def log_exec_status(job_id: str, exec_stage: str, exec_status: str,
job_details: str):
"""Log execution status (job_id, status, job_details) to DB """
with engine.connect() as connection:
ins_stmt = insert(
ex_stat
).values( # Postgres-specific insert() supporting ON CONFLICT
job_id=job_id,
stage=exec_stage,
status=exec_status,
details=json.dumps(job_details))
# If key already present in DB, do update instead
upsert = ins_stmt.on_conflict_do_update(
constraint='uq_job_id',
set_=dict(stage=exec_stage,
status=exec_status,
details=json.dumps(job_details)))
try:
connection.execute(upsert)
except Exception as e:
current_app.logger.error("Insert/Update failed Execution status")
current_app.logger.exception(e)
def update_profil(username, profil):
update = (User_tbl.update().values(profil=profil).where(
User_tbl.c.username == username))
conn = engine.connect()
conn.execute(update)
conn.close()
def supp_secteur(nom_secteur, nom_chantier):
delete = Secteur_tbl.delete().where(
(Secteur_tbl.c.nom_secteur == nom_secteur)
& (Secteur_tbl.c.nom_chantier == nom_chantier))
conn = engine.connect()
conn.execute(delete)
conn.close()
def get_user_cards(id):
stmt = select([Credit_tbl.c.card_num]).where(Credit_tbl.c.id == id)
conn = engine.connect()
rs = conn.execute(stmt)
conn.close()
return rs
def update_graph_3D(focus, sizeref, secteur_selected, chantier):
if secteur_selected == {}:
return empty_figure()
else:
try:
df = format_df_vector(
memoized_data(chantier, "actif", "topographie", "topo.csv")
)
secteur = secteur_selected["secteur"]
cibles = secteur_selected["cible"]
with engine.connect() as con:
query1 = f"SELECT * FROM cible_param where nom_chantier = '{chantier}' and masquer = 'x'"
query3 = f"SELECT * FROM secteur where nom_chantier = '{chantier}' and nom_secteur='{secteur}'"
secteur_params = pd.read_sql_query(query3, con=con)
cibles_masque = pd.read_sql_query(query1, con=con).nom_capteur.tolist()
liste_cibles = df.cible.tolist()
for i in cibles_masque:
try:
liste_cibles.remove(i)
except ValueError:
pass
df = df[df.cible.isin(liste_cibles)]
lat1 = secteur_params.lat1[0]
lat2 = secteur_params.lat2[0]
lon1 = secteur_params.lon1[0]
lon2 = secteur_params.lon2[0]
return graph_vecteurs(df, lat1, lat2, lon1, lon2, secteur, cibles, sizeref, focus)
except KeyError:
return empty_figure()
def get_360(matching_id):
result = {}
with engine.connect() as connection:
query = text("select * from pdp_contacts where matching_id = :matching_id and archived_date is null")
query_result = connection.execute(query, matching_id=matching_id)
result["contact_details"] = [dict(row) for row in query_result]
for row in result["contact_details"]:
if row["source_type"] == "salesforcecontacts":
donations_query = text("select * from salesforcedonations where contact_id like :salesforcecontacts_id")
salesforce_contacts_query_result = connection.execute(donations_query,
salesforcecontacts_id=row["source_id"] + "%")
salesforce_donations_results = [dict(row) for row in salesforce_contacts_query_result]
result['donations'] = salesforce_donations_results
if row["source_type"] == "volgistics":
shifts_query = text("select * from volgisticsshifts where number = :volgistics_id")
volgistics_shifts_query_result = connection.execute(shifts_query, volgistics_id=row["source_id"])
volgisticsshifts_results = []
# todo: temporary fix until formatted in the pipeline
for r in volgistics_shifts_query_result:
shifts = dict(r)
# normalize date string
parsed_date_from = dateutil.parser.parse(shifts["from"], ignoretz=True)
normalized_date_from = parsed_date_from.strftime("%Y-%m-%d")
shifts["from"] = normalized_date_from
volgisticsshifts_results.append(shifts)
result['shifts'] = volgisticsshifts_results
if row["source_type"] == "shelterluvpeople":
adoptions = []
person = requests.get("http://shelterluv.com/api/v1/people/{}".format(row["source_id"]),
headers={"x-api-key": SHELTERLUV_SECRET_TOKEN})
person_json = person.json()
animal_ids = person_json["Animal_ids"]
for animal_id in animal_ids:
animal_events = requests.get("http://shelterluv.com/api/v1/animals/{}/events".format(animal_id),
headers={"x-api-key": SHELTERLUV_SECRET_TOKEN})
animal_events_json = animal_events.json()
for event in animal_events_json["events"]:
for adoption in event["AssociatedRecords"]:
if adoption["Type"] == "Person" and adoption["Id"] == row["source_id"]:
del event["AssociatedRecords"]
animal_details = requests.get(
