def generous_merge_into(cls, session: Session, dest_prj_id: int,
src_prj_id: int):
"""
Merge privileges from source project into destination project.
"""
# Each user who is present in both projects, gets the highest privilege from both projects.
# TODO: Arguable
sql = text("""
UPDATE projectspriv ppdst
SET privilege = CASE WHEN 'Manage' IN (ppsrc.privilege, ppdst.privilege)
THEN 'Manage'
WHEN 'Annotate' IN (ppsrc.privilege, ppdst.privilege)
THEN 'Annotate'
ELSE 'View'
END
FROM projectspriv ppsrc
WHERE ppsrc.projid = :src_prj
AND ppdst.projid = :dst_prj
AND ppsrc.member = ppdst.member""")
session.execute(sql, {"dst_prj": dest_prj_id, "src_prj": src_prj_id})
# Users who were only in source project get their privileges transferred into destination
# TODO: Arguable
sql = text("""
UPDATE projectspriv
SET projid = :dst_prj
WHERE projid = :src_prj
AND member NOT IN (SELECT member
FROM projectspriv
WHERE projid = :dst_prj)""")
session.execute(sql, {"dst_prj": dest_prj_id, "src_prj": src_prj_id})
def incremental_update_taxo_stats(cls, session: Session, prj_id: int, collated_changes: Dict):
"""
Do not recompute the full stats for a project (which can be long).
Instead, apply deltas because in this context we know them.
TODO: All SQL to SQLAlchemy form
"""
needed_ids = list(collated_changes.keys())
# Lock taxo lines to prevent re-entering, during validation it's often a handful of them.
pts_sql = """SELECT id
FROM taxonomy
WHERE id = ANY(:ids)
FOR NO KEY UPDATE
"""
session.execute(text(pts_sql), {"ids": needed_ids})
# Lock the rows we are going to update, including -1 for unclassified
pts_sql = """SELECT id, nbr
FROM projects_taxo_stat
WHERE projid = :prj
AND id = ANY(:ids)
FOR NO KEY UPDATE"""
res = session.execute(text(pts_sql), {"prj": prj_id, "ids": needed_ids})
ids_in_db = {classif_id: nbr for (classif_id, nbr) in res.fetchall()}
ids_not_in_db = set(needed_ids).difference(ids_in_db.keys())
if len(ids_not_in_db) > 0:
# Insert rows for missing IDs
pts_ins = """INSERT INTO projects_taxo_stat(projid, id, nbr, nbr_v, nbr_d, nbr_p)
SELECT :prj, COALESCE(obh.classif_id, -1), COUNT(*) nbr,
COUNT(CASE WHEN obh.classif_qual = 'V' THEN 1 END) nbr_v,
COUNT(CASE WHEN obh.classif_qual = 'D' THEN 1 END) nbr_d,
COUNT(CASE WHEN obh.classif_qual = 'P' THEN 1 END) nbr_p
FROM obj_head obh
JOIN acquisitions acq ON acq.acquisid = obh.acquisid
JOIN samples sam ON sam.sampleid = acq.acq_sample_id AND sam.projid = :prj
WHERE COALESCE(obh.classif_id, -1) = ANY(:ids)
GROUP BY obh.classif_id"""
session.execute(text(pts_ins), {'prj': prj_id, 'ids': list(ids_not_in_db)})
# Apply delta
for classif_id, chg in collated_changes.items():
if classif_id in ids_not_in_db:
# The line was created just above, with OK values
continue
if ids_in_db[classif_id] + chg['n'] == 0:
# The delta means 0 for this taxon in this project, delete the line
sqlparam = {'prj': prj_id, 'cid': classif_id}
ts_sql = """DELETE FROM projects_taxo_stat
WHERE projid = :prj AND id = :cid"""
else:
# General case
sqlparam = {'prj': prj_id, 'cid': classif_id,
'nul': chg['n'], 'val': chg['V'], 'dub': chg['D'], 'prd': chg['P']}
ts_sql = """UPDATE projects_taxo_stat
SET nbr=nbr+:nul, nbr_v=nbr_v+:val, nbr_d=nbr_d+:dub, nbr_p=nbr_p+:prd
WHERE projid = :prj AND id = :cid"""
session.execute(text(ts_sql), sqlparam)
def historize_classification(self, only_qual=None, manual=True):
"""
Copy current classification information into history table, for all rows in self.
:param only_qual: If set, only historize for current rows with this classification.
:param manual: If set, historize manual entries, otherwise, pick automatic ones.
