Upsert statement with Flask-SQLAlchemy - postgresql

I have a Flask app that parses a CSV of public election data and inserts the results into a Postgres database. It's a port of an old, not-Flask, Python 2 app that uses various libraries that no longer work. I'm mostly trying to base the application's structure on this tutorial. I've been using Flask-SQLAlchemy to construct some models for the database tables and populate the data from the CSV.
In this case I'm working with an Area model, which corresponds to a geographic area that might have an election (house district, school board district, etc). Here's what I've got in my basic blueprint route:
election = None
#bp.route('/areas')
def scrape_areas():
area = Area()
sources = area.read_sources()
election = area.set_election()
if election not in sources:
return
# Get metadata about election
election_meta = sources[election]['meta'] if 'meta' in sources[election] else {}
for i in sources[election]:
source = sources[election][i]
if 'type' in source and source['type'] == 'areas':
rows = area.parse_election(source, election_meta)
count = 0
for row in rows:
parsed = area.parser(row, i)
area = Area()
area.from_dict(parsed, new=True)
# this shows the generated string of area_id
# which is a UNIQUE key in the database
print(area)
db.session.add(area)
db.session.commit()
count = count + 1
return count
And here's the models.py:
import logging
import os
import json
import re
import csv
import urllib.request
import calendar
import datetime
from flask import current_app
from app import db
LOG = logging.getLogger(__name__)
scraper_sources_inline = None
class ScraperModel(object):
nonpartisan_parties = ['NP', 'WI', 'N P']
def __init__(self, group_type = None):
"""
Constructor
"""
# this is where scraperwiki was creating and connecting to its database
# we do this in the imported sql file instead
self.read_sources()
def read_sources(self):
"""
Read the scraper_sources.json file.
"""
if scraper_sources_inline is not None:
self.sources = json.loads(scraper_sources_inline)
else:
#sources_file = current_app.config['SOURCES_FILE']
sources_file = os.path.join(current_app.root_path, '../scraper_sources.json')
data = open(sources_file)
self.sources = json.load(data)
return self.sources
def set_election(self):
# Get the newest set
newest = 0
for s in self.sources:
newest = int(s) if int(s) > newest else newest
newest_election = str(newest)
election = newest_election
# Usually we just want the newest election but allow for other situations
election = election if election is not None and election != '' else newest_election
return election
def parse_election(self, source, election_meta = {}):
# Ensure we have a valid parser for this type
parser_method = getattr(self, "parser", None)
if callable(parser_method):
# Check if election has base_url
source['url'] = election_meta['base_url'] + source['url'] if 'base_url' in election_meta else source['url']
# Get data from URL
try:
response = urllib.request.urlopen(source['url'])
lines = [l.decode('latin-1') for l in response.readlines()]
rows = csv.reader(lines, delimiter=';')
return rows
except Exception as err:
LOG.exception('[%s] Error when trying to read URL and parse CSV: %s' % (source['type'], source['url']))
raise
def from_dict(self, data, new=False):
for field in data:
setattr(self, field, data[field])
class Area(ScraperModel, db.Model):
__tablename__ = "areas"
id = db.Column(db.Integer, primary_key=True, autoincrement=True)
area_id = db.Column(db.String(255), unique=True, nullable=False)
areas_group = db.Column(db.String(255))
county_id = db.Column(db.String(255))
county_name = db.Column(db.String(255))
ward_id = db.Column(db.String(255))
precinct_id = db.Column(db.String(255))
precinct_name = db.Column(db.String(255))
state_senate_id = db.Column(db.String(255))
state_house_id = db.Column(db.String(255))
county_commissioner_id = db.Column(db.String(255))
district_court_id = db.Column(db.String(255))
soil_water_id = db.Column(db.String(255))
school_district_id = db.Column(db.String(255))
school_district_name = db.Column(db.String(255))
mcd_id = db.Column(db.String(255))
precincts = db.Column(db.String(255))
name = db.Column(db.String(255))
updated = db.Column(db.DateTime, default=db.func.current_timestamp(), onupdate=db.func.current_timestamp())
def __repr__(self):
