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https://github.com/danielhasan1/fastapi-listing
Advanced items listing library that gives you freedom to design complex listing REST APIs that can be read by human.
https://github.com/danielhasan1/fastapi-listing
fastapi json library listing-api python rest-api web
Last synced: 3 months ago
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Advanced items listing library that gives you freedom to design complex listing REST APIs that can be read by human.
- Host: GitHub
- URL: https://github.com/danielhasan1/fastapi-listing
- Owner: danielhasan1
- License: mit
- Created: 2023-03-24T09:47:15.000Z (almost 2 years ago)
- Default Branch: dev
- Last Pushed: 2024-02-08T08:37:54.000Z (11 months ago)
- Last Synced: 2024-09-28T16:41:26.375Z (3 months ago)
- Topics: fastapi, json, library, listing-api, python, rest-api, web
- Language: Python
- Homepage:
- Size: 31.9 MB
- Stars: 38
- Watchers: 2
- Forks: 2
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# fastapi-listing
Advanced items listing library that gives you freedom to design really complex listing APIs using component based architecture.
[](https://github.com/danielhasan1/fastapi-listing/actions/workflows/deploy.yml)
[](https://github.com/danielhasan1/fastapi-listing/actions/workflows/tests.yml) 
[](https://codecov.io/gh/danielhasan1/fastapi-listing) [](https://pepy.tech/project/fastapi-listing)
Comes with:
- pre defined filters
- pre defined paginator
- pre defined sorter
## Advantage
- simplify the intricate process of designing and developing complex listing APIs
- Design components(USP) and plug them from anywhere
- Components can be **reusable**
- Best for fast changing needs
## Installing
Using [pip](https://pip.pypa.io/):
```python
pip install fastapi-listing
```
## Quick Example
Attaching example of it running against the [mysql employee db](https://dev.mysql.com/doc/employee/en/)
There are two ways to implement a listing API using fastapi listing
- inline implementation
- class based implementation
for both we will be needing a dao(data access object) class
### First let's look at inline implementation.
```python
# main.py
from fastapi import FastAPI
from pydantic import BaseModel, Field
from datetime import date
from sqlalchemy import Column, Date, Enum, Integer, String
from sqlalchemy.orm import declarative_base
from sqlalchemy.orm import Session
from fastapi_listing.paginator import ListingPage
from fastapi_listing import FastapiListing, MetaInfo
from fastapi_listing.dao import GenericDao
Base = declarative_base()
app = FastAPI()
class Employee(Base):
__tablename__ = 'employees'
emp_no = Column(Integer, primary_key=True)
birth_date = Column(Date, nullable=False)
first_name = Column(String(14), nullable=False)
last_name = Column(String(16), nullable=False)
gender = Column(Enum('M', 'F'), nullable=False)
hire_date = Column(Date, nullable=False)
# Dao class
class EmployeeDao(GenericDao):
"""write your data layer access logic here. keep it raw!"""
name = "employee"
model = Employee # sqlalchemy model class (support for pymongo/tortoise orm is in progress)
class EmployeeListDetails(BaseModel):
emp_no: int = Field(alias="empid", title="Employee ID")
birth_date: date = Field(alias="bdt", title="Birth Date")
first_name: str = Field(alias="fnm", title="First Name")
last_name: str = Field(alias="lnm", title="Last Name")
gender: str = Field(alias="gdr", title="Gender")
hire_date: date = Field(alias="hdt", title="Hiring Date")
class Config:
orm_mode = True
allow_population_by_field_name = True
@app.get("/employees", response_model=ListingPage[EmployeeListDetails])
def get_employees(db: Session):
dao = EmployeeDao(read_db=db)
# passing pydantic serializer is optional, automatically generates a
# select query based on pydantic class fields for easy cases like columns of same table
# if not passed then provide a select query in dao layer
return FastapiListing(dao=dao, pydantic_serializer=EmployeeListDetails
).get_response(MetaInfo(default_srt_on="emp_no")) # by default sort in desc order
# let's say pydantic class contains compute fields then pass custom_fields=True (by default False)
return FastapiListing(dao=dao,
pydantic_serializer=EmployeeListDetails,
custom_fields=True # here setting custom field True to avoid unknown attributes error
).get_response(MetaInfo(default_srt_on="emp_no"))
```
Voila 🎉 your very first listing response
Auto generated query doesn't fulfil your use case❓️
```python
# Overwriting default read method in dao class
class EmployeeDao(GenericDao):
"""write your data layer access logic here. keep it raw!"""