"""
# Light up a bit the SQLA expressions
oh = ObjectHeader
och = ObjectsClassifHisto
# What we want to historize, as a subquery
if manual:
# What we want to historize, as a subquery
sel_subqry = select([
oh.objid, oh.classif_when,
text("'M'"), oh.classif_id, oh.classif_qual, oh.classif_who
])
if only_qual is not None:
qual_cond = oh.classif_qual.in_(only_qual)
else:
qual_cond = true()
sel_subqry = sel_subqry.where(
and_(oh.objid == any_(self.object_ids),
oh.classif_when.isnot(None), qual_cond))
ins_columns = [
och.objid, och.classif_date, och.classif_type, och.classif_id,
och.classif_qual, och.classif_who
]
else:
# What we want to historize, as a subquery
sel_subqry = select([
oh.objid, oh.classif_auto_when,
text("'A'"), oh.classif_auto_id, oh.classif_qual,
oh.classif_auto_score
])
sel_subqry = sel_subqry.where(
and_(oh.objid == any_(self.object_ids),
oh.classif_auto_id.isnot(None),
oh.classif_auto_when.isnot(None)))
ins_columns = [
och.objid, och.classif_date, och.classif_type, och.classif_id,
och.classif_qual, och.classif_score
]
# Insert into the log table
ins_qry: Insert = pg_insert(och.__table__)
ins_qry = ins_qry.from_select(ins_columns, sel_subqry)
ins_qry = ins_qry.on_conflict_do_nothing(
constraint='objectsclassifhisto_pkey')
# TODO: mypy crashes due to pg_dialect below
# logger.info("Histo query: %s", ins_qry.compile(dialect=pg_dialect()))
nb_objs = self.session.execute(ins_qry).rowcount
logger.info(" %d out of %d rows copied to log", nb_objs,
len(self.object_ids))
return oh
def remap(session: Session, prj_id: int, table: MappedTableTypeT, remaps: List[RemapOp]):
"""
Apply remapping operations onto the given table for given project.
"""
# Do the remapping, including blanking of unused columns
values = {a_remap.to: text(a_remap.frm) if a_remap.frm is not None else a_remap.frm
for a_remap in remaps}
qry: Query = session.query(table)
samples_4_prj: Query
acqs_4_samples: Query
if table == Sample:
qry = qry.filter(Sample.projid == prj_id) # type: ignore
elif table == Acquisition:
samples_4_prj = Query(Sample.sampleid).filter(Sample.projid == prj_id)
qry = qry.filter(Acquisition.acq_sample_id.in_(samples_4_prj)) # type: ignore
elif table == Process:
samples_4_prj = Query(Sample.sampleid).filter(Sample.projid == prj_id)
acqs_4_samples = Query(Acquisition.acquisid).filter(Acquisition.acq_sample_id.in_(samples_4_prj))
qry = qry.filter(Process.processid.in_(acqs_4_samples)) # type: ignore
elif table == ObjectFields:
samples_4_prj = Query(Sample.sampleid).filter(Sample.projid == prj_id)
acqs_4_samples = Query(Acquisition.acquisid).filter(Acquisition.acq_sample_id.in_(samples_4_prj))
objs_for_acqs: Query = Query(ObjectHeader.objid).filter(ObjectHeader.acquisid.in_(acqs_4_samples))
qry = qry.filter(ObjectFields.objfid.in_(objs_for_acqs)) # type: ignore
qry = qry.update(values=values, synchronize_session=False)
logger.info("Remap query for %s: %s", table.__tablename__, qry)
def read_taxo_stats(session: Session,
prj_ids: ProjectIDListT,
taxa_ids: Union[str, ClassifIDListT]) -> List[ProjectTaxoStats]:
sql = """
SELECT pts.projid, ARRAY_AGG(pts.id) as ids,
SUM(CASE WHEN pts.id = -1 THEN pts.nbr ELSE 0 END) as nb_u,
SUM(pts.nbr_v) as nb_v, SUM(pts.nbr_d) as nb_d, SUM(pts.nbr_p) as nb_p
FROM projects_taxo_stat pts
WHERE pts.projid = ANY(:ids)"""
params: Dict[str, Any] = {'ids': prj_ids}
if len(taxa_ids) > 0:
if taxa_ids == 'all':
pass
else:
sql += " AND pts.id = ANY(:tids)"
params["tids"] = taxa_ids
sql += """
GROUP BY pts.projid"""
if len(taxa_ids) > 0:
sql += ", pts.id"
res: Result = session.execute(text(sql), params)
with CodeTimer("stats for %d projects:" % len(prj_ids), logger):
ret = [ProjectTaxoStats(rec) for rec in res.fetchall()]
for a_stat in ret:
a_stat.used_taxa.sort()
return ret
def get_bounding_geo(cls, session: Session, project_ids: ProjectIDListT) -> Iterable[float]:
# TODO: Why using the view?
sql = ("SELECT min(o.latitude), max(o.latitude), min(o.longitude), max(o.longitude)"
" FROM objects o "
" WHERE o.projid = ANY(:prj)")
res: Result = session.execute(text(sql), {"prj": project_ids})
vals = res.first()
assert vals
return [a_val for a_val in vals]
def get_date_range(cls, session: Session, project_ids: ProjectIDListT) -> Iterable[datetime]:
# TODO: Why using the view?
sql = ("SELECT min(o.objdate), max(o.objdate)"
" FROM objects o "
" WHERE o.projid = ANY(:prj)")
res: Result = session.execute(text(sql), {"prj": project_ids})
vals = res.first()
assert vals
return [a_val for a_val in vals]
def create_or_link_slaves(how: ImportHow, session: Session,
object_head_to_write, object_fields_to_write,
image_to_write) -> int:
"""
Create, link or update slave entities, i.e. head, fields, image.