return '<Area {}>'.format(self.area_id)
def parser(self, row, group):
# General data
parsed = {
'area_id': group + '-',
'areas_group': group,
'county_id': None,
'county_name': None,
'ward_id': None,
'precinct_id': None,
'precinct_name': '',
'state_senate_id': None,
'state_house_id': None,
'county_commissioner_id': None,
'district_court_id': None,
'soil_water_id': None,
'school_district_id': None,
'school_district_name': '',
'mcd_id': None,
'precincts': None,
'name': ''
}
if group == 'municipalities':
parsed['area_id'] = parsed['area_id'] + row[0] + '-' + row[2]
parsed['county_id'] = row[0]
parsed['county_name'] = row[1]
parsed['mcd_id'] = "{0:05d}".format(int(row[2])) #enforce 5 digit
parsed['name'] = row[1]
if group == 'counties':
parsed['area_id'] = parsed['area_id'] + row[0]
parsed['county_id'] = row[0]
parsed['county_name'] = row[1]
parsed['precincts'] = row[2]
if group == 'precincts':
parsed['area_id'] = parsed['area_id'] + row[0] + '-' + row[1]
parsed['county_id'] = row[0]
parsed['precinct_id'] = row[1]
parsed['precinct_name'] = row[2]
parsed['state_senate_id'] = row[3]
parsed['state_house_id'] = row[4]
parsed['county_commissioner_id'] = row[5]
parsed['district_court_id'] = row[6]
parsed['soil_water_id'] = row[7]
parsed['mcd_id'] = row[8]
if group == 'school_districts':
parsed['area_id'] = parsed['area_id'] + row[0]
parsed['school_district_id'] = row[0]
parsed['school_district_name'] = row[1]
parsed['county_id'] = row[2]
parsed['county_name'] = row[3]
return parsed
So Areas is an extension of my default model class because it allows me to set up the fields that are specific to a given area based on the CSV.
Where this code fails is a (relatively) rare case in the CSV data where there might be multiple rows that, in the old application, correspond to the same row in the table. That old application had an array (usually with just one item, representing a UNIQUE column in the database) to instruct the code to run an UPDATE on those rows.
It returns an error like this:
sqlalchemy.exc.IntegrityError: (psycopg2.errors.UniqueViolation) duplicate key value violates unique constraint "areas_area_id_key"
DETAIL: Key (area_id)=(counties-01) already exists.
An example of how it runs when I'm just logging my UNIQUE key value from the model instead of inserting it:
<Area precincts-87-0140>
<Area precincts-87-0145>
<Area precincts-87-0150>
<Area precincts-87-0155>
<Area precincts-87-0160>
<Area precincts-87-0165>
<Area school_districts-0001>
<Area school_districts-0001>
<Area school_districts-0001>
<Area school_districts-0002>
<Area school_districts-0004>
<Area school_districts-0006>
<Area school_districts-0012>
<Area school_districts-0013>
<Area school_districts-0014>
So I've been looking at different methods that Flask can use to run an UPSERT statement because I'd need to update all of the fields, and they'd be different based on both which type of area it is, and also in the other models (election contests or results, for example). Most of what I'm finding uses SQLAlchemy rather than Flask-SQLAlchemy.
I found this answer that looked promising. Here's what I added to my model:
from sqlalchemy.ext.compiler import compiles
from sqlalchemy.sql.expression import Insert
Then I modified the ScraperModel class like this:
class ScraperModel(object):
#compiles(Insert)
def compile_upsert(insert_stmt, compiler, **kwargs):
"""
converts every SQL insert to an upsert i.e;
INSERT INTO test (foo, bar) VALUES (1, 'a')
becomes:
INSERT INTO test (foo, bar) VALUES (1, 'a') ON CONFLICT(foo) DO UPDATE SET (bar = EXCLUDED.bar)
(assuming foo is a primary key)
:param insert_stmt: Original insert statement
:param compiler: SQL Compiler
:param kwargs: optional arguments
:return: upsert statement
"""
pk = insert_stmt.table.primary_key
insert = compiler.visit_insert(insert_stmt, **kwargs)
ondup = f'ON CONFLICT ({",".join(c.name for c in pk)}) DO UPDATE SET'
updates = ', '.join(f"{c.name}=EXCLUDED.{c.name}" for c in insert_stmt.table.columns)
upsert = ' '.join((insert, ondup, updates))
return upsert
I'm clearly misunderstanding how the insert_stmt works because of how the query comes out, but here's the error that it generates:
sqlalchemy.exc.ProgrammingError: (psycopg2.errors.SyntaxError) syntax error at or near "ON"
LINE 1: ..., '54', '', CURRENT_TIMESTAMP) RETURNING areas.id ON CONFLIC...