name = "employee"
model = Employee
def get_default_read(self, fields_to_read: Optional[list]):
"""
Extend and return your query from here.
Use it when use cases are comparatively easier than complex.
Alternatively fastapi-listing provides a robust way to write performance packed queries
for complex APIs which we will look at later.
"""
query = self._read_db.query(Employee)
return query
@app.get("/employees", response_model=ListingPage[EmployeeListDetails])
def get_employees(db: Session):
dao = EmployeeDao(read_db=db)
# note we removed all optional named params here
return FastapiListing(dao=dao).get_response(MetaInfo(default_srt_on="emp_no"))
```
# Adding client site features
Django admin users gonna love filter feature. But before that lets do a little setup which no once can avoid to support a broad spectrum of clients unless you use native query param format which I doubt.
## Add your custom adaptor class for reading filter/sorter/paginator client request params
Below is the default implementation. You will be writing your own adaptor definition
```python
from typing import Literal
from fastapi_listing.service.adapters import CoreListingParamsAdapter
from fastapi_listing import utils
class YourAdapterClass(CoreListingParamsAdapter): # Extend to add your behaviour
"""Utilise this adapter class to make your remote client site:
- filter,
- sorter,
- paginator.
query params adapt to fastapi listing library.
With this you can utilise same listing api to multiple remote client
even if it's a front end server or other backend server.
fastapi listing is always going to request one of the following fundamental key if you want to use it
- sort
- filter
- pagination
supported formats for
filter:
simple filter - [{"field":"", "value":{"search":""}}, ...]
if you are using a range filter -
[{"field":"", "value":{"start":"", "end": ""}}, ...]
if you are using a list filter i.e. search on given items
[{"field":"", "value":{"list":[""]}}, ...]
sort:
[{"field":<"key used in sort mapper>", "type":"asc or "dsc"}, ...]
by default single sort allowed you can change it by extending sort interceptor
pagination:
{"pageSize": , "page": }
"""
def get(self, key: Literal["sort", "filter", "pagination"]):
"""
@param key: Literal["sort", "filter", "pagination"]
@return: List[Optional[dict]] for filter/sort and dict for paginator
"""
return utils.dictify_query_params(self.dependency.get(key))
```
### Once your adaptor class is set
## Adding filter feature
➡️ lets add filters on Employee for:
1. gender - return only **Employees** belonging to 'X' gender where X could be anything.
2. DOB - return **Employees** belonging to a specific range of DOB.
3. First Name - return **Employees** only starting with specific first names.
```python
from fastapi import Request
from sqlalchemy.orm import Session
from fastapi_listing.paginator import ListingPage
from fastapi_listing.filters import generic_filters # collection of inbuilt filters
from fastapi_listing.factory import filter_factory # register filter against a listing
from fastapi_listing import MetaInfo, FastapiListing
emp_filter_mapper = {
"gdr": ("Employee.gender", generic_filters.EqualityFilter),
"bdt": ("Employee.birth_date", generic_filters.MySqlNativeDateFormateRangeFilter),
"fnm": ("Employee.first_name", generic_filters.StringStartsWithFilter),
}
filter_factory.register_filter_mapper(emp_filter_mapper)
@app.get("/employees", response_model=ListingPage[EmployeeListDetails])
def get_employees(request: Request, db: Session):
dao = EmployeeDao(read_db=db)
return FastapiListing(request=request, dao=dao).get_response(
MetaInfo(default_srt_on="emp_no",
filter_mapper=emp_filter_mapper,
feature_params_adapter=YourAdapterClass))