Also update them... TODO: Split/fork the def
:returns the number of new records
"""
if object_head_to_write.orig_id in how.existing_objects:
# Set the objid which will be copied for storing the image, the object itself
# will not be stored due to returned value.
objid = how.existing_objects[object_head_to_write.orig_id]
object_head_to_write.objid = objid
if how.can_update_only:
# noinspection DuplicatedCode
for a_cls, its_pk, an_upd in zip(
[ObjectHeader, ObjectFields], ['objid', 'objfid'],
[object_head_to_write, object_fields_to_write]):
filter_for_id = text("%s=%d" % (its_pk, objid))
# Fetch the record to update
obj = session.query(a_cls).filter(filter_for_id).first()
if a_cls == ObjectHeader:
# Eventually refresh sun position
if an_upd.nb_fields_from(USED_FIELDS_FOR_SUNPOS) > 0:
# Give the bean enough data for computation
for a_field in USED_FIELDS_FOR_SUNPOS.difference(
an_upd.keys()):
an_upd[a_field] = getattr(obj, a_field)
TSVFile.do_sun_position_field(an_upd)
updates = TSVFile.update_orm_object(obj,
an_upd) # type: ignore
if len(updates) > 0:
logger.info("Updating '%s' using %s", filter_for_id,
updates)
session.flush()
ret = 0 # nothing to write
else:
# 'Simply' a line with a complementary image
logger.info("One more image for %s:%s ",
object_head_to_write.orig_id, image_to_write)
ret = 1 # just a new image
else:
if how.can_update_only:
# No objects creation while updating
logger.info("Object %s not found while updating ",
object_head_to_write.orig_id)
ret = 0
else:
# or create it
# object_head_to_write.projid = how.prj_id
object_head_to_write.random_value = random.randint(1, 99999999)
# Below left NULL @see self.update_counts_and_img0
# object_head_to_write.img0id = XXXXX
ret = 3 # new image + new object_head + new object_fields
return ret
def create_summary(self, src_project: Project):
req = self.req
proj_id = src_project.projid
self.update_progress(1, "Start Summary export")
now_txt = DateTime.now_time().strftime("%Y%m%d_%H%M")
self.out_file_name = "export_summary_{0:d}_{1:s}.tsv".format(
src_project.projid, now_txt)
out_file = self.temp_for_jobs.base_dir_for(
self.job_id) / self.out_file_name
# Prepare a where clause and parameters from filter
object_set: DescribedObjectSet = DescribedObjectSet(
self.ro_session, proj_id, self.filters)
# By default, select (and group by) unambiguous category name
sels = ["txo.display_name"]
if self.req.sum_subtotal == "A":
sels[:0] = ["acq.orig_id"]
elif self.req.sum_subtotal == "S":
sels[:0] = [
"sam.orig_id", "sam.latitude", "sam.longitude",
"MAX(obh.objdate) AS date"
]
sels.append("COUNT(*) AS nbr")
select_clause = "SELECT " + ", ".join(sels)
not_aggregated = [a_sel for a_sel in sels if " " not in a_sel]
group_clause = " GROUP BY " + ", ".join(not_aggregated)
order_clause = OrderClause()
for a_sel in not_aggregated:
alias, col = a_sel.split(".")
order_clause.add_expression(alias, col)
# Base SQL comes from filters
from_, where, params = object_set.get_sql(self._get_owner_id(),
order_clause, select_clause)
sql = select_clause + " FROM " + from_.get_sql() + where.get_sql(
) + group_clause + order_clause.get_sql()
logger.info("Execute SQL : %s", sql)
logger.info("Params : %s", params)
res = self.ro_session.execute(text(sql), params)
msg = "Creating file %s" % out_file
logger.info(msg)
self.update_progress(50, msg)
nb_lines = self.write_result_to_csv(res, out_file)
msg = "Extracted %d rows" % nb_lines
logger.info(msg)
self.update_progress(90, msg)
return nb_lines
def get_sums_by_taxon(cls, session: Session, acquis_id: AcquisitionIDT) \
-> Dict[ClassifIDT, int]:
sql = text("SELECT o.classif_id, count(1)"
" FROM obj_head o "
" WHERE o.acquisid = :acq "
" AND o.classif_id IS NOT NULL "
" AND o.classif_qual = 'V'"
" GROUP BY o.classif_id")
res: Result = session.execute(sql, {"acq": acquis_id})
return {
int(classif_id): int(cnt)
for (classif_id, cnt) in res.fetchall()
}
def fetch_existing_images(session: Session, prj_id):
"""
Get all object/image pairs from the project
"""
