model.tjoin(tmax_seconds, tmax_offset, 0.0)
return tmin, tmax
[docs] def get_deltat_span(self, kind):
'''
Get min and max sampling interval of all content of given kind.
:param kind: Content kind
:type kind: :py:class:`str`
:returns: (deltat_min, deltat_max)
'''
deltats = [
deltat for deltat in self.get_deltats(kind)
if deltat is not None]
if deltats:
return min(deltats), max(deltats)
else:
return None, None
def get_waveform_deltat_span(self):
return self.get_deltat_span('waveform')
[docs] def iter_kinds(self, codes=None):
'''
Iterate over content types available in selection.
:param codes: if given, get kinds only for selected codes identifier
Complexity: O(1), independent of number of nuts
'''
return self._database._iter_kinds(
codes=codes,
kind_codes_count='%(db)s.%(kind_codes_count)s' % self._names)
[docs] def iter_deltats(self, kind=None):
'''
Iterate over sampling intervals available in selection.
:param kind: if given, get sampling intervals only for a given content
type
:type kind: :py:class:`str`
Complexity: O(1), independent of number of nuts
'''
return self._database._iter_deltats(
kind=kind,
kind_codes_count='%(db)s.%(kind_codes_count)s' % self._names)
[docs] def iter_codes(self, kind=None):
'''
Iterate over content identifier code sequences available in selection.
:param kind: if given, get codes only for a given content type
:type kind: :py:class:`str`
Complexity: O(1), independent of number of nuts
'''
return self._database._iter_codes(
kind=kind,
kind_codes_count='%(db)s.%(kind_codes_count)s' % self._names)
[docs] def iter_counts(self, kind=None):
'''
Iterate over number of occurrences of any (kind, codes) combination.
:param kind: if given, get counts only for selected content type
Yields tuples ``((kind, codes), count)``
Complexity: O(1), independent of number of nuts
'''
return self._database._iter_counts(
kind=kind,
kind_codes_count='%(db)s.%(kind_codes_count)s' % self._names)
[docs] def get_kinds(self, codes=None):
'''
Get content types available in selection.
:param codes: if given, get kinds only for selected codes identifier
Complexity: O(1), independent of number of nuts
:returns: sorted list of available content types
'''
return sorted(list(self.iter_kinds(codes=codes)))
[docs] def get_deltats(self, kind=None):
'''
Get sampling intervals available in selection.
:param kind: if given, get codes only for selected content type
Complexity: O(1), independent of number of nuts
:returns: sorted list of available sampling intervals
'''
return sorted(list(self.iter_deltats(kind=kind)))
[docs] def get_codes(self, kind=None):
'''
Get identifier code sequences available in selection.
:param kind: if given, get codes only for selected content type
Complexity: O(1), independent of number of nuts
:returns: sorted list of available codes as tuples of strings
'''
return sorted(list(self.iter_codes(kind=kind)))
[docs] def get_counts(self, kind=None):
'''
Get number of occurrences of any (kind, codes) combination.
:param kind: if given, get codes only for selected content type
Complexity: O(1), independent of number of nuts
:returns: ``dict`` with ``counts[kind][codes] or ``counts[codes]``
if kind is not ``None``
'''
d = {}
for (k, codes, deltat), count in self.iter_counts():
if k not in d:
v = d[k] = {}
else:
v = d[k]
if codes not in v:
v[codes] = 0
v[codes] += count
if kind is not None:
return d[kind]
else:
return d
def resolve_kind_codes(self, kind, codes_list):
args = [to_kind_id(kind)]
pats = []
for codes in codes_list:
pats.extend(codes_patterns_for_kind(kind, codes))
codes_cond = ' ( %s ) ' % ' OR '.join(
('kind_codes.codes GLOB ?',) * len(pats))
args.extend(separator.join(pat) for pat in pats)
sql = self._sql('''
SELECT kind_codes_id, codes, deltat FROM kind_codes
WHERE
kind_id == ?
AND ''' + codes_cond)
return list(map(list, self._conn.execute(sql, args)))
[docs] def update(self, constraint=None, **kwargs):
'''
Update inventory of remote content for a given selection.
This function triggers all attached remote sources, to check for
updates in the metadata. The sources will only submit queries when
their expiration date has passed, or if the selection spans into
previously unseen times or areas.