"http://shelterluv.com/api/v1/animals/{}".format(animal_id),
headers={"x-api-key": SHELTERLUV_SECRET_TOKEN})
animal_details_json = animal_details.json()
event["animal_details"] = animal_details_json
adoptions.append(event)
result['adoptions'] = adoptions
return jsonify({'result': result})
def get_contacts(search_text):
with engine.connect() as connection:
search_text = search_text.lower()
names = search_text.split(" ")
if len(names) == 2:
query = text(
"select * from pdp_contacts where archived_date is null AND ( \
(lower(first_name) like lower(:name1) and lower(last_name) like lower(:name2)) \
OR (lower(first_name) like lower(:name2) and lower(last_name) like lower(:name1)) )\
order by lower(last_name), lower(first_name)")
query_result = connection.execute(query,
name1='{}%'.format(names[0]),
name2='{}%'.format(names[1]))
elif len(names) == 1:
query = text("select * from pdp_contacts \
WHERE lower(first_name) like lower(:search_text) \
OR lower(last_name) like lower(:search_text) order by lower(last_name), lower(first_name)"
)
query_result = connection.execute(
query, search_text='{}%'.format(search_text))
query_result_json = [dict(row) for row in query_result]
results = jsonify({'result': query_result_json})
return results
def get_person_animal_events(matching_id, animal_id):
result = {}
events = []
with engine.connect() as connection:
query = text(
"select * from pdp_contacts where matching_id = :matching_id and source_type = 'shelterluvpeople' and archived_date is null"
)
query_result = connection.execute(query, matching_id=matching_id)
rows = [dict(row) for row in query_result]
if len(rows) > 0:
row = rows[0]
shelterluv_id = row["source_id"]
animal_url = f"http://shelterluv.com/api/v1/animals/{animal_id}/events"
event_details = requests.get(animal_url,
headers={
"x-api-key":
SHELTERLUV_SECRET_TOKEN
}).json()
for event in event_details["events"]:
for record in event["AssociatedRecords"]:
if record["Type"] == "Person" and record[
"Id"] == shelterluv_id:
events.append(event)
result[animal_id] = events
return result
def get_animals(matching_id):
result = {}
with engine.connect() as connection:
query = text(
"select * from pdp_contacts where matching_id = :matching_id and source_type = 'shelterluvpeople' and archived_date is null"
)
query_result = connection.execute(query, matching_id=matching_id)
rows = [dict(row) for row in query_result]
if len(rows) > 0:
row = rows[0]
shelterluv_id = row["source_id"]
person_url = f"http://shelterluv.com/api/v1/people/{shelterluv_id}"
person_details = requests.get(person_url,
headers={
"x-api-key":
SHELTERLUV_SECRET_TOKEN
}).json()
animal_ids = person_details["Animal_ids"]
for animal_id in animal_ids:
animal_url = f"http://shelterluv.com/api/v1/animals/{animal_id}"
animal_details = requests.get(animal_url,
headers={
"x-api-key":
SHELTERLUV_SECRET_TOKEN
}).json()
result[animal_id] = animal_details
return result
def get_360(salesforce_id):
result = {'salesforcecontacts': None}
with engine.connect() as connection:
query_result = connection.execute(
"select * from master where salesforcecontacts_id='{}'".format(
salesforce_id))
master_row = {'result': [dict(row) for row in query_result]}
query_result = connection.execute(
"select * from salesforcecontacts where contact_id='{}'".format(
salesforce_id))
if 'salesforcecontacts' in result:
result['salesforcecontacts'] = [dict(row)
for row in query_result][0]
query_result = connection.execute(
"select * from petpoint where outcome_person_num='{}'".format(
master_row['result'][0]['petpoint_id']))
if 'petpoint' in result:
result['petpoint'] = [dict(row) for row in query_result][0]
if master_row['result'][0]['volgistics_id']:
query_result = connection.execute(
"select * from volgistics where number='{}'".format(
master_row['result'][0]['volgistics_id']))
if 'volgistics' in result:
result['volgistics'] = [dict(row) for row in query_result][0]
return jsonify(result)
def user_refresh():
""" If user still active, send back an access_token with a new expiration stamp """
old_jwt = jwt_ops.validate_decode_jwt()
# If token bad, should be handled & error message sent by jwt_required() and we won't get here
if old_jwt:
user_name = old_jwt['sub']
with engine.connect() as connection:
s = text("""select active from pdp_users where username=:u """)
s = s.bindparams(u=user_name)
result = connection.execute(s)
if result.rowcount: # Did we get a match on username?
