def test_count_with_bindparams(self):
User = self.classes.User
bq = self.bakery(lambda s: s.query(User))
sess = Session()
eq_(
bq(sess).count(),
4
)
bq += lambda q: q.filter(User.name == bindparam("uname"))
# calling with *args
eq_(
bq(sess).params(uname='fred').count(), 1
)
# with multiple params, the **kwargs will be used
bq += lambda q: q.filter(User.id == bindparam("anid"))
eq_(
bq(sess).params(uname='fred', anid=9).count(), 1
)
eq_(
# wrong id, so 0 results:
bq(sess).params(uname='fred', anid=8).count(), 0
)
def delete(jobs):
"""Delete a job or a list of jobs. This does **NOT** resolve any
dependencies but removes the relationships.
**Note** that no searched on the jobs dependencies are performed. You
have to create the job list with all the jobs you want updated manually.
You can use :py:func:`jip.jobs.get_subgraph` to get a full subgraph of a
job, or :py:func:`jip.jobs.get_group_jobs` to create a list of all jobs
that are related due to grouping or piping.
:param jobs: single job or list of jobs
"""
if not isinstance(jobs, (list, tuple)):
jobs = [jobs]
# create delete statement for the job
stmt = [Job.__table__.delete().where(Job.id == bindparam("_id"))]
# delete entries in the relationship tables
for relation_table in [job_dependencies, job_pipes, job_groups]:
dep = relation_table.delete().where(
(relation_table.c.source == bindparam("_id")) |
(relation_table.c.target == bindparam("_id"))
)
stmt.append(dep)
# delete entries in file tables
for relation_table in [InputFile.__table__, OutputFile.__table__]:
dep = relation_table.delete().where(
relation_table.c.job_id == bindparam("_id")
)
stmt.append(dep)
# convert the job values
values = [{"_id": j.id} for j in jobs if j.id is not None]
if values:
_execute(stmt[::-1], values) # Reverse the elements in the list to remove first the relations
def test_update(self):
with self.engine.connect() as conn:
conn.execute(
self.tables.data.insert(),
[
{"x": "x1", "y": "y1"},
{"x": "x2", "y": "y2"},
{"x": "x3", "y": "y3"}
]
)
conn.execute(
self.tables.data.update().
where(self.tables.data.c.x == bindparam('xval')).
values(y=bindparam('yval')),
[
{"xval": "x1", "yval": "y5"},
{"xval": "x3", "yval": "y6"}
]
)
eq_(
conn.execute(
select([self.tables.data]).
order_by(self.tables.data.c.id)).
fetchall(),
[
(1, "x1", "y5", 5),
(2, "x2", "y2", 5),
(3, "x3", "y6", 5)
]
)
def search_for_scraped(session, argument_oyez_id=None, section_number=None, number=None):
baked_query = bakery(lambda session: session.query(Turn).join(Section, Turn.section).join(Argument, Section.argument))
baked_query += lambda q: q.filter(Argument.oyez_id == bindparam('argument_oyez_id'))
baked_query += lambda q: q.filter(Section.number == bindparam('section_number'))
baked_query += lambda q: q.filter(Turn.number == bindparam('number'))
result = baked_query(session).params(argument_oyez_id=argument_oyez_id, section_number=section_number, number=number).one_or_none()
return result
def fast_load_module_id(cls, name, version, path, code_hash, # pylint: disable=too-many-arguments
session=None):
"""Load module id by name, version and code_hash
Compile SQLAlchemy core query into string for optimization
Keyword arguments:
session -- specify session for loading (default=relational.session)
"""
session = session or relational.session
if not hasattr(cls, "_load_or_create_module_id"):
tmodule = cls.t
_query = select([tmodule.c.id]).where(
(tmodule.c.name == bindparam("name")) &
((is_none(tmodule.c.version)) |
(tmodule.c.version == bindparam("version"))) &
((is_none(tmodule.c.code_hash)) |
(tmodule.c.code_hash == bindparam("code_hash")))
)
cls._load_or_create_module_id = str(_query)
info = dict(name=name, path=path, version=version, code_hash=code_hash)
an_id = session.execute(
cls._load_or_create_module_id, info).fetchone()
if an_id:
return an_id[0]
def update_data(table, thing_id, **vals):
transactions.add_engine(table.bind)
u = table.update(sa.and_(table.c.thing_id == thing_id, table.c.key == sa.bindparam("_key")))
d = table.delete(sa.and_(table.c.thing_id == thing_id, table.c.key == sa.bindparam("_key")))
inserts = []
for key, val in vals.iteritems():
if key[0:5] == "multi":
# vks = [py2db(v, return_kind=True) for v in vs]
# vals = [vk[0] for vk in vks]
val = [py2db(v, return_kind=False) for v in val]
kind = "num"
d.execute(_key=key)
for v in val:
inserts.append({"key": key, "value": v, "kind": kind})
else:
val, kind = py2db(val, return_kind=True)
uresult = u.execute(_key=key, value=val, kind=kind)
if not uresult.rowcount:
inserts.append({"key": key, "value": val, "kind": kind})
# do one insert
if inserts:
i = table.insert(values=dict(thing_id=thing_id))
i.execute(*inserts)
def insert_dataset(self, metadata_doc, dataset_id, dataset_type_id):
"""
Insert dataset if not already indexed.
:type metadata_doc: dict
:type dataset_id: str or uuid.UUID
:type dataset_type_id: int
:return: whether it was inserted
:rtype: bool
"""
try:
dataset_type_ref = bindparam('dataset_type_ref')
ret = self._connection.execute(
DATASET.insert().from_select(
['id', 'dataset_type_ref', 'metadata_type_ref', 'metadata'],
select([
bindparam('id'), dataset_type_ref,
select([
DATASET_TYPE.c.metadata_type_ref
]).where(
DATASET_TYPE.c.id == dataset_type_ref
).label('metadata_type_ref'),
bindparam('metadata', type_=JSONB)
])
),
id=dataset_id,
dataset_type_ref=dataset_type_id,
metadata=metadata_doc
)
return ret.rowcount > 0
except IntegrityError as e:
if e.orig.pgcode == PGCODE_UNIQUE_CONSTRAINT:
raise DuplicateRecordError('Duplicate dataset, not inserting: %s' % dataset_id)
raise
def resolve(cls, localpart, domain_name):
alias_preserve_case = cls.query.filter(
sqlalchemy.and_(cls.domain_name == domain_name,
sqlalchemy.or_(
sqlalchemy.and_(
cls.wildcard == False,
cls.localpart == localpart
), sqlalchemy.and_(
cls.wildcard == True,
sqlalchemy.bindparam("l", localpart).like(cls.localpart)
)
)
)
).order_by(cls.wildcard, sqlalchemy.func.char_length(cls.localpart).desc()).first()
if alias_preserve_case:
return alias_preserve_case
if localpart:
localpart = localpart.lower()
return cls.query.filter(
sqlalchemy.and_(cls.domain_name == domain_name,
sqlalchemy.or_(
sqlalchemy.and_(
cls.wildcard == False,
sqlalchemy.func.lower(cls.localpart) == localpart
), sqlalchemy.and_(
cls.wildcard == True,
sqlalchemy.bindparam("l", localpart).like(sqlalchemy.func.lower(cls.localpart))
)
)
)
).order_by(cls.wildcard, sqlalchemy.func.char_length(sqlalchemy.func.lower(cls.localpart)).desc()).first()
def get_original_details(self, iid=None, detail_name=None, os=None):
"""
tested by: TestItemTable.test_get_original_details_* functions
:param iid: get detail for specific iid or all if None
:param detail_name: get detail with specific name or all names if None
:param os: get detail for os name or for all oses if None
:return: list original details in the order they were inserted
"""
if "get_original_details" not in self.baked_queries_map:
the_query = self.bakery(lambda session: session.query(IndexItemDetailRow))
the_query += lambda q: q.join(IndexItemRow)
the_query += lambda q: q.filter(IndexItemRow.iid.like(bindparam('iid')))
the_query += lambda q: q.filter(IndexItemDetailRow.detail_name.like(bindparam('detail_name')))
the_query += lambda q: q.filter(IndexItemDetailRow.os_id.like(bindparam('os')))
the_query += lambda q: q.order_by(IndexItemDetailRow._id)
self.baked_queries_map["get_original_details"] = the_query
else:
the_query = self.baked_queries_map["get_original_details"]
# params with None are turned to '%'
params = [iid, detail_name, os]
for iparam in range(len(params)):
if params[iparam] is None: params[iparam] = '%'
retVal = the_query(self.session).params(iid=params[0], detail_name=params[1], os=params[2]).all()
return retVal
def updateRegion(mapper, connection, target):
sitePosition = target.newPosition
stmt = text('''SELECT dbo.[fn_GetRegionFromLatLon] (:lat,:lon)
''').bindparams(bindparam('lat', sitePosition.LAT),
bindparam('lon', sitePosition.LON))
regionID = connection.execute(stmt).scalar()
target.FK_Region = regionID
def test_functions_with_cols(self):
users = table(
'users',
column('id'),
column('name'),
column('fullname'))
calculate = select([column('q'), column('z'), column('r')], from_obj=[
func.calculate(
bindparam('x', None), bindparam('y', None)
)])
self.assert_compile(select([users], users.c.id > calculate.c.z),
"SELECT users.id, users.name, users.fullname "
"FROM users, (SELECT q, z, r "
"FROM calculate(:x, :y)) "
"WHERE users.id > z"
)
s = select([users], users.c.id.between(
calculate.alias('c1').unique_params(x=17, y=45).c.z,
calculate.alias('c2').unique_params(x=5, y=12).c.z))
self.assert_compile(
s, "SELECT users.id, users.name, users.fullname "
"FROM users, (SELECT q, z, r "
"FROM calculate(:x_1, :y_1)) AS c1, (SELECT q, z, r "
"FROM calculate(:x_2, :y_2)) AS c2 "
"WHERE users.id BETWEEN c1.z AND c2.z", checkparams={
'y_1': 45, 'x_1': 17, 'y_2': 12, 'x_2': 5})
def list_notifications(self, tenant_id, offset, limit):
rows = []
with self._db_engine.connect() as conn:
nm = self.nm
select_nm_query = (select([nm])
.where(nm.c.tenant_id == bindparam('b_tenant_id')))
parms = {'b_tenant_id': tenant_id}
if offset:
select_nm_query = (select_nm_query
.where(nm.c.id > bindparam('b_offset')))
parms['b_offset'] = offset.encode('utf8')
select_nm_query = (select_nm_query
.order_by(nm.c.id)
.limit(bindparam('b_limit')))
parms['b_limit'] = limit + 1
rows = conn.execute(select_nm_query, parms).fetchall()
return [dict(row) for row in rows]
def delete_exercise(user_id, exercise_id):
"""
Submit a request to have an exercise deleted.
:param exercise_id: ID of the exercise we're requesting to have deleted
:return: Nothing.
"""
conn = eng.connect()
exercise_parm = bindparam("exercise_id", type_=Integer)
user_parm = bindparam("user_id", type_=String)
query = select([exercise_table.c.id]).where(
and_(exercise_table.c.id == exercise_parm, exercise_table.c.user_id == user_parm)
)
is_valid_user = conn.execute(query, exercise_id=exercise_id, user_id=user_id).fetchone()
if is_valid_user:
with conn.begin() as trans:
query = attempt_table.delete().where(attempt_table.c.exercise_id == exercise_parm)
conn.execute(query, exercise_id=exercise_id)
query = resource_by_exercise_table.delete().where(resource_by_exercise_table.c.exercise_id == exercise_parm)
conn.execute(query, exercise_id=exercise_id)
query = exercise_table.delete().where(exercise_table.c.id == exercise_parm)
conn.execute(query, exercise_id=exercise_id)
trans.commit()
msg = "Executed deleteion query on exercise: {} belonging to user: {}".format(exercise_id, user_id)
else:
msg = "User: {} not the owner of exercise: {}".format(user_id, exercise_id)
conn.close()
return msg
def get_resources_for_exercise(exercise_id, user_id):
"""
Get all resources connected to the given exercise
:param exercise_id: ID of the exercise in question
:param user_id: Owning user
:return: A list the appropriate resources.
"""
conn = eng.connect()
user_id_parm = bindparam("user_id")
exercise_parm = bindparam("exercise_id")
query = (
select([resource_table.c.id, resource_table.c.caption, resource_table.c.url, resource_table.c.user_id])
.select_from(resource_table.join(resource_by_exercise_table))
.where(
and_(resource_table.c.user_id == user_id_parm, resource_by_exercise_table.c.exercise_id == exercise_parm)
)
)
result = conn.execute(query, user_id=user_id, exercise_id=exercise_id)
resources = [
dict(resource_id=resource_id, user_id=user_id, caption=caption, url=url)
for resource_id, caption, url, user_id in result.fetchall()
]
conn.close()
return resources
def add_resource(caption, url, user_id, exercise_id=None):
"""
Add a clickable resource to the data store
:param caption: The text to show up for the user to click on.
:param url: Where clicking the text takes you.
:param user_id: Who owns this link.
:param exercise_id The exercise that this resource refers to.
:return: Nothing.
"""
if len(caption) > CHARACTER_LIMIT or len(url) > CHARACTER_LIMIT:
msg = "Either new caption or new url exceeded char limit of {} chars".format(CHARACTER_LIMIT)
raise Exception(msg)
caption_parm = bindparam("caption", type_=String)
url_parm = bindparam("url", type_=String)
user_parm = bindparam("user_id", type_=String)
exercise_parm = bindparam("exercise_id", type_=Integer)
conn = eng.connect()
with conn.begin() as trans:
query = resource_table.insert().values(caption=caption_parm, url=url_parm, user_id=user_parm)
result = conn.execute(query, caption=caption, url=url, user_id=user_id)
new_resource_id = result.inserted_primary_key[0]
query = resource_by_exercise_table.insert().values(exercise_id=exercise_parm, resource_id=new_resource_id)
conn.execute(query, exercise_id=exercise_id, user_id=user_id)
trans.commit()
conn.close()
msg = ""
return msg
def author(mit_id, conn):
"""
Returns an author object for insertion into mongo summary collection.
The format is as follows:
{"_id": {"name": <name>, "mitid": <mitid>},
"type": "author",
"size": <num docs>,
"downloads": <num downloads>,
"countries": [
{"country": <3 ltr code>, "downloads": <num downloads>},...
]
"dates": [
{"date": <YYYY-MM-DD>, "downloads": <num>},...