'''
if constraint is None:
constraint = client.Constraint(**kwargs)
for source in self._sources:
source.update_channel_inventory(self, constraint)
source.update_event_inventory(self, constraint)
def update_waveform_promises(self, constraint=None, **kwargs):
if constraint is None:
constraint = client.Constraint(**kwargs)
for source in self._sources:
source.update_waveform_promises(self, constraint)
[docs] def get_nfiles(self):
'''
Get number of files in selection.
'''
sql = self._sql('''SELECT COUNT(*) FROM %(db)s.%(file_states)s''')
for row in self._conn.execute(sql):
return row[0]
[docs] def get_nnuts(self):
'''
Get number of nuts in selection.
'''
sql = self._sql('''SELECT COUNT(*) FROM %(db)s.%(nuts)s''')
for row in self._conn.execute(sql):
return row[0]
[docs] def get_total_size(self):
'''
Get aggregated file size available in selection.
'''
sql = self._sql('''
SELECT SUM(files.size) FROM %(db)s.%(file_states)s
INNER JOIN files
ON %(db)s.%(file_states)s.file_id = files.file_id
''')
for row in self._conn.execute(sql):
return row[0] or 0
[docs] def get_stats(self):
'''
Get statistics on contents available through this selection.
'''
tmin, tmax = self.get_time_span()
return SquirrelStats(
nfiles=self.get_nfiles(),
nnuts=self.get_nnuts(),
kinds=self.get_kinds(),
codes=self.get_codes(),
total_size=self.get_total_size(),
counts=self.get_counts(),
tmin=tmin,
tmax=tmax)
[docs] def get_content(self, nut, cache='default', accessor='default'):
'''
Get and possibly load full content for a given index entry from file.
Loads the actual content objects (channel, station, waveform, ...) from
file. For efficiency sibling content (all stuff in the same file
segment) will also be loaded as a side effect. The loaded contents are
cached in the Squirrel object.
'''
content_cache = self._content_caches[cache]
if not content_cache.has(nut):
for nut_loaded in io.iload(
nut.file_path,
segment=nut.file_segment,
format=nut.file_format,
database=self._database):
content_cache.put(nut_loaded)
try:
return content_cache.get(nut, accessor)
except KeyError:
raise error.NotAvailable(
'Unable to retrieve content: %s, %s, %s, %s' % nut.key)
def advance_accessor(self, accessor, cache=None):
for cache_ in (
self._content_caches.keys() if cache is None else [cache]):
self._content_caches[cache_].advance_accessor(accessor)
def clear_accessor(self, accessor, cache=None):
for cache_ in (
self._content_caches.keys() if cache is None else [cache]):
self._content_caches[cache_].clear_accessor(accessor)
def check_duplicates(self, nuts):
d = defaultdict(list)
for nut in nuts:
d[nut.codes].append(nut)
for codes, group in d.items():
if len(group) > 1:
logger.warn(
'Multiple entries matching codes %s'
% '.'.join(codes.split(separator)))
def get_stations(self, *args, **kwargs):
args = self._get_selection_args(*args, **kwargs)
nuts = sorted(
self.iter_nuts('station', *args), key=lambda nut: nut.dkey)
self.check_duplicates(nuts)
return [self.get_content(nut) for nut in nuts]
def get_channels(self, *args, **kwargs):
args = self._get_selection_args(*args, **kwargs)
nuts = sorted(
self.iter_nuts('channel', *args), key=lambda nut: nut.dkey)
self.check_duplicates(nuts)
return [self.get_content(nut) for nut in nuts]
def get_events(self, *args, **kwargs):
args = self._get_selection_args(*args, **kwargs)
nuts = sorted(
self.iter_nuts('event', *args), key=lambda nut: nut.dkey)
self.check_duplicates(nuts)
return [self.get_content(nut) for nut in nuts]
def _redeem_promises(self, *args):
tmin, tmax, _ = args
waveforms = list(self.iter_nuts('waveform', *args))
promises = list(self.iter_nuts('waveform_promise', *args))
codes_to_avail = defaultdict(list)
for nut in waveforms:
codes_to_avail[nut.codes].append((nut.tmin, nut.tmax+nut.deltat))
def tts(x):
if isinstance(x, tuple):
return tuple(tts(e) for e in x)
elif isinstance(x, list):
return list(tts(e) for e in x)
else:
return util.time_to_str(x)
orders = []
for promise in promises:
waveforms_avail = codes_to_avail[promise.codes]
for block_tmin, block_tmax in blocks(
