{"id":18712,"date":"2017-09-20T12:15:06","date_gmt":"2017-09-20T09:15:06","guid":{"rendered":"http:\/\/www.webcodegeeks.com\/?p=18712"},"modified":"2017-09-19T11:46:54","modified_gmt":"2017-09-19T08:46:54","slug":"flask-recipe-restful-crud-using-sqlalchemy","status":"publish","type":"post","link":"https:\/\/www.webcodegeeks.com\/python\/flask-recipe-restful-crud-using-sqlalchemy\/","title":{"rendered":"Flask Recipe \u2013 RESTful CRUD using sqlalchemy"},"content":{"rendered":"

RESTful apps are a thing these days. When your application\u2019s userbase gets quite large and the client could vary from a laptop to an android device to an iOS device, it pays to keep the backend code separate and use the server only for making RESTful calls using HTTP methods that pertain to basic OLTP transactions: SELECT, INSERT, UPDATE and DELETE.<\/span><\/p>\n

Popular third-party apps like\u00a0Firebase<\/a>\u00a0essentially provide you this same thing \u2013 A REST based front to a database that could be accessed online using simple HTTP methods. But in this tutorial, we will learn how to create such a backend ourselves using Python\u2019s\u00a0flask<\/code>framework and\u00a0sqlalchemy<\/code>, a light-weight but powerful ORM library that can access ANY database using its flexible\u00a0sql expression language<\/em>.<\/p>\n

\"\"<\/a><\/p>\n

Rather than using firebase, if you develop your own implementation of your back-end, not only will it help you learn and become a better programmer, but also give you a flexible solution that you can scale and change as per your needs. Its also much cheaper to host your own solution on Amazon EC2 (or Lambda) compared to other costlier alternatives.<\/p>\n

Contrary to popular thinking, its not very difficult to create a database agnostic backend such as the one represented in the above diagram. With a minimal and powerful web framework such as\u00a0flask<\/code>, combined with the power of\u00a0sqlalchemy<\/code>, you can get up and running within minutes. In fact, I\u2019ve developed a prototype version called\u00a0Tiddly<\/a>\u00a0that essentially does the same thing as above using just 172 lines of Python code. You can refer to that github repository for reference as we proceed through this tutorial, or directly start using it. But make sure you install the following dependencies before running it:<\/p>\n