]}
"""
requests_to_authors = requests.join(documents)\
.join(documents_authors)\
.join(authors)
totals = select([
authors.c.mit_id,
authors.c.name,
select([func.count()])
.select_from(documents_authors.join(authors))
.where(authors.c.mit_id==bindparam('mit_id'))
.label('size'),
select([func.count()])
.select_from(requests_to_authors)
.where(authors.c.mit_id==bindparam('mit_id'))
.label('downloads')
])\
.where(authors.c.mit_id==bindparam('mit_id'))
countries = select([requests.c.country, func.count().label('downloads')])\
.select_from(requests_to_authors)\
.where(authors.c.mit_id==bindparam('mit_id'))\
.group_by(requests.c.country)
dates = select([
func.date_trunc('day', requests.c.datetime).label('date'),
func.count().label('downloads')])\
.select_from(requests_to_authors)\
.where(authors.c.mit_id==bindparam('mit_id'))\
.group_by(func.date_trunc('day', requests.c.datetime))
author_obj = {'type': 'author'}
res = conn.execute(totals, mit_id=mit_id).first()
author_obj['_id'] = {'name': res['name'], 'mitid': res['mit_id']}
author_obj['size'] = res['size']
author_obj['downloads'] = res['downloads']
res = conn.execute(countries, mit_id=mit_id)
for row in res:
author_obj.setdefault('countries', [])\
.append({'country': row['country'], 'downloads': row['downloads']})
res = conn.execute(dates, mit_id=mit_id)
for row in res:
author_obj.setdefault('dates', [])\
.append({'date': row['date'].strftime('%Y-%m-%d'),
'downloads': row['downloads']})
return author_obj
def migrate_post_photos():
photo_map = {}
photo_attrs = [
photos.c.caption,
photos.c.filename,
]
for row in conn.execute(
select([posts, photos], use_labels=True).select_from(
posts.join(photos))):
post_id = row[posts.c.id]
photo_json = {
attr.name: row[attr] for attr in photo_attrs if row[attr]
}
photo_map.setdefault(post_id, []).append(photo_json)
photo_batch = []
for post_id, photo_blob in photo_map.items():
photo_batch.append({
'post_id': post_id,
'photos': json.dumps(photo_blob),
})
update_photos = posts.update()\
.where(posts.c.id == bindparam('post_id'))\
.values(photos=bindparam('photos'))
conn.execute(update_photos, photo_batch)
def auto_validate_stored_procGSM_Argos(ptt, ind_id,user,type_,freq,session):
procStockDict = {
'argos': '[sp_auto_validate_Argos_GPS]',
'gsm': '[sp_auto_validate_GSM]'
}
if type_ == 'argos' :
table = ArgosDatasWithIndiv
elif type_ == 'gsm' :
table = GsmDatasWithIndiv
if ind_id is None:
stmt = update(table).where(and_(table.c['FK_Individual'] == None, table.c['FK_ptt'] == ptt)
).where(table.c['checked'] == 0).values(checked =1)
session.execute(stmt)
nb_insert = exist = error = 0
else:
stmt = text(""" DECLARE @nb_insert int , @exist int , @error int;
exec """+ dbConfig['data_schema'] + """."""+procStockDict[type_]+""" :ptt , :ind_id , :user ,:freq , @nb_insert OUTPUT, @exist OUTPUT, @error OUTPUT;
SELECT @nb_insert, @exist, @error; """
).bindparams(bindparam('ind_id', ind_id),bindparam('user', user),bindparam('freq', freq),bindparam('ptt', ptt))
nb_insert, exist , error= session.execute(stmt).fetchone()
return nb_insert, exist , error
def list_notifications(self, tenant_id, sort_by, offset, limit):
rows = []
with self._db_engine.connect() as conn:
nm = self.nm
select_nm_query = (select([nm])
.where(nm.c.tenant_id == bindparam('b_tenant_id')))
parms = {'b_tenant_id': tenant_id}
if sort_by is not None:
order_columns = [literal_column(col) for col in sort_by]
if 'id' not in sort_by:
order_columns.append(nm.c.id)
else:
order_columns = [nm.c.id]
select_nm_query = select_nm_query.order_by(*order_columns)
select_nm_query = (select_nm_query
.order_by(nm.c.id)
.limit(bindparam('b_limit')))
parms['b_limit'] = limit + 1
if offset:
select_nm_query = select_nm_query.offset(bindparam('b_offset'))
parms['b_offset'] = offset
rows = conn.execute(select_nm_query, parms).fetchall()
return [dict(row) for row in rows]
def _add_missing_mau(self, table_prefix, days_ago):
# Locate beginning table
tables = self._get_filtered_tables(table_prefix, days_ago+30)
first_date = self._date_from_tablename(tables[0].name)
grouped_monthly_unique = select([
monthly_rollup.c.date,
func.sum(monthly_rollup.c.count).label("count")
]).\
where(monthly_rollup.c.date >= first_date).\
group_by(monthly_rollup.c.date).\
order_by(monthly_rollup.c.date)
# Average them over 6 days prior inclding today for MAU's
maus = select([
grouped_monthly_unique.c.date,
func.avg(grouped_monthly_unique.c.count).over(
order_by=text("date ROWS 6 PRECEDING")
).label("mau")
]).\
order_by(grouped_monthly_unique.c.date)
results = self._conn.execute(maus).fetchall()
if not results:
return
# Update appropriate rows
stmt = daily_stats.update().\
where(daily_stats.c.date == bindparam("update_date")).\
values(mau=bindparam("mau"))
self._conn.execute(stmt, [
{"update_date": x.date, "mau": x.mau}
for x in results[-days_ago:]
])
def copy(self, conn, ins_rows, table_bound):
ins = (
table_bound.update()
.where(table_bound.c.property == sqlalchemy.bindparam("_property"))
.values({table_bound.c.item: sqlalchemy.bindparam("_item")})
)
conn.execute(ins, ins_rows)
def __init__(self, meta, name, osmtables, subset=None, change=None,
column_geom='geom', geom_change=None):
super().__init__(meta, name, osmtables.node, subset=subset,
change=change)
# need a geometry column
if isinstance(column_geom, Column):
self.column_geom = column_geom
srid = column_geom.type.srid
else:
srid = meta.info.get('srid', self.src.data.c.geom.type.srid)
self.column_geom = Column(column_geom, Geometry('POINT', srid=srid))
self.data.append_column(self.column_geom)
# add an additional transform to the insert statement if the srid changes
params = {}
for c in self.data.c:
if c == self.column_geom and self.src.data.c.geom.type.srid != srid:
geomparam = bindparam(c.name, type_=self.column_geom.type)
params[c.name] = ST_Transform(geomparam, self.column_geom.type.srid)
else:
params[c.name] = bindparam(c.name)
self.stm_insert = self.stm_insert.values(params)
# the table to remember geometry changes
self.geom_change = geom_change
def test_missing_bind_posn(self):
assert_raises_message(
exc.ArgumentError,
"This text\(\) construct doesn't define a bound parameter named 'bar'",
text(":foo").bindparams,
bindparam('foo', value=5), bindparam('bar', value=7)
)
def test_select_where(self):
stmt = (
select([self.tables.foo])
.where(self.tables.foo.c.data == bindparam("data"))
.where(self.tables.foo.c.x == bindparam("x"))
)
self._assert_raises(stmt, {"data": "data"})
def update_canonicals(canonicals):
'''
Update canonical data for android devices.
'''
global ENGINE
binding = [{"p_{}".format(k): v for k, v in canonical.items()} for canonical in canonicals]
device_table = model.metadata.tables['device']
stmt = update(device_table).\
values(device_token_new=bindparam('p_new_token')).\
where(and_(device_table.c.login_id == bindparam('p_login_id'),
func.coalesce(device_table.c.device_token_new, device_table.c.device_token) == bindparam('p_old_token')))
ENGINE.execute(stmt, binding)
with session_scope() as session:
query = text('SELECT keep_max_users_per_device( \
(:platform_id)::int2, :device_token, (:max_users_per_device)::int2)')
for canonical in canonicals:
session.execute(query,
{'platform_id': constants.PLATFORM_ANDROID,
'device_token': canonical['new_token'],
'max_users_per_device': config.max_users_per_device
})
session.execute(query,
{'platform_id': constants.PLATFORM_ANDROID_TABLET,
'device_token': canonical['new_token'],
'max_users_per_device': config.max_users_per_device
})
session.commit()
def test_updatemany(self):
# MySQL-Python 1.2.2 breaks functions in execute_many :(
if (testing.against('mysql+mysqldb') and
testing.db.dialect.dbapi.version_info[:3] == (1, 2, 2)):
return
t.insert().execute({}, {}, {})
t.update(t.c.col1 == sa.bindparam('pkval')).execute(
{'pkval': 51, 'col7': None, 'col8': None, 'boolcol1': False})
t.update(t.c.col1 == sa.bindparam('pkval')).execute(
{'pkval': 51},
{'pkval': 52},
{'pkval': 53})
l = t.select().execute()
ctexec = currenttime.scalar()
today = datetime.date.today()
eq_(l.fetchall(),
[(51, 'im the update', f2, ts, ts, ctexec, False, False,
13, today, 'py', 'hi'),
(52, 'im the update', f2, ts, ts, ctexec, True, False,
13, today, 'py', 'hi'),
(53, 'im the update', f2, ts, ts, ctexec, True, False,
13, today, 'py', 'hi')])
def test_expanding_in_special_chars(self):
testing.db.execute(
users.insert(),
[
dict(user_id=7, user_name='jack'),
dict(user_id=8, user_name='fred'),
]
)
with testing.db.connect() as conn:
stmt = select([users]).where(
users.c.user_name.in_(bindparam('u35', expanding=True))
).where(
users.c.user_id == bindparam("u46")
).order_by(users.c.user_id)
eq_(
conn.execute(
stmt, {"u35": ['jack', 'fred'], "u46": 7}).fetchall(),
[(7, 'jack')]
)
stmt = select([users]).where(
users.c.user_name.in_(bindparam('u.35', expanding=True))
).where(
users.c.user_id == bindparam("u.46")
).order_by(users.c.user_id)
eq_(
conn.execute(
stmt, {"u.35": ['jack', 'fred'], "u.46": 7}).fetchall(),
[(7, 'jack')]
)
def test_dbapi_raw(n):
"""The DBAPI's API inserting rows in bulk."""
conn = engine.pool._creator()
cursor = conn.cursor()
compiled = Customer.__table__.insert().values(
name=bindparam('name'),
description=bindparam('description')).\
compile(dialect=engine.dialect)
if compiled.positional:
args = (
('customer name %d' % i, 'customer description %d' % i)
for i in range(n))
else:
args = (
dict(
name='customer name %d' % i,
description='customer description %d' % i
)
for i in range(n)
)
cursor.executemany(
str(compiled),
list(args)
)
conn.commit()
conn.close()
def test_bound_limit_offset(self):
table = self.tables.some_table
self._assert_result(
select([table]).order_by(table.c.id).
limit(bindparam("l")).offset(bindparam("o")),
[(2, 2, 3), (3, 3, 4)],
params={"l": 2, "o": 1}
)
def lastseenuid(account_id, session, folder_id):
q = bakery(lambda session: session.query(func.max(ImapUid.msg_uid)))
q += lambda q: q.filter(
ImapUid.account_id == bindparam('account_id'),
ImapUid.folder_id == bindparam('folder_id'))
res = q(session).params(account_id=account_id,
folder_id=folder_id).one()[0]
return res or 0
def get_alarms(self, tenant_id, query_parms=None, offset=None, limit=None):
if not query_parms:
query_parms = {}
with self._db_engine.connect() as conn:
parms = {}
ad = self.ad
am = self.am
mdd = self.mdd
md = self.md
a = self.a
query = (self.base_subquery_list.where(
ad.c.tenant_id == bindparam('b_tenant_id')))
parms['b_tenant_id'] = tenant_id
if 'alarm_definition_id' in query_parms:
query = query.where(
ad.c.id == bindparam('b_alarm_definition_id'))
parms['b_alarm_definition_id'] = query_parms[
'alarm_definition_id']
if 'metric_name' in query_parms:
query = query.where(a.c.id.in_(self.get_a_am_query))
parms['b_md_name'] = query_parms['metric_name'].encode('utf8') if six.PY2 else \
query_parms['metric_name']
if 'severity' in query_parms:
severities = query_parms['severity'].split('|')
query = query.where(
or_(ad.c.severity == bindparam('b_severity' + str(i))
for i in range(len(severities))))
for i, s in enumerate(severities):
parms['b_severity' +
str(i)] = s if six.PY3 else s.encode('utf-8')
if 'state' in query_parms:
query = query.where(a.c.state == bindparam('b_state'))
parms['b_state'] = query_parms['state']
if 'lifecycle_state' in query_parms:
query = (query.where(
a.c.lifecycle_state == bindparam('b_lifecycle_state')))
parms['b_lifecycle_state'] = query_parms['lifecycle_state'] \
if six.PY3 else query_parms['lifecycle_state'].encode('utf8')
if 'link' in query_parms:
query = query.where(a.c.link == bindparam('b_link'))
parms['b_link'] = query_parms['link'] if six.PY3 \
else query_parms['link'].encode('utf8')
if 'state_updated_start_time' in query_parms:
query = (query.where(
a.c.state_updated_at >= bindparam('b_state_updated_at')))
date_str = query_parms['state_updated_start_time'] if six.PY3 \
else query_parms['state_updated_start_time'].encode('utf8')
date_param = datetime.strptime(date_str,
'%Y-%m-%dT%H:%M:%S.%fZ')
parms['b_state_updated_at'] = date_param
if 'metric_dimensions' in query_parms:
sub_query = select([a.c.id])
sub_query_from = (a.join(am, am.c.alarm_id == a.c.id).join(
mdd, mdd.c.id == am.c.metric_definition_dimensions_id))
sub_query_md_base = select([md.c.dimension_set_id
]).select_from(md)
for i, metric_dimension in enumerate(
query_parms['metric_dimensions'].items()):
md_name = "b_md_name_{}".format(i)
values_cond = None
values_cond_flag = False
if metric_dimension and metric_dimension[1]:
if '|' in metric_dimension[1]:
values = metric_dimension[1].encode('utf8').split('|') if six.PY2 else \
metric_dimension[1].split('|')
sub_values_cond = []
for j, value in enumerate(values):
sub_md_value = "b_md_value_{}_{}".format(i, j)
sub_values_cond.append(
md.c.value == bindparam(sub_md_value))
parms[sub_md_value] = value
values_cond = or_(*sub_values_cond)
values_cond_flag = True
else:
md_value = "b_md_value_{}".format(i)
values_cond = (md.c.value == bindparam(md_value))
values_cond_flag = True
parms[md_value] = metric_dimension[1]
sub_query_md = (sub_query_md_base.where(
md.c.name == bindparam(md_name)))
if values_cond_flag:
sub_query_md = (sub_query_md.where(values_cond))
sub_query_md = (sub_query_md.distinct().alias(
'md_{}'.format(i)))
sub_query_from = (sub_query_from.join(
sub_query_md, sub_query_md.c.dimension_set_id ==
mdd.c.metric_dimension_set_id))
parms[md_name] = metric_dimension[0].encode('utf8') if six.PY2 else \
metric_dimension[0]
sub_query = (
sub_query.select_from(sub_query_from).distinct())
query = query.where(a.c.id.in_(sub_query))
order_columns = []
if 'sort_by' in query_parms:
columns_mapper = \
{'alarm_id': a.c.id,
'alarm_definition_id': ad.c.id,
'alarm_definition_name': ad.c.name,
'state_updated_timestamp': a.c.state_updated_at,
'updated_timestamp': a.c.updated_at,
'created_timestamp': a.c.created_at,
'severity': models.field_sort(ad.c.severity, list(map(text, ["'LOW'",
"'MEDIUM'",
"'HIGH'",
"'CRITICAL'"]))),
'state': models.field_sort(a.c.state, list(map(text, ["'OK'",
"'UNDETERMINED'",
"'ALARM'"])))}
order_columns, received_cols = self._remap_columns(
query_parms['sort_by'], columns_mapper)
if not received_cols.get('alarm_id', False):
order_columns.append(a.c.id)
else:
order_columns = [a.c.id]
if limit:
query = query.limit(bindparam('b_limit'))
parms['b_limit'] = limit + 1
if offset:
query = query.offset(bindparam('b_offset'))
parms['b_offset'] = offset
query = (query.order_by(*order_columns).alias('alarm_id_list'))
main_query = (self.base_query.select_from(
self.base_query_from.join(query,
query.c.id == a.c.id)).distinct())
main_query = main_query.order_by(*order_columns)
return [
dict(row)
for row in conn.execute(main_query, parms).fetchall()
]
def __init__(self):
super(AlarmsRepository, self).__init__()
metadata = MetaData()
self.a_du = models.create_a_model(metadata)
self.aa = models.create_aa_model(metadata).alias('aa')
self.sa = models.create_sa_model(metadata).alias('sa')
self.ad = models.create_ad_model(metadata).alias('ad')
self.am = models.create_am_model(metadata).alias('am')
self.md = models.create_md_model(metadata).alias('md')
self.mdd = models.create_mdd_model(metadata).alias('mdd')
self.mde = models.create_mde_model(metadata).alias('mde')
self.sad = models.create_sad_model(metadata).alias('sad')
self.sadd = models.create_sadd_model(metadata).alias('sadd')
a = self.a_du
self.a = a.alias('a')
a_s = self.a
sa = self.sa
ad = self.ad
am = self.am
md = self.md
mdd = self.mdd
mde = self.mde
gc_columns = [md.c.name + text("'='") + md.c.value]
mdg = (select([
md.c.dimension_set_id,
models.group_concat(gc_columns).label('dimensions')
]).select_from(md).group_by(md.c.dimension_set_id).alias('mdg'))
self.base_query_from = (a_s.join(
ad, ad.c.id == a_s.c.alarm_definition_id).join(
am, am.c.alarm_id == a_s.c.id).join(
mdd,
mdd.c.id == am.c.metric_definition_dimensions_id).join(
mde, mde.c.id == mdd.c.metric_definition_id).outerjoin(
mdg, mdg.c.dimension_set_id ==
mdd.c.metric_dimension_set_id))
self.base_query = select([
a_s.c.id.label('alarm_id'), a_s.c.state,
a_s.c.state_updated_at.label('state_updated_timestamp'),
a_s.c.updated_at.label('updated_timestamp'),
a_s.c.created_at.label('created_timestamp'), a_s.c.lifecycle_state,
a_s.c.link,
ad.c.id.label('alarm_definition_id'),
ad.c.name.label('alarm_definition_name'), ad.c.severity,
mde.c.name.label('metric_name'),
mdg.c.dimensions.label('metric_dimensions')
])
self.base_subquery_list = (select([a_s.c.id]).select_from(
a_s.join(ad, a_s.c.alarm_definition_id == ad.c.id)))
self.get_ad_query = (select([ad]).select_from(
ad.join(a, ad.c.id == a.c.alarm_definition_id)).where(
ad.c.tenant_id == bindparam('b_tenant_id')).where(
a.c.id == bindparam('b_id')))
self.get_am_query = (select([
a_s.c.id.label('alarm_id'), mde.c.name, mdg.c.dimensions
]).select_from(
a_s.join(am, am.c.alarm_id == a_s.c.id).join(
mdd, mdd.c.id == am.c.metric_definition_dimensions_id).join(
mde, mde.c.id == mdd.c.metric_definition_id).outerjoin(
mdg, mdg.c.dimension_set_id ==
mdd.c.metric_dimension_set_id)).where(
a_s.c.id == bindparam('b_id')).order_by(
a_s.c.id).distinct())
self.get_sa_query = (select([
sa.c.id.label('sub_alarm_id'), sa.c.alarm_id, sa.c.expression,
ad.c.id.label('alarm_definition_id')
]).select_from(
sa.join(a_s, a_s.c.id == sa.c.alarm_id).join(
ad, ad.c.id == a_s.c.alarm_definition_id)).where(
ad.c.tenant_id == bindparam('b_tenant_id')).where(
a_s.c.id == bindparam('b_id')).distinct())
self.get_a_query = (select(
[a_s.c.state, a_s.c.link, a_s.c.lifecycle_state]).select_from(
a_s.join(ad, ad.c.id == a_s.c.alarm_definition_id)).where(
ad.c.tenant_id == bindparam('b_tenant_id')).where(
a_s.c.id == bindparam('b_id')))
self.get_a_ad_query = (select([a_s.c.id]).select_from(
a_s.join(ad, ad.c.id == a_s.c.alarm_definition_id)).where(
ad.c.tenant_id == bindparam('b_tenant_id')).where(
a_s.c.id == bindparam('b_id')).alias('a_ad'))
select_tmp = (select([literal_column('id')]).select_from(
self.get_a_ad_query).distinct().alias('temporarytable'))
self.delete_alarm_query = (delete(a).where(a.c.id.in_(select_tmp)))
md_ = (select([
mde.c.id
]).where(mde.c.name == bindparam('b_md_name')).alias('md_'))
self.get_a_am_query = (select([a_s.c.id]).select_from(
a_s.join(am, am.c.alarm_id == a_s.c.id).join(
mdd, mdd.c.id == am.c.metric_definition_dimensions_id).join(
md_, md_.c.id == mdd.c.metric_definition_id)))
def get_significant_states_with_session(
hass: HomeAssistant,
session: Session,
start_time: datetime,
end_time: datetime | None = None,
entity_ids: list[str] | None = None,
filters: Any = None,
include_start_time_state: bool = True,
significant_changes_only: bool = True,
minimal_response: bool = False,
no_attributes: bool = False,
) -> MutableMapping[str, Iterable[LazyState | State | dict[str, Any]]]:
"""
Return states changes during UTC period start_time - end_time.