max(tmin, promise.tmin),
min(tmax, promise.tmax),
promise.deltat):
orders.append(
WaveformOrder(
source_id=promise.file_path,
codes=tuple(promise.codes.split(separator)),
tmin=block_tmin,
tmax=block_tmax,
deltat=promise.deltat,
gaps=gaps(waveforms_avail, block_tmin, block_tmax)))
orders_noop, orders = lpick(lambda order: order.gaps, orders)
order_keys_noop = set(order_key(order) for order in orders_noop)
if len(order_keys_noop) != 0 or len(orders_noop) != 0:
logger.info(
'Waveform orders already satisified with cached/local data: '
'%i (%i)' % (len(order_keys_noop), len(orders_noop)))
source_ids = []
sources = {}
for source in self._sources:
source_ids.append(source._source_id)
sources[source._source_id] = source
source_priority = dict(
(source_id, i) for (i, source_id) in enumerate(source_ids))
order_groups = defaultdict(list)
for order in orders:
order_groups[order_key(order)].append(order)
for k, order_group in order_groups.items():
order_group.sort(
key=lambda order: source_priority[order.source_id])
if len(order_groups) != 0 or len(orders) != 0:
logger.info(
'Waveform orders standing for download: %i (%i)'
% (len(order_groups), len(orders)))
def release_order_group(order):
del order_groups[order_key(order)]
def split_promise(order):
self._split_nuts(
'waveform_promise',
order.tmin, order.tmax,
codes=order.codes,
path=order.source_id)
def noop(order):
pass
def success(order):
release_order_group(order)
split_promise(order)
for order in orders_noop:
split_promise(order)
while order_groups:
orders_now = []
empty = []
for k, order_group in order_groups.items():
try:
orders_now.append(order_group.pop(0))
except IndexError:
empty.append(k)
for k in empty:
del order_groups[k]
by_source_id = defaultdict(list)
for order in orders_now:
by_source_id[order.source_id].append(order)
# TODO: parallelize this loop
for source_id in by_source_id:
sources[source_id].download_waveforms(
self, by_source_id[source_id],
success=success,
error_permanent=split_promise,
error_temporary=noop)
def get_waveform_nuts(self, *args, **kwargs):
args = self._get_selection_args(*args, **kwargs)
self._redeem_promises(*args)
return sorted(
self.iter_nuts('waveform', *args), key=lambda nut: nut.dkey)
def get_waveforms(self, *args, **kwargs):
nuts = self.get_waveform_nuts(*args, **kwargs)
# self.check_duplicates(nuts)
return [self.get_content(nut, 'waveform') for nut in nuts]
def get_pyrocko_stations(self, *args, **kwargs):
from pyrocko import model as pmodel
by_nsl = defaultdict(lambda: (list(), list()))
for station in self.get_stations(*args, **kwargs):
sargs = station._get_pyrocko_station_args()
nsl = sargs[1:4]
by_nsl[nsl][0].append(sargs)
for channel in self.get_channels(*args, **kwargs):
sargs = channel._get_pyrocko_station_args()
nsl = sargs[1:4]
sargs_list, channels_list = by_nsl[nsl]
sargs_list.append(sargs)
channels_list.append(channel)
pstations = []
nsls = list(by_nsl.keys())
nsls.sort()
for nsl in nsls:
sargs_list, channels_list = by_nsl[nsl]
sargs = util.consistency_merge(sargs_list)
by_c = defaultdict(list)
for ch in channels_list:
by_c[ch.channel].append(ch._get_pyrocko_channel_args())
chas = list(by_c.keys())
chas.sort()
pchannels = []
for cha in chas:
list_of_cargs = by_c[cha]
cargs = util.consistency_merge(list_of_cargs)
pchannels.append(pmodel.Channel(
name=cargs[0],
azimuth=cargs[1],
dip=cargs[2]))
pstations.append(pmodel.Station(
network=sargs[0],
station=sargs[1],
location=sargs[2],
lat=sargs[3],
lon=sargs[4],
elevation=sargs[5],
depth=sargs[6] or 0.0,
channels=pchannels))
return pstations
@property
def pile(self):
if self._pile is None:
self._pile = pile.Pile(self)
return self._pile
def snuffle(self):
self.pile.snuffle()
def gather_codes_keys(self, kind, gather, selector):
return set(
gather(codes)
for codes in self.iter_codes(kind)
if selector is None or selector(codes))
def __str__(self):
return str(self.get_stats())
[docs] def get_coverage(
self, kind, tmin=None, tmax=None, codes_list=None, limit=None):
'''
Get coverage information.