# Must be reloaded from DB, as phase 1 added all objects for duplicates checking
# TODO: Why using the view?
sql = text("SELECT concat(o.orig_id,'*',i.orig_file_name) "
" FROM images i "
" JOIN objects o ON i.objid = o.objid "
" WHERE o.projid = :prj")
res: Result = session.execute(sql, {"prj": prj_id})
ret = {img_id for img_id, in res}
return ret
def update_taxo_stats(session: Session, projid: int):
sql = text("""
DELETE FROM projects_taxo_stat pts
WHERE pts.projid = :prjid;
INSERT INTO projects_taxo_stat(projid, id, nbr, nbr_v, nbr_d, nbr_p)
SELECT sam.projid, COALESCE(obh.classif_id, -1) id, COUNT(*) nbr,
COUNT(CASE WHEN obh.classif_qual = 'V' THEN 1 END) nbr_v,
COUNT(CASE WHEN obh.classif_qual = 'D' THEN 1 END) nbr_d,
COUNT(CASE WHEN obh.classif_qual = 'P' THEN 1 END) nbr_p
FROM obj_head obh
JOIN acquisitions acq ON acq.acquisid = obh.acquisid
JOIN samples sam ON sam.sampleid = acq.acq_sample_id AND sam.projid = :prjid
GROUP BY sam.projid, obh.classif_id;""")
session.execute(sql, {'prjid': projid})
def update_stats(session: Session, projid: int):
sql = text("""
UPDATE projects
SET objcount=q.nbr_sum,
pctclassified=100.0*nbrclassified/q.nbr_sum,
pctvalidated=100.0*nbrvalidated/q.nbr_sum
FROM projects p
LEFT JOIN
(SELECT projid, SUM(nbr) nbr_sum, SUM(CASE WHEN id>0 THEN nbr END) nbrclassified, SUM(nbr_v) nbrvalidated
FROM projects_taxo_stat
WHERE projid = :prjid
GROUP BY projid) q ON p.projid = q.projid
WHERE projects.projid = :prjid
AND p.projid = :prjid""")
session.execute(sql, {'prjid': projid})
def read_taxo_stats(self) -> List[SampleTaxoStats]:
sql = text("""
SELECT sam.sampleid,
ARRAY_AGG(DISTINCT COALESCE(obh.classif_id, -1)) as ids,
SUM(CASE WHEN obh.classif_id <> -1 THEN 0 ELSE 1 END) as nb_u,
COUNT(CASE WHEN obh.classif_qual = 'V' THEN 1 END) nbr_v,
COUNT(CASE WHEN obh.classif_qual = 'D' THEN 1 END) nbr_d,
COUNT(CASE WHEN obh.classif_qual = 'P' THEN 1 END) nbr_p
FROM obj_head obh
JOIN acquisitions acq ON acq.acquisid = obh.acquisid
JOIN samples sam ON sam.sampleid = acq.acq_sample_id
WHERE sam.sampleid = ANY(:ids)
GROUP BY sam.sampleid;""")
with CodeTimer("Stats for %d samples: " % len(self.ids), logger):
res = self.session.execute(sql, {'ids': self.ids})
ret = [SampleTaxoStats(rec) for rec in res]
return ret
def __init__(self, session: Session, project_ids: ProjectIDListT):
qry: Query = session.query(Acquisition.instrument)
qry = qry.join(Sample).join(Project)
# TODO: WTF WTF just for adding a column to the select
qry = qry.add_columns(
text(Project.__table__.name + "." +
Project.__table__.c.projid.name))
# Below SQLAlchemy complains
# qry = qry.add_columns(Project.projid)
if len(project_ids) > 0:
qry = qry.filter(Project.projid.in_(project_ids))
qry = qry.distinct()
instruments_by_proj: Dict[ProjectIDT, Set[InstrumentIDT]] = {}
instrument_names = set()
for ins_name, projid in qry.all():
if ins_name:
instruments_by_proj.setdefault(projid, set()).add(ins_name)
instrument_names.add(ins_name)
else:
pass # Filter NULL & empty strings
self.by_project = instruments_by_proj
self.instrument_names = sorted(list(instrument_names))
def classify_validate(self, user_id: UserIDT, classif_ids: ClassifIDListT, wanted_qualif: str) \
-> Tuple[int, Dict[Tuple, ObjectIDListT]]:
"""
Set current classifications in self and/or validate current classification.
:param user_id: The User who did these changes.
:param classif_ids: One category id for each of the object ids in self. -1 means "keep current".
:param wanted_qualif: Validate or Dubious
:returns updated rows and a summary of changes, for MRU and logging.
"""