entity_ids is an optional iterable of entities to include in the results.
filters is an optional SQLAlchemy filter which will be applied to the database
queries unless entity_ids is given, in which case its ignored.
Significant states are all states where there is a state change,
as well as all states from certain domains (for instance
thermostat so that we get current temperature in our graphs).
"""
timer_start = time.perf_counter()
baked_query, join_attributes = bake_query_and_join_attributes(
hass, no_attributes)
if entity_ids is not None and len(entity_ids) == 1:
if (significant_changes_only and split_entity_id(entity_ids[0])[0]
not in SIGNIFICANT_DOMAINS):
baked_query += lambda q: q.filter(States.last_changed == States.
last_updated)
elif significant_changes_only:
baked_query += lambda q: q.filter(
or_(
*[
States.entity_id.like(entity_domain)
for entity_domain in SIGNIFICANT_DOMAINS_ENTITY_ID_LIKE
],
(States.last_changed == States.last_updated),
))
if entity_ids is not None:
baked_query += lambda q: q.filter(
States.entity_id.in_(bindparam("entity_ids", expanding=True)))
else:
baked_query += lambda q: q.filter(
and_(*[
~States.entity_id.like(entity_domain)
for entity_domain in IGNORE_DOMAINS_ENTITY_ID_LIKE
]))
if filters:
filters.bake(baked_query)
baked_query += lambda q: q.filter(States.last_updated > bindparam(
"start_time"))
if end_time is not None:
baked_query += lambda q: q.filter(States.last_updated < bindparam(
"end_time"))
if join_attributes:
baked_query += lambda q: q.outerjoin(
StateAttributes, States.attributes_id == StateAttributes.
attributes_id)
baked_query += lambda q: q.order_by(States.entity_id, States.last_updated)
states = execute(
baked_query(session).params(start_time=start_time,
end_time=end_time,
entity_ids=entity_ids))
if _LOGGER.isEnabledFor(logging.DEBUG):
elapsed = time.perf_counter() - timer_start
_LOGGER.debug("get_significant_states took %fs", elapsed)
return _sorted_states_to_dict(
hass,
session,
states,
start_time,
entity_ids,
filters,
include_start_time_state,
minimal_response,
no_attributes,
)
def __parse_sql_statement(self, text, **params):
"""
Parse and bind paramaters to create a SQL statement.
adapted from https://github.com/cs50/python-cs50
"""
class UserDefinedType(sqlalchemy.TypeDecorator):
"""
Add support for expandable values, a la https://bitbucket.org/zzzeek/sqlalchemy/issues/3953/expanding-parameter.
"""
impl = sqlalchemy.types.UserDefinedType
def process_literal_param(self, value, dialect):
"""Receive a literal parameter value to be rendered inline within a statement."""
def process(value):
"""Render a literal value, escaping as needed."""
# bool
if isinstance(value, bool):
return sqlalchemy.types.Boolean().literal_processor(dialect)(value)
# datetime.date
elif isinstance(value, datetime.date):
return sqlalchemy.types.String().literal_processor(dialect)(value.strftime("%Y-%m-%d"))
# datetime.datetime
elif isinstance(value, datetime.datetime):
return sqlalchemy.types.String().literal_processor(dialect)(value.strftime("%Y-%m-%d %H:%M:%S"))
# datetime.time
elif isinstance(value, datetime.time):
return sqlalchemy.types.String().literal_processor(dialect)(value.strftime("%H:%M:%S"))
# float
elif isinstance(value, float):
return sqlalchemy.types.Float().literal_processor(dialect)(value)
# int
elif isinstance(value, int):
return sqlalchemy.types.Integer().literal_processor(dialect)(value)
# long - modified to use int instead of long in py3 so i dont need this
# - see https://docs.python.org/3.3/whatsnew/3.0.html#integers
# elif sys.version_info.major != 3 and isinstance(value, long):
# return sqlalchemy.types.Integer().literal_processor(dialect)(value)
# str
elif isinstance(value, str):
return sqlalchemy.types.String().literal_processor(dialect)(value)
# None
elif isinstance(value, sqlalchemy.sql.elements.Null):
return sqlalchemy.types.NullType().literal_processor(dialect)(value)
# Unsupported value
raise RuntimeError("unsupported value")
# Process value(s), separating with commas as needed
if type(value) is list:
return ", ".join([process(v) for v in value])
else:
return process(value)
# Allow only one statement at a time
# SQLite does not support executing many statements
# https://docs.python.org/3/library/sqlite3.html#sqlite3.Cursor.execute
if (len(sqlparse.split(text)) > 1 and
self.__common_engine.url.get_backend_name() == "sqlite"):
raise RuntimeError("too many statements at once")
# Raise exceptions for warnings
warnings.filterwarnings("error")
log = re.sub(r"\n\s*", " ", text)
# Prepare, execute statement
try:
# Construct a new TextClause clause
statement = sqlalchemy.text(text)
# Iterate over parameters
for key, value in params.items():
# Translate None to NULL
if value is None:
value = sqlalchemy.sql.null()
if self.__common_engine.url.get_backend_name() == "sqlite":
# for some reason, bool isnt being converted to int
if value == True:
value = 1
elif value == False:
value = 0
# Bind parameters before statement reaches database, so that bound parameters appear in exceptions
# http://docs.sqlalchemy.org/en/latest/core/sqlelement.html#sqlalchemy.sql.expression.text
statement = statement.bindparams(sqlalchemy.bindparam(
key, value=value, type_=UserDefinedType()))
# Stringify bound parameters
# http://docs.sqlalchemy.org/en/latest/faq/sqlexpressions.html#how-do-i-render-sql-expressions-as-strings-possibly-with-bound-parameters-inlined
statement = str(statement.compile(compile_kwargs={"literal_binds": True}))
log = re.sub(r"\n\s*", " ", sqlparse.format(statement, reindent=True))
return statement
except:
self.logger.debug(termcolor.colored(log, "red"))
self.logger.debug(termcolor.colored(sys.exc_info()[0], "red"))
raise
def fn2(q):
canary.fn2()
return q.filter(User.id == bindparam("id"))
def param(self, parameter: str) -> Union[BindParameter]:
if self._is_sqlalchemy:
return bindparam(parameter)
raise NotImplementedError()
def upgrade():
from depot.manager import DepotManager
from depot.fields.upload import UploadedFile
from sqlalchemy import bindparam, Unicode, Column
from kotti import DBSession, metadata
files = sa.Table('files', metadata)
files.c.data.type = sa.LargeBinary() # this restores to old column type
dn = DepotManager.get_default()
_saved = []
def process(thing):
id, data, filename, mimetype = thing
uploaded_file = UploadedFile({'depot_name': dn, 'files': []})
# noinspection PyProtectedMember
uploaded_file._thaw()
uploaded_file.process_content(
data, filename=filename, content_type=mimetype)
_saved.append({'nodeid': id, 'data': uploaded_file.encode()})
log.info(f"Saved data for node id {id}")
query = DBSession.query(
files.c.id, files.c.data, files.c.filename, files.c.mimetype
).order_by(files.c.id).yield_per(10)
window_size = 10
window_idx = 0
log.info("Starting migration of blob data")
now = time.time()
while True:
start, stop = window_size * window_idx, window_size * (window_idx + 1)
things = query.slice(start, stop).all()
if things is None:
break
for thing in things:
process(thing)
if len(things) < window_size:
break
window_idx += 1
log.info("Files written on disk, saving information to DB")
op.drop_column('files', 'data')
op.add_column('files', Column('data', Unicode(4096)))
files.c.data.type = Unicode(4096)
update = files.update().where(files.c.id == bindparam('nodeid')).\
values({files.c.data: bindparam('data')})
def chunks(l, n):
for i in range(0, len(l), n):
yield l[i:i + n]
for cdata in chunks(_saved, 10):
DBSession.execute(update, cdata)
log.info("Blob migration completed in {} seconds".format(
int(time.time() - now)))
def test_insert(self):
stmt = self.tables.foo.insert().values(
x=bindparam('x'), data=bindparam('data'))
self._assert_raises(stmt, {'data': 'data'})
async def bulk_update( # noqa: CCR001
self,
objects: List["Model"],
columns: List[str] = None) -> None:
"""
Performs bulk update in one database session to speed up the process.
Allows to update multiple instance at once.
All `Models` passed need to have primary key column populated.
You can also select which fields to update by passing `columns` list
as a list of string names.
Bulk operations do not send signals.
:param objects: list of ormar models
:type objects: List[Model]
:param columns: list of columns to update
:type columns: List[str]
"""
ready_objects = []
pk_name = self.model_meta.pkname
if not columns:
columns = list(self.model.extract_db_own_fields().union(
self.model.extract_related_names()))
if pk_name not in columns:
columns.append(pk_name)
columns = [self.model.get_column_alias(k) for k in columns]
for objt in objects:
new_kwargs = objt.dict()
if pk_name not in new_kwargs or new_kwargs.get(pk_name) is None:
raise ModelPersistenceError(
"You cannot update unsaved objects. "
f"{self.model.__name__} has to have {pk_name} filled.")
new_kwargs = self.model.substitute_models_with_pks(new_kwargs)
new_kwargs = self.model.translate_columns_to_aliases(new_kwargs)
new_kwargs = {
"new_" + k: v
for k, v in new_kwargs.items() if k in columns
}
ready_objects.append(new_kwargs)
pk_column = self.model_meta.table.c.get(
self.model.get_column_alias(pk_name))
pk_column_name = self.model.get_column_alias(pk_name)
table_columns = [c.name for c in self.model_meta.table.c]
expr = self.table.update().where(
pk_column == bindparam("new_" + pk_column_name))
expr = expr.values(
**{
k: bindparam("new_" + k)
for k in columns if k != pk_column_name and k in table_columns
})
# databases bind params only where query is passed as string
# otherwise it just passes all data to values and results in unconsumed columns
expr = str(expr)
await self.database.execute_many(expr, ready_objects)
for objt in objects:
objt.set_save_status(True)
def get_alarms_count(self,
tenant_id,
query_parms=None,
offset=None,
limit=None):
if not query_parms:
query_parms = {}
with self._db_engine.connect() as conn:
parms = {}
ad = self.ad
am = self.am
mdd = self.mdd
mde = self.mde
md = self.md
a = self.a
query_from = a.join(ad, ad.c.id == a.c.alarm_definition_id)
parms['b_tenant_id'] = tenant_id
group_by_columns = []
if 'group_by' in query_parms:
group_by_columns = query_parms['group_by']
sub_group_by_columns = []
metric_group_by = {
'metric_name', 'dimension_name', 'dimension_value'
}.intersection(set(query_parms['group_by']))
if metric_group_by:
sub_query_columns = [am.c.alarm_id]
if 'metric_name' in metric_group_by:
sub_group_by_columns.append(
mde.c.name.label('metric_name'))
if 'dimension_name' in metric_group_by:
sub_group_by_columns.append(
md.c.name.label('dimension_name'))
if 'dimension_value' in metric_group_by:
sub_group_by_columns.append(
md.c.value.label('dimension_value'))
sub_query_columns.extend(sub_group_by_columns)
sub_query_from = (mde.join(
mdd, mde.c.id == mdd.c.metric_definition_id).join(
md, mdd.c.metric_dimension_set_id ==
md.c.dimension_set_id).join(
am, am.c.metric_definition_dimensions_id ==
mdd.c.id))
sub_query = (select(sub_query_columns).select_from(
sub_query_from).distinct().alias('metrics'))
query_from = query_from.join(
sub_query, sub_query.c.alarm_id == a.c.id)
query_columns = [func.count().label('count')]
query_columns.extend(group_by_columns)
query = (select(query_columns).select_from(query_from).where(
ad.c.tenant_id == bindparam('b_tenant_id')))
parms['b_tenant_id'] = tenant_id
if 'alarm_definition_id' in query_parms:
parms['b_alarm_definition_id'] = query_parms[
'alarm_definition_id']
query = query.where(
ad.c.id == bindparam('b_alarm_definition_id'))
if 'state' in query_parms:
parms['b_state'] = query_parms['state'] if six.PY3 else \
query_parms['state'].encode('utf8')
query = query.where(a.c.state == bindparam('b_state'))
if 'severity' in query_parms:
severities = query_parms['severity'].split('|')
query = query.where(
or_(ad.c.severity == bindparam('b_severity' + str(i))
for i in range(len(severities))))
for i, s in enumerate(severities):
parms['b_severity' +
str(i)] = s if six.PY3 else s.encode('utf8')
if 'lifecycle_state' in query_parms:
parms['b_lifecycle_state'] = query_parms['lifecycle_state'] if six.PY3 else \
query_parms['lifecycle_state'].encode('utf8')
query = query.where(
a.c.lifecycle_state == bindparam('b_lifecycle_state'))
if 'link' in query_parms:
parms['b_link'] = query_parms['link'] if six.PY3 else \
query_parms['link'].encode('utf8')
query = query.where(a.c.link == bindparam('b_link'))
if 'state_updated_start_time' in query_parms:
date_str = query_parms['state_updated_start_time'] if six.PY3 \
else query_parms['state_updated_start_time'].encode('utf8')
date_param = datetime.strptime(date_str,
'%Y-%m-%dT%H:%M:%S.%fZ')
parms['b_state_updated_at'] = date_param
query = query.where(
a.c.state_updated_at >= bindparam('b_state_updated_at'))
if 'metric_name' in query_parms:
query = query.where(a.c.id.in_(self.get_a_am_query))
parms['b_md_name'] = query_parms['metric_name'] if six.PY3 else \
query_parms['metric_name'].encode('utf8')
if 'metric_dimensions' in query_parms:
sub_query = select([a.c.id])
sub_query_from = (a.join(am, am.c.alarm_id == a.c.id).join(
mdd, mdd.c.id == am.c.metric_definition_dimensions_id))
sub_query_md_base = select([md.c.dimension_set_id
]).select_from(md)
for i, metric_dimension in enumerate(
query_parms['metric_dimensions'].items()):
dimension_value = metric_dimension[1] if six.PY3 else \
metric_dimension[1].encode('utf8')
if '|' in dimension_value:
dimension_value = tuple(dimension_value.split('|'))
md_name = "b_md_name_{}".format(i)
md_value = "b_md_value_{}".format(i)
sub_query_md = (sub_query_md_base.where(
md.c.name == bindparam(md_name)))
if isinstance(dimension_value, tuple):
sub_query_md = (sub_query_md.where(
md.c.value.op('IN')(bindparam(md_value))))
else:
sub_query_md = (sub_query_md.where(
md.c.value == bindparam(md_value)))
sub_query_md = (sub_query_md.distinct().alias(
'md_{}'.format(i)))
sub_query_from = (sub_query_from.join(
sub_query_md, sub_query_md.c.dimension_set_id ==
mdd.c.metric_dimension_set_id))
parms[md_name] = metric_dimension[0] if six.PY3 else \
metric_dimension[0].encode('utf8')
parms[md_value] = dimension_value
sub_query = (
sub_query.select_from(sub_query_from).distinct())
query = query.where(a.c.id.in_(sub_query))
if group_by_columns:
query = (query.order_by(*group_by_columns).group_by(
*group_by_columns))
if limit:
query = query.limit(bindparam('b_limit'))
parms['b_limit'] = limit + 1
if offset:
query = query.offset(bindparam('b_offset'))
parms['b_offset'] = offset
query = query.distinct()
return [dict(row) for row in conn.execute(query, parms).fetchall()]
def messages_or_drafts(namespace_id, drafts, subject, from_addr, to_addr,
cc_addr, bcc_addr, any_email, thread_public_id,
started_before, started_after, last_message_before,
last_message_after, received_before, received_after,
filename, in_, unread, starred, limit, offset, view,
db_session):