Get information about strips of gapless data coverage.
:param kind:
Content kind to be queried.
:param tmin:
Start time of query interval.
:param tmin:
End time of query interval.
:param codes_list:
List of code patterns to query.
:param limit:
Limit query to return only up to a given maximum number of entries
per matching channel (without setting this option, very gappy data
could cause the query to execute for a very long time).
:returns: list of entries of the form
``(pattern, codes, deltat, tmin, tmax, data)`` where ``pattern`` is
the request pattern which yielded this entry, ``codes`` are the
matching channel codes, ``tmin`` and ``tmax`` are the global min
and max times for which data for this channel is available,
regardless of any time restrictions in the query. ``data`` is
another list with (up to ``limit``) checkpoints of the form
``(time, count)`` where a ``count`` of zero indicates a data gap, a
value of 1 normal data coverage and higher values indicate
duplicate/redundant data.
'''
tmin_seconds, tmin_offset = model.tsplit(tmin)
tmax_seconds, tmax_offset = model.tsplit(tmax)
kdata_all = []
for pattern in codes_list:
kdata = self.resolve_kind_codes(kind, [pattern])
for row in kdata:
row[0:0] = [pattern]
kdata_all.extend(kdata)
kind_codes_ids = [x[1] for x in kdata_all]
counts_at_tmin = {}
if tmin is not None:
for nut in self.iter_nuts(
kind, tmin, tmin, kind_codes_ids=kind_codes_ids):
codes = nut.codes
if codes not in counts_at_tmin:
counts_at_tmin[codes] = 0
counts_at_tmin[codes] += 1
coverage = []
for pattern, kind_codes_id, codes, deltat in kdata_all:
entry = [pattern, codes, deltat, None, None, []]
for i, order in [(0, 'ASC'), (1, 'DESC')]:
sql = self._sql('''
SELECT
time_seconds,
time_offset
FROM %(db)s.%(coverage)s
WHERE
kind_codes_id == ?
ORDER BY
kind_codes_id ''' + order + ''',
time_seconds ''' + order + ''',
time_offset ''' + order + '''
LIMIT 1
''')
for row in self._conn.execute(sql, [kind_codes_id]):
entry[3+i] = model.tjoin(row[0], row[1], deltat)
if None in entry[3:5]:
continue
args = [kind_codes_id]
sql_time = ''
if tmin is not None:
# intentionally < because (== tmin) is queried from nuts
sql_time += ' AND ( ? < time_seconds ' \
'OR ( ? == time_seconds AND ? < time_offset ) ) '
args.extend([tmin_seconds, tmin_seconds, tmin_offset])
if tmax is not None:
sql_time += ' AND ( time_seconds < ? ' \
'OR ( ? == time_seconds AND time_offset < ? ) ) '
args.extend([tmax_seconds, tmax_seconds, tmax_offset])
sql_limit = ''
if limit is not None:
sql_limit = ' LIMIT ?'
args.append(limit)
sql = self._sql('''
SELECT
time_seconds,
time_offset,
step
FROM %(db)s.%(coverage)s
WHERE
kind_codes_id == ?
''' + sql_time + '''
ORDER BY
kind_codes_id,
time_seconds,
time_offset
''' + sql_limit)
rows = list(self._conn.execute(sql, args))
if limit is not None and len(rows) == limit:
entry[-1] = None
else:
counts = counts_at_tmin.get(codes, 0)
if tmin is not None:
entry[-1].append((tmin, counts))
for row in rows:
t = model.tjoin(row[0], row[1], deltat)
counts += row[2]
entry[-1].append((t, counts))
if tmax is not None:
entry[-1].append((tmax, counts))
coverage.append(entry)
return coverage
[docs] def print_tables(self, table_names=None, stream=None):
'''
Dump raw database tables in textual form (for debugging purposes).
:param table_names:
Names of tables to be dumped or ``None`` to dump all.
