My objective is to create a new field based on another field after a Request is posted to FastAPI. My attempt was:
import functools
from datetime import date, datetime
from slugify import slugify
from sqlmodel import Field, SQLModel
class ProjectBase(SQLModel):
is_active: bool = Field(default=True, nullable=False)
name: str = Field(..., nullable=False)
publish_date: date = Field(default_factory=datetime.now().date, nullable=False)
# # post_init
repr_name: str = Field(
default_factory=functools.partial(slugify, name, separator='_'),
description="The project represented name, it must contain no whitespace, each word is separated by an underscore and it is slugified using the python-slugify library.",
nullable=False)
I have also tried __post_init__ but I think SQLModel does not have such a mechanism, it belongs to dataclasses within pydantic.
My desired output would be something like if a Request like the below was POST-ed:
request = {
'is_active': true,
'name': 'hello world bye',
'publish_date': '2023-01-01'
}
Then, the following Response is gotten and inserted into the database:
response = {
'is_active': true,
'name': 'hello world bye',
'repr_name': 'hello_world_bye', # output of slugify(`name`, separator='_')
'publish_date': '2023-01-01'
}
Thankfully sqlmodel.SQLModel inherits from pydantic.BaseModel. (And their metaclasses are also related.)
This is yet another job for custom validators. We just need a default sentinel value to check against, if no explicit value is provided by the user. I would just make the field type a union of str and None and make None the default, but then always ensure a str ends up as the value via the validator.
Here is an example:
from datetime import date, datetime
from typing import Any, Optional
from pydantic import validator
from slugify import slugify
from sqlmodel import Field, SQLModel
class ProjectBase(SQLModel):
name: str = Field(..., nullable=False)
publish_date: date = Field(default_factory=datetime.now().date, nullable=False)
repr_name: Optional[str] = Field(default=None, nullable=False)
#validator("repr_name", always=True)
def slugify_name(cls, v: Optional[str], values: dict[str, Any]) -> str:
if v is None:
return slugify(values["name"], separator="_")
return slugify(v, separator="_")
print(ProjectBase(name="foo bar baz").json(indent=2))
print(ProjectBase(name="spam", repr_name="Eggs and Bacon").json(indent=2))
Output:
{
"name": "foo bar baz",
"publish_date": "2023-02-11",
"repr_name": "foo_bar_baz"
}
{
"name": "spam",
"publish_date": "2023-02-11",
"repr_name": "eggs_and_bacon"
}
The always=True is important to trigger validation, when no value was explicitly provided.
The order of the fields is also important because the values dictionary in the validator method will only contain previously validated fields and field validation occurs in the order the fields were defined (see docs link above), so since name comes before repr_name, it will be validated and its value therefore present in the dictionary, when repr_name validation is triggered.
Important: Validation will not work, if the validators belong to a table=True model. To get around this, define a base model with the fields you need validated and inherit from that in your table=True model; then parse data through the parent model before instantiating the table model with it.
This bit seems pretty limiting, so I would not rule out the possibility that this will change in the future, at least to a certain extent. But in the current state of SQLModel that is what we have.
The long title contain also a mini-exaple because I couldn't explain well what I'm trying to do. Nonethless, the similar questions windows led me to various implementation. But since I read multiple times that it's a bad design, I would like to ask if what I'm trying to do is a bad design rather asking how to do it. For this reason I will try to explain my use case with a minial functional code.
Suppose I have a two classes, each of them with their own parameters:
class MyClass1:
def __init__(self,param1=1,param2=2):
self.param1=param1
self.param2=param2
class MyClass2:
def __init__(self,param3=3,param4=4):
self.param3=param3
self.param4=param4
I want to print param1...param4 as a string (i.e. "param1"..."param4") and not its value (i.e.=1...4).
Why? Two reasons in my case:
I have a GUI where the user is asked to select one of of the class
type (Myclass1, Myclass2) and then it's asked to insert the values
for the parameters of that class. The GUI then must show the
parameter names ("param1", "param2" if MyClass1 was chosen) as a
label with the Entry Widget to get the value. Now, suppose the
number of MyClass and parameter is very high, like 10 classes and 20
parameters per class. In order to minimize the written code and to
make it flexible (add or remove parameters from classes without
modifying the GUI code) I would like to cycle all the parameter of
Myclass and for each of them create the relative widget, thus I need
the paramx names under the form od string. The real application I'm
working on is even more complex, like parameter are inside other
objects of classes, but I used the simpliest example. One solution
would be to define every parameter as an object where
param1.name="param1" and param1.value=1. Thus in the GUI I would
print param1.name. But this lead to a specifi problem of my
implementation, that's reason 2:
MyClass1..MyClassN will be at some point printed in a JSON. The JSON
will be a huge file, and also since it's a complex tree (the example
is simple) I want to make it as simple as possibile. To explain why
I don't like to solution above, suppose this situation:
class MyClass1:
def init(self,param1,param2,combinations=[]):
self.param1=param1
self.param2=param2
self.combinations=combinations
Supposse param1 and param2 are now list of variable size, and
combination is a list where each element is composed by all the
combination of param1 and param2, and generate an output from some
sort of calculation. Each element of the list combinations is an
object SingleCombination,for example (metacode):
param1=[1,2] param2=[5,6] SingleCombination.param1=1
SingleCombination.param2=5 SingleCombination.output=1*5
MyInst1.combinations.append(SingleCombination).