# Warning: complexities ahead. This function sets up the query that gets
# results for the /messages API. It loads from several tables, supports a
# variety of views and filters, and is performance-critical for the API. As
# such, it is not super simple.
#
# We bake the generated query to avoid paying query compilation overhead on
# every request. This requires some attention: every parameter that can
# vary between calls *must* be inserted via bindparam(), or else the first
# value passed will be baked into the query and reused on each request.
# Subqueries (on contact tables) can't be properly baked, so we have to
# call query.spoil() on those code paths.
param_dict = {
'namespace_id': namespace_id,
'drafts': drafts,
'subject': subject,
'from_addr': from_addr,
'to_addr': to_addr,
'cc_addr': cc_addr,
'bcc_addr': bcc_addr,
'any_email': any_email,
'thread_public_id': thread_public_id,
'received_before': received_before,
'received_after': received_after,
'started_before': started_before,
'started_after': started_after,
'last_message_before': last_message_before,
'last_message_after': last_message_after,
'filename': filename,
'in_': in_,
'unread': unread,
'starred': starred,
'limit': limit,
'offset': offset
}
if view == 'count':
target = func.count(Message.id)
elif view == 'ids':
target = Message.public_id
else:
target = Message
query = bakery(lambda s: s.query(target))
query += lambda q: q.join(Thread)
query += lambda q: q.filter(
Message.namespace_id == bindparam('namespace_id'), Message.is_draft ==
bindparam('drafts'))
if subject is not None:
query += lambda q: q.filter(Message.subject == bindparam('subject'))
if unread is not None:
query += lambda q: q.filter(Message.is_read != bindparam('unread'))
if starred is not None:
query += lambda q: q.filter(Message.is_starred == bindparam('starred'))
if thread_public_id is not None:
query += lambda q: q.filter(Thread.public_id == bindparam(
'thread_public_id'))
# TODO: deprecate thread-oriented date filters on message endpoints.
if started_before is not None:
query += lambda q: q.filter(
Thread.subjectdate < bindparam('started_before'), Thread.
namespace_id == bindparam('namespace_id'))
if started_after is not None:
query += lambda q: q.filter(
Thread.subjectdate > bindparam('started_after'), Thread.
namespace_id == bindparam('namespace_id'))
if last_message_before is not None:
query += lambda q: q.filter(
Thread.recentdate < bindparam('last_message_before'), Thread.
namespace_id == bindparam('namespace_id'))
if last_message_after is not None:
query += lambda q: q.filter(
Thread.recentdate > bindparam('last_message_after'), Thread.
namespace_id == bindparam('namespace_id'))
if received_before is not None:
query += lambda q: q.filter(Message.received_date <= bindparam(
'received_before'))
if received_after is not None:
query += lambda q: q.filter(Message.received_date > bindparam(
'received_after'))
if to_addr is not None:
query.spoil()
to_query = db_session.query(MessageContactAssociation.message_id). \
join(Contact).filter(
MessageContactAssociation.field == 'to_addr',
Contact.email_address == to_addr,
Contact.namespace_id == bindparam('namespace_id')).subquery()
query += lambda q: q.filter(Message.id.in_(to_query))
if from_addr is not None:
query.spoil()
from_query = db_session.query(MessageContactAssociation.message_id). \
join(Contact).filter(
MessageContactAssociation.field == 'from_addr',
Contact.email_address == from_addr,
Contact.namespace_id == bindparam('namespace_id')).subquery()
query += lambda q: q.filter(Message.id.in_(from_query))
if cc_addr is not None:
query.spoil()
cc_query = db_session.query(MessageContactAssociation.message_id). \
join(Contact).filter(
MessageContactAssociation.field == 'cc_addr',
Contact.email_address == cc_addr,
Contact.namespace_id == bindparam('namespace_id')).subquery()
query += lambda q: q.filter(Message.id.in_(cc_query))
if bcc_addr is not None:
query.spoil()
bcc_query = db_session.query(MessageContactAssociation.message_id). \
join(Contact).filter(
MessageContactAssociation.field == 'bcc_addr',
Contact.email_address == bcc_addr,
Contact.namespace_id == bindparam('namespace_id')).subquery()
query += lambda q: q.filter(Message.id.in_(bcc_query))
if any_email is not None:
query.spoil()
any_email_query = db_session.query(
MessageContactAssociation.message_id).join(Contact). \
filter(Contact.email_address == any_email,
Contact.namespace_id == bindparam('namespace_id')). \
subquery()
query += lambda q: q.filter(Message.id.in_(any_email_query))
if filename is not None:
query += lambda q: q.join(Part).join(Block). \
filter(Block.filename == bindparam('filename'),
Block.namespace_id == bindparam('namespace_id'))
if in_ is not None:
query.spoil()
category_filters = [
Category.name == bindparam('in_'),
Category.display_name == bindparam('in_')
]
try:
valid_public_id(in_)
category_filters.append(Category.public_id == bindparam('in_id'))
# Type conversion and bindparams interact poorly -- you can't do
# e.g.
# query.filter(or_(Category.name == bindparam('in_'),
# Category.public_id == bindparam('in_')))
# because the binary conversion defined by Category.public_id will
# be applied to the bound value prior to its insertion in the
# query. So we define another bindparam for the public_id:
param_dict['in_id'] = in_
except InputError:
pass
query += lambda q: q.join(MessageCategory).join(Category). \
filter(Category.namespace_id == namespace_id,
or_(*category_filters))
if view == 'count':
res = query(db_session).params(**param_dict).one()[0]
return {"count": res}
query += lambda q: q.order_by(desc(Message.received_date))
query += lambda q: q.limit(bindparam('limit'))
if offset:
query += lambda q: q.offset(bindparam('offset'))
if view == 'ids':
res = query(db_session).params(**param_dict).all()
return [x[0] for x in res]
# Eager-load related attributes to make constructing API representations
# faster.
query += lambda q: q.options(
contains_eager(Message.thread),
subqueryload(Message.messagecategories).joinedload('category'),
subqueryload(Message.parts).joinedload(Part.block),
subqueryload(Message.events))
prepared = query(db_session).params(**param_dict)
return prepared.all()
def _get_significant_states(
hass,
session,
start_time,
end_time=None,
entity_ids=None,
filters=None,
include_start_time_state=True,
significant_changes_only=True,
minimal_response=False,
):
"""
Return states changes during UTC period start_time - end_time.
Significant states are all states where there is a state change,
as well as all states from certain domains (for instance
thermostat so that we get current temperature in our graphs).
"""
timer_start = time.perf_counter()
baked_query = hass.data[HISTORY_BAKERY](
lambda session: session.query(*QUERY_STATES)
)
if significant_changes_only:
baked_query += lambda q: q.filter(
(
States.domain.in_(SIGNIFICANT_DOMAINS)
| (States.last_changed == States.last_updated)
)
& (States.last_updated > bindparam("start_time"))
)
else:
baked_query += lambda q: q.filter(States.last_updated > bindparam("start_time"))
if entity_ids is not None:
baked_query += lambda q: q.filter(
States.entity_id.in_(bindparam("entity_ids", expanding=True))
)
else:
baked_query += lambda q: q.filter(~States.domain.in_(IGNORE_DOMAINS))
if filters:
filters.bake(baked_query)
if end_time is not None:
baked_query += lambda q: q.filter(States.last_updated < bindparam("end_time"))
baked_query += lambda q: q.order_by(States.entity_id, States.last_updated)
states = execute(
baked_query(session).params(
start_time=start_time, end_time=end_time, entity_ids=entity_ids
)
)
if _LOGGER.isEnabledFor(logging.DEBUG):
elapsed = time.perf_counter() - timer_start
_LOGGER.debug("get_significant_states took %fs", elapsed)
return _sorted_states_to_dict(
hass,
session,
states,
start_time,
entity_ids,
filters,
include_start_time_state,
minimal_response,
)
def check_password(environ, user, password):
"""
:param environ: Dictionary that contains the apache environment variables.
There's a lot of overlap of what you get from this dictionary
and http://php.net/manual/en/reserved.variables.server.php
:param user: String containing the username passed to the apache authentication box
:param password: String containing the password passed to the apache authentication box
:return: Boolean for whether user was properly authenticated (True) or not (False)
"""
# The REQUEST_URI will contain stuff after the usual /<VCS>/<SEMESTER>/<COURSE>/<G_ID>/<USER_ID> that have
# to do with the GIT and whether it's pushing, pulling, cloning, etc.
params = list(
filter(lambda x: len(x) > 0, environ['REQUEST_URI'].split("/")))
vcs = params[0]
vcs_paths = []
if vcs == 'git':
# info/refs?service=git-upload-pack
vcs_paths = [
'info', 'git-upload-pack', 'refs?service=git-upload-pack',
'refs?service=git-receive-pack', 'git-receive-pack'
]
params = list(filter(lambda x: x not in vcs_paths, params))
if len(params) == 5:
semester, course, gradeable = params[1:4]
# check if this is a team or individual gradeable
course_db = "submitty_{}_{}".format(semester, course)
if os.path.isdir(DATABASE_HOST):
course_conn_string = "postgresql://{}:{}@/{}?host={}".format(
DATABASE_USER, DATABASE_PASS, course_db, DATABASE_HOST)
else:
course_conn_string = "postgresql://{}:{}@{}/{}".format(
DATABASE_USER, DATABASE_PASS, DATABASE_HOST, course_db)
course_engine = create_engine(course_conn_string)
course_connection = course_engine.connect()
course_metadata = MetaData(bind=course_engine)
eg_table = Table('electronic_gradeable',
course_metadata,
autoload=True)
select = eg_table.select().where(
eg_table.c.g_id == bindparam('gradeable_id'))
eg = course_connection.execute(select,
gradeable_id=gradeable).fetchone()
if eg is None:
is_team = False
else:
is_team = eg.eg_team_assignment
if is_team:
user_id = None
team_id = params[4]
else:
user_id = params[4]
team_id = None
else:
return None
engine = connection = metadata = None
authenticated = False
if AUTHENTICATION_METHOD == 'PamAuthentication':
authenticated = check_pam(user, password)
# print(authenticated)
elif AUTHENTICATION_METHOD == 'DatabaseAuthentication':
engine, connection, metadata = open_database()
authenticated = check_database(user, password, connection, metadata)
if authenticated is not True or user == user_id:
close_database(engine, connection)
close_database(course_engine, course_connection)
return authenticated
if is_team:
teams_table = Table('teams', course_metadata, autoload=True)
select = teams_table.select().where(
teams_table.c.team_id == bindparam('team_id')).where(
teams_table.c.user_id == bindparam('user_id'))
team_user = course_connection.execute(select,
team_id=team_id,
user_id=user).fetchone()
if team_user is not None:
close_database(engine, connection)
close_database(course_engine, course_connection)
return authenticated
if engine is None:
engine, connection, metadata = open_database()
users_table = Table('courses_users', metadata, autoload=True)
select = users_table.select().where(users_table.c.user_id == bindparam('user_id'))\
.where(users_table.c.semester == bindparam('semester')).where(users_table.c.course == bindparam('course'))
course_user = connection.execute(select,
user_id=user,
semester=semester,
course=course).fetchone()
if course_user is None:
authenticated = None
else:
if course_user['user_group'] <= 2:
authenticated = True
else:
authenticated = False
close_database(engine, connection)
close_database(course_engine, course_connection)
return authenticated
def visit_unload_from_select(element, compiler, **kw):
"""Returns the actual sql query for the UnloadFromSelect class."""
template = """
UNLOAD (:select) TO :unload_location
CREDENTIALS :credentials
{manifest}
{header}
{format}
{delimiter}
{encrypted}
{fixed_width}
{gzip}
{add_quotes}
{null}
{escape}
{allow_overwrite}
{parallel}
{region}
{max_file_size}
"""
el = element
if el.format is None:
format_ = ''
elif el.format == Format.csv:
format_ = 'FORMAT AS {}'.format(el.format.value)
if el.delimiter is not None or el.fixed_width is not None:
raise ValueError(
'CSV format cannot be used with delimiter or fixed_width')
elif el.format == Format.parquet:
format_ = 'FORMAT AS {}'.format(el.format.value)
if any((
el.delimiter, el.fixed_width, el.add_quotes, el.escape, el.null,
el.header, el.gzip
)):
raise ValueError(
"Parquet format can't be used with `delimiter`, `fixed_width`,"
' `add_quotes`, `escape`, `null`, `header`, or `gzip`.'
)
else:
raise ValueError(
'Only CSV and Parquet formats are currently supported.'
)
qs = template.format(
manifest='MANIFEST' if el.manifest else '',
header='HEADER' if el.header else '',
format=format_,
delimiter=(
'DELIMITER AS :delimiter' if el.delimiter is not None else ''
),
encrypted='ENCRYPTED' if el.encrypted else '',
fixed_width='FIXEDWIDTH AS :fixed_width' if el.fixed_width else '',
gzip='GZIP' if el.gzip else '',
add_quotes='ADDQUOTES' if el.add_quotes else '',
escape='ESCAPE' if el.escape else '',
null='NULL AS :null_as' if el.null is not None else '',
allow_overwrite='ALLOWOVERWRITE' if el.allow_overwrite else '',
parallel='PARALLEL OFF' if not el.parallel else '',
region='REGION :region' if el.region is not None else '',
max_file_size=(
'MAXFILESIZE :max_file_size MB'
if el.max_file_size is not None else ''
),
)
query = sa.text(qs)
if el.delimiter is not None:
query = query.bindparams(sa.bindparam(
'delimiter', value=element.delimiter, type_=sa.String,
))
if el.fixed_width:
query = query.bindparams(sa.bindparam(
'fixed_width',
value=_process_fixed_width(el.fixed_width),
type_=sa.String,
))
if el.null is not None:
query = query.bindparams(sa.bindparam(
'null_as', value=el.null, type_=sa.String
))
if el.region is not None:
query = query.bindparams(sa.bindparam(
'region', value=el.region, type_=sa.String
))
if el.max_file_size is not None:
max_file_size_mib = float(el.max_file_size) / 1024 / 1024
query = query.bindparams(sa.bindparam(
'max_file_size', value=max_file_size_mib, type_=sa.Float
))
return compiler.process(
query.bindparams(
sa.bindparam('credentials', value=el.credentials, type_=sa.String),
sa.bindparam(
'unload_location', value=el.unload_location, type_=sa.String,
),
sa.bindparam(
'select',
value=compiler.process(
el.select,
literal_binds=True,
),
type_=sa.String,
),
),
**kw
)
def test_custom_bind(self):
Address, addresses, users, User = (
self.classes.Address,
self.tables.addresses,
self.tables.users,
self.classes.User,
)
mapper(
User,
users,
properties=dict(
addresses=relationship(
mapper(Address, addresses),
lazy="select",
primaryjoin=and_(
users.c.id == addresses.c.user_id,
users.c.name == bindparam("name"),
),
)
),
)
canary = mock.Mock()
class MyOption(MapperOption):
propagate_to_loaders = True
def __init__(self, crit):
self.crit = crit
def process_query_conditionally(self, query):
"""process query during a lazyload"""
canary()
params = dict(query.load_options._params)
query.load_options += {"_params": params}
query.load_options._params.update(dict(name=self.crit))
s = Session()
ed = s.query(User).options(MyOption("ed")).filter_by(name="ed").one()
eq_(
ed.addresses,
[
Address(id=2, user_id=8),
Address(id=3, user_id=8),
Address(id=4, user_id=8),
],
)
eq_(canary.mock_calls, [mock.call()])
fred = (
s.query(User).options(MyOption("ed")).filter_by(name="fred").one()
)
eq_(fred.addresses, []) # fred is missing
eq_(canary.mock_calls, [mock.call(), mock.call()])
# the lazy query was not cached; the option is re-applied to the
# Fred object due to populate_existing()
fred = (
s.query(User)
.populate_existing()
.options(MyOption("fred"))
.filter_by(name="fred")
.one()
)
eq_(fred.addresses, [Address(id=5, user_id=9)]) # fred is there
eq_(canary.mock_calls, [mock.call(), mock.call(), mock.call()])
def setUpClass(cls):
from sqlalchemy import engine_from_config
engine = engine_from_config({'url': 'sqlite://'}, prefix='')
qry = open('monasca_api/tests/sqlite_alarm.sql', 'r').read()
sconn = engine.raw_connection()
c = sconn.cursor()
c.executescript(qry)
sconn.commit()
c.close()
cls.engine = engine
def _fake_engine_from_config(*args, **kw):
return cls.engine
cls.fixture = fixtures.MonkeyPatch('sqlalchemy.create_engine',
_fake_engine_from_config)
cls.fixture.setUp()
metadata = MetaData()
cls.aa = models.create_aa_model(metadata)
cls._delete_aa_query = delete(cls.aa)
cls._insert_aa_query = (insert(cls.aa).values(
alarm_definition_id=bindparam('alarm_definition_id'),
alarm_state=bindparam('alarm_state'),
action_id=bindparam('action_id')))
cls.ad = models.create_ad_model(metadata)
cls._delete_ad_query = delete(cls.ad)
cls._insert_ad_query = (insert(cls.ad).values(
id=bindparam('id'),
tenant_id=bindparam('tenant_id'),
name=bindparam('name'),
severity=bindparam('severity'),
expression=bindparam('expression'),
match_by=bindparam('match_by'),
actions_enabled=bindparam('actions_enabled'),
created_at=bindparam('created_at'),
updated_at=bindparam('updated_at'),
deleted_at=bindparam('deleted_at')))
cls.sad = models.create_sad_model(metadata)
cls._delete_sad_query = delete(cls.sad)
cls._insert_sad_query = (insert(cls.sad).values(
id=bindparam('id'),
alarm_definition_id=bindparam('alarm_definition_id'),
function=bindparam('function'),
metric_name=bindparam('metric_name'),
operator=bindparam('operator'),
threshold=bindparam('threshold'),
period=bindparam('period'),
periods=bindparam('periods'),
created_at=bindparam('created_at'),
updated_at=bindparam('updated_at')))
cls.sadd = models.create_sadd_model(metadata)
cls._delete_sadd_query = delete(cls.sadd)
cls._insert_sadd_query = (insert(cls.sadd).values(
sub_alarm_definition_id=bindparam('sub_alarm_definition_id'),
dimension_name=bindparam('dimension_name'),
value=bindparam('value')))
cls.nm = models.create_nm_model(metadata)
cls._delete_nm_query = delete(cls.nm)
cls._insert_nm_query = (insert(cls.nm).values(
id=bindparam('id'),
tenant_id=bindparam('tenant_id'),
name=bindparam('name'),
type=bindparam('type'),
address=bindparam('address'),
created_at=bindparam('created_at'),
updated_at=bindparam('updated_at')))
def main(inicio, fin, ci):
"""
En el archivo bandejas.cfg se guardan los parametros de configuracion para la base de datos. El procedimiento toma el archivo de desde el mismo directorio donde se encuentra. En el archivo config.cfg se guardan parametros de configuracion.