:type table_names:
:py:class:`list` of :py:class:`str`
:param stream:
Open file or ``None`` to dump to standard output.
'''
if stream is None:
stream = sys.stdout
if isinstance(table_names, str):
table_names = [table_names]
if table_names is None:
table_names = [
'selection_file_states',
'selection_nuts',
'selection_kind_codes_count',
'files', 'nuts', 'kind_codes', 'kind_codes_count']
m = {
'selection_file_states': '%(db)s.%(file_states)s',
'selection_nuts': '%(db)s.%(nuts)s',
'selection_kind_codes_count': '%(db)s.%(kind_codes_count)s',
'files': 'files',
'nuts': 'nuts',
'kind_codes': 'kind_codes',
'kind_codes_count': 'kind_codes_count'}
for table_name in table_names:
self._database.print_table(
m[table_name] % self._names, stream=stream)
[docs]class DatabaseStats(Object):
'''
Container to hold statistics about contents cached in meta-information db.
'''
nfiles = Int.T(
help='number of files in database')
nnuts = Int.T(
help='number of index nuts in database')
codes = List.T(
Tuple.T(content_t=String.T()),
help='available code sequences in database, e.g. '
'(agency, network, station, location) for stations nuts.')
kinds = List.T(
String.T(),
help='available content types in database')
total_size = Int.T(
help='aggregated file size of files referenced in database')
counts = Dict.T(
String.T(), Dict.T(Tuple.T(content_t=String.T()), Int.T()),
help='breakdown of how many nuts of any content type and code '
'sequence are available in database, ``counts[kind][codes]``')
def __str__(self):
kind_counts = dict(
(kind, sum(self.counts[kind].values())) for kind in self.kinds)
codes = ['.'.join(x) for x in self.codes]
if len(codes) > 20:
scodes = '\n' + util.ewrap(codes[:10], indent=' ') \
+ '\n [%i more]\n' % (len(codes) - 20) \
+ util.ewrap(codes[-10:], indent=' ')
else:
scodes = '\n' + util.ewrap(codes, indent=' ') \
if codes else '<none>'
s = '''
Available codes: %s
Number of files: %i
Total size of known files: %s
Number of index nuts: %i
Available content kinds: %s''' % (
scodes,
self.nfiles,
util.human_bytesize(self.total_size),
self.nnuts,
', '.join('%s: %i' % (
kind, kind_counts[kind]) for kind in sorted(self.kinds)))
return s
g_databases = {}
def get_database(path=None):
path = os.path.abspath(path)
if path not in g_databases:
g_databases[path] = Database(path)
return g_databases[path]
[docs]class Database(object):
'''
Shared meta-information database used by Squirrel.
'''
def __init__(self, database_path=':memory:', log_statements=False):
self._database_path = database_path
try:
util.ensuredirs(database_path)
logger.debug('Opening connection to database: %s' % database_path)
self._conn = sqlite3.connect(database_path)
except sqlite3.OperationalError:
raise error.SquirrelError(
'Cannot connect to database: %s' % database_path)
self._conn.text_factory = str
self._tables = {}
self._initialize_db()
self._need_commit = False
if log_statements:
self._conn.set_trace_callback(self._log_statement)
def _log_statement(self, statement):
logger.debug(statement)
def get_connection(self):
return self._conn
def _register_table(self, s):
m = re.search(r'(\S+)\s*\(([^)]+)\)', s)
table_name = m.group(1)
dtypes = m.group(2)
table_header = []
for dele in dtypes.split(','):
table_header.append(dele.split()[:2])
self._tables[table_name] = table_header
return s
def _initialize_db(self):
c = self._conn
with c:
if 1 == len(list(
c.execute(
'''
SELECT name FROM sqlite_master
WHERE type = 'table' AND name = '{files}'
'''))):
return
c.execute(
'''PRAGMA recursive_triggers = true''')
c.execute(self._register_table(
'''
CREATE TABLE IF NOT EXISTS files (
file_id integer PRIMARY KEY,
path text,
format text,
mtime float,
size integer)
'''))
c.execute(
'''
CREATE UNIQUE INDEX IF NOT EXISTS index_files_path
ON files (path)
''')
