Commit fd9da3c1 authored by Aurélien Campéas's avatar Aurélien Campéas
Browse files

tsio: style (cnx -> cn)

parent 872e2ce9e2cc
......@@ -62,14 +62,14 @@ class TimeSerie(BaseTS):
_saveme = None
_snapshot_interval = 100
def insert(self, cnx, ts, name, author=None, extra_scalars={}):
initial_insertion = not self.exists(cnx, name)
def insert(self, cn, ts, name, author=None, extra_scalars={}):
initial_insertion = not self.exists(cn, name)
if initial_insertion and not extra_scalars.get('manual', False):
if ts.isnull().all():
return None
ts = ts[~ts.isnull()]
self._saveme = {'autosnapshot': ts}
diff = super(TimeSerie, self).insert(cnx, ts, name, author=author,
diff = super(TimeSerie, self).insert(cn, ts, name, author=author,
extra_scalars=extra_scalars)
return diff
......@@ -109,28 +109,28 @@ class TimeSerie(BaseTS):
)
self._saveme = None
def _latest_item(self, cnx, table, column):
def _latest_item(self, cn, table, column):
# fetch the top-level things (e.g. snapshot, autosnapshot)
sql = select([table.c[column]]
).order_by(desc(table.c.id)
).limit(1)
return cnx.execute(sql).scalar()
return cn.execute(sql).scalar()
def _purge_snapshot_at(self, cnx, table, diffid):
cnx.execute(
def _purge_snapshot_at(self, cn, table, diffid):
cn.execute(
table.update(
).where(table.c.id == diffid
).values(snapshot=None, autosnapshot=None)
)
def _compute_diff_and_newsnapshot(self, cnx, table, newts, manual=False):
auto = self._latest_item(cnx, table, 'autosnapshot')
def _compute_diff_and_newsnapshot(self, cn, table, newts, manual=False):
auto = self._latest_item(cn, table, 'autosnapshot')
if auto is None:
auto = self._build_snapshot_upto(cnx, table,
auto = self._build_snapshot_upto(cn, table,
[lambda _, table: table.c.manual == False])
else:
auto = self._deserialize(auto, table.name)
synthetic = self._build_snapshot_upto(cnx, table)
synthetic = self._build_snapshot_upto(cn, table)
self._validate_type(auto, newts, table.name)
self._validate_type(synthetic, newts, table.name)
......@@ -151,12 +151,12 @@ class TimeSerie(BaseTS):
# we still need a full-blown history reconstruction routine
# for arbitrary revision_dates
def _build_snapshots_upto(self, cnx, table, qfilter,
def _build_snapshots_upto(self, cn, table, qfilter,
from_value_date=None, to_value_date=None):
snapid, synthsnap = self._find_snapshot(cnx, table, qfilter,
snapid, synthsnap = self._find_snapshot(cn, table, qfilter,
from_value_date=from_value_date,
to_value_date=to_value_date)
auto_snapid, autosnap = self._find_snapshot(cnx, table, qfilter,
auto_snapid, autosnap = self._find_snapshot(cn, table, qfilter,
column='autosnapshot',
from_value_date=from_value_date,
to_value_date=to_value_date)
......@@ -179,7 +179,7 @@ class TimeSerie(BaseTS):
for filtercb in qfilter:
sql = sql.where(filtercb(cset, table))
alldiffs = pd.read_sql(sql, cnx)
alldiffs = pd.read_sql(sql, cn)
if len(alldiffs) == 0:
manual_ts = self._compute_diff(autosnap, synthsnap)
......@@ -205,30 +205,30 @@ class TimeSerie(BaseTS):
manual_ts = self._compute_diff(auto_ts, synth_ts)
return auto_ts, manual_ts
def _onthefly(self, cnx, table, revision_date,
def _onthefly(self, cn, table, revision_date,
from_value_date=None, to_value_date=None):
qfilter = []
if revision_date:
qfilter.append(lambda cset, _: cset.c.insertion_date <= revision_date)
return self._build_snapshots_upto(cnx, table, qfilter,
return self._build_snapshots_upto(cn, table, qfilter,
from_value_date=from_value_date,
to_value_date=to_value_date)
# public API redefinition
def get(self, cnx, name, revision_date=None):
table = self._get_ts_table(cnx, name)
def get(self, cn, name, revision_date=None):
table = self._get_ts_table(cn, name)
if table is None:
return
if revision_date:
auto, residualmanual = self._onthefly(cnx, table, revision_date)
auto, residualmanual = self._onthefly(cn, table, revision_date)
ts = self._apply_diff(auto, residualmanual)
else:
# fetch the top-level snapshot
synthetic = self._latest_item(cnx, table, 'snapshot')
synthetic = self._latest_item(cn, table, 'snapshot')
if synthetic is None: # head just got chopped
ts = self._build_snapshot_upto(cnx, table)
ts = self._build_snapshot_upto(cn, table)
else:
ts = self._deserialize(synthetic, name)
......@@ -265,13 +265,13 @@ class TimeSerie(BaseTS):
# supervision specific API
def get_ts_marker(self, cnx, name, revision_date=None,
def get_ts_marker(self, cn, name, revision_date=None,
from_value_date=None, to_value_date=None):
table = self._get_ts_table(cnx, name)
table = self._get_ts_table(cn, name)
if table is None:
return None, None
auto, manual = self._onthefly(cnx, table, revision_date,
auto, manual = self._onthefly(cn, table, revision_date,
from_value_date=from_value_date,
to_value_date=to_value_date)
unionindex = join_index(auto, manual)
......
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