^
[SQL: INSERT INTO areas (area_id, areas_group, county_id, county_name, ward_id, precinct_id, precinct_name, state_senate_id, state_house_id, county_commissioner_id, district_court_id, soil_water_id, school_district_id, school_district_name, mcd_id, precincts, name, updated) VALUES (%(area_id)s, %(areas_group)s, %(county_id)s, %(county_name)s, %(ward_id)s, %(precinct_id)s, %(precinct_name)s, %(state_senate_id)s, %(state_house_id)s, %(county_commissioner_id)s, %(district_court_id)s, %(soil_water_id)s, %(school_district_id)s, %(school_district_name)s, %(mcd_id)s, %(precincts)s, %(name)s, CURRENT_TIMESTAMP) RETURNING areas.id ON CONFLICT (id) DO UPDATE SET id=EXCLUDED.id, area_id=EXCLUDED.area_id, areas_group=EXCLUDED.areas_group, county_id=EXCLUDED.county_id, county_name=EXCLUDED.county_name, ward_id=EXCLUDED.ward_id, precinct_id=EXCLUDED.precinct_id, precinct_name=EXCLUDED.precinct_name, state_senate_id=EXCLUDED.state_senate_id, state_house_id=EXCLUDED.state_house_id, county_commissioner_id=EXCLUDED.county_commissioner_id, district_court_id=EXCLUDED.district_court_id, soil_water_id=EXCLUDED.soil_water_id, school_district_id=EXCLUDED.school_district_id, school_district_name=EXCLUDED.school_district_name, mcd_id=EXCLUDED.mcd_id, precincts=EXCLUDED.precincts, name=EXCLUDED.name, updated=EXCLUDED.updated]
[parameters: {'area_id': 'counties-01', 'areas_group': 'counties', 'county_id': '01', 'county_name': 'Aitkin', 'ward_id': None, 'precinct_id': None, 'precinct_name': '', 'state_senate_id': None, 'state_house_id': None, 'county_commissioner_id': None, 'district_court_id': None, 'soil_water_id': None, 'school_district_id': None, 'school_district_name': '', 'mcd_id': None, 'precincts': '54', 'name': ''}]
(Background on this error at: https://sqlalche.me/e/14/f405)
I'm hoping I didn't paste too much to be helpful there.
I also found this answer that I read as creating its own insert statement instead of compiling the built in one. Here's what I changed. In the blueprint's imports:
from sqlalchemy.dialects.postgresql import insert
And in the blueprint's loop:
for i in sources[election]:
source = sources[election][i]
if 'type' in source and source['type'] == 'areas':
rows = area.parse_election(source, election_meta)
count = 0
for row in rows:
parsed = area.parser(row, i)
area = Area()
area.from_dict(parsed, new=True)
stmt = insert(Area.__table__).values(parsed)
stmt = stmt.on_conflict_do_update(
# Let's use the constraint name which was visible in the original posts error msg
constraint="['area_id']",
# The columns that should be updated on conflict
set_={
parsed
}
)
db.session.execute(stmt)
count = count + 1
return count
It results in a different error:
TypeError: unhashable type: 'dict'
All that to say, I'm currently at a loss. It's clear to me that I need to modify the INSERT statement, but it's not clear to me which route I should take to modify it, how to make sure that it matches on the correct field (which is called area_id and the key is called areas_id_unique), or how to make sure it updates the correct fields when it does find a match.