# or you dont wanna pass request?
# extract required data from reqeust and pass it directly
params = request.query_params
filter_, sort_, pagination = params.get("filter"), params.get("sort"), params.get("paginator")
dao = EmployeeDao(read_db=db)
return FastapiListing(dao=dao).get_response(
MetaInfo(default_srt_on="emp_no",
filter_mapper=emp_filter_mapper,
feature_params_adapter=YourAdapterClass,
filter=filter_,
sort=sort_,
paginator=pagination))
```
### Let's break it down
**Filter mapper** - a collection of allowed filters on your listing API. Any request outside of this mapper scope
will not be executed for filtering safeguarding you from creepy API users.
`generic_filters` a collection of inbuilt filters supported by sqlalchemy orm
A dictionary is defined with structure:
`{"alias": tuple("sqlalchemy_model.field", filter_implementation)}`
`alias` - A string used by client in case if you wanna avoid actual column names to client site.
`tuple` - will contain two items field name and filter implementation
```python
from fastapi_listing.filters import generic_filters
emp_filter_mapper = {
"gdr": ("Employee.gender", generic_filters.EqualityFilter),
"bdt": ("Employee.birth_date", generic_filters.MySqlNativeDateFormateRangeFilter),
"fnm": ("Employee.first_name", generic_filters.StringStartsWithFilter),
}
```
Register the above mapper with filter factory.
```python
from fastapi_listing.factory import filter_factory
filter_factory.register_filter_mapper(emp_filter_mapper) # Register in global space or module level.
```
A client could request you like `v1/employees?filter=[{"gdr":"M"}]`
parse the above query_param in your adapter class like `[{"field":"gdr", "value":{"search":"M"}}]` if passed externally as kwarg then access it via `self.extra_context` in your adapter class or if passed request then
access `self.request` directly there.
Assuming everything goes right above will produce a response with items filtered on gender field matching rows with 'M'
**Sort Mapper** - a collection of allowed sort on listing any request outside of this mapper scope will
not be permitted for sort.
Simply define a dictionary with structure `{"alias": "field"}` if sorting on same column them omit model name &
if sorting on a joined table column then add sqlalchemy class name like we did for filter `{"alias":"sqlalchemy_model.field"}`
```python
listing_sort_mapper = {
"code": "emp_no"
}
return FastapiListing(dao=dao).get_response(
MetaInfo(default_srt_on="emp_no",
filter_mapper=emp_filter_mapper,
sort_mapper=listing_sort_mapper,
feature_params_adapter=YourAdapterClass,
filter=filter_,
sort=sort_,
paginator=pagination))
# OR if passing request obj
return FastapiListing(request=request, dao=dao).get_response(
MetaInfo(default_srt_on="emp_no",
filter_mapper=emp_filter_mapper,
sort_mapper=listing_sort_mapper,
feature_params_adapter=YourAdapterClass))
```
A client could request you like `v1/employees?sort={"code":}` or followed by filter `v1/employees?filter=[{"gdr":"M"}]&sort={"code":, "type":"asc"}`
and the response should contain list items sorted by employee code column in ascending order.
**Note** we didn't registered sort mapper like we did for filter mapper.
Similarly, for paginator `v1/employees?pagination={"page":1, "pageSize":10}` or followed by filter and sort `v1/employees?filter=[{"gdr":"M"}]&sort={"code":, "type":"asc"}&pagination={"page":1, "pageSize":10}`
Above will produce listing page of items 10 or dynamically client could change page size.