pip install flask\r\npip install sqlalchemy<\/pre>\n
The first step towards creating the app is creating your database models. Once you\u2019ve done the brainstorming and decided what tables and fields you are going to need, you can create a\u00a0models.py<\/code>\u00a0source file with something like this:<\/p>\n
import sqlalchemy\r\nfrom sqlalchemy import create_engine\r\nfrom sqlalchemy import Column, String, Integer\r\nfrom sqlalchemy.orm import sessionmaker\r\nfrom sqlalchemy.ext.declarative import declarative_base\r\n\r\n#TODO: Change as needed:\r\nengine = create_engine(\"sqlite:\/\/\/tiddly.db\", echo=True)\r\nBase = declarative_base()\r\n\r\nSession = sessionmaker(bind=engine)\r\ndbsession = Session()\r\n\r\nclass User(Base):\r\n\t__tablename__ = \"user\"\r\n\tid = Column(Integer, primary_key=True)\r\n\temail = Column(String)\r\n\tpassword = Column(String)\r\n\tname = Column(String)\r\n\tdef repr(self):\r\n\t\treturn \"<User(name=%s, email=%s, )>\" % (name, email)\r\n\t\t\r\nclass Dual(Base):\r\n\t__tablename__ = \"dual\"\r\n\tid = Column(Integer, primary_key=True)\r\n\ttext = Column(String)\r\n\tdef repr(self):\r\n\t\treturn \"<Dual(id=%s, text=%s, )>\" % (id, text)<\/pre>\n
I\u2019m using sqlite database for example here, but you can use any one of your choice. A\u00a0user<\/code>table is a pretty basic one in almost every app as it is used for authentication. Apart from that, I\u2019ve also created a\u00a0dual<\/code>\u00a0table just to play around with.<\/p>\n
After that, create the second file\u00a0app.py<\/code>\u00a0that contains our application code. Define the following import statements along with your models as they will come very handy:<\/p>\n
import flask\r\nfrom flask import request, jsonify, session\r\nimport sqlalchemy\r\nfrom sqlalchemy import inspect, desc\r\nimport json\r\nimport models\r\nfrom models import engine, dbsession<\/pre>\n
Now, the only thing that remains to be done is the plumbing the\u00a0HTTP<\/code>\u00a0methods to their respective database operations. You can either create a separate view function for each one or use a single one for all of them. In this example, I\u2019m using a single function for simplicity.<\/p>\n
@app.route(\"\/<table_name>\", methods=[\"POST\", \"PUT\", \"DELETE\", \"FETCH\"])\r\ndef fetch(table_name):\r\n\tprint(\"verb: %s, tablename: %s\" % (request.method, table_name))\r\n\tif request.method == \"POST\" or request.method == \"PUT\":\r\n\t\tdata = request.get_json(force=True)\r\n\t\tprint(\"data:\", data)\r\n\t\ttry:\r\n\t\t\tTableClass = models.get_class_by_tablename(table_name)\r\n\t\t\tif TableClass == None: raise Exception(\"Table not found: %s\" % table_name)\r\n\t\t\tif request.method == \"POST\": #insert data\r\n\t\t\t\tobject = TableClass(**data)\r\n\t\t\t\tdbsession.add(object)\r\n\t\t\t\tdbsession.commit()\r\n\t\t\telse: #update data\r\n\t\t\t\tobject = dbsession.query(TableClass).filter_by(**{\"id\":id}).first()\r\n\t\t\t\tif object == None: raise Exception(\"No data found.\")\r\n\t\t\t\t#object.update(**data)\r\n\t\t\t\tfor key in data.keys():\r\n\t\t\t\t\tsetattr(object, key, data[key])\r\n\t\t\t\t#dbsession.add(object)\r\n\t\t\t\tdbsession.commit()\r\n\t\t\treturn jsonify({\r\n\t\t\t\t\"status\": \"success\",\r\n\t\t\t\t\"id\": object.id,\r\n\t\t\t\t})\r\n\t\texcept Exception as e:\r\n\t\t\treturn jsonify({\r\n\t\t\t\t\"status\": \"error\",\r\n\t\t\t\t\"error\": str(e),\r\n\t\t\t\t})\r\n\telif request.method == \"DELETE\":\r\n\t\ttry:\r\n\t\t\tTableClass = models.get_class_by_tablename(table_name)\r\n\t\t\tif TableClass == None: raise Exception(\"Table not found: %s\" % table_name)\r\n\t\t\tobject = dbsession.query(TableClass).filter_by(**{\"id\":id}).first()\r\n\t\t\tif object == None: raise Exception(\"No data found.\")\r\n\t\t\tdbsession.delete(object)\r\n\t\t\tdbsession.commit()\r\n\t\t\treturn jsonify({\r\n\t\t\t\t\"status\": \"success\",\r\n\t\t\t\t\"id\": object.id,\r\n\t\t\t\t})\r\n\t\texcept Exception as e:\r\n\t\t\treturn jsonify({\r\n\t\t\t\t\"status\": \"error\",\r\n\t\t\t\t\"error\": str(e),\r\n\t\t\t\t})\r\n\telif request.method == \"FETCH\":\r\n\t\ttry:\r\n\t\t\tdata = request.get_json(force=True)\r\n\t\t\tdata = json.loads(data)\r\n\t\t\tprint(\"data: \", data)\r\n\t\t\tprint(\"data-type: \", type(data))\r\n\t\t\tTableClass = models.get_class_by_tablename(table_name)\r\n\t\t\tif TableClass == None: raise Exception(\"Table not found: %s\" % table_name)\r\n\t\t\t\r\n\t\t\tquery = dbsession.query(TableClass).filter_by(**data['where'])\r\n\t\t\tif 'orderby' in data:\r\n\t\t\t\tfor cname in data['orderby'].split(','):\r\n\t\t\t\t\treverse = False\r\n\t\t\t\t\tif cname.endswith(' desc'):\r\n\t\t\t\t\t\treverse = True\r\n\t\t\t\t\t\tcname = cname[:-5]\r\n\t\t\t\t\telif cname.endswith(' asc'):\r\n\t\t\t\t\t\tcname = cname[:-4]\r\n\t\t\t\t\tprint(\"cname: \", cname)\r\n\t\t\t\t\tcolumn = getattr(TableClass, cname)\r\n\t\t\t\t\tif reverse: column = desc(column)\r\n\t\t\t\t\tquery = query.order_by(column)\r\n\t\t\tif 'limit' in data:\r\n\t\t\t\tquery = query.limit(data['limit'])\r\n\t\t\t\tquery = query.offset(data['offset'])\r\n\t\t\tobject = query.all()\r\n\t\t\tdata = [object_as_dict(t) for t in object]\r\n\t\t\treturn jsonify({\r\n\t\t\t\t\"status\": \"success\", \r\n\t\t\t\t\"data\": data\r\n\t\t\t\t})\r\n\t\texcept Exception as e:\r\n\t\t\treturn jsonify({\r\n\t\t\t\t\"status\": \"error\",\r\n\t\t\t\t\"error\": str(e),\r\n\t\t\t\t})\r\n\telse:\r\n\t\treturn jsonify({\r\n\t\t\t\"status\": \"error\", \"error\": \"Unrecognized verb.\",\r\n\t\t\t})<\/pre>\n
I\u2019ve used a non-standard HTTP method,\u00a0FETCH<\/code>\u00a0for the\u00a0SELECT<\/code>\u00a0action. That\u2019s because if you use the\u00a0GET<\/code>\u00a0method, you aren\u2019t allowed to actually post data (as in actual posting, don\u2019t confuse with\u00a0POST<\/code>\u00a0method) as per the HTTP specification. The other methods, viz\u00a0POST<\/code>,\u00a0PUT<\/code>and\u00a0DELETE<\/code>\u00a0are self-apparent and they stand for\u00a0INSERT<\/code>,\u00a0UPDATE<\/code>\u00a0and\u00a0DELETE<\/code>\u00a0actions respectively.<\/p>\n
As you can see, the app makes good use of the sql expression language of sqlalchemy to dynamically query any kind of data, not only using the usual\u00a0where<\/code>\u00a0clause, but also using ordering and pagination (limit\/offset) parameters:<\/p>\n
if 'orderby' in data:\r\n\tfor cname in data['orderby'].split(','):\r\n\t\treverse = False\r\n\t\tif cname.endswith(' desc'):\r\n\t\t\treverse = True\r\n\t\t\tcname = cname[:-5]\r\n\t\telif cname.endswith(' asc'):\r\n\t\t\tcname = cname[:-4]\r\n\t\tprint(\"cname: \", cname)\r\n\t\tcolumn = getattr(TableClass, cname)\r\n\t\tif reverse: column = desc(column)\r\n\t\tquery = query.order_by(column)\r\nif 'limit' in data:\r\n\tquery = query.limit(data['limit'])\r\n\tquery = query.offset(data['offset'])<\/pre>\n
The front-end sends whatever it needs to the back-end using JSON format and the result is also in JSON. For example, the following JSON when posted to\u00a0\/user<\/code>\u00a0endpoint using\u00a0FETCH<\/code>method, returns the record from user table where\u00a0name<\/code>\u00a0field matches\u00a0admin<\/code>\u00a0and orders the results by email in descending order.<\/p>\n
{\"where\": {\"name\":\"admin\"}, \"orderby\": \"email desc\"}<\/pre>\n
Adding the\u00a0limit<\/code>\u00a0and\u00a0offset<\/code>\u00a0clauses to the same can help the front-end with pagination.<\/p>\n
{\"where\": {\"name\":\"admin\"}, \"orderby\": \"email desc\", \"limit\":2, \"offset\": 2}<\/pre>\n
Its also pretty trivial to implement user authentication with this design. I haven\u2019t done it in this example for simplicity, but you can find it in the\u00a0github code<\/a>.<\/p>\n
All code in this tutorial and on github is\u00a0MIT<\/code>\u00a0licensed and free to use. So, enjoy coding, build your own RESTful CRUD app, and let me know how it goes via comments below!<\/p>\n
\n\n\n\n
Reference: <\/span><\/td>\nFlask Recipe \u2013 RESTful CRUD using sqlalchemy<\/a> from our WCG partner<\/a> Prahlad Yeri at the Prahlad Yeri<\/a> blog.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n","protected":false},"excerpt":{"rendered":"
RESTful apps are a thing these days. When your application\u2019s userbase gets quite large and the client could vary from a laptop to an android device to an iOS device, it pays to keep the backend code separate and use the server only for making RESTful calls using HTTP methods that pertain to basic OLTP …<\/p>\n","protected":false},"author":20,"featured_media":1651,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[53],"tags":[],"class_list":["post-18712","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-python"],"yoast_head":"\nFlask Recipe \u2013 RESTful CRUD using sqlalchemy - Web Code Geeks - 2026<\/title>\n<meta name=\"description\" content=\"RESTful apps are a thing these days. 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