What I think I'm finding is that none of this would work because I wasn't matching on a primary key, but on a unique key. What I've done is change the unique key area_id to a primary key. Then, I can use the upsert statement from above.
#compiles(Insert)
def compile_upsert(insert_stmt, compiler, **kwargs):
"""
converts every SQL insert to an upsert i.e;
INSERT INTO test (foo, bar) VALUES (1, 'a')
becomes:
INSERT INTO test (foo, bar) VALUES (1, 'a') ON CONFLICT(foo) DO UPDATE SET (bar = EXCLUDED.bar)
(assuming foo is a primary key)
:param insert_stmt: Original insert statement
:param compiler: SQL Compiler
:param kwargs: optional arguments
:return: upsert statement
"""
pk = insert_stmt.table.primary_key
insert = compiler.visit_insert(insert_stmt, **kwargs)
ondup = f'ON CONFLICT ({",".join(c.name for c in pk)}) DO UPDATE SET'
updates = ', '.join(f"{c.name}=EXCLUDED.{c.name}" for c in insert_stmt.table.columns)
upsert = ' '.join((insert, ondup, updates))
return upsert
I had been trying to change the pk = insert_stmt.table.primary_key line to check for the unique key with no success, but it works just like this if I change that field.
Changing the primary key also fixed the other solution I was trying:
group = []
for row in rows:
parsed = area.parser(row, i)
area = Area()
area.from_dict(parsed, new=True)
group.append(area)
insert(db.session, Area, group)
def insert(session, model, rows):
table = model.__table__
stmt = insert(table)
primary_keys = [key.name for key in inspect(table).primary_key]
update_dict = {c.name: c for c in stmt.excluded if not c.primary_key}
if not update_dict:
raise ValueError("insert_or_update resulted in an empty update_dict")
stmt = stmt.on_conflict_do_update(
index_elements=primary_keys,
set_=update_dict
)
So both solutions were (relatively) workable, but only with a primary key instead of a unique key and that just hadn't been clear to me.

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I quickly realized that I wasn't sure how to handle composite data types. For example, suppose that I have a composite data type of the form (integer, box). How do I specify its value for the parameters arg of boto3.client('rds-data').execute_statement()?
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Heroku Postgres throwing int out of range error for ints that should be in range

I'm attempting to collect options data using a heroku dyno (hobby $7 version) and a heroku Postgres database (standard $50 version). I've got a small script set up that uses yfinance to collect options data for a set of ticker symbols and SQLAlchemy + psycopg2 to insert this data into the postgres database.
I seem to be encountering a very strange error when inserting into the database. For many of the records, I'm seeing a (psycopg2.errors.NumericValueOutOfRange) integer out of range Exception thrown for records that should not have any integers out of range... I've included an example of the error below as well as my model definition. At first I thought maybe it was the id / pk column, but according to SQLAlchemy's docs they automatically treat these fields as a serial data type. So I'm not sure why this error is being thrown with all integer columns clearly in the range of the INT data type.
Is this a heroku thing? Has anyone seen / dealt with this before? I'm not sure how to debug the underlying issue. Thanks in advance!
2021-03-24 12:25:16 ERROR Unable to commit Option(id=None, ticker=EDIT, option_type=PUT, contractSymbol=EDIT230120P00017500, lastTradeDate=2020-11-05 14:38:12, strike=17.5, lastPrice=4.7, bid=0.0, ask=0.0, change=0.0, percentChange=0.0, volume=1.0, openInterest=0, impliedVolatility=0.12500875, inTheMoney=False, contractSize=REGULAR, currency=USD)
2021-03-24 12:25:16 ERROR This Session's transaction has been rolled back due to a previous exception during flush. To begin a new transaction with this Session, first issue Session.rollback(). Original exception was: (psycopg2.errors.NumericValueOutOfRange) integer out of range
(Background on this error at: http://sqlalche.me/e/14/9h9h) (Background on this error at: http://sqlalche.me/e/14/7s2a)
Continuing.
