使用 RedisJSON 构建快速、灵活且可搜索的产品目录

Prerequisites:
Python 3.9+
Redis & RedisJSON 2.0
To run:
## if you want to run the container locally
docker run -d -p 6379:6379 redislabs/rejson:preview
pip3 install poetry
poetry install
poetry run python3 redismart_product_catalog.py
Access by navigating to
https://#:5000

[tool.poetry]
name = "redismart_product_catalog"
version = "0.1.0"
description = "Accompanying Code for RedisMart Blog Pt. 2"
authors = []
license = "BSD"

[tool.poetry.dependencies]
python = "^3.9"
redis = "^3.5.3"
rejson = "^0.5.4"
redisearch = {git = "https://github.com/RediSearch/redisearch-py", rev = "master"}
Flask = "^2.0.2"

[tool.poetry.dev-dependencies]

[build-system]
requires = ["poetry-core>=1.0.0"]
build-backend = "poetry.core.masonry.api"

# Copyright 2021 Redis Ltd.
#
# Redistribution and use in source and binary forms, with or without modification, 
# are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, 
# this list of conditions and the following disclaimer.
#
# 2. Redistributions in binary form must reproduce the above copyright notice, 
# this list of conditions and the following disclaimer in the documentation and/or 
# other materials provided with the distribution.
#
# 3. Neither the name of the copyright holder nor the names of its contributors 
# may be used to endorse or promote products derived from this software without 
# specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS 
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, 
# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES 
# (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, 
# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING 
# IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

from json import JSONDecoder, loads

from flask import Flask, request, Response, escape, jsonify
from rejson import Client, Path
from redis import ResponseError
from redisearch.client import IndexType
from redisearch import (Client as SearchClient, 
                        NumericField, 
                        TextField, 
                        TagField, 
                        IndexDefinition, 
                        Suggestion,
                        AutoCompleter,
                        NumericFilter,
                        Query)

class RedisJsonDecoder(JSONDecoder):
    def decode(self, s, *args, **kwargs):
        if isinstance(s, bytes):
            s = s.decode('UTF-8')
        elif isinstance(s, list):
            return s[0]
        return super(RedisJsonDecoder, self).decode(s, *args, **kwargs)

R = Client(decode_responses=True,
           encoding_errors='ignore',
           decoder=RedisJsonDecoder())

assert R.ping()

app = Flask(__name__)

                                    #########
                                    ## API ##
                                    #########

ALLOWED_FIELDS = ['SKU', 'name', 'categories', 'short_description', 'long_description', 'price', 'rating']

@app.route('/')
def get_search():
    '''
    Search the product catalog
    URL Args:
    name - name of the product 
    categories - comma delimited category list (category1,category2)
    price - price range, hyphen delimited (price_low-price_high)
    rating - rating range, hyphen delmited (rating_low-rating_high)
    fields - object fields to return in response
    paging - tuple of item range to show in this page (beginning, end)
    sort_by - field to sort by
    ascending - ascending or descending
    '''
    return jsonify(search_products(**request.args))    

@app.route('/suggestions/<string:stem>')
def get_suggestions(stem):
    '''
    Get autocomplete suggestions for a given stem
    '''
    return jsonify(get_suggestions(escape(stem)))

@app.route('/product', methods=['POST'])
def post_product():
    '''
    HTTP POST request to create/update a product
    '''
    product = {}
    for k, v in request.form.items():
        if k not in ALLOWED_FIELDS:
            return f'{k} not allowed in product POST request', 403
        product[k] = v

    key = PRODUCTS_KEY.format(product['SKU'])
    R.jsonset(key, Path.rootPath(), product)
    return Response(status=200)

@app.route('/product/<string:sku>')
def get_product(sku):
    '''
    Get the JSON object for a product from its SKU
    '''
    key = PRODUCTS_KEY.format(sku)
    return jsonify(R.jsonget(key))