\nEjecucion
El procedimiento se ejecuta de la siguiente forma:
(ejemplo)\n
$python bj.py --inicio='2018-05-01' --fin='2018-05-14'
- Novedades en el periodo [inicio, fin) , incluyendo inicio y no incluye la fecha de fin.Las novedades se refiere a las altas de designacion, ceses de designacion, anulaciones y pasajes a suplencias
- Para todas las personas (PerId) que tuvieron novedades en el periodo indicado, se toman los datos de toda la historia de altas, ceses, con tope el 01/03 del año correspondiente a la fecha de inicio que es pasada como parametro.
"""
with open('bandejas.cfg', 'r') as ymlfile:
cdb = yaml.load(ymlfile)
with open('config.cfg', 'r') as ymlfile:
cfg = yaml.load(ymlfile)
engine = create_engine('mysql+pymysql://' + cdb['personal']['usr'] + ':' +
cdb['personal']['password'] + '@' +
cdb['personal']['host'] + '/' +
cdb['personal']['bd'])
engine_bandeja_in = create_engine('mysql+pymysql://' +
cdb['bandeja_in']['usr'] + ':' +
cdb['bandeja_in']['password'] + '@' +
cdb['bandeja_in']['host'] + '/' +
cdb['bandeja_in']['bd'])
engine_bandeja_out = create_engine('mysql+pymysql://' +
cdb['bandeja_out']['usr'] + ':' +
cdb['bandeja_out']['password'] + '@' +
cdb['bandeja_out']['host'] + '/' +
cdb['bandeja_out']['bd'])
puestos_funcion = cfg[
'puestos_funcion'] # los puestos considerados docencia directa
parametros = {}
parametros['p1d'] = dt.date(int(inicio.split('-')[0]),
int(inicio.split('-')[1]),
int(inicio.split('-')[2]))
parametros['p2d'] = dt.date(int(fin.split('-')[0]), int(fin.split('-')[1]),
int(fin.split('-')[2]))
# no voy a dejar pasar designaciones que inicien a partir de este tope (el mes siguiente al dado como fin)
parametros['tope'] = dt.date(
int(fin.split('-')[0]) + (1 if (fin.split('-')[1] == '12') else 0),
1 if (fin.split('-')[1] == '12') else int(fin.split('-')[1]) + 1, 1)
# las causales de suplencia que interesan
suplcausales = cfg['suplcausales']
parametros['inicioLectivo'] = dt.datetime(
int(inicio.split('-')[0]) - (1 if inicio.split('-')[1] < '03' else 0),
03, 01)
#cargo metadatos del modelo Personal
metadata = sa.MetaData()
relaciones_laborales = sa.Table('RELACIONES_LABORALES',
metadata,
autoload=True,
autoload_with=engine)
anulaciones = sa.Table('ANULACIONES',
metadata,
autoload=True,
autoload_with=engine)
funciones_relacion_laboral = sa.Table('FUNCIONES_RELACION_LABORAL',
metadata,
autoload=True,
autoload_with=engine)
funciones_asignadas = sa.Table('FUNCIONES_ASIGNADAS',
metadata,
autoload=True,
autoload_with=engine)
sillas = sa.Table('SILLAS', metadata, autoload=True, autoload_with=engine)
cargas_horarias = sa.Table('CARGAS_HORARIAS',
metadata,
autoload=True,
autoload_with=engine)
silla_grupo_materia = sa.Table('SILLAGRUPOMATERIA',
metadata,
autoload=True,
autoload_with=engine)
puestos = sa.Table('PUESTOS',
metadata,
autoload=True,
autoload_with=engine)
denominaciones_cargo = sa.Table('DENOMINACIONES_CARGOS',
metadata,
autoload=True,
autoload_with=engine)
suplencias = sa.Table('SUPLENCIAS',
metadata,
autoload=True,
autoload_with=engine)
funciones_agrup_lin = sa.Table('FUNCION_AGRUP_LIN',
metadata,
autoload=True,
autoload_with=engine)
# cargo metadatos de Personas
personas = sa.Table('PERSONAS',
metadata,
schema="Personas",
autoload=True,
autoload_with=engine)
personas_documentos = sa.Table('PERSONASDOCUMENTOS',
metadata,
schema="Personas",
autoload=True,
autoload_with=engine)
# cargo los datos de materias de estudiantil
asignaturas_materias = sa.Table('ASIGNATURAS_MATERIAS',
metadata,
schema="Estudiantil",
autoload=True,
autoload_with=engine)
# cargo las materias de estudiantil
query_asignaturas_materias = sa.select([asignaturas_materias])
df_asignaturas_materias = pd.read_sql_query(query_asignaturas_materias,
engine,
params=parametros)
# cargo los datos de la base de siap para las dependencias
tabla_institucional = sa.Table('tabla_institucional',
metadata,
autoload=True,
autoload_with=engine_bandeja_in)
query_tabla_institucional = sa.select([
tabla_institucional.c.DEP_AS400.label('dependid'),
tabla_institucional.c.DEP_DBC.label('dependidSiap')
]).select_from(tabla_institucional)
df_tabla_institucional = pd.read_sql_query(query_tabla_institucional,
engine_bandeja_in,
params=parametros)
# cargo las funciones para identificar las horas de apoyo o POB , POP, talleristas , codigo 68
query_funciones_cargo = sa.select([funciones_agrup_lin])
df_funciones_cargo = pd.read_sql_query(query_funciones_cargo,
engine,
params=parametros)
df_funciones_hap = df_funciones_cargo.loc[
df_funciones_cargo.Funcion_Agrup_Cab_Id == 1, 'FuncionId']
df_funciones_POB = df_funciones_cargo.loc[
df_funciones_cargo.Funcion_Agrup_Cab_Id == 8, 'FuncionId']
df_funciones_POP = df_funciones_cargo.loc[
df_funciones_cargo.Funcion_Agrup_Cab_Id == 7, 'FuncionId']
df_funciones_68 = df_funciones_cargo.loc[
df_funciones_cargo.Funcion_Agrup_Cab_Id == 5, 'FuncionId']
df_funciones_talleristas = df_funciones_cargo.loc[
df_funciones_cargo.Funcion_Agrup_Cab_Id == 9, 'FuncionId']
df_coordinadores_especiales = df_funciones_cargo.loc[
df_funciones_cargo.Funcion_Agrup_Cab_Id == 10, 'FuncionId']
# novedades
query_novedades = sa. \
select([relaciones_laborales.c.PersonalPerId, relaciones_laborales.c.RelLabId]). \
select_from(relaciones_laborales.join(puestos)). \
where( \
(puestos.c.PuestoFuncionId.in_(puestos_funcion)) & \
# RL designada
(relaciones_laborales.c.PersonalPerId <> None) & \
( \
# se inicia en el período de la bandeja
( \
(relaciones_laborales.c.RelLabFchIniActividades >= sa.bindparam('p1d')) & \
(relaciones_laborales.c.RelLabFchIniActividades < sa.bindparam('p2d')) \
) | \
# o termina en el período de la bandeja
( \
(relaciones_laborales.c.RelLabCeseFchReal >= sa.bindparam('p1d')) & \
(relaciones_laborales.c.RelLabCeseFchReal < sa.bindparam('p2d')) \
) | \
# o cambiaron el alta con retraso
( \
(relaciones_laborales.c.RelLabFchIniActividades < sa.bindparam('p1d')) & \
(relaciones_laborales.c.RelLabDesignFchAlta >= sa.bindparam('p1d')) & \
(relaciones_laborales.c.RelLabDesignFchAlta < sa.bindparam('p2d')) \
) | \
# o cambiaron el cese con retraso
( \
(relaciones_laborales.c.RelLabCeseFchReal < sa.bindparam('p1d')) & \
(relaciones_laborales.c.RelLabCeseFchAlta >= sa.bindparam('p1d')) & \
(relaciones_laborales.c.RelLabCeseFchAlta < sa.bindparam('p2d'))
) \
) \
)
df_novedades = pd.read_sql_query(query_novedades,
engine,
params=parametros)
# cargo las anulaciones del periodo
query_anulaciones_periodo = sa. \
select([relaciones_laborales.c.PersonalPerId,relaciones_laborales.c.RelLabId, anulaciones.c.AnulacionFchAlta]). \
select_from(anulaciones.join(relaciones_laborales, cast(anulaciones.c.AnulacionValorPkTabla,Integer)==relaciones_laborales.c.RelLabId).join(puestos)). \
where( \
(anulaciones.c.AnulacionFchAlta >= sa.bindparam('p1d')) & \
(anulaciones.c.AnulacionFchAlta < sa.bindparam('p2d')) & \
(anulaciones.c.AnulacionTipoNombre=='DESIGNACION') & \
(puestos.c.PuestoFuncionId.in_(puestos_funcion)) \
)
df_anulaciones_periodo = pd.read_sql(query_anulaciones_periodo,
engine,
params=parametros)
rlt = aliased(relaciones_laborales) # RL de los titulares
rls = aliased(relaciones_laborales) # RL de los suplentes
# perids que tuvieron novedades o tienen eventos en el período de la bandeja (o el que vino de parámetro)
if ci != None: # si me pasaron una ci como parametro me interesan solo las novedades de esa ci
query_perid = sa.select([personas_documentos.c.PerId
]).select_from(personas_documentos).where(
(personas_documentos.c.PaisCod == 'UY')
& (personas_documentos.c.DocCod == 'CI')
& (personas_documentos.c.PerDocId == ci))
set_perids_novedades = pd.read_sql_query(
query_perid, engine, params=parametros)['PerId'].unique().tolist()
else:
# cargo las suplencias del período
query_suplencias = sa. \
select([rlt.c.PersonalPerId,suplencias.c.RelLabId,func.GREATEST(cast(suplencias.c.SuplFchAlta,Date),rlt.c.RelLabFchIniActividades).label('SuplFchAlta'),suplencias.c.SuplCausId,rlt.c.RelLabFchIniActividades,rlt.c.RelLabCeseFchReal,rls.c.RelLabAnulada.label('RelLabAnuladaS'),rls.c.RelLabFchIniActividades.label('RelLabFchIniActividadesS'),rls.c.RelLabCeseFchReal.label('RelLabCeseFchRealS')]). \
select_from(rlt.join(puestos).join(suplencias, suplencias.c.RelLabId==rlt.c.RelLabId).join(rls, rls.c.RelLabId==suplencias.c.SuplRelLabId)). \
where((puestos.c.PuestoFuncionId.in_(puestos_funcion)) & \
(suplencias.c.SuplCausId.in_(suplcausales)) & \
(rlt.c.RelLabAnulada==0) & \
((rlt.c.RelLabFchIniActividades < rlt.c.RelLabCeseFchReal) | (rlt.c.RelLabCeseFchReal==None)) & \
# la rls podría estar anulada y en ese caso se marca la novedad en RelLabCeseFchAlta
( \
# inicio de la suplencia está en el período de la bandeja:
((func.GREATEST(cast(suplencias.c.SuplFchAlta,Date),rlt.c.RelLabFchIniActividades) < sa.bindparam('p2d')) & \
(func.GREATEST(cast(suplencias.c.SuplFchAlta,Date),rlt.c.RelLabFchIniActividades) >= sa.bindparam('p1d')) \
) | \
# o el inicio de la suplencia fue modificado en el período de la bandeja:
((cast(suplencias.c.Suplencias_FchUltAct,Date) < sa.bindparam('p2d')) & \
(cast(suplencias.c.Suplencias_FchUltAct,Date) >= sa.bindparam('p1d')) \
) | \
# o el fin de la suplencia está en el período de la bandeja:
(((rls.c.RelLabCeseFchReal < sa.bindparam('p2d')) | (rls.c.RelLabCeseFchReal==None)) & \
(rls.c.RelLabCeseFchReal >= sa.bindparam('p1d')) \
) | \
# o el fin de la suplencia fue modificado o anulado en el período de la bandeja:
((rls.c.RelLabCeseFchAlta < sa.bindparam('p2d')) & \
(rls.c.RelLabCeseFchAlta >= sa.bindparam('p1d')) \
) \
) \
)
df_suplencias = pd.read_sql_query(query_suplencias,
engine,
params=parametros)
set_perids_novedades = df_novedades['PersonalPerId'].append(
df_anulaciones_periodo['PersonalPerId']).append(
df_suplencias['PersonalPerId']).unique().tolist()
if len(set_perids_novedades) == 0: #si no tengo cédulas para procesar
return
## Tomo la historia de los perid con novedades
# join historia básica
j3 = rlt.join(puestos).join(funciones_relacion_laboral).join(
funciones_asignadas).join(sillas).join(
silla_grupo_materia,
sillas.c.SillaId == silla_grupo_materia.c.SillaId,
isouter=True).join(
asignaturas_materias,
sillas.c.MateriaId == asignaturas_materias.c.MateriaId,
isouter=True)
# join suplencias
jsupl = suplencias.join(rls,
((rls.c.RelLabId == suplencias.c.SuplRelLabId) &
(rls.c.RelLabAnulada == 0) &
(suplencias.c.SuplCausId.in_(suplcausales))))
# clone de join suplencias para encontrar la siguiente
supl_siguiente = aliased(suplencias) # suplencia consecutiva a la actual
rls_siguiente = aliased(relaciones_laborales)
jsupl_siguiente = supl_siguiente.join(
rls_siguiente,
((rls_siguiente.c.RelLabId == supl_siguiente.c.SuplRelLabId) &
(rls_siguiente.c.RelLabAnulada == 0) &
(supl_siguiente.c.SuplCausId.in_(suplcausales))))
# clone de join suplencias para asegurar que no hay una intermedia entre la actual y la siguiente
supl_intermedia = aliased(suplencias) # suplencia consecutiva a la actual
rls_intermedia = aliased(relaciones_laborales)
jsupl_intermedia = supl_intermedia.join(
rls_intermedia,
((rls_intermedia.c.RelLabId == supl_intermedia.c.SuplRelLabId) &
(rls_intermedia.c.RelLabAnulada == 0) &
(supl_intermedia.c.SuplCausId.in_(suplcausales))))
# historia básica de los perids con novedades, no incluye RL bajadas a suplencia
query_historia_rl = sa. \
select([rlt.c.PersonalPerId, puestos.c.PuestoFuncionId,rlt.c.RelLabId,rlt.c.RelLabDesignCaracter,rlt.c.RelLabCicloPago,rlt.c.RelLabFchIniActividades, rlt.c.RelLabCeseFchReal, rlt.c.CauBajCod,silla_grupo_materia.c.GrupoMateriaId,sillas.c.TurnoId, sillas.c.SillaDependId,funciones_relacion_laboral.c.FuncRelLabCantHrs,sillas.c.FuncionId,rlt.c.RelLabAnulada,puestos.c.PuestoAsignId,asignaturas_materias.c.AsignId]). \
select_from( \
j3. \
join(jsupl, ((rlt.c.RelLabId==suplencias.c.RelLabId)), isouter=True) \
). \
where((rlt.c.RelLabFchIniActividades >= sa.bindparam('inicioLectivo')) & \
(rlt.c.PersonalPerId.in_(set_perids_novedades)) & \
(puestos.c.PuestoFuncionId.in_(puestos_funcion)) & \
(suplencias.c.RelLabId==None) \
)
df_historia_rl = pd.read_sql_query(query_historia_rl,
engine,
params=parametros)
df_historia_rl.loc[:, 'Origen'] = ['df_historia_rl']
# Cambio el número de asignatura de las Coordinaciones
df_historia_rl.loc[df_historia_rl['AsignId'] == 90,
['AsignId', 'RelLabDesignCaracter']] = [75, 'I']