One thing to **Note** here is fastapi listing by default limits the client to reuqest maximum of 50 items at a time to safeguard your database
if you want to increase/decrease this default limit then simply pass the limit in `MetaInfo`
**You can also change the default page size from 10 to anything you would want**
```python
return FastapiListing(request=request, dao=dao).get_response(
MetaInfo(default_srt_on="emp_no",
filter_mapper=emp_filter_mapper,
sort_mapper=listing_sort_mapper,
max_page_size=25, # here change max page size
default_page_size=10, # here change default page size
feature_params_adapter=YourAdapterClass))
```
### Class Based implementation
Quick Example to convey the context
```python
from fastapi import FastAPI
from sqlalchemy import Column, Date, String, ForeignKey
from sqlalchemy.orm import declarative_base
from sqlalchemy.orm import Session, relationship
from fastapi_listing import ListingService, FastapiListing
from fastapi_listing.filters import generic_filters
from fastapi_listing import loader
from fastapi_listing.paginator import ListingPage
Base = declarative_base()
app = FastAPI()
class Title(Base):
__tablename__ = 'titles'
emp_no = Column(ForeignKey('employees.emp_no', ondelete='CASCADE'), primary_key=True, nullable=False)
title = Column(String(50), primary_key=True, nullable=False)
from_date = Column(Date, primary_key=True, nullable=False)
to_date = Column(Date)
employee = relationship('Employee')
class EmployeeDao(GenericDao):
name = "employee"
model = Employee
class TitleDao(GenericDao):
name = "title"
model = Title
@loader.register()
class EmployeeListingService(ListingService):
"""Class based listing API implementation"""
filter_mapper = {
"gdr": ("Employee.gender", generic_filters.EqualityFilter),
"bdt": ("Employee.birth_date", generic_filters.MySqlNativeDateFormateRangeFilter),
"fnm": ("Employee.first_name", generic_filters.StringStartsWithFilter),
"lnm": ("Employee.last_name", generic_filters.StringEndsWithFilter),
# below feature will require customisation to work at query level
"desg": ("Employee.Title.title", generic_filters.StringLikeFilter, lambda x: getattr(Title, x)) # registering filter with joined table field
}
sort_mapper = {
"cd": "emp_no"
}
default_srt_on = "Employee.emp_no"
default_dao = EmployeeDao
def get_listing(self):
# similar to above inline but instead of passing meta info uncompressed we pass self
# rest is handled implicityly like filter register
# one advantage here is every expect is validated so you get error when running server
resp = FastapiListing(self.request, self.dao, pydantic_serializer=EmployeeListDetails).get_response(self.MetaInfo(self))
return resp
@app.get("/employees", response_model=ListingPage[EmployeeListDetails])
def get_employees(db: Session):
return EmployeeListingService(read_db=db).get_listing()
```
Check out [docs](https://fastapi-listing.readthedocs.io/en/latest/tutorials.html#adding-filters-to-your-listing-api) for supported list of filters.
Additionally, you can create **custom filters** as well.
## Provided features are not meeting your requirements???
The Applications are endless with customisations
➡️ You can write custom:
* Query
* Filter
* Sorter
* Paginator
You can check out customisation section in docs after going through basics and tutorials.
Check out my other [repo](https://github.com/danielhasan1/test-fastapi-listing/blob/master/app/router/router.py) to see some examples
## Features and Readability hand in hand 🤝
- Well defined interface for filter, sorter, paginator
- Support Dependency Injection for easy testing
- Room to adapt the existing remote client query param semantics
- Write standardise listing APIs that will be understood by generations of upcoming developers
- Write listing features which is easy on human mind to extend or understand
- Break down the most complex listing data APIs into digestible piece of code
Why readability and code quality matters in one picture...
# Documentation
View full documentation at: https://fastapi-listing.readthedocs.io (A work in progress)
# Feedback, Questions?
Any form of feedback and questions are welcome! Please create an issue 💭
[here](https://github.com/danielhasan1/fastapi-listing/issues/new).