# Gather state of classification, for impacted objects, before the change. Keep a lock on rows.
present = self._fetch_classifs_and_lock()
# Cook a diff b/w present and wanted values, both for the update of obj_head and preparing the ones on _stat
# Group the updates as lots of them are identical
updates: Dict[Tuple, EnumeratedObjectSet] = {}
all_changes: OrderedDict[Tuple, List[int]] = OrderedDict()
# A bit of obsessive optimization
classif_id_col = ObjectHeader.classif_id.name
classif_qual_col = ObjectHeader.classif_qual.name
classif_who_col = ObjectHeader.classif_who.name
classif_when_col = ObjectHeader.classif_when.name
for obj_id, v in zip(self.object_ids, classif_ids):
prev_obj = present[obj_id]
prev_classif_id: Optional[int] = prev_obj['classif_id']
new_classif_id: Optional[int]
if v == -1: # special value from validate all
# Arrange that no change can happen for this field
# Note: prev_classif_id can be None
new_classif_id = prev_classif_id
else:
new_classif_id = v
prev_classif_qual = prev_obj['classif_qual']
if (prev_classif_id == new_classif_id
and prev_classif_qual == wanted_qualif
and prev_obj['classif_who'] == user_id):
continue
# There was at least 1 field change for this object
an_update = updates.setdefault(
(new_classif_id, wanted_qualif),
EnumeratedObjectSet(self.session, []))
an_update.add_object(obj_id)
# Compact changes, grouped by operation
change_key = (prev_classif_id, prev_classif_qual, new_classif_id,
wanted_qualif)
for_this_change = all_changes.setdefault(change_key, [])
for_this_change.append(obj_id)
# Keep the recently used in first
all_changes.move_to_end(change_key, last=False)
if len(updates) == 0:
# Nothing to do
return 0, all_changes
# Update of obj_head, grouped by similar operations.
nb_updated = 0
sql_now = text("now()")
for (new_classif_id, wanted_qualif), an_obj_set in updates.items():
# Historize the updated rows (can be a lot!)
an_obj_set.historize_classification()
row_upd = {
classif_id_col: new_classif_id,
classif_qual_col: wanted_qualif,
classif_who_col: user_id,
classif_when_col: sql_now
}
# Do the update itsef
nb_updated += an_obj_set.update_all(row_upd)
logger.info("%d rows updated in %d queries", nb_updated, len(updates))
# Return statuses
return nb_updated, all_changes
def classify_auto(self, classif_ids: ClassifIDListT, scores: List[float], keep_logs: bool) \
-> Tuple[int, Dict[Tuple, ObjectIDListT]]:
"""
Set automatic classifications in self.
:param classif_ids: One category id for each of the object ids in self.
:param scores: One confidence score for each object from automatic classification algorithm.
:param keep_logs: Self-explained
:returns updated rows and a summary of changes, for stats.
"""
# Gather state of classification, for impacted objects, before the change. Keep a lock on rows.
prev = self._fetch_classifs_and_lock()
# Cook a diff b/w present and wanted values, both for the update of obj_head and preparing the ones on _stat
# updates: Dict[Tuple, EnumeratedObjectSet] = {}
all_changes: OrderedDict[Tuple, List[int]] = OrderedDict()
# A bit of obsessive optimization
classif_auto_id_col = ObjectHeader.classif_auto_id.name
classif_auto_score_col = ObjectHeader.classif_auto_score.name
classif_id_col = ObjectHeader.classif_id.name
classif_qual_col = ObjectHeader.classif_qual.name
overriden_by_prediction = {None, PREDICTED_CLASSIF_QUAL}
full_updates = []
partial_updates = []
objid_param = "_objid"
for obj_id, classif, score in zip(self.object_ids, classif_ids,
scores):
prev_obj = prev[obj_id]
prev_classif_id: Optional[int] = prev_obj['classif_id']
prev_classif_qual = prev_obj['classif_qual']
# Whatever, set the auto_* fields
an_update: Dict[str, Any] = {
objid_param: obj_id,
classif_auto_id_col: classif,
classif_auto_score_col: score
}
if prev_classif_qual in overriden_by_prediction:
# If not manually modified, go to Predicted state and set prediction as classification
an_update[classif_id_col] = classif
an_update[classif_qual_col] = PREDICTED_CLASSIF_QUAL
full_updates.append(an_update)
change_key = (prev_classif_id, prev_classif_qual, classif,
PREDICTED_CLASSIF_QUAL)
# Compact changes, grouped by operation
for_this_change = all_changes.setdefault(change_key, [])
for_this_change.append(obj_id)
else:
# Just store prediction, no change on user-visible data
partial_updates.append(an_update)
# Historize (auto)
if keep_logs:
self.historize_classification(None, True)
# Bulk (or sort of) update of obj_head
sql_now = text("now()")
obj_upd_qry: Update = ObjectHeader.__table__.update()
obj_upd_qry = obj_upd_qry.where(
ObjectHeader.objid == bindparam(objid_param))
nb_updated = 0
if len(full_updates) > 0:
full_upd_qry = obj_upd_qry.values(
classif_id=bindparam(classif_id_col),
classif_qual=bindparam(classif_qual_col),
classif_auto_id=bindparam(classif_auto_id_col),
classif_auto_score=bindparam(classif_auto_score_col),
classif_auto_when=sql_now)
nb_updated += self.session.execute(full_upd_qry,
full_updates).rowcount
# Partial updates
if len(partial_updates) > 0:
part_upd_qry = obj_upd_qry.values(
classif_auto_id=bindparam(classif_auto_id_col),
classif_auto_score=bindparam(classif_auto_score_col),
classif_auto_when=sql_now)
nb_updated += self.session.execute(part_upd_qry,
partial_updates).rowcount
# TODO: Cache upd
logger.info("_auto: %d and %d gives %d rows updated ",
len(full_updates), len(partial_updates), nb_updated)
# Return statuses
return nb_updated, all_changes
def create_tsv(self, src_project: Project,
end_progress: int) -> Tuple[int, int]:
"""
Create the TSV file.