c.execute(self._register_table(
'''
CREATE TABLE IF NOT EXISTS nuts (
nut_id integer PRIMARY KEY AUTOINCREMENT,
file_id integer,
file_segment integer,
file_element integer,
kind_id integer,
kind_codes_id integer,
tmin_seconds integer,
tmin_offset integer,
tmax_seconds integer,
tmax_offset integer,
kscale integer)
'''))
c.execute(
'''
CREATE UNIQUE INDEX IF NOT EXISTS index_nuts_file_element
ON nuts (file_id, file_segment, file_element)
''')
c.execute(self._register_table(
'''
CREATE TABLE IF NOT EXISTS kind_codes (
kind_codes_id integer PRIMARY KEY,
kind_id integer,
codes text,
deltat float)
'''))
c.execute(
'''
CREATE UNIQUE INDEX IF NOT EXISTS index_kind_codes
ON kind_codes (kind_id, codes, deltat)
''')
c.execute(self._register_table(
'''
CREATE TABLE IF NOT EXISTS kind_codes_count (
kind_codes_id integer PRIMARY KEY,
count integer)
'''))
c.execute(
'''
CREATE INDEX IF NOT EXISTS index_nuts_file_id
ON nuts (file_id)
''')
c.execute(
'''
CREATE TRIGGER IF NOT EXISTS delete_nuts_on_delete_file
BEFORE DELETE ON files FOR EACH ROW
BEGIN
DELETE FROM nuts where file_id == old.file_id;
END
''')
# trigger only on size to make silent update of mtime possible
c.execute(
'''
CREATE TRIGGER IF NOT EXISTS delete_nuts_on_update_file
BEFORE UPDATE OF size ON files FOR EACH ROW
BEGIN
DELETE FROM nuts where file_id == old.file_id;
END
''')
c.execute(
'''
CREATE TRIGGER IF NOT EXISTS increment_kind_codes
BEFORE INSERT ON nuts FOR EACH ROW
BEGIN
INSERT OR IGNORE INTO kind_codes_count
VALUES (new.kind_codes_id, 0);
UPDATE kind_codes_count
SET count = count + 1
WHERE new.kind_codes_id == kind_codes_id;
END
''')
c.execute(
'''
CREATE TRIGGER IF NOT EXISTS decrement_kind_codes
BEFORE DELETE ON nuts FOR EACH ROW
BEGIN
UPDATE kind_codes_count
SET count = count - 1
WHERE old.kind_codes_id == kind_codes_id;
END
''')
[docs] def dig(self, nuts):
'''
Store or update content meta-information.
Given ``nuts`` are assumed to represent an up-to-date and complete
inventory of a set of files. Any old information about these files is
first pruned from the database (via database triggers). If such content
is part of a live selection, it is also removed there. Then the new
content meta-information is inserted into the main database. The
content is not automatically inserted into the live selections again.
It is in the responsibility of the selection object to perform this
step.
'''
nuts = list(nuts)
if not nuts:
return
c = self._conn.cursor()
files = set()
kind_codes = set()
for nut in nuts:
files.add((
nut.file_path,
nut.file_format,
nut.file_mtime,
nut.file_size))
kind_codes.add((nut.kind_id, nut.codes, nut.deltat or 0.0))
c.executemany(
'INSERT OR IGNORE INTO files VALUES (NULL,?,?,?,?)', files)
c.executemany(
'''UPDATE files SET
format = ?, mtime = ?, size = ?
WHERE path == ?
''',
((x[1], x[2], x[3], x[0]) for x in files))
c.executemany(
'INSERT OR IGNORE INTO kind_codes VALUES (NULL,?,?,?)', kind_codes)
c.executemany(
'''
INSERT INTO nuts VALUES
(NULL, (
SELECT file_id FROM files
WHERE path == ?
),?,?,?,
(
SELECT kind_codes_id FROM kind_codes
WHERE kind_id == ? AND codes == ? AND deltat == ?
), ?,?,?,?,?)
''',
((nut.file_path, nut.file_segment, nut.file_element,
nut.kind_id,
nut.kind_id, nut.codes, nut.deltat or 0.0,
nut.tmin_seconds, nut.tmin_offset,
nut.tmax_seconds, nut.tmax_offset,
nut.kscale) for nut in nuts))
self._need_commit = True
c.close()
def undig(self, path):
sql = '''
SELECT
files.path,
files.format,
files.mtime,
files.size,
nuts.file_segment,
nuts.file_element,
kind_codes.kind_id,
kind_codes.codes,
nuts.tmin_seconds,
nuts.tmin_offset,
nuts.tmax_seconds,
nuts.tmax_offset,
kind_codes.deltat
FROM files
INNER JOIN nuts ON files.file_id = nuts.file_id
INNER JOIN kind_codes
ON nuts.kind_codes_id == kind_codes.kind_codes_id
WHERE path == ?