Model definition:
class Option(config.Base):
__tablename__ = "options"
id = Column(Integer, primary_key=True)
ticker = Column(String, nullable=False)
dt_created_db = Column(
DateTime, nullable=False, default=datetime.datetime.utcnow()
)
dt_updated_db = Column(
DateTime, nullable=False, default=datetime.datetime.utcnow()
)
dt_created_market_time_db = Column(
DateTime, nullable=False,
default=datetime.datetime.now().astimezone(
pytz.timezone(
"America/New_York"
)
)
)
option_type = Column(String, nullable=False) # CALL or PUT
contractSymbol = Column(String, nullable=False)
lastTradeDate = Column(DateTime, nullable=False)
strike = Column(Float, nullable=False)
lastPrice = Column(Float, nullable=False)
bid = Column(Float)
ask = Column(Float)
change = Column(Float)
percentChange = Column(Float)
volume = Column(Float)
openInterest = Column(Integer)
impliedVolatility = Column(Numeric)
inTheMoney = Column(Boolean)
contractSize = Column(String)
currency = Column(String)
#classmethod
def create_option_record(cls, ticker, record, opt_type):
"""Creates an Option model instance.
Args:
ticker: The ticker symbol.
record: A pandas dataframe row with "." access to columns.
opt_type: A string, either CALL or PUT.
Returns:
Option object.
"""
return cls(
ticker=ticker,
option_type=opt_type,
contractSymbol=record.contractSymbol,
lastTradeDate=record.lastTradeDate,
strike=record.strike,
lastPrice=record.lastPrice,
bid=record.bid,
ask=record.ask,
change=record.change,
percentChange=record.percentChange,
volume=record.volume,
openInterest=record.openInterest,
impliedVolatility=round(record.impliedVolatility, 20),
inTheMoney=record.inTheMoney,
contractSize=record.contractSize,
currency=record.currency
)
def __str__(self):
return (
f"Option("
f"id={self.id}, "
f"ticker={self.ticker}, "
f"option_type={self.option_type}, "
f"contractSymbol={self.contractSymbol}, "
f"lastTradeDate={self.lastTradeDate}, "
f"strike={self.strike}, "
f"lastPrice={self.lastPrice}, "
f"bid={self.bid}, "
f"ask={self.ask}, "
f"change={self.change}, "
f"percentChange={self.percentChange}, "
f"volume={self.volume}, "
f"openInterest={self.openInterest}, "
f"impliedVolatility={self.impliedVolatility}, "
f"inTheMoney={self.inTheMoney}, "
f"contractSize={self.contractSize}, "
f"currency={self.currency}"
f")"
)
I've solved this. It turns out the database logs were behind the compute logs and so the record I thought was causing the error was not actually causing the error.
The root cause was that an np.nan value was being inserted into an INTEGER column. I had to replace np.nan's with None and this solved the problem.

Insert to postgres DB: invalid String format (parsing exception error)

I am creating a log db where I track execution steps and catch where it might or might not fail.
I am having issues inserting the Exceptions thrown to a DB.
I am calling an endpoint first in order then query a django database.
In this case I wanted to catch a mistake in the selection_query and thus being unable to fetch the data from the DB.
I want to log this message.
Example:
Exception catch
try:
select_query = "SELECT columnn from row"
cur.execute(select_query)
selected_vals = cur.fetchall()
except Exception as e:
response = insert_into_logging(message = f"{e}", logging_id = 3)
Error
File "/usr/lib/python3.6/json/decoder.py", line 357, in raw_decode
raise JSONDecodeError("Expecting value", s, err.value) from None
This is because of the value passed in the message argument.
(message = f"{e}")
It is not insertable in the DB
The value of "e" is:
auto_close_alarm relation "row" does not exist
LINE 1: SELECT columnn from row
^
I tried to pass
str(e)
Value passed: identical output as above
repr(e.args[0])
Output: 'relation "row" does not exist\nLINE 1: SELECT columnn from row\n ^\n'
repr(e)
Value passed: UndefinedTable('relation "row" does not exist\nLINE 1: SELECT columnn from row\n ^\n',)
And multiple other ways but to no avail.
They all result in the same JSONDecodeError.