In my case I will further incapsulated param1,param2 in a object
called parameters, so every condition will hace a nice tree with
only two object, parameters and output, and expanding parameters
node will show all the parameters with their value.
If I use JSON pickle to generate a JSON from the situation above, it
is nicely displayed since the name of the node will be the name of
the varaible ("param1", "param2" as strings in the JSON). But if I
do the trick at the end of situation (1), creating an object of
paramN as paramN.name and paramN.value, the JSON tree will become
ugly but especially huge, because if I have a big number of
condition, every paramN contains 2 sub-element. I wrote the
situation and displayed with a JSON Viewer, see the attached immage
I could pre processing the data structure before creating the JSON,
the problem is that I use the JSON to recreate the data structure in
another session of the program, so I need all the pieces of the data
structure to be in the JSON.
So, from my requirements, it seems that the workround to avoid print the variable names creates some side effect on the JSON visualization that I don't know how to solve without changing the logic of my program...
If you use dataclasses, getting the field names is pretty straightforward:
from dataclasses import dataclass, fields
#dataclass
class MyClass1:
first:int = 4
>>> fields(MyClass1)
(Field(name='first',type=<class 'int'>,default=4,...),)
This way, you can iterate over the class fields and ask your user to fill them. Note the field has a type, which you could use to eg ask the user for several values, as in your example.
You could add functions to extract programatically the param names (_show_inputs below ) from the class and values from instances (_json below ):
def blossom(cls):
"""decorate a class with `_json` (classmethod) and `_show_inputs` (bound)"""
def _json(self):
return json.dumps(self, cls=DataClassEncoder)
def _show_inputs(cls):
return {
field.name: field.type.__name__
for field in fields(cls)
}
cls._json = _json
cls._show_inputs = classmethod(_show_inputs)
return cls
NOTE 1: There's actually no need to decorate the classes with blossom. You could just use its internal functions programatically.
Using a custom json encoder to dump the dataclass objects, including properties:
import json
class DataClassPropEncoder(json.JSONEncoder): # https://stackoverflow.com/a/51286749/7814595
def default(self, o):
if is_dataclass(o):
cls = type(o)
# inject instance properties
props = {
name: getattr(o, name)
for name, value in cls.__dict__.items() if isinstance(value, property)
}
return {
**props,
**asdict(o)
}
return super().default(o)
Finally, wrap the computations inside properties so they are
serialized as well when using the decorated class. Full code example:
from dataclasses import asdict
from dataclasses import dataclass
from dataclasses import fields
from dataclasses import is_dataclass
import json
from itertools import product
from typing import List
class DataClassPropEncoder(json.JSONEncoder): # https://stackoverflow.com/a/51286749/7814595
def default(self, o):
if is_dataclass(o):
cls = type(o)
props = {
name: getattr(o, name)
for name, value in cls.__dict__.items() if isinstance(value, property)
}
return {
**props,
**asdict(o)
}
return super().default(o)
def blossom(cls):
def _json(self):
return json.dumps(self, cls=DataClassEncoder)
def _show_inputs(cls):
return {
field.name: field.type.__name__
for field in fields(cls)
}
cls._json = _json
cls._show_inputs = classmethod(_show_inputs)
return cls
#blossom
#dataclass
class MyClass1:
param1:int
param2:int
#blossom
#dataclass
class MyClass2:
param3: List[str]
param4: List[int]
def _compute_single(self, values): # TODO: implmement this
return values[0]*values[1]
#property
def combinations(self):
# TODO: cache if used more than once
# TODO: combinations might explode
field_names = []
field_values = []
cls = type(self)
for field in fields(cls):
field_names.append(field.name)
field_values.append(getattr(self, field.name))
results = []
for values in product(*field_values):
result = {
**{
field_names[idx]: value
for idx, value in enumerate(values)
},
"output": self._compute_single(values)
}
results.append(result)
return results
>>> print(f"MyClass1:\n{MyClass1._show_inputs()}")
MyClass1:
{'param1': 'int', 'param2': 'int'}
>>> print(f"MyClass2:\n{MyClass2._show_inputs()}")
MyClass2:
{'param3': 'List', 'param4': 'List'}
>>> obj_1 = MyClass1(3,4)
>>> print(f"obj_1:\n{obj_1._json()}")
obj_1:
{"param1": 3, "param2": 4}
>>> obj_2 = MyClass2(["first", "second"],[4,2])._json()
>>> print(f"obj_2:\n{obj_2._json()}")
obj_2:
{"combinations": [{"param3": "first", "param4": 4, "output": "firstfirstfirstfirst"}, {"param3": "first", "param4": 2, "output": "firstfirst"}, {"param3": "second", "param4": 4, "output": "secondsecondsecondsecond"}, {"param3": "second", "param4": 2, "output": "secondsecond"}], "param3": ["first", "second"], "param4": [4, 2]}
NOTE 2: If you need to perform several computations per class, it might be a good idea to abstract away the pattern in the combinations property to avoid repeating code.