# Cambio el número de asignatura de AAM
df_historia_rl.loc[df_historia_rl['AsignId'] == 98, 'AsignId'] = 77
# SUPLENCIAS
# Para cada bajada a suplencia implica (recorriéndolas en orden de fecha) hay que:
# (1) agregar un registro desde el fin de la suplencia hasta el final original (luego el paso 2 le puede cambiar el cese)
# (2) cesar la RL vigente en la fecha de inicio de la suplencia
# (3) si el causal de bajada corresponde, hay que crear un registro (alta) para el período de suplencia paga
# (1) altas inyectadas en la bandeja para el período posterior a cada licencia
query_alta_luego_de_suplencia = sa. \
select([rlt.c.PersonalPerId,puestos.c.PuestoFuncionId,rlt.c.RelLabId,rlt.c.RelLabDesignCaracter,rlt.c.RelLabCicloPago,func.GREATEST(rlt.c.RelLabFchIniActividades,func.ADDDATE(rls.c.RelLabCeseFchReal,1)).label('RelLabFchIniActividades'),func.IF(supl_siguiente.c.SuplId==None,rlt.c.RelLabCeseFchReal,cast(supl_siguiente.c.SuplFchAlta,Date)).label('RelLabCeseFchReal'),func.IF(supl_siguiente.c.SuplId==None,rlt.c.CauBajCod,'50').label('CauBajCod'),silla_grupo_materia.c.GrupoMateriaId,sillas.c.TurnoId,sillas.c.SillaDependId,funciones_relacion_laboral.c.FuncRelLabCantHrs,sillas.c.FuncionId,rlt.c.RelLabAnulada,puestos.c.PuestoAsignId,asignaturas_materias.c.AsignId]). \
select_from( \
jsupl. \
join(j3, ((rlt.c.RelLabId==suplencias.c.RelLabId) & (rlt.c.RelLabAnulada==0))). \
join(jsupl_siguiente,
((supl_siguiente.c.RelLabId==rlt.c.RelLabId) & (supl_siguiente.c.SuplId<>suplencias.c.SuplId) & (supl_siguiente.c.SuplFchAlta>=suplencias.c.SuplFchAlta)), \
isouter=True). \
join(jsupl_intermedia, \
((supl_intermedia.c.RelLabId==rlt.c.RelLabId) & (supl_intermedia.c.SuplId<>suplencias.c.SuplId) & (supl_intermedia.c.SuplFchAlta>=suplencias.c.SuplFchAlta) & (supl_intermedia.c.SuplId<>supl_siguiente.c.SuplId) & (supl_intermedia.c.SuplFchAlta<=supl_siguiente.c.SuplFchAlta)), \
isouter=True) \
). \
where( \
(rlt.c.RelLabFchIniActividades >= sa.bindparam('inicioLectivo')) & \
(rlt.c.PersonalPerId.in_(set_perids_novedades)) & \
(puestos.c.PuestoFuncionId.in_(puestos_funcion)) & \
(rls.c.RelLabCeseFchReal<>None) & \
(supl_intermedia.c.SuplId==None) & \
((supl_siguiente.c.SuplId==None) | ((rls.c.RelLabCeseFchReal<>None) & (cast(supl_siguiente.c.SuplFchAlta,Date) > rls.c.RelLabCeseFchReal))) & \
(func.ADDDATE(rls.c.RelLabCeseFchReal,1) < func.IF(supl_siguiente.c.SuplId==None,rlt.c.RelLabCeseFchReal,cast(supl_siguiente.c.SuplFchAlta,Date))) \
)
df_alta_luego_de_suplencia = pd.read_sql_query(
query_alta_luego_de_suplencia, engine, params=parametros)
df_alta_luego_de_suplencia.loc[:,
'Origen'] = ['df_alta_luego_de_suplencia']
# (2) alta inyectada para el período antes de la primer licencia
query_primera_suplencia = sa. \
select([rlt.c.PersonalPerId,puestos.c.PuestoFuncionId,rlt.c.RelLabId,rlt.c.RelLabDesignCaracter,rlt.c.RelLabCicloPago,rlt.c.RelLabFchIniActividades,cast(suplencias.c.SuplFchAlta,Date).label('RelLabCeseFchReal'),literal_column('50').label('CauBajCod'),silla_grupo_materia.c.GrupoMateriaId,sillas.c.TurnoId,sillas.c.SillaDependId,funciones_relacion_laboral.c.FuncRelLabCantHrs,sillas.c.FuncionId,rlt.c.RelLabAnulada,puestos.c.PuestoAsignId, asignaturas_materias.c.AsignId]). \
select_from(
jsupl. \
join(j3, ((rlt.c.RelLabId==suplencias.c.RelLabId) & (rlt.c.RelLabAnulada==0))). \
join(jsupl_intermedia, \
((supl_intermedia.c.RelLabId==rlt.c.RelLabId) & (supl_intermedia.c.SuplId<>suplencias.c.SuplId) & (supl_intermedia.c.SuplFchAlta<=suplencias.c.SuplFchAlta)),
isouter=True) \
). \
where( \
(rlt.c.RelLabFchIniActividades >= sa.bindparam('inicioLectivo')) & \
(rlt.c.PersonalPerId.in_(set_perids_novedades)) & \
(puestos.c.PuestoFuncionId.in_(puestos_funcion)) & \
(supl_intermedia.c.SuplId==None) & \
(rlt.c.RelLabFchIniActividades < cast(suplencias.c.SuplFchAlta,Date)) \
)
df_primera_suplencia = pd.read_sql_query(query_primera_suplencia,
engine,
params=parametros)
df_primera_suplencia.loc[:, 'Origen'] = ['df_primera_suplencia']
# (3) altas inyectadas en la bandeja para el período de licencia si es Junta Médica o Pase en Comisión
query_alta_suplencia_paga = sa. \
select([rlt.c.PersonalPerId,puestos.c.PuestoFuncionId,rlt.c.RelLabId,rlt.c.RelLabDesignCaracter,rlt.c.RelLabCicloPago,func.GREATEST(rlt.c.RelLabFchIniActividades,func.ADDDATE(cast(suplencias.c.SuplFchAlta,Date),1)).label('RelLabFchIniActividades'),func.IFNULL(rls.c.RelLabCeseFchReal,rlt.c.RelLabFchFinPrevista).label('RelLabCeseFchReal'),literal_column('50').label('CauBajCod'),silla_grupo_materia.c.GrupoMateriaId,sillas.c.TurnoId,sillas.c.SillaDependId,funciones_relacion_laboral.c.FuncRelLabCantHrs,sillas.c.FuncionId,rlt.c.RelLabAnulada,puestos.c.PuestoAsignId,asignaturas_materias.c.AsignId,suplencias.c.SuplCausId]). \
select_from(
jsupl.
join(j3, ((rlt.c.RelLabId==suplencias.c.RelLabId) & (rlt.c.RelLabAnulada==0))) \
). \
where( \
(rlt.c.RelLabFchIniActividades >= sa.bindparam('inicioLectivo')) & \
(rlt.c.PersonalPerId.in_(set_perids_novedades)) & \
(puestos.c.PuestoFuncionId.in_(puestos_funcion)) & \
(suplencias.c.SuplCausId.in_([16, 17, 162])) & \
(func.GREATEST(rlt.c.RelLabFchIniActividades,func.ADDDATE(cast(suplencias.c.SuplFchAlta,Date),1)) <= func.IFNULL(rls.c.RelLabCeseFchReal,rlt.c.RelLabFchFinPrevista)) \
)
df_alta_suplencia_paga = pd.read_sql_query(query_alta_suplencia_paga,
engine,
params=parametros)
df_alta_suplencia_paga.loc[:, 'Origen'] = ['df_alta_suplencia_paga']
# Las Juntas Médicas van con asignatura 162:
df_alta_suplencia_paga.loc[df_alta_suplencia_paga['SuplCausId'] == 162,
['AsignId', 'CauBajCod']] = [162, 66]
# Los pases en comisión DENTRO ANEP van con dependencia 8902
df_alta_suplencia_paga.loc[df_alta_suplencia_paga['SuplCausId'] == 16,
['SillaDependId', 'CauBajCod']] = [8902, 66]
# Los pases en comisión FUERA SECUN van con dependencia 8901
df_alta_suplencia_paga.loc[df_alta_suplencia_paga['SuplCausId'] == 17,
['SillaDependId', 'CauBajCod']] = [8901, 66]
del df_alta_suplencia_paga['SuplCausId']
df_historia_completa = pd.concat([
df_historia_rl, df_primera_suplencia, df_alta_luego_de_suplencia,
df_alta_suplencia_paga
],
axis=0)
df_historia_completa = df_historia_completa.rename(
columns={
'RelLabFchIniActividades': 'falta',
'RelLabCeseFchReal': 'fcese',
'SillaDependId': 'dependid'
})
df_historia_completa = df_historia_completa.reset_index(drop=True)
df_historia_completa.merge(df_anulaciones_periodo,
on='RelLabId',
how='left')
df_anulaciones_a_eliminar = df_anulaciones_periodo[
df_anulaciones_periodo['RelLabId'].isin(df_novedades['RelLabId'])]
# Elimino los anulaciones de la historia
df_historia_completa = df_historia_completa[
df_historia_completa['RelLabId'].isin(
df_anulaciones_a_eliminar['RelLabId']) == False]
# obtengo los datos de las personas
query_personas = sa.select([
personas.c.PerId.label('PersonalPerId'), personas_documentos.c.PerDocId
]).select_from(personas.join(personas_documentos)).where(
(personas_documentos.c.PaisCod == 'UY')
& (personas_documentos.c.DocCod == 'CI')
& (personas.c.PerId.in_(set_perids_novedades)))
df_personas = pd.read_sql_query(query_personas, engine, params=parametros)
df_historia_completa = df_historia_completa.merge(df_personas,
on='PersonalPerId',
how='left')
# agrego asignatura 151 a todos los que no la tienen
df_historia_completa.loc[(
(df_historia_completa['AsignId'].isnull()) &
(df_historia_completa['PuestoAsignId'].notnull())),
'AsignId'] = df_historia_completa['PuestoAsignId']
df_historia_completa.loc[(df_historia_completa['AsignId'].isnull()),
'AsignId'] = cfg['asignid_otros']
df_historia_completa = df_historia_completa.loc[:, [
'PerDocId', 'dependid', 'AsignId', 'RelLabCicloPago',
'RelLabDesignCaracter', 'FuncRelLabCantHrs', 'falta', 'fcese',
'CauBajCod', 'GrupoMateriaId', 'FuncionId', 'RelLabAnulada',
'PersonalPerId', 'RelLabId'
]]
# atributos hardcoded
df_historia_completa['PerDocTpo'] = 'DO'
df_historia_completa.loc[
df_historia_completa['FuncionId'].isin(df_funciones_hap.tolist()),
'RelLabDesignCaracter'] = cfg['caracter_horas_apoyo']
df_historia_completa.loc[
df_historia_completa['FuncionId'].isin(df_funciones_hap.tolist()),
'AsignId'] = cfg['asignid_horas_apoyo']
df_historia_completa.loc[
df_historia_completa['FuncionId'].isin(df_funciones_POB.tolist()),
'RelLabDesignCaracter'] = cfg['caracter_pob']
df_historia_completa.loc[
df_historia_completa['FuncionId'].isin(df_funciones_POB.tolist()),
'AsignId'] = cfg['asignid_pob']
df_historia_completa.loc[
df_historia_completa['FuncionId'].isin(df_funciones_POP.tolist()),
'RelLabDesignCaracter'] = cfg['caracter_pop']
df_historia_completa.loc[
df_historia_completa['FuncionId'].isin(df_funciones_POP.tolist()),
'AsignId'] = cfg['asignid_pop']
df_historia_completa.loc[
df_historia_completa['FuncionId'].isin(df_funciones_68.tolist()),
'RelLabDesignCaracter'] = cfg['caracter_68']
df_historia_completa.loc[
df_historia_completa['FuncionId'].isin(df_funciones_68.tolist()),
'AsignId'] = cfg['asignid_68']
df_historia_completa.loc[
df_historia_completa['FuncionId'].isin(df_funciones_talleristas.tolist(
)), 'RelLabDesignCaracter'] = cfg['caracter_talleristas']
df_historia_completa.loc[df_historia_completa['FuncionId'].
isin(df_funciones_talleristas.tolist()),
'AsignId'] = cfg['asignid_talleristas']
df_historia_completa.loc[
df_historia_completa['FuncionId'].isin(df_coordinadores_especiales.
tolist()),
'RelLabDesignCaracter'] = cfg['caracter_especiales']
df_historia_completa.loc[df_historia_completa['FuncionId'].
isin(df_coordinadores_especiales.tolist()),
'AsignId'] = cfg['asignid_especiales']
df_historia_completa.loc[(df_historia_completa['AsignId'] == 75) &
(df_historia_completa['fcese'].notnull()),
'CauBajCod'] = cfg['causal_coordinacion']
df_historia_completa.loc[(df_historia_completa['RelLabAnulada'] == 1),
'CauBajCod'] = cfg['causal_anulacion']
df_historia_completa['PerDocPaisCod'] = 'UY'
df_historia_completa['HorClaCurTpo'] = ''
df_historia_completa['HorClaCur'] = ''
df_historia_completa['HorClaArea'] = ''
df_historia_completa['HorClaAnio'] = 0
df_historia_completa['HorClaHorTope'] = 0
df_historia_completa['HorClaObs'] = ''
df_historia_completa['HorClaNumInt'] = 0
df_historia_completa['HorClaParPreCod'] = 0
df_historia_completa['HorClaCompPor'] = 0
df_historia_completa['HorClaCompPor'] = 0
df_historia_completa['HorClaLote'] = 0
df_historia_completa['HorClaAudUsu'] = 0
df_historia_completa['HorClaMod'] = 0
df_historia_completa['HorClaEmpCod'] = 1
df_historia_completa['HorClaCarNum'] = 0
df_historia_completa['DesFchCarga'] = date.today()
df_historia_completa['Resultado'] = 'PE'
df_historia_completa['Mensaje'] = ''
df_historia_completa['HorClaFchLib'] = df_historia_completa['fcese']
df_historia_completa.loc[(df_historia_completa['CauBajCod'].isnull()),
'CauBajCod'] = 0
del df_historia_completa['FuncionId']
del df_historia_completa['PersonalPerId']
#Transformacion de la dependencia a Siap
df_historia_completa = df_historia_completa.merge(df_tabla_institucional)
del df_historia_completa[
'dependid'] #borro la dependencia ya que voy a usar la dependidSiap
# filtro los que tienen fcese < falta
df_historia_completa = df_historia_completa.loc[
(df_historia_completa['fcese'] >= df_historia_completa['falta']) |
(df_historia_completa['fcese'].isnull())]
# filtro los que tienen falta >= tope
df_historia_completa = df_historia_completa.loc[
df_historia_completa['falta'] < parametros['tope']]
# filtro los que tienen cero horas
df_historia_completa = df_historia_completa.loc[
df_historia_completa['FuncRelLabCantHrs'] > 0]
if ci != None: # si me pasaron una ci como parametro filtro la historia solo para esa ci.
df_historia_completa = df_historia_completa.loc[
df_historia_completa['PerDocId'] == ci]
# Le pongo los nombres de los campos que corresponden a la tabla ihorasclase de siap
df_historia_completa = df_historia_completa.rename(
columns={
'PerDocId': 'PerDocNum',
'RelLabDesignCaracter': 'HorClaCar',
'RelLabCicloPago': 'HorClaCic',
'falta': 'HorClaFchPos',
'fcese': 'HorClaFchCese',
'CauBajCod': 'HorClaCauBajCod',
'GrupoMateriaId': 'HorClaGrupo',
'dependidSiap': 'HorClaInsCod',
'FuncRelLabCantHrs': 'HorClaHor',
'AsignId': 'HorClaAsiCod',
'RelLabAnulada': 'HorClaBajLog'
})
df_historia_completa.to_sql(name='ihorasclase',
con=engine_bandeja_out,
if_exists='append',
index=False)
def compile_hourly_statistics(instance: Recorder, session: scoped_session,
start: datetime) -> None:
"""Compile hourly statistics.