@app.route('/product/<string:sku>', methods=['DELETE'])
def delete_product(sku):
    '''
    Remove a product from the catalog
    '''
    key = PRODUCTS_KEY.format(sku)
    key_deleted = R.delete(key)
    if key_deleted:
        return Response(status=200)
    else:
        return Response(status=404)

                                    ########
                                    ## DB ##
                                    ########

PRODUCTS_KEY = 'prod:{}'
PRODUCTS_INDEX_KEY = 'idx:prod'
AUTOCOMPLETE_KEY = 'ac:prods&cats'

SAMPLE_DATA = [{'SKU': '43214563',
 'categories': 'electronics,headphones',
 'long_description': 'Monocle ipsum dolor sit amet k-pop smart bespoke, alluring wardrobe espresso Zürich charming Nordic ANA destination elegant bureaux handsome Melbourne. ',
 'name': 'Craniumcandy - Wireless Over-the-Ear Headphones - Crazy Tropical',
 'price': 100,
 'rating': 1,
 'short_description': 'Toto, K-pop sharp the highest quality sleepy boutique joy.'},
 {'SKU': '431553432',
 'name': 'Doodle - Sprite Buds True Wireless In-Ear Headphones - Night Black',
 'short_description': 'Beams the highest quality remarkable Swiss concierge. Cosy signature the best extraordinary.',
 'long_description': 'Discerning airport first-class, elegant conversation artisanal Beams flat white ryokan Helsinki Boeing 787 K-pop concierge soft power iconic. Toto Melbourne pintxos, joy destination global craftsmanship St Moritz smart premium boutique. Boeing 787 premium first-class extraordinary the best Zürich discerning elegant. Charming impeccable emerging sophisticated international Airbus A380 efficient Beams cosy Marylebone Muji Asia-Pacific. Charming uniforms Beams airport, essential Zürich global Nordic extraordinary Boeing 787 iconic vibrant.',
 'price': 180,
 'rating': 5,
 'categories': 'electronics,headphones'},
  {'SKU': '8743153432',
 'name': 'Doodle - Sprite 6 Expert',
 'short_description': 'Beams the highest quality remarkable Swiss concierge. Cosy signature the best extraordinary.',
 'long_description': 'Discerning airport first-class, elegant conversation artisanal Beams flat white ryokan Helsinki Boeing 787 K-pop concierge soft power iconic. Toto Melbourne pintxos, joy destination global craftsmanship St Moritz smart premium boutique. Boeing 787 premium first-class extraordinary the best Zürich discerning elegant. Charming impeccable emerging sophisticated international Airbus A380 efficient Beams cosy Marylebone Muji Asia-Pacific. Charming uniforms Beams airport, essential Zürich global Nordic extraordinary Boeing 787 iconic vibrant.',
 'price': 899,
 'rating': 5,
 'categories': 'cell phone,electronics'},
 {'SKU': '4316647899',
 'name': 'Blues Banjo Songs for Noobs - Gal Nimoy',
 'short_description': 'The best Boeing 787 Lufthansa Toto. Destination Singapore efficient Nordic craftsmanship.',
 'long_description': 'Wardrobe Fast Lane exclusive perfect delightful extraordinary Melbourne K-pop classic Airbus A380 elegant the highest quality. Emerging boutique concierge quality of life finest, punctual elegant delightful pintxos airport tote bag Muji flat white Swiss.',
 'price': 23,
 'rating': 3,
 'categories': 'books,music'},
  {'SKU': '84836424542',
 'name': 'Be Here Now - Richard Alpert',
 'short_description': 'The best Boeing 787 Lufthansa Toto. Destination Singapore efficient Nordic craftsmanship.',
 'long_description': 'Wardrobe Fast Lane exclusive perfect delightful extraordinary Melbourne K-pop classic Airbus A380 elegant the highest quality. Emerging boutique concierge quality of life finest, punctual elegant delightful pintxos airport tote bag Muji flat white Swiss.',
 'price': 42,
 'rating': 3,
 'categories': 'books'}]