Basically the key problem is that this is not a valid String format for it to be able to be parsed in the DB.
All I need is a representation of this Exception error for it to be insertable
Flow of data:
insert function
def insert_into_logging(message, logging_id, date_time):
url = f"""url/insert-into-logging/"""
data = {
"message": message,
"logging_id": logging_id,
}
response = r.post(url, data=json.dumps(data, indent=4, sort_keys=True, default=str))
print(response)
return response.json()
Querying DB
def insert_to_logging(request):
from datetime import datetime, timedelta
if request.method != 'POST':
print(request.method)
return JsonResponse({'status':'error', 'message':'Client insertion only accepts post requests.' + str(request.method)})
today = datetime.today()
body = json.loads(request.body)
message = body.get('message')
logging_id = body.get('logging_id')
Logging.objects.create(message = message, logging_id = logging_id, time_stamp = today)
return JsonResponse({'status':'OK', 'message':'Logging successful'})
Django Model
class Logging(models.Model):
objects = GetOrNoneManager()
message = models.CharField(max_length=64, blank=True, null=True)
logging_id = models.IntegerField(blank=True, null=True)
time_stamp = models.DateTimeField(blank=True, null=True)
class Meta:
db_table = 'logging'

Integer range in Flask REST API using SQLAlchemy

I am creating a REST API using Flask, SQLAlchemy, and Marshmallow. I have defined my Product Model in app.py as:
from flask import Flask, request, jsonify
from flask_sqlalchemy import SQLAlchemy
from flask_marshmallow import Marshmallow
import os
# Initialize App
app = Flask(__name__)
basedir = os.path.abspath(os.path.dirname(__file__))
# Database Setup
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///' + os.path.join(basedir, 'db.sqlite')
app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
# Init db
db = SQLAlchemy(app)
# Init marshmallow
ma = Marshmallow(app)
# Product Class/Model
class Product(db.Model):
id = db.Column(db.Integer, primary_key=True)
price = db.Column(db.Integer)
qty = db.Column(db.Integer)
def __init__(self, price, qty):
self.price = price
self.qty = qty
# Product Schema
class ProductSchema(ma.Schema):
class Meta:
fields = ('id', 'price', 'qty')
# Init Schema
product_schema = ProductSchema()
products_schema = ProductSchema(many=True)
# Create Product
#app.route('/product', methods=['POST'])
def add_product():
price = request.json['price']
qty = request.json['qty']
new_product = Product(price, qty)
db.session.add(new_product)
db.session.commit()
return product_schema.jsonify(new_product)
# Run the Server
if __name__ == '__main__':
app.run(debug=True)
I have to perform the following logic:
Setting price value between 0 - 100
Setting qty value between 0 - 100
If success return 200, if anything wrong return 500.
I am not able to set Integer value between the given range by db.Integer([0, 100]) as its giving me error:
TypeError: Integer() takes no arguments
How do I implement the above logic?
Edit: I've misunderstood the question and made a new function.
def ExpectedRange(var1):
return 200 if var1 in range(0,100) else 500
# Create Product
#app.route('/product', methods=['POST'])
def add_product():
price = request.json['price']
qty = request.json['qty']
if ExpectedRange(price) and ExpectedRange(qty) == 200:
new_product = Product(price, qty)
db.session.add(new_product)
db.session.commit()
return product_schema.jsonify(new_product)
#else:
# Show error. I recommend you using the method 'flash' in flask.
I think the problem with your code by using db.Integer([0, 100]) as a way to find the value between 0 and 100, instead, what you should be doing is by using range with the help of a method called randrange from the library random. With all due respect, I actually don't know what you are trying to accomplish, if I am wrong, please correct me in the comments and I'll correct my post.