'''
return [model.Nut(values_nocheck=row)
for row in self._conn.execute(sql, (path,))]
def undig_all(self):
sql = '''
SELECT
files.path,
files.format,
files.mtime,
files.size,
nuts.file_segment,
nuts.file_element,
kind_codes.kind_id,
kind_codes.codes,
nuts.tmin_seconds,
nuts.tmin_offset,
nuts.tmax_seconds,
nuts.tmax_offset,
kind_codes.deltat
FROM files
INNER JOIN nuts ON files.file_id == nuts.file_id
INNER JOIN kind_codes
ON nuts.kind_codes_id == kind_codes.kind_codes_id
'''
nuts = []
path = None
for values in self._conn.execute(sql):
if path is not None and values[0] != path:
yield path, nuts
nuts = []
if values[1] is not None:
nuts.append(model.Nut(values_nocheck=values))
path = values[0]
if path is not None:
yield path, nuts
def undig_many(self, paths):
selection = self.new_selection(paths)
for (_, path), nuts in selection.undig_grouped():
yield path, nuts
del selection
def new_selection(self, paths=None):
selection = Selection(self)
if paths:
selection.add(paths)
return selection
def commit(self):
if self._need_commit:
self._conn.commit()
self._need_commit = False
def undig_content(self, nut):
return None
[docs] def remove(self, path):
'''
Prune content meta-inforamation about a given file.
All content pieces belonging to file ``path`` are removed from the
main database and any attached live selections (via database triggers).
'''
self._conn.execute(
'DELETE FROM files WHERE path = ?', (path,))
[docs] def reset(self, path):
'''
Prune information associated with a given file, but keep the file path.
This method is called when reading a file failed. File attributes,
format, size and modification time are set to NULL. File content
meta-information is removed from the database and any attached live
selections (via database triggers).
'''
self._conn.execute(
'''
UPDATE files SET
format = NULL,
mtime = NULL,
size = NULL
WHERE path = ?
''', (path,))
[docs] def silent_touch(self, path):
'''
Update modification time of file without initiating reindexing.
Useful to prolong validity period of data with expiration date.
'''
c = self._conn
with c:
sql = 'SELECT format, size FROM files WHERE path = ?'
fmt, size = execute_get1(c, sql, (path,))
mod = io.get_backend(fmt)
mod.touch(path)
file_stats = mod.get_stats(path)
if file_stats[1] != size:
raise FileLoadError(
'Silent update for file "%s" failed: size has changed.'
% path)
sql = '''
UPDATE files
SET mtime = ?
WHERE path = ?
'''
c.execute(sql, (file_stats[0], path))
def _iter_counts(self, kind=None, kind_codes_count='kind_codes_count'):
args = []
sel = ''
if kind is not None:
sel = 'AND kind_codes.kind_id == ?'
args.append(to_kind_id(kind))
sql = ('''
SELECT
kind_codes.kind_id,
kind_codes.codes,
kind_codes.deltat,
%(kind_codes_count)s.count
FROM %(kind_codes_count)s
INNER JOIN kind_codes
ON %(kind_codes_count)s.kind_codes_id
== kind_codes.kind_codes_id
WHERE %(kind_codes_count)s.count > 0
''' + sel + '''
''') % {'kind_codes_count': kind_codes_count}
for kind_id, codes, deltat, count in self._conn.execute(sql, args):
yield (
to_kind(kind_id),
tuple(codes.split(separator)),
deltat), count
def _iter_deltats(self, kind=None, kind_codes_count='kind_codes_count'):
args = []
sel = ''
if kind is not None:
assert isinstance(kind, str)
sel = 'AND kind_codes.kind_id == ?'