def get_suggestions(stem):
    '''
    Get a list of auto complete suggestions from a given stem
    '''
    ac = AutoCompleter(AUTOCOMPLETE_KEY, conn=R)
    return [str(sugg) for sugg in ac.get_suggestions(stem)]

def search_products(name=None, categories=None, price=None, rating=None, fields=None,
                     paging=None, sort_by='name', ascending=True, **kwargs):
    '''
    Search the product catalog
    name - name of the product 
    categories - comma delimited category list (category1,category2)
    price - price range, hyphen delimited (price_low-price_high)
    rating - rating range, hyphen delmited (rating_low-rating_high)
    fields - object fields to return in response
    paging - comma delimited, show item range in this page (paging_start,paging_end)
    sort_by - field to sort by
    ascending - ascending or descending
    '''
    ## for non-numeric search terms, we'll build the term query
    search_terms = []
    if name:
        search_terms.append(f'@name:{name}')
    if categories:
        _categories = categories.split(',')
        search_terms.append(f'@categories:{{{"|".join(_categories)}}}') ## tag search uses {} vs () for compounds

    if search_terms:
        ## join the non-numeric terms together to create the query object
        terms_query = ' '.join(search_terms)
    else:
        ## no non-numeric ones were set, wildcard
        terms_query = '*'

    ## create and configure query object
    query = Query(terms_query)
    query.sort_by(sort_by, asc=ascending)
    if paging is not None:
        query.paging(*paging.split(','))
    if fields is not None:
        query.return_fields(*fields.split(','))

    ## numeric terms and other query parameters
    if price:
        price_low, price_high = price.split('-')
        query.add_filter(NumericFilter('price', price_low, price_high))
    if rating:
        rating_low, rating_high = rating.split('-')
        query.add_filter(NumericFilter('rating', rating_low, rating_high))

    ## execute search
    result = product_index().search(query)
    return [loads(doc.json) for doc in result.docs] # in order to get these all into one json obj, we'll need to transerialze them

def product_index():
    '''
    Get or Create the product search index
    '''
    ## check to see if the client exists, otherwise create it
    client = SearchClient(PRODUCTS_INDEX_KEY, conn=R)
    try:
        client.info()
        return client
    except ResponseError:
        print("index doesn't exist, creating")

    ## Index Defn Base
    definition = IndexDefinition(prefix=[PRODUCTS_KEY.format('')], index_type=IndexType.JSON)

    ## Categories implemented as Tags - allows for more complex searching
    ctg_field = TagField('$.categories', as_name='categories')
    ctg_field_params = list(ctg_field.args)
    ctg_field.args = tuple(ctg_field_params)

    ## actually create the index
    client.create_index((
        TagField("$.SKU", as_name='SKU'),
        TextField("$.name", as_name='name'),
        TextField("$.short_description", as_name='short_description'),
        TextField("$.long_description", as_name='long_description'),
        NumericField("$.price", sortable=True, as_name='price'),
        NumericField("$.rating", sortable=True, as_name='rating'),
        ctg_field),
        definition=definition)

    return client

def add_products():
    '''
    Ingests the sample data into the DB
    '''
    with R.pipeline(transaction=False) as pipeline:
        for product in SAMPLE_DATA:
            key = PRODUCTS_KEY.format(product['SKU'])
            pipeline.jsonset(key, Path.rootPath(), product)
            
            ac = AutoCompleter(AUTOCOMPLETE_KEY, conn=pipeline)
            categories = product['categories'].split(',')
            suggestions = [Suggestion(product['name'])]
            suggestions.extend([Suggestion(category) for category in categories])
            ac.add_suggestions(*suggestions)

        pipeline.execute()

if __name__ == '__main__':
    product_index()
    add_products()
    app.run(debug=True)