What I recommend you doing is to not set the price and qty in the model class, but rather, in an entirely different function and using your model class to create the elements within your database. For example:
from random import randrange
class Product(db.Model):
id = db.Column(db.Integer, primary_key=True)
price = db.Column(db.Integer)
qty = db.Column(db.Integer)
def ProductRange(range1, range2):
return randrange(range1, range2)
print(ProductRange(1,100))
What the function ProductRange will do is to choose the range between the variable range1 and range2. As for returning 200 and 500, I am not sure what you could use with this value, but I recommend doing boolean. If it is needed, 200 and 500 is simply a constant, and you could easily implement it via putting it in a function rather than using the returned value to calculate things. So, how would you use the ProductRange function? Just follow the code below.
from random import randrange
class Product(db.Model):
id = db.Column(db.Integer, primary_key=True)
product_name = db.Column(db.String) # Ignore this line, this just for the /addpost route to get the method POST
price = db.Column(db.Integer)
qty = db.Column(db.Integer)
def ProductRange(range1, range2):
return randrange(range1, range2)
# This route is just an example of how you would use the function ProductRange
#app.route('/addpost', methods=['POST'])
def addpost():
product_name = request.form['product_name']
price = ProductRange(1,100)
qty = ProductRange(1,100)
post = Product[product_name=product_name, price=price, qty=qty]
db.session.add(post)
db.session.commit()
return redirect(url_for('index'))
If it doesn't work, please comment down below for me to help you further with this question of yours. I wish you good luck.
since you have installed marshmallow, install the marmallow-sqlalchemy and use SQLAlchemyAutoSchema feature which will allow to you to refer directly to the model and create an instance after successful load of the json object sent in request body, plus you can define your own constraints in the schema class. the marshmallow conf. will look like:
from marshmallow import ValidationError, fields
from marshmallow.validate import Range
from marshmallow_sqlalchemy import SQLAlchemyAutoSchema
ma = Marshmallow(app)
# to return marshmallow parsing error
#app.errorhandler(ValidationError)
def handle_marshmallow_validation(err):
print(err)
return jsonify(err.messages), 400
# Product Schema
class ProductSchema(ma.SQLAlchemyAutoSchema):
id = fields.Integer(required=False)
price = fields.Integer(required=True, validate=[Range(max=100, error="Value must be 100 or less")])
qty = fields.Integer(required=True, validate=[Range(max=100, error="Value must be 100 or less")])
class Meta:
model = Product
load_instance = True
now the ressource will look like:
# Create Product
#app.route('/product', methods=['POST'])
def add_product():
# here we can check the payload validity, parse it and transform it directly to instance
product_json = request.get_json()
new_product = product_schema.load(product_json)
db.session.add(new_product)
db.session.commit()
return product_schema.dump(new_product)
now if you sent value outside the range you will receive response like this
{
"price": [
"Value must be 100 or less"
],
"qty": [
"Value must be 100 or less"
]
}

Using sqlalchemy, how transform 1 & 0 to boolean in postgres?

I'm getting some data in JSON, where boolean values are 0 & 1.
In the postgres table is a boolean field, and expect true & false.
I try this when loading the table:
class PGBool(types.TypeDecorator):
impl = types.BOOLEAN
def process_result_value(self, value, dialect):
#print value
if value is not None:
return bool(value)
return value
def listen(self, table, column_info):
type_ = column_info['type']
print column_info['name'], type_
if str(type_).split('.')[-1] == 'BOOLEAN':
column_info['type'] = PGBool
return column_info
def getTable(self, name):
return sq.Table(
name,
self.meta,
autoload=True,
autoload_with=self.con,
listeners=[
('column_reflect', listen)
]
)
def saveRecord(self, table, data):
..
..
if exist:
self.con.execute(
table.update().where(table.c.id == theGuid),
data
)
else:
self.con.execute(
table.insert(),
data
)
But the data is not converted, and still try to insert 0 & 1.
when you use TypeDecorator, there's two sides to the data to be concerned with. One is the data going into the database, and the other is the data coming out. The side going in is referred to as the "bind parameters" and the side going out is the "result" data. Since you want here to deal with an INSERT, you're on the bind side, so the TypeDecorator would look like:
from sqlalchemy.types import TypeDecorator, Boolean
class CoerceToBool(TypeDecorator):
impl = Boolean
def process_bind_param(self, value, dialect):
if value is not None:
value = bool(value)
return value