This will summarize 5-minute statistics for one hour:
- average, min max is computed by a database query
- sum is taken from the last 5-minute entry during the hour
"""
start_time = start.replace(minute=0)
end_time = start_time + timedelta(hours=1)
# Compute last hour's average, min, max
summary: dict[str, StatisticData] = {}
baked_query = instance.hass.data[STATISTICS_SHORT_TERM_BAKERY](
lambda session: session.query(*QUERY_STATISTICS_SUMMARY_MEAN))
baked_query += lambda q: q.filter(StatisticsShortTerm.start >= bindparam(
"start_time"))
baked_query += lambda q: q.filter(StatisticsShortTerm.start < bindparam(
"end_time"))
baked_query += lambda q: q.group_by(StatisticsShortTerm.metadata_id)
baked_query += lambda q: q.order_by(StatisticsShortTerm.metadata_id)
stats = execute(
baked_query(session).params(start_time=start_time, end_time=end_time))
if stats:
for stat in stats:
metadata_id, _mean, _min, _max = stat
summary[metadata_id] = {
"start": start_time,
"mean": _mean,
"min": _min,
"max": _max,
}
# Get last hour's last sum
if instance._db_supports_row_number: # pylint: disable=[protected-access]
subquery = (session.query(*QUERY_STATISTICS_SUMMARY_SUM).filter(
StatisticsShortTerm.start >= bindparam("start_time")).filter(
StatisticsShortTerm.start < bindparam("end_time")).subquery())
query = (session.query(subquery).filter(
subquery.c.rownum == 1).order_by(subquery.c.metadata_id))
stats = execute(query.params(start_time=start_time, end_time=end_time))
if stats:
for stat in stats:
metadata_id, start, last_reset, state, _sum, _ = stat
if metadata_id in summary:
summary[metadata_id].update({
"last_reset":
process_timestamp(last_reset),
"state":
state,
"sum":
_sum,
})
else:
summary[metadata_id] = {
"start": start_time,
"last_reset": process_timestamp(last_reset),
"state": state,
"sum": _sum,
}
else:
baked_query = instance.hass.data[STATISTICS_SHORT_TERM_BAKERY](
lambda session: session.query(*QUERY_STATISTICS_SUMMARY_SUM_LEGACY
))
baked_query += lambda q: q.filter(StatisticsShortTerm.start >=
bindparam("start_time"))
baked_query += lambda q: q.filter(StatisticsShortTerm.start <
bindparam("end_time"))
baked_query += lambda q: q.order_by(StatisticsShortTerm.metadata_id,
StatisticsShortTerm.start.desc())
stats = execute(
baked_query(session).params(start_time=start_time,
end_time=end_time))
if stats:
for metadata_id, group in groupby(
stats, lambda stat: stat["metadata_id"]): # type: ignore
(
metadata_id,
last_reset,
state,
_sum,
) = next(group)
if metadata_id in summary:
summary[metadata_id].update({
"start":
start_time,
"last_reset":
process_timestamp(last_reset),
"state":
state,
"sum":
_sum,
})
else:
summary[metadata_id] = {
"start": start_time,
"last_reset": process_timestamp(last_reset),
"state": state,
"sum": _sum,
}
# Insert compiled hourly statistics in the database
for metadata_id, stat in summary.items():
session.add(Statistics.from_stats(metadata_id, stat))
def l2(q):
return q.filter(User.name == bindparam("name"))
def test_reaction(self):
# dummy query to ensure that GUC params are initialized
_ = engine.execute(select([func.rdkit_version()])).fetchall()
stmt = pg_settings.update()
stmt = stmt.where(pg_settings.c.name == bindparam('param'))
stmt = stmt.values(setting=bindparam('value'))
engine.execute(stmt, [
{
'param': 'rdkit.ignore_reaction_agents',
'value': False
},
{
'param': 'rdkit.agent_FP_bit_ratio',
'value': 0.2
},
{
'param': 'rdkit.difference_FP_weight_agents',
'value': 1
},
{
'param': 'rdkit.difference_FP_weight_nonagents',
'value': 10
},
{
'param': 'rdkit.move_unmmapped_reactants_to_agents',
'value': True
},
{
'param': 'rdkit.threshold_unmapped_reactant_atoms',
'value': 0.2
},
{
'param': 'rdkit.init_reaction',
'value': True
},
])
rs = engine.execute(
select([func.reaction_from_smiles('c1ccccc1>>c1cccnc1')]))
self.assertEqual(rs.fetchall()[0][0], 'c1ccccc1>>c1ccncc1')
rs = engine.execute(
select([func.reaction_from_smiles('c1ccccc1>CC(=O)O>c1cccnc1')]))
self.assertEqual(rs.fetchall()[0][0], 'c1ccccc1>CC(=O)O>c1ccncc1')
rs = engine.execute(
select([
func.reaction_from_smarts(
'[c1:1][c:2][c:3][c:4]c[c1:5]>CC(=O)O>[c1:1][c:2][c:3][c:4]n[c1:5]'
)
]))
self.assertEqual(
rs.fetchall()[0][0],
'c([cH:4][cH:3][cH:2][cH2:1])[cH2:5]>CC(=O)O>n([cH:4][cH:3][cH:2][cH2:1])[cH2:5]'
)
rs = engine.execute(
select([
func.reaction_from_smarts(
'C(F)(F)F.[c1:1][c:2][c:3][c:4]c[c1:5]>CC(=O)O>[c1:1][c:2][c:3][c:4]n[c1:5]'
)
]))
self.assertEqual(
rs.fetchall()[0][0],
'c([cH:4][cH:3][cH:2][cH2:1])[cH2:5]>CC(=O)O.FC(F)F>n([cH:4][cH:3][cH:2][cH2:1])[cH2:5]'
)
rs = engine.execute(
select([func.reaction_from_smarts('c1ccc[n,c]c1>>c1nccnc1')]))
self.assertEqual(rs.fetchall()[0][0], '*1ccccc1>>c1cnccn1')
rs = engine.execute(
select([
func.reaction_to_smiles(
func.reaction_from_smiles('c1ccccc1>>c1cccnc1'))
]))
self.assertEqual(rs.fetchall()[0][0], 'c1ccccc1>>c1ccncc1')
rs = engine.execute(
select([
func.reaction_from_ctab('''$RXN
RDKit
1 1
$MOL
RDKit
6 6 0 0 0 0 0 0 0 0999 V2000
0.0000 0.0000 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
0.0000 0.0000 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
0.0000 0.0000 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
0.0000 0.0000 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
0.0000 0.0000 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
0.0000 0.0000 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
1 2 4 0
2 3 4 0
3 4 4 0
4 5 4 0
5 6 4 0
6 1 4 0
M END
$MOL
RDKit
6 6 0 0 0 0 0 0 0 0999 V2000
0.0000 0.0000 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
0.0000 0.0000 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
0.0000 0.0000 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
0.0000 0.0000 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
0.0000 0.0000 0.0000 N 0 0 0 0 0 0 0 0 0 0 0 0
0.0000 0.0000 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0
1 2 4 0
2 3 4 0
3 4 4 0
4 5 4 0
5 6 4 0
6 1 4 0
M END
''')
]))
self.assertEqual(rs.fetchall()[0][0], 'c1ccccc1>>c1ccncc1')
rs = engine.execute(
select([
func.reaction_numreactants(
func.reaction_from_smiles('[Cl].c1ccccc1>>c1cccnc1.[OH2]'))
]))
self.assertEqual(rs.fetchall()[0][0], 2)
rs = engine.execute(
select([
func.reaction_numproducts(
func.reaction_from_smiles('[Cl].c1ccccc1>>c1cccnc1.[OH2]'))
]))
self.assertEqual(rs.fetchall()[0][0], 2)
rs = engine.execute(
select([
func.reaction_numagents(
func.reaction_from_smiles(
'[Cl].c1ccccc1>CC(=O)O.[Na+]>c1cccnc1.[OH2]'))
]))
self.assertEqual(rs.fetchall()[0][0], 2)
rs = engine.execute(
select([
func.reaction_numagents(
func.reaction_from_smarts(
'C(F)(F)F.[c1:1][c:2][c:3][c:4]c[c1:5]>CC(=O)O>[c1:1][c:2][c:3][c:4]n[c1:5]'
))
]))
self.assertEqual(rs.fetchall()[0][0], 2)
engine.execute(stmt, [
{
'param': 'rdkit.move_unmmapped_reactants_to_agents',
'value': False
},
])
rs = engine.execute(
select([
func.reaction_numagents(
func.reaction_from_smarts(
'C(F)(F)F.[c1:1][c:2][c:3][c:4]c[c1:5]>CC(=O)O>[c1:1][c:2][c:3][c:4]n[c1:5]'
))
]))
self.assertEqual(rs.fetchall()[0][0], 1)
engine.execute(stmt, [
{
'param': 'rdkit.move_unmmapped_reactants_to_agents',
'value': True
},
{
'param': 'rdkit.threshold_unmapped_reactant_atoms',
'value': 0.9
},
])
rs = engine.execute(
select([
func.reaction_numagents(
func.reaction_from_smarts(
'C(F)(F)F.[c1:1][c:2][c:3][c:4]c[c1:5]>CC(=O)O>[c1:1][c:2][c:3][c:4]n[c1:5]'
))
]))
self.assertEqual(rs.fetchall()[0][0], 3)
engine.execute(stmt, [
{
'param': 'rdkit.threshold_unmapped_reactant_atoms',
'value': 0.2
},
])
rs = engine.execute(
select([
func.reaction('c1ccccc1>>c1cccnc1') == func.reaction(
'c1ccccc1>>c1cccnc1')
]))
self.assertEqual(rs.fetchall()[0][0], True)
rs = engine.execute(
select([
func.reaction('c1ccccc1>>c1cccnc1') == func.reaction(
'c1ccccc1>>c1cncnc1')
]))
self.assertEqual(rs.fetchall()[0][0], False)
def test_reaction(self):
self.assertTrue(os.path.exists(data_filepath))
with open(data_filepath, 'rt') as f:
sample_data = [line.split() for line in f]
# dummy query to ensure that GUC params are initialized
_ = engine.execute(select([func.rdkit_version()])).fetchall()
stmt = pg_settings.update()
stmt = stmt.where(pg_settings.c.name == bindparam('param'))
stmt = stmt.values(setting=bindparam('value'))
engine.execute(stmt, [
{
'param': 'rdkit.ignore_reaction_agents',
'value': False
},
{
'param': 'rdkit.agent_FP_bit_ratio',
'value': 0.2
},
{
'param': 'rdkit.difference_FP_weight_agents',
'value': 1
},
{
'param': 'rdkit.difference_FP_weight_nonagents',
'value': 10
},
{
'param': 'rdkit.move_unmmapped_reactants_to_agents',
'value': True
},
{
'param': 'rdkit.threshold_unmapped_reactant_atoms',
'value': 0.2
},
{
'param': 'rdkit.init_reaction',
'value': True
},
])
engine.execute(
reactions.insert(),
[{
'rxn': rsmiles,
} for _, rsmiles in sample_data],
)
rs = engine.execute(select([func.count()]).select_from(reactions))
sz = rs.fetchall()[0][0]
self.assertEqual(sz, len(sample_data))
engine.execute(stmt, [
{
'param': 'rdkit.move_unmmapped_reactants_to_agents',
'value': False
},
])
engine.execute(
reactions_unchanged.insert(),
[{
'rxn': rsmiles,
} for _, rsmiles in sample_data],
)
engine.execute(stmt, [
{
'param': 'rdkit.move_unmmapped_reactants_to_agents',
'value': True
},
])
rs = engine.execute(
select([func.count()]).select_from(reactions_unchanged))
sz = rs.fetchall()[0][0]
self.assertEqual(sz, len(sample_data))
rs = engine.execute(
select([func.sum(func.reaction_numreactants(reactions.c.rxn))]))
sum_reactants = rs.fetchall()[0][0]
self.assertEqual(sum_reactants, 1898)
rs = engine.execute(
select([
func.sum(func.reaction_numreactants(reactions_unchanged.c.rxn))
]))
sum_reactants = rs.fetchall()[0][0]
self.assertEqual(sum_reactants, 3517)
rs = engine.execute(
select([func.sum(func.reaction_numproducts(reactions.c.rxn))]))
sum_products = rs.fetchall()[0][0]
self.assertEqual(sum_products, 1157)
rs = engine.execute(
select([
func.sum(func.reaction_numproducts(reactions_unchanged.c.rxn))
]))
sum_products = rs.fetchall()[0][0]
self.assertEqual(sum_products, 1157)
rs = engine.execute(
select([func.sum(func.reaction_numagents(reactions.c.rxn))]))
sum_agents = rs.fetchall()[0][0]
self.assertEqual(sum_agents, 2528)
rs = engine.execute(
select([
func.sum(func.reaction_numagents(reactions_unchanged.c.rxn))
]))
sum_agents = rs.fetchall()[0][0]
self.assertEqual(sum_agents, 909)
rs = engine.execute(
select([func.count()]).select_from(reactions).where(
reactions.c.rxn.hassubstruct('c1ccccc1>>c1ccncc1')))
self.assertEqual(rs.fetchall()[0][0], 47)
rs = engine.execute(
select([func.count()]).select_from(reactions).where(
reactions.c.rxn.hassubstruct('c1cnccc1>>c1ccccc1')))
self.assertEqual(rs.fetchall()[0][0], 50)
rs = engine.execute(
select([func.count()]).select_from(reactions).where(
reactions.c.rxn.hassubstruct('c1ccccc1>>')))
self.assertEqual(rs.fetchall()[0][0], 667)
rs = engine.execute(
select([func.count()]).select_from(reactions).where(
reactions.c.rxn.hassubstruct('c1cnccc1>>')))
self.assertEqual(rs.fetchall()[0][0], 83)
rs = engine.execute(
select([func.count()]).select_from(reactions).where(
reactions.c.rxn.hassubstruct('>>c1ccncc1')))
self.assertEqual(rs.fetchall()[0][0], 79)
rs = engine.execute(
select([func.count()]).select_from(reactions).where(
reactions.c.rxn.hassubstruct('>>c1ccccc1')))
self.assertEqual(rs.fetchall()[0][0], 650)
rs = engine.execute(
select([func.count()]).select_from(reactions).where(
reactions.c.rxn.hassubstructfp('c1ccccc1>>c1ccncc1')))
self.assertEqual(rs.fetchall()[0][0], 47)
rs = engine.execute(
select([func.count()]).select_from(reactions).where(
reactions.c.rxn.hassubstructfp('c1cnccc1>>c1ccccc1')))
self.assertEqual(rs.fetchall()[0][0], 50)
rs = engine.execute(
select([func.count()]).select_from(reactions).where(
reactions.c.rxn.hassubstructfp('c1ccccc1>>')))
self.assertEqual(rs.fetchall()[0][0], 667)
rs = engine.execute(
select([func.count()]).select_from(reactions).where(
reactions.c.rxn.hassubstructfp('c1cnccc1>>')))
self.assertEqual(rs.fetchall()[0][0], 83)
rs = engine.execute(
select([func.count()]).select_from(reactions).where(
reactions.c.rxn.hassubstructfp('>>c1ccncc1')))
self.assertEqual(rs.fetchall()[0][0], 79)
rs = engine.execute(
select([func.count()]).select_from(reactions).where(
reactions.c.rxn.hassubstructfp('>>c1ccccc1')))
self.assertEqual(rs.fetchall()[0][0], 650)
rs = engine.execute(
select([
func.tanimoto_sml(
func.reaction_difference_fp('c1ccccc1>>c1ccncc1', 1),
func.reaction_difference_fp('c1ccccc1>>c1ccncc1', 1))
]))
self.assertEqual(rs.fetchall()[0][0], 1.0)
rs = engine.execute(
select([
func.tanimoto_sml(
func.reaction_difference_fp('c1ccccc1>>c1ccncc1', 1),
func.reaction_difference_fp('c1ncccc1>>c1ncncc1', 1))
]))
self.assertAlmostEqual(rs.fetchall()[0][0], 0.636363636363636)
rs = engine.execute(
select([
func.tanimoto_sml(
func.reaction_difference_fp(
'c1ccccc1>CC(=O)O.[Na+]>c1ccncc1', 1),
func.reaction_difference_fp(
'c1ccccc1>CC(=O)O.[Na+]>c1ccncc1', 1))
]))
self.assertEqual(rs.fetchall()[0][0], 1.0)
rs = engine.execute(
select([
func.tanimoto_sml(
func.reaction_difference_fp(
'c1ccccc1>CC(=O)O.[Na+]>c1ccncc1', 1),
func.reaction_difference_fp('c1ncccc1>[Na+]>c1ncncc1', 1))
]))
self.assertAlmostEqual(rs.fetchall()[0][0], 0.603448275862069)
rs = engine.execute(
select([
func.tanimoto_sml(
func.reaction_difference_fp('c1ccccc1>>c1ccncc1', 2),
func.reaction_difference_fp('c1ccccc1>>c1ccncc1', 2))
]))
self.assertEqual(rs.fetchall()[0][0], 1.0)
rs = engine.execute(
select([
func.tanimoto_sml(
func.reaction_difference_fp('c1ccccc1>>c1ccncc1', 2),
func.reaction_difference_fp('c1ncccc1>>c1ncncc1', 2))
]))
self.assertAlmostEqual(rs.fetchall()[0][0], 0.2)
rs = engine.execute(
select([
func.tanimoto_sml(
func.reaction_difference_fp(
'c1ccccc1>CC(=O)O.[Na+]>c1ccncc1', 2),
func.reaction_difference_fp(
'c1ccccc1>CC(=O)O.[Na+]>c1ccncc1', 2))
]))
self.assertEqual(rs.fetchall()[0][0], 1.0)
rs = engine.execute(
select([
func.tanimoto_sml(
func.reaction_difference_fp(
'c1ccccc1>CC(=O)O.[Na+]>c1ccncc1', 2),
func.reaction_difference_fp('c1ncccc1>[Na+]>c1ncncc1', 2))
]))
self.assertAlmostEqual(rs.fetchall()[0][0], 0.2)
rs = engine.execute(
select([
func.tanimoto_sml(
func.reaction_difference_fp('c1ccccc1>>c1ccncc1', 3),
func.reaction_difference_fp('c1ccccc1>>c1ccncc1', 3))
]))
self.assertEqual(rs.fetchall()[0][0], 1.0)
rs = engine.execute(
select([
func.tanimoto_sml(
func.reaction_difference_fp('c1ccccc1>>c1ccncc1', 3),
func.reaction_difference_fp('c1ncccc1>>c1ncncc1', 3))
]))
self.assertAlmostEqual(rs.fetchall()[0][0], 0.454545454545455)
rs = engine.execute(
select([
func.tanimoto_sml(
func.reaction_difference_fp(
'c1ccccc1>CC(=O)O.[Na+]>c1ccncc1', 3),
func.reaction_difference_fp(
'c1ccccc1>CC(=O)O.[Na+]>c1ccncc1', 3))
]))
self.assertEqual(rs.fetchall()[0][0], 1.0)
rs = engine.execute(
select([
func.tanimoto_sml(
func.reaction_difference_fp(
'c1ccccc1>CC(=O)O.[Na+]>c1ccncc1', 3),
func.reaction_difference_fp('c1ncccc1>[Na+]>c1ncncc1', 3))
]))
self.assertAlmostEqual(rs.fetchall()[0][0], 0.444933920704846)
rs = engine.execute(
select([
func.tanimoto_sml(
func.reaction_structural_bfp('c1ccccc1>>c1ccncc1', 1),
func.reaction_structural_bfp('c1ccccc1>>c1ccncc1', 1))
]))
self.assertEqual(rs.fetchall()[0][0], 1.0)
rs = engine.execute(
select([
func.tanimoto_sml(
func.reaction_structural_bfp('c1ccccc1>>c1ccncc1', 1),
func.reaction_structural_bfp('c1ncccc1>>c1ncncc1', 1))
]))
self.assertAlmostEqual(rs.fetchall()[0][0], 0.620689655172414)
rs = engine.execute(
select([
func.tanimoto_sml(
func.reaction_structural_bfp(
'c1ccccc1>CC(=O)O.[Na+]>c1ccncc1', 1),
func.reaction_structural_bfp(
'c1ccccc1>CC(=O)O.[Na+]>c1ccncc1', 1))
]))
self.assertEqual(rs.fetchall()[0][0], 1.0)
rs = engine.execute(
select([
func.tanimoto_sml(
func.reaction_structural_bfp(
'c1ccccc1>CC(=O)O.[Na+]>c1ccncc1', 1),
func.reaction_structural_bfp('c1ncccc1>[Na+]>c1ncncc1', 1))
]))
self.assertAlmostEqual(rs.fetchall()[0][0], 0.514285714285714)
def visit_unload_from_select(element, compiler, **kw):
"""Returns the actual sql query for the UnloadFromSelect class."""