is_active = result.fetchone()
else:
log_user_action(
user_name, "Failure",
"Valid JWT presented for refesh attempt on unknown username"
)
return jsonify("Bad credentials"), 401
if is_active[0].lower() == 'y': # In the user DB and still Active?
token = jwt_ops.create_token(user_name, old_jwt['role'])
log_user_action(user_name, "Success", "Refreshed token")
return token
else:
return jsonify("Bad credentials"), 401
def afficher_chantier():
select_stmt = select(
[
Chantier_tbl.c.nom_chantier,
Chantier_tbl.c.username,
Chantier_tbl.c.adresse,
]
)
conn = engine.connect()
results = conn.execute(select_stmt)
chantiers = []
for result in results:
chantiers.append(
{
"nom_chantier": result[0],
"username": result[1],
"adresse": result[2],
}
)
conn.close()
return chantiers
def list_statistics():
""" Pull Last Execution stats from DB. """
current_app.logger.info("list_statistics() request")
last_execution_details = '{}' # Empty but valid JSON
engine.dispose() # we don't want other process's conn pool
with engine.connect() as conn:
try: # See Alembic Revision ID: 05e0693f8cbb for table definition
s = text(
"select valcol from kv_unique where keycol = 'last_execution_time';"
)
result = conn.execute(s)
if result.rowcount > 0:
last_execution_details = result.fetchone()[0]
except Exception as e:
current_app.logger.error(
"Failure reading Last Execution stats from DB - OK on first run"
)
# Will happen on first run, shouldn't after
return last_execution_details
def update_table_chantier(page):
''' Conversion de la requete SQL en dictionnaire'''
with engine.connect() as con:
return pd.read_sql("chantier",
con=con)[["nom_chantier", "username",
"adresse"]].to_dict("records")
def get_user_count():
"""Return number of records in pdp_users table """
with engine.connect() as connection:
s = text("select count(user) from pdp_users;")
result = connection.execute(s)
user_count = result.fetchone()
return jsonify(user_count[0])
def load_to_postgres(csv_path, table_name, drop_first_col=False):
# connect to or create database
# load csv into a dataframe
df = pd.read_csv(csv_path, encoding='cp1252')
# drop the first column - so far all csvs have had a first column that's an index and doesn't have a name
if drop_first_col:
df = df.drop(df.columns[0], axis=1)
# strip whitespace and periods from headers, convert to lowercase
df.columns = df.columns.str.lower().str.strip()
df.columns = df.columns.str.replace(' ', '_')
df.columns = df.columns.map(lambda x: re.sub(r'\.+', '_', x))
# get conneciton from engine and use in with clause to automatically handle transaction cleanup
with engine.connect() as connection:
connection.execute(f'DROP TABLE IF EXISTS {table_name}')
# load dataframe into database table
current_app.logger.info('Creating table: ' + table_name)
df.to_sql(
table_name,
engine,
index=False,
)
current_app.logger.info('Finished creating generic table for: ' +
table_name)
def __find_new_rows(result, table_name):
source_id = DATASOURCE_MAPPING[table_name]['id']
current_app.logger.info(table_name + ' ' + source_id)
with engine.connect() as conn:
# find new rows
rows = conn.execute(
'select t.* from {} t left join {} v on v."{}" = t."{}" where v."{}" is null'
.format(table_name + "_stage", table_name, source_id, source_id,
source_id))
rows_data = []
now = datetime.now()
tracked_columns = DATASOURCE_MAPPING[table_name]['tracked_columns']
for row in rows:
row_dict = {}
json_dict = {}
for key_value in row.items():
if key_value[0] in tracked_columns:
if key_value[0] == DATASOURCE_MAPPING['volgistics']['id']:
row_dict[key_value[0]] = str(key_value[1])
else:
row_dict[key_value[0]] = key_value[1]
json_dict[key_value[0]] = key_value[1]
row_dict['json'] = json_dict
row_dict['created_date'] = now
rows_data.append(row_dict)
result['new_rows'][table_name] = rows_data
ins = meta.tables[table_name].insert()
conn.execute(ins, rows_data)
def get_360(matching_id):
result = {}
with engine.connect() as connection:
query = text("select * from pdp_contacts where matching_id = :matching_id and archived_date is null")
query_result = connection.execute(query, matching_id=matching_id)
result["contact_details"] = [dict(row) for row in query_result]
result["shifts"] = []
result["donations"] = []
result["adoptions"] = []
# todo: complete retrieving details for response
for row in query_result:
if row["source_type"] == "volgistics":
query = text("select * from volgisticsshifts where number = :volgistics_id")
