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📝 Add docs for integrating with NoSQL
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**FastAPI** can also be integrated with any <abbr title="Distributed database (Big Data), also 'Not Only SQL'">NoSQL</abbr>.
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Here we'll see an example using **<a href="https://www.couchbase.com/" target="_blank">Couchbase</a>**, a <abbr title="Document here refers to a JSON object (a dict), with keys and values, and those values can also be other JSON objects, arrays (lists), numbers, strings, booleans, etc.">document</abbr> based NoSQL database.
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You can adapt it to any other NoSQL database like:
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* **MongoDB**
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* **Cassandra**
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* **CouchDB**
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* **ArangoDB**
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* **ElasticSearch**, etc.
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## Import Couchbase components
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For now, don't pay attention to the rest, only the imports:
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```Python hl_lines="6 7 8"
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{!./tutorial/src/nosql-databases/tutorial001.py!}
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```
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## Define a constant to use as a "document type"
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We will use it later as a fixed field `type` in our documents.
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This is not required by Couchbase, but is a good practice that will help you afterwards.
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```Python hl_lines="10"
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{!./tutorial/src/nosql-databases/tutorial001.py!}
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```
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## Add a function to get a `Bucket`
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In **Couchbase**, a bucket is a set of documents, that can be of different types.
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They are generally all related to the same application.
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The analogy in the relational database world would be a "database" (a specific database, not the database server).
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The analogy in **MongoDB** would be a "collection".
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In the code, a `Bucket` represents the main entrypoint of communication with the database.
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This utility function will:
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* Connect to a **Couchbase** cluster (that might be a single machine).
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* Authenticate in the cluster.
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* Get a `Bucket` instance.
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* Return it.
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```Python hl_lines="13 14 15 16 17 18"
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{!./tutorial/src/nosql-databases/tutorial001.py!}
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```
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## Create Pydantic models
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As **Couchbase** "documents" are actually just "JSON objects", we can model them with Pydantic.
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### `User` model
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First, let's create a `User` model:
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```Python hl_lines="21 22 23 24 25"
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{!./tutorial/src/nosql-databases/tutorial001.py!}
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```
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We will use this model in our path operation function, so, we don't include in it the `hashed_password`.
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### `UserInDB` model
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Now, let's create a `UserInDB` model.
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This will have the data that is actually stored in the database.
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In Couchbase, each document has a document <abbr title="Identification">ID</abbr> or "key".
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But it is not part of the document itself.
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It is stored as "metadata" of the document.
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So, to be able to have that document ID as part of our model without it being part of the attributes (document contents), we can do a simple trick.
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We can create an internal `class`, in this case named `Meta`, and declare the extra attribute(s) in that class.
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This class doesn't have any special meaning and doesn't provide any special functionality other than not being directly an attribute of our main model:
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```Python hl_lines="28 29 30 31 32 33"
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{!./tutorial/src/nosql-databases/tutorial001.py!}
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```
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This `Meta` class won't be included when we generate a `dict` from our model, but we will be able to access it's data with something like:
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```Python
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my_user.Meta.key
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```
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!!! note
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Notice that we have a `hashed_password` and a `type` field that will be stored in the database.
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But it is not part of the general `User` model (the one we will return in the path operation).
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## Get the user
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Now create a function that will:
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* Take a username.
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* Generate a document ID from it.
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* Get the document with that ID.
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* Put the contents of the document in a `UserInDB` model.
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* Add the extracted document `key` to our model.
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By creating a function that is only dedicated to getting your user from a `username` (or any other parameter) independent of your path operation function, you can more easily re-use it in multiple parts and also add <abbr title="Automated test, written in code, that checks if another piece of code is working correctly.">unit tests</abbr> for it:
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```Python hl_lines="36 37 38 39 40 41 42 43"
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{!./tutorial/src/nosql-databases/tutorial001.py!}
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```
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### f-strings
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If you are not familiar with the `f"userprofile::{username}"`, it is a Python "<a href="https://docs.python.org/3/glossary.html#term-f-string" target="_blank">f-string</a>".
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Any variable that is put inside of `{}` in an f-string will be expanded / injected in the string.
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### `dict` unpacking
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If you are not familiar with the `UserInDB(**result.value)`, <a href="https://docs.python.org/3/glossary.html#term-argument" target="_blank">it is using `dict` "unpacking"</a>.
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It will take the `dict` at `result.value`, and take each of its keys and values and pass them as key-values to `UserInDB` as keyword arguments.
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So, if the `dict` contains:
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```Python
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{
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"username": "johndoe",
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"hashed_password": "some_hash",
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}
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```
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It will be passed to `UserInDB` as:
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```Python
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UserInDB(username="johndoe", hashed_password="some_hash")
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```
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## Create your **FastAPI** code
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### Create the `FastAPI` app
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```Python hl_lines="47"
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{!./tutorial/src/nosql-databases/tutorial001.py!}
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```
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### Create the path operation function
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As our code is calling Couchbase and we are not using the <a href="https://docs.couchbase.com/python-sdk/2.5/async-programming.html#asyncio-python-3-5" target="_blank">experimental Python <code>await</code> support</a>, we should declare our function with normal `def` instead of `async def`.
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Also, Couchbase recommends not using a single `Bucket` object in multiple "<abbr title="A sequence of code being executed by the program, while at the same time, or at intervals, there can be others being executed too.">thread</abbr>s", so, we can get just get the bucket directly and pass it to our utility functions:
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```Python hl_lines="50 51 52 53 54"
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{!./tutorial/src/nosql-databases/tutorial001.py!}
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```
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## Recap
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You can integrate any third party NoSQL database, just using their standard packages.
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The same applies to any other external tool, system or API.
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from typing import Optional
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from fastapi import FastAPI
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from pydantic import BaseModel
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from couchbase import LOCKMODE_WAIT
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from couchbase.bucket import Bucket
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from couchbase.cluster import Cluster, PasswordAuthenticator
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USERPROFILE_DOC_TYPE = "userprofile"
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def get_bucket():
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cluster = Cluster("couchbase://couchbasehost:8091")
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authenticator = PasswordAuthenticator("username", "password")
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cluster.authenticate(authenticator)
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bucket: Bucket = cluster.open_bucket("bucket