template = """
UNLOAD (:select) TO :unload_location
CREDENTIALS :credentials
{manifest}
{header}
{delimiter}
{encrypted}
{fixed_width}
{gzip}
{add_quotes}
{null}
{escape}
{allow_overwrite}
{parallel}
"""
el = element
qs = template.format(
manifest='MANIFEST' if el.manifest else '',
header='HEADER' if el.header else '',
delimiter=('DELIMITER AS :delimiter'
if el.delimiter is not None else ''),
encrypted='ENCRYPTED' if el.encrypted else '',
fixed_width='FIXEDWIDTH AS :fixed_width' if el.fixed_width else '',
gzip='GZIP' if el.gzip else '',
add_quotes='ADDQUOTES' if el.add_quotes else '',
escape='ESCAPE' if el.escape else '',
null='NULL AS :null_as' if el.null is not None else '',
allow_overwrite='ALLOWOVERWRITE' if el.allow_overwrite else '',
parallel='PARALLEL OFF' if not el.parallel else '',
)
query = sa.text(qs)
if el.delimiter is not None:
query = query.bindparams(
sa.bindparam(
'delimiter',
value=element.delimiter,
type_=sa.String,
))
if el.fixed_width:
query = query.bindparams(
sa.bindparam(
'fixed_width',
value=_process_fixed_width(el.fixed_width),
type_=sa.String,
))
if el.null is not None:
query = query.bindparams(
sa.bindparam('null_as', value=el.null, type_=sa.String))
return compiler.process(
query.bindparams(
sa.bindparam('credentials', value=el.credentials, type_=sa.String),
sa.bindparam(
'unload_location',
value=el.unload_location,
type_=sa.String,
),
sa.bindparam(
'select',
value=compiler.process(
el.select,
literal_binds=True,
),
type_=sa.String,
),
), **kw)
def test_select_columns(self):
stmt = select([bindparam('data'), bindparam('x')])
self._assert_raises(
stmt, {'data': 'data'}
)
def test_updatemany(self, connection):
t = self.tables.default_test
connection.execute(t.insert(), [{}, {}, {}])
connection.execute(
t.update().where(t.c.col1 == sa.bindparam("pkval")),
{"pkval": 51, "col7": None, "col8": None, "boolcol1": False},
)
connection.execute(
t.update().where(t.c.col1 == sa.bindparam("pkval")),
[{"pkval": 51}, {"pkval": 52}, {"pkval": 53}],
)
ctexec = connection.scalar(self.currenttime)
today = datetime.date.today()
result = connection.execute(t.select().order_by(t.c.col1))
eq_(
list(result),
[
(
51,
"im the update",
self.f2,
self.ts,
self.ts,
ctexec,
False,
False,
13,
today,
"py",
"hi",
"BINDfoo",
),
(
52,
"im the update",
self.f2,
self.ts,
self.ts,
ctexec,
True,
False,
13,
today,
"py",
"hi",
"BINDfoo",
),
(
53,
"im the update",
self.f2,
self.ts,
self.ts,
ctexec,
True,
False,
13,
today,
"py",
"hi",
"BINDfoo",
),
],
)
def test_insert_w_newlines(self, connection):
from psycopg2 import extras
t = self.tables.data
ins = (t.insert().inline().values(
id=bindparam("id"),
x=select(literal_column("5")).select_from(
self.tables.data).scalar_subquery(),
y=bindparam("y"),
z=bindparam("z"),
))
# compiled SQL has a newline in it
eq_(
str(ins.compile(testing.db)),
"INSERT INTO data (id, x, y, z) VALUES (%(id)s, "
"(SELECT 5 \nFROM data), %(y)s, %(z)s)",
)
meth = extras.execute_values
with mock.patch.object(extras, "execute_values",
side_effect=meth) as mock_exec:
connection.execute(
ins,
[
{
"id": 1,
"y": "y1",
"z": 1
},
{
"id": 2,
"y": "y2",
"z": 2
},
{
"id": 3,
"y": "y3",
"z": 3
},
],
)
eq_(
mock_exec.mock_calls,
[
mock.call(
mock.ANY,
"INSERT INTO data (id, x, y, z) VALUES %s",
(
{
"id": 1,
"y": "y1",
"z": 1
},
{
"id": 2,
"y": "y2",
"z": 2
},
{
"id": 3,
"y": "y3",
"z": 3
},
),
template="(%(id)s, (SELECT 5 \nFROM data), %(y)s, %(z)s)",
fetch=False,
page_size=connection.dialect.executemany_values_page_size,
)
],
)
def test_select_where(self):
stmt = select([self.tables.foo]). \
where(self.tables.foo.c.data == bindparam('data')). \
where(self.tables.foo.c.x == bindparam('x'))
self._assert_raises(stmt, {'data': 'data'})
def test_insert_modified_by_event(self, connection):
from psycopg2 import extras
t = self.tables.data
ins = (t.insert().inline().values(
id=bindparam("id"),
x=select(literal_column("5")).select_from(
self.tables.data).scalar_subquery(),
y=bindparam("y"),
z=bindparam("z"),
))
# compiled SQL has a newline in it
eq_(
str(ins.compile(testing.db)),
"INSERT INTO data (id, x, y, z) VALUES (%(id)s, "
"(SELECT 5 \nFROM data), %(y)s, %(z)s)",
)
meth = extras.execute_batch
with mock.patch.object(
extras, "execute_values") as mock_values, mock.patch.object(
extras, "execute_batch", side_effect=meth) as mock_batch:
# create an event hook that will change the statement to
# something else, meaning the dialect has to detect that
# insert_single_values_expr is no longer useful
@event.listens_for(connection,
"before_cursor_execute",
retval=True)
def before_cursor_execute(conn, cursor, statement, parameters,
context, executemany):
statement = ("INSERT INTO data (id, y, z) VALUES "
"(%(id)s, %(y)s, %(z)s)")
return statement, parameters
connection.execute(
ins,
[
{
"id": 1,
"y": "y1",
"z": 1
},
{
"id": 2,
"y": "y2",
"z": 2
},
{
"id": 3,
"y": "y3",
"z": 3
},
],
)
eq_(mock_values.mock_calls, [])
if connection.dialect.executemany_mode & EXECUTEMANY_BATCH:
eq_(
mock_batch.mock_calls,
[
mock.call(
mock.ANY,
"INSERT INTO data (id, y, z) VALUES "
"(%(id)s, %(y)s, %(z)s)",
(
{
"id": 1,
"y": "y1",
"z": 1
},
{
"id": 2,
"y": "y2",
"z": 2
},
{
"id": 3,
"y": "y3",
"z": 3
},
),
)
],
)
else:
eq_(mock_batch.mock_calls, [])
def test_core_just_statement_construct_plus_cache_key(n):
for i in range(n):
stmt = future_select(
Customer.__table__).where(Customer.id == bindparam("id"))
stmt._generate_cache_key()
def visit_copy_command(element, compiler, **kw):
"""
Returns the actual sql query for the CopyCommand class.
"""
qs = """COPY {table}{columns} FROM :data_location
WITH CREDENTIALS AS :credentials
{format}
{parameters}"""
parameters = []
bindparams = [
sa.bindparam(
'data_location',
value=element.data_location,
type_=sa.String,
),
sa.bindparam(
'credentials',
value=element.credentials,
type_=sa.String,
),
]
if element.format == Format.csv:
format_ = 'FORMAT AS CSV'
if element.quote is not None:
format_ += ' QUOTE AS :quote_character'
bindparams.append(
sa.bindparam(
'quote_character',
value=element.quote,
type_=sa.String,
))
elif element.format == Format.json:
format_ = 'FORMAT AS JSON AS :json_option'
bindparams.append(
sa.bindparam(
'json_option',
value=element.path_file,
type_=sa.String,
))
elif element.format == Format.avro:
format_ = 'FORMAT AS AVRO AS :avro_option'
bindparams.append(
sa.bindparam(
'avro_option',
value=element.path_file,
type_=sa.String,
))
elif element.format == Format.orc:
format_ = 'FORMAT AS ORC'
elif element.format == Format.parquet:
format_ = 'FORMAT AS PARQUET'
elif element.format == Format.fixed_width and element.fixed_width is None:
raise sa_exc.CompileError(
"'fixed_width' argument required for format 'FIXEDWIDTH'.")
else:
format_ = ''
if element.delimiter is not None:
parameters.append('DELIMITER AS :delimiter_char')
bindparams.append(
sa.bindparam(
'delimiter_char',
value=element.delimiter,
type_=sa.String,
))
if element.fixed_width is not None:
parameters.append('FIXEDWIDTH AS :fixedwidth_spec')
bindparams.append(
sa.bindparam(
'fixedwidth_spec',
value=_process_fixed_width(element.fixed_width),
type_=sa.String,
))
if element.compression is not None:
parameters.append(Compression(element.compression).value)
if element.manifest:
parameters.append('MANIFEST')
if element.accept_any_date:
parameters.append('ACCEPTANYDATE')
if element.accept_inv_chars is not None:
parameters.append('ACCEPTINVCHARS AS :replacement_char')
bindparams.append(
sa.bindparam('replacement_char',
value=element.accept_inv_chars,
type_=sa.String))
if element.blanks_as_null:
parameters.append('BLANKSASNULL')
if element.date_format is not None:
parameters.append('DATEFORMAT AS :dateformat_string')
bindparams.append(
sa.bindparam(
'dateformat_string',
value=element.date_format,
type_=sa.String,
))
if element.empty_as_null:
parameters.append('EMPTYASNULL')
if element.encoding is not None:
parameters.append('ENCODING AS ' + Encoding(element.encoding).value)
if element.escape:
parameters.append('ESCAPE')
if element.explicit_ids:
parameters.append('EXPLICIT_IDS')
if element.fill_record:
parameters.append('FILLRECORD')
if element.ignore_blank_lines:
parameters.append('IGNOREBLANKLINES')
if element.ignore_header is not None:
parameters.append('IGNOREHEADER AS :number_rows')
bindparams.append(
sa.bindparam(
'number_rows',
value=element.ignore_header,
type_=sa.Integer,
))
if element.dangerous_null_delimiter is not None:
parameters.append("NULL AS '%s'" % element.dangerous_null_delimiter)
if element.remove_quotes:
parameters.append('REMOVEQUOTES')
if element.roundec:
parameters.append('ROUNDEC')
if element.time_format is not None:
parameters.append('TIMEFORMAT AS :timeformat_string')
bindparams.append(
sa.bindparam(
'timeformat_string',
value=element.time_format,
type_=sa.String,
))
if element.trim_blanks:
parameters.append('TRIMBLANKS')
if element.truncate_columns:
parameters.append('TRUNCATECOLUMNS')
if element.comp_rows:
parameters.append('COMPROWS :numrows')
bindparams.append(
sa.bindparam(
'numrows',
value=element.comp_rows,
type_=sa.Integer,
))
if element.comp_update:
parameters.append('COMPUPDATE ON')
elif element.comp_update is not None:
parameters.append('COMPUPDATE OFF')
if element.max_error is not None:
parameters.append('MAXERROR AS :error_count')
bindparams.append(
sa.bindparam(
'error_count',
value=element.max_error,
type_=sa.Integer,
))
if element.no_load:
parameters.append('NOLOAD')
if element.stat_update:
parameters.append('STATUPDATE ON')
elif element.stat_update is not None:
parameters.append('STATUPDATE OFF')
columns = ' (%s)' % ', '.join(
compiler.preparer.format_column(column)
for column in element.columns) if element.columns else ''
qs = qs.format(table=compiler.preparer.format_table(element.table),
columns=columns,
format=format_,
parameters='\n'.join(parameters))
return compiler.process(sa.text(qs).bindparams(*bindparams), **kw)
def test_compiled_insert_execute(self):
users.insert().compile().execute(user_id=7, user_name='jack')
s = select([users], users.c.user_id == bindparam('id')).compile()
c = testing.db.connect()
assert c.execute(s, id=7).fetchall()[0]['user_id'] == 7