args.append(to_kind_id(kind))
sql = ('''
SELECT DISTINCT kind_codes.deltat FROM %(kind_codes_count)s
INNER JOIN kind_codes
ON %(kind_codes_count)s.kind_codes_id
== kind_codes.kind_codes_id
WHERE %(kind_codes_count)s.count > 0
''' + sel + '''
ORDER BY kind_codes.deltat
''') % {'kind_codes_count': kind_codes_count}
for row in self._conn.execute(sql, args):
yield row[0]
def _iter_codes(self, kind=None, kind_codes_count='kind_codes_count'):
args = []
sel = ''
if kind is not None:
assert isinstance(kind, str)
sel = 'AND kind_codes.kind_id == ?'
args.append(to_kind_id(kind))
sql = ('''
SELECT DISTINCT kind_codes.codes FROM %(kind_codes_count)s
INNER JOIN kind_codes
ON %(kind_codes_count)s.kind_codes_id
== kind_codes.kind_codes_id
WHERE %(kind_codes_count)s.count > 0
''' + sel + '''
ORDER BY kind_codes.codes
''') % {'kind_codes_count': kind_codes_count}
for row in self._conn.execute(sql, args):
yield tuple(row[0].split(separator))
def _iter_kinds(self, codes=None, kind_codes_count='kind_codes_count'):
args = []
sel = ''
if codes is not None:
assert isinstance(codes, tuple)
sel = 'AND kind_codes.codes == ?'
args.append(separator.join(codes))
sql = ('''
SELECT DISTINCT kind_codes.kind_id FROM %(kind_codes_count)s
INNER JOIN kind_codes
ON %(kind_codes_count)s.kind_codes_id
== kind_codes.kind_codes_id
WHERE %(kind_codes_count)s.count > 0
''' + sel + '''
ORDER BY kind_codes.kind_id
''') % {'kind_codes_count': kind_codes_count}
for row in self._conn.execute(sql, args):
yield to_kind(row[0])
def iter_kinds(self, codes=None):
return self._iter_kinds(codes=codes)
def iter_codes(self, kind=None):
return self._iter_codes(kind=kind)
def iter_counts(self, kind=None):
return self._iter_counts(kind=kind)
def get_kinds(self, codes=None):
return list(self.iter_kinds(codes=codes))
def get_codes(self, kind=None):
return list(self.iter_codes(kind=kind))
def get_counts(self, kind=None):
d = {}
for (k, codes, deltat), count in self.iter_counts():
if k not in d:
v = d[k] = {}
else:
v = d[k]
if codes not in v:
v[codes] = 0
v[codes] += count
if kind is not None:
return d[kind]
else:
return d
def get_nfiles(self):
sql = '''SELECT COUNT(*) FROM files'''
for row in self._conn.execute(sql):
return row[0]
def get_nnuts(self):
sql = '''SELECT COUNT(*) FROM nuts'''
for row in self._conn.execute(sql):
return row[0]
def get_total_size(self):
sql = '''
SELECT SUM(files.size) FROM files
'''
for row in self._conn.execute(sql):
return row[0] or 0
def get_stats(self):
return DatabaseStats(
nfiles=self.get_nfiles(),
nnuts=self.get_nnuts(),
kinds=self.get_kinds(),
codes=self.get_codes(),
counts=self.get_counts(),
total_size=self.get_total_size())
def __str__(self):
return str(self.get_stats())
def print_tables(self, stream=None):
for table in [
'files',
'nuts',
'kind_codes',
'kind_codes_count']:
self.print_table(table, stream=stream)
def print_table(self, name, stream=None):
if stream is None:
stream = sys.stdout
class hstr(str):
def __repr__(self):
return self
w = stream.write
w('\n')
w('\n')
w(name)
w('\n')
sql = 'SELECT * FROM %s' % name
tab = []
if name in self._tables:
headers = self._tables[name]
tab.append([None for _ in headers])
tab.append([hstr(x[0]) for x in headers])
tab.append([hstr(x[1]) for x in headers])
tab.append([None for _ in headers])
for row in self._conn.execute(sql):
tab.append([x for x in row])
widths = [
max((len(repr(x)) if x is not None else 0) for x in col)
for col in zip(*tab)]
for row in tab:
w(' '.join(
(repr(x).ljust(wid) if x is not None else ''.ljust(wid, '-'))
for (x, wid) in zip(row, widths)))
w('\n')
w('\n')
__all__ = [
'Squirrel',
'Selection',
'SquirrelStats',
'Database',
'DatabaseStats',
]