query_result = connection.execute(query, volgistics_id=row["source_id"])
result["shifts"] += [dict(row) for row in query_result]
'''
query = text("select * from salesforcedonations where contact_id = :salesforcecontacts_id")
query_result = connection.execute(query, salesforcecontacts_id=salesforcecontacts_id)
salesforcedonations_results = [dict(row) for row in query_result]
if salesforcedonations_results:
result['salesforcedonations'] = salesforcedonations_results
'''
return jsonify({'result': result})
def show_plan():
select_cmd = select(
[Plan_tbl.c.strategy_name, Plan_tbl.c.stock_code, Plan_tbl.c.capital])
conn = engine.connect()
rs = conn.execute(select_cmd)
conn.close()
return rs
def add_plan(user_id, strategy_name, stock_code, capital):
insert_cmd = Plan_tbl.insert().values(user_id=user_id,
strategy_name=strategy_name,
stock_code=stock_code,
capital=capital)
conn = engine.connect()
conn.execute(insert_cmd)
conn.close()
def reset_habit(username: str, habit: str):
conn = engine.connect()
stmt = Habit_tbl.update().\
values(count=0).\
where(Habit_tbl.c.username == username and Habit_tbl.c.habit == habit)
conn.execute(stmt)
conn.close()
return 0
def update_choix_chantier(page):
with engine.connect() as con:
query = f"SELECT * FROM chantier where username = '******'"
liste_chantiers = pd.read_sql_query(query, con=con).nom_chantier.tolist()
if len(liste_chantiers) == 0:
return []
else:
return [{"label": chantier, "value": chantier} for chantier in liste_chantiers]
async def execute_sql(sql: str) -> ResultProxy:
conn = engine.connect()
try:
return conn.execute(sql)
except BaseException as e:
raise e
finally:
conn.close()
def add_forecast(stock_code, future):
conn = engine.connect()
for index, row in future.iterrows():
insert_cmd = Forecast_tbl.insert().values(stock_code=stock_code,
date=index,
close=row['close'])
conn.execute(insert_cmd)
conn.close()
def maj_secteur(nom_secteur, nom_chantier, lat1, lat2, lon1, lon2):
update = (Secteur_tbl.update().values(
lat1=lat1, lat2=lat2, lon1=lon1,
lon2=lon2).where((Secteur_tbl.c.nom_secteur == nom_secteur)
& (Secteur_tbl.c.nom_chantier == nom_chantier)))
conn = engine.connect()
conn.execute(update)
conn.close()
def add_optimal(strategy_name, stock_code, capital, x, y):
insert_cmd = Optimal_tbl.insert().values(strategy_name=strategy_name,
stock_code=stock_code,
capital=capital,
x=x,
y=y)
conn = engine.connect()
conn.execute(insert_cmd)
conn.close()
def update_password(username, password):
hashed_password = generate_password_hash(password, method="sha256")
update = (User_tbl.update().values(password=hashed_password).where(
User_tbl.c.username == username))
conn = engine.connect()
conn.execute(update)
conn.close()
def add_user(username, password, role):
hashed_password = generate_password_hash(password, method='sha256')
ins = User_tbl.insert().values(
username=username, password=hashed_password, role=role)
conn = engine.connect()
conn.execute(ins)
conn.close()
def maj_capteur(nom_capteur, nom_chantier, type, lat, lon):
update = (Capteur_tbl.update().values(
lat=lat,
lon=lon).where((Capteur_tbl.c.nom_capteur == nom_capteur)
& (Capteur_tbl.c.nom_chantier == nom_chantier)))
conn = engine.connect()
conn.execute(update)
conn.close()
def show_all_credit():
select_st = select([Credit_tbl.c.id, Credit_tbl.c.card_num])
conn = engine.connect()
rs = conn.execute(select_st)
for row in rs:
print(row)
conn.close()
from sqlalchemy import Table, Column, ForeignKey, MetaData
from sqlalchemy.dialects.mysql import VARCHAR, BOOLEAN, TEXT, INTEGER, DATE
from datetime import datetime
from config import engine
metadata = MetaData()
connection = engine.connect()
department = Table(
"Department", metadata, Column("id", INTEGER, primary_key=True), Column("name", VARCHAR(127), nullable=False)
)
customer = Table(
"Customer",
metadata,
Column("id", INTEGER, primary_key=True),
Column("first_name", VARCHAR(127), nullable=False),
Column("last_name", VARCHAR(127), nullable=False),
Column("department_id", INTEGER, ForeignKey("department.id"), nullable=True),
)
computer = Table(
"Computer",
metadata,
Column("id", INTEGER, primary_key=True),
Column("customer_id", INTEGER, ForeignKey("customer.id"), nullable=False),
Column("po_number", VARCHAR(127), nullable=True),
Column("hw_type", TEXT, nullable=True),
Column("customization", TEXT, nullable=True),
Column("notes", TEXT, nullable=True),