"""
req = self.req
proj_id = src_project.projid
self.update_progress(1, "Start TSV export")
progress_range = end_progress - 1
# Get a fast count of the maximum of what to do
count_sql = "SELECT SUM(nbr) AS cnt FROM projects_taxo_stat WHERE projid = :prj"
res = self.ro_session.execute(text(count_sql), {"prj": proj_id})
obj_count = res.first()[0]
# Prepare a where clause and parameters from filter
object_set: DescribedObjectSet = DescribedObjectSet(
self.ro_session, proj_id, self.filters)
# Backup or not, the column namings are taken from common mapping
# @See Mapping.py
# TSV column order
# field_order = ["object_id", "object_lat", "object_lon", "object_date", "object_time", "object_depth_max",
# "object_annotation_status", "object_annotation_person_name", "object_annotation_person_email",
# "object_annotation_date", "object_annotation_time", "object_annotation_category"]
# formats = {"object_date": "TO_CHAR({0},'YYYYMMDD')",
# "object_time": "TO_CHAR({0},'HH24MISS')",
# "object_annotation_date": "TO_CHAR({0},'YYYYMMDD')",
# "object_annotation_time": "TO_CHAR({0},'HH24MISS')",
# "object_annotation_status": """
# CASE {0}
# WHEN 'V' then 'validated'
# WHEN 'P' then 'predicted'
# WHEN 'D' then 'dubious'
# ELSE {0}
# END
# """
# }
# prefices = {ObjectHeader.__tablename__: "obh",
# }
# for a_fld in field_order:
# mpg = GlobalMapping.PREDEFINED_FIELDS[a_fld]
# mpg[""]
# assert a_fld in GlobalMapping.PREDEFINED_FIELDS, "%s is not a mapped column" % a_fld
date_fmt, time_fmt = "YYYYMMDD", "HH24MISS"
if req.format_dates_times:
date_fmt, time_fmt = "YYYY-MM-DD", "HH24:MI:SS"
select_clause = "select "
if req.with_images or (req.exp_type == ExportTypeEnum.backup):
select_clause += "img.orig_file_name AS img_file_name, img.imgrank AS img_rank"
if req.with_images:
select_clause += ", img.file_name AS img_src_path"
select_clause += ",\n"
select_clause += """obh.orig_id AS object_id, obh.latitude AS object_lat, obh.longitude AS object_lon,
TO_CHAR(obh.objdate,'{0}') AS object_date,
TO_CHAR(obh.objtime,'{1}') AS object_time,
obh.object_link, obh.depth_min AS object_depth_min, obh.depth_max AS object_depth_max,
CASE obh.classif_qual
WHEN 'V' then 'validated'
WHEN 'P' then 'predicted'
WHEN 'D' then 'dubious'
ELSE obh.classif_qual
END AS object_annotation_status,
usr.name AS object_annotation_person_name, usr.email AS object_annotation_person_email,
TO_CHAR(obh.classif_when,'{0}') AS object_annotation_date,
TO_CHAR(obh.classif_when,'{1}') AS object_annotation_time,
txo.display_name AS object_annotation_category
""".format(date_fmt, time_fmt)
if req.exp_type == ExportTypeEnum.backup:
select_clause += ", txo.id AS object_annotation_category_id"
else:
select_clause += "," + TaxonomyBO.parents_sql(
"obh.classif_id") + " AS object_annotation_hierarchy"
if 'C' in req.tsv_entities:
select_clause += "\n, obh.complement_info"
# Deal with mappings, the goal is to emit SQL which will reconstitute the TSV structure
src_mappings = ProjectMapping().load_from_project(src_project)
if 'O' in req.tsv_entities:
select_clause += "\n " + src_mappings.object_mappings.as_select_list(
"obf")
if 'S' in req.tsv_entities:
select_clause += "\n, sam.orig_id AS sample_id, sam.dataportal_descriptor AS sample_dataportal_descriptor "
select_clause += src_mappings.sample_mappings.as_select_list("sam")
if 'P' in req.tsv_entities:
select_clause += "\n, prc.orig_id AS process_id "
select_clause += src_mappings.process_mappings.as_select_list(
"prc")
if 'A' in req.tsv_entities:
select_clause += "\n, acq.orig_id AS acq_id, acq.instrument AS acq_instrument "
select_clause += src_mappings.acquisition_mappings.as_select_list(
"acq")
if req.exp_type == ExportTypeEnum.dig_obj_ident:
select_clause += "\n, obh.objid"
if req.with_internal_ids:
select_clause += """\n, obh.objid,
obh.acquisid AS processid_internal, obh.acquisid AS acq_id_internal,
sam.sampleid AS sample_id_internal,
obh.classif_id, obh.classif_who, obh.classif_auto_id, txp.name classif_auto_name,
obh.classif_auto_score, obh.classif_auto_when,
obh.random_value object_random_value, obh.sunpos object_sunpos """
if 'S' in req.tsv_entities:
select_clause += "\n, sam.latitude sample_lat, sam.longitude sample_long "
# TODO: The condition on o.projid=1 in historical code below prevents any data production
# if 'H' in req.tsv_entities:
# sql1 += " , oh.classif_date AS histoclassif_date, classif_type AS histoclassif_type, " \
# "to3.name histoclassif_name, oh.classif_qual histoclassif_qual,uo3.name histoclassif_who, " \
# "classif_score histoclassif_score"
# sql2 += """ LEFT JOIN (select o.objid, classif_date, classif_type, och.classif_id,
# och.classif_qual, och.classif_who, classif_score
# from objectsclassifhisto och
# join objects o on o.objid=och.objid and o.projid=1 {0}
# union all
# select o.objid, o.classif_when classif_date, 'C' classif_type, classif_id,
# classif_qual, classif_who, NULL
# from objects o {0} where o.projid=1
# ) oh on o.objid=oh.objid
# LEFT JOIN taxonomy to3 on oh.classif_id=to3.id
# LEFT JOIN users uo3 on oh.classif_who=uo3.id
# """.format(samplefilter)
order_clause = OrderClause()