NOTE 3: If you need access to the properties several times and not ust once, you might want to consider caching their values to avoid re-computation.
Once you have an instance of MyClass / MyClass2, you can call vars() or vars().keys() and it will give you the attributes as a str. Unlike dir, it will not show all the builtin attributes/methods starting with __.
class MyClass2:
def __init__(self,param3=3,param4=4):
self.param3=param3
self.param4=param4
instance_of_myclass2 = MyClass2(param3="what", param4="ever")
print(vars(instance_of_myclass2))
{'param3': 'what', 'param4': 'ever'}
print(vars(instance_of_myclass2).keys())
dict_keys(['param3', 'param4'])
dir(instance_of_myclass2)
['__class__', '__delattr__', '__dict__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__le__', '__lt__', '__module__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', '__weakref__', 'param3', 'param4']
i tried to fetch data from mongodb using mongoengine with flask. query is work perfect the problem is when i convert query result into json its show only fields name.
here is my code
view.py
from model import Users
result = Users.objects()
print(dumps(result))
model.py
class Users(DynamicDocument):
meta = {'collection' : 'users'}
user_name = StringField()
phone = StringField()
output
[["id", "user_name", "phone"], ["id", "user_name", "phone"]]
why its show only fields name ?
Your query returns a queryset. Use the .to_json() method to convert it.
Depending on what you need from there, you may want to use something like json.loads() to get a python dictionary.
For example:
from model import Users
# This returns <class 'mongoengine.queryset.queryset.QuerySet'>
q_set = Users.objects()
json_data = q_set.to_json()
# You might also find it useful to create python dictionaries
import json
dicts = json.loads(json_data)
I would like to generate a simple json file from an database.
I am not an expert in parsing json files using python nor NDB database engine nor GQL.
What is the right query to search the data? see https://developers.google.com/appengine/docs/python/ndb/queries
How should I write the code to generate the JSON using the same schema as the json described here below?
Many thanks for your help
Model Class definition using NDB:
# coding=UTF-8
from google.appengine.ext import ndb
import logging
class Albums(ndb.Model):
"""Models an individual Event entry with content and date."""
SingerName = ndb.StringProperty()
albumName = ndb.StringProperty()
Expected output:
{
"Madonna": ["Madonna Album", "Like a Virgin", "True Blue", "Like a Prayer"],
"Lady Gaga": ["The Fame", "Born This Way"],
"Bruce Dickinson": ["Iron Maiden", "Killers", "The Number of the Beast", "Piece of Mind"]
}
For consistency, model names should by singular (Album not Albums), and property names should be lowercase_with_underscores:
class Album(ndb.Model):
singer_name = ndb.StringProperty()
album_name = ndb.StringProperty()
To generate the JSON as described in your question:
1) Query the Album entities from the datastore:
albums = Album.query().fetch(100)
2) Iterate over them to form a python data structure:
albums_dict = {}
for album in albums:
if not album.singer_name in albums_dict:
albums_dict[album.singer_name] = []
albums_dict[album.singer_name].append(album.album_name)
3) use json.dumps() method to encode to JSON.
albums_json = json.dumps(albums_dict)
Alternatively, you could use the built in to_dict() method:
albums = Album.query().fetch(100)
albums_json = json.dumps([a.to_dict() for a in albums])
Table structure like -
db.define_table('parent',
Field('name'),format='%(name)s')
db.define_table('children',
Field('name'),
Field('mother','reference parent'),
Field('father','reference parent'))
db.children.mother.requires = IS_IN_DB(db, db.parent.id,'%(name)s')
db.children.father.requires = IS_IN_DB(db, db.parent.id,'%(name)s')
Controller :
grid = SQLFORM.grid(db.children, orderby=[db.children.id],
csv=True,
fields=[db.children.id, db.children.name, db.children.mother, db.children.father])
return dict(grid=grid)
Here grid shows proper values i.e names of the mother and father from the parent table.
But when I try to export it via csv link - resulted excelsheet shows ids and not the names of mother and father.
Please help!
The CSV download just gives you the raw database values without first applying each field's represent attribute. If you want the "represented" values of each field, you have two options. First, you can choose the TSV (tab-separated-values) download instead of CSV. Second, you can define a custom export class:
import cStringIO
class CSVExporter(object):
file_ext = "csv"
content_type = "text/csv"
def __init__(self, rows):
self.rows = rows
def export(self):
if self.rows:
s = cStringIO.StringIO()
self.rows.export_to_csv_file(s, represent=True)
return s.getvalue()
else:
return ''
grid = SQLFORM.grid(db.mytable, exportclasses=dict(csv=(CSVExporter, 'CSV')))
The exportclasses argument is a dictionary of custom download types that can be used to override existing types or add new ones. Each item is a tuple including the exporter class and the label to be used for the download link in the UI.
We should probably add this as an option.