if req.split_by == "sample":
order_clause.add_expression("sam", "orig_id")
split_field = "sample_id" # AKA sam.orig_id, but renamed in select list
elif req.split_by == "taxo":
select_clause += "\n, txo.display_name AS taxo_parent_child "
order_clause.add_expression(None, "taxo_parent_child")
split_field = "taxo_parent_child"
else:
order_clause.add_expression("sam", "orig_id")
split_field = "object_id" # cette valeur permet d'éviter des erreurs plus loin dans r[split_field]
order_clause.add_expression("obh", "objid")
if req.with_images or (req.exp_type == ExportTypeEnum.backup):
order_clause.add_expression(None, "img_rank")
# Base SQL comes from filters
from_, where, params = object_set.get_sql(
self._get_owner_id(),
order_clause,
select_clause,
all_images=not req.only_first_image)
sql = select_clause + " FROM " + from_.get_sql() + where.get_sql(
) + order_clause.get_sql()
logger.info("Execute SQL : %s" % sql)
logger.info("Params : %s" % params)
res = self.ro_session.execute(text(sql), params)
now_txt = DateTime.now_time().strftime("%Y%m%d_%H%M")
self.out_file_name = "export_{0:d}_{1:s}.{2}".format(
proj_id, now_txt, "zip")
produced_path = self.out_path / self.out_file_name
zfile = zipfile.ZipFile(produced_path,
'w',
allowZip64=True,
compression=zipfile.ZIP_DEFLATED)
splitcsv = (req.split_by != "")
csv_filename = 'data.tsv' # Just a temp name as there is a rename while filling up the Zip
if splitcsv:
# Produce into the same temp file all the time, at zipping time the name in archive will vary
prev_value = "NotAssigned" # To trigger a sequence change immediately
else:
# The zip will contain a single TSV with same base name as the zip
prev_value = self.out_file_name.replace('.zip', '')
csv_path: Path = self.out_path / csv_filename # Constant path to a (sometimes) changing file
csv_fd: Optional[IO] = None
csv_wtr = None
# Store the images to save in a separate CSV. Useless if not exporting images but who cares.
temp_img_file = self.out_path / "images.csv"
img_file_fd = open(temp_img_file, 'w')
img_wtr = csv.DictWriter(img_file_fd, ["src_path", "dst_path"],
delimiter='\t',
quotechar='"',
lineterminator='\n')
img_wtr.writeheader()
# Prepare TSV structure
col_descs = [
a_desc for a_desc in res.cursor.description
if a_desc.name != "img_src_path"
]
# read latitude column to get float DB type
for a_desc in col_descs:
if a_desc.name == "object_lat":
db_float_type = a_desc.type_code
break
else:
raise
float_cols = set()
# Prepare float separator conversion, if not required the set will just be empty
if req.coma_as_separator:
for a_desc in col_descs:
if a_desc.type_code == db_float_type:
float_cols.add(a_desc.name)
tsv_cols = [a_desc.name for a_desc in col_descs]
tsv_types_line = {
name: ('[f]' if a_desc.type_code == db_float_type else '[t]')
for name, a_desc in zip(tsv_cols, col_descs)
}
nb_rows = 0
nb_images = 0
used_dst_pathes = set()
for r in res:
# Rows from SQLAlchemy are not mutable, so we need a clone for arranging values
a_row = dict(r)
if ((splitcsv and (prev_value != a_row[split_field])
) # At each split column values change
or (nb_rows == 0)): # And anyway for the first row
# Start of sequence, eventually end of previous sequence
if csv_fd:
csv_fd.close() # Close previous file
self.store_csv_into_zip(zfile, prev_value, csv_path)
if splitcsv:
prev_value = a_row[split_field]
logger.info("Writing into file %s", csv_path)
csv_fd = open(csv_path, 'w', encoding='latin_1')
csv_wtr = csv.DictWriter(csv_fd,
tsv_cols,
delimiter='\t',
quotechar='"',
lineterminator='\n',
quoting=csv.QUOTE_NONNUMERIC)
csv_wtr.writeheader()
if req.exp_type == ExportTypeEnum.backup:
# Write types line for backup type
csv_wtr.writerow(tsv_types_line)
if req.with_images:
copy_op = {"src_path": a_row.pop("img_src_path")}
if req.exp_type == ExportTypeEnum.dig_obj_ident:
# Images will be stored in a per-category directory, but there is a single TSV at the Zip root
categ = a_row['object_annotation_category']
# All names cannot directly become directories
a_row['img_file_name'] = self.get_DOI_imgfile_name(
a_row['objid'], a_row['img_rank'], categ,
a_row['img_file_name'])
copy_op["dst_path"] = a_row['img_file_name']
else: # It's a backup
# Images are stored in the Zip subdirectory per sample/taxo, i.e. at the same place as
# their referring TSV
dst_path = "{0}/{1}".format(prev_value,
a_row['img_file_name'])
if dst_path in used_dst_pathes:
# Avoid duplicates in zip as only the last entry will be present during unzip
# root cause: for UVP6 bundles, the vignette and original image are both stored
# with the same name.
img_with_rank = "{0}/{1}".format(
a_row['img_rank'], a_row['img_file_name'])
a_row[
'img_file_name'] = img_with_rank # write into TSV the corrected path
dst_path = prev_value + "/" + img_with_rank
used_dst_pathes.add(dst_path)
copy_op["dst_path"] = dst_path
img_wtr.writerow(copy_op)
nb_images += 1
# Remove CR from comments
if 'C' in req.tsv_entities and a_row['complement_info']:
a_row['complement_info'] = ' '.join(
a_row['complement_info'].splitlines())
# Replace decimal separator
for cname in float_cols:
if a_row[cname] is not None:
a_row[cname] = str(a_row[cname]).replace('.', ',')
assert csv_wtr is not None
# Produce the row in the TSV
csv_wtr.writerow(a_row)
nb_rows += 1
if nb_rows % self.ROWS_REPORT_EVERY == 0:
msg = "Row %d of max %d" % (nb_rows, obj_count)
logger.info(msg)
self.update_progress(1 + progress_range / obj_count * nb_rows,
msg)
if csv_fd:
csv_fd.close() # Close last file
self.store_csv_into_zip(zfile, prev_value, csv_path)
logger.info("Extracted %d rows", nb_rows)
img_file_fd.close()
if zfile:
zfile.close()
return nb_rows, nb_images
def projects_for_user(session: Session, user: User,
for_managing: bool = False,
not_granted: bool = False,
title_filter: str = '',
instrument_filter: str = '',
filter_subset: bool = False) -> List[ProjectIDT]:
"""
:param session:
:param user: The user for which the list is needed.
:param for_managing: If set, list the projects that the user can manage.
:param not_granted: If set, list (only) the projects on which given user has no right, so user can
request access to them.
:param title_filter: If set, filter out the projects with title not matching the required string,
or if set to a number, filter out the projects of which ID does not match.
:param instrument_filter: If set, filter out the projects which do not have given instrument in at least
one sample.
:param filter_subset: If set, filter out any project of which title contains 'subset'.
:return: The project IDs
"""
sql_params: Dict[str, Any] = {"user_id": user.id}
# Default query: all projects, eventually with first manager information
# noinspection SqlResolve
sql = """SELECT p.projid
FROM projects p
LEFT JOIN ( """ + ProjectPrivilegeBO.first_manager_by_project() + """ ) fpm
ON fpm.projid = p.projid """
if not_granted:
# Add the projects for which no entry is found in ProjectPrivilege
sql += """
LEFT JOIN projectspriv pp ON p.projid = pp.projid AND pp.member = :user_id
WHERE pp.member is null """
if for_managing:
sql += " AND False "
else:
if not user.has_role(Role.APP_ADMINISTRATOR):
# Not an admin, so restrict to projects which current user can work on, or view
sql += """
JOIN projectspriv pp
ON p.projid = pp.projid
AND pp.member = :user_id """
if for_managing:
sql += """
AND pp.privilege = '%s' """ % ProjectPrivilegeBO.MANAGE
sql += " WHERE 1 = 1 "
if title_filter != '':
sql += """
AND ( title ILIKE '%%'|| :title ||'%%'
OR TO_CHAR(p.projid,'999999') LIKE '%%'|| :title ) """
sql_params["title"] = title_filter
if instrument_filter != '':
sql += """
AND p.projid IN (SELECT DISTINCT sam.projid FROM samples sam, acquisitions acq
WHERE acq.acq_sample_id = sam.sampleid
AND acq.instrument ILIKE '%%'|| :instrum ||'%%' ) """
sql_params["instrum"] = instrument_filter
if filter_subset:
sql += """
AND NOT title ILIKE '%%subset%%' """
with CodeTimer("Projects query:", logger):
res: Result = session.execute(text(sql), sql_params)
# single-element tuple :( DBAPI
ret = [an_id for an_id, in res.fetchall()]
return ret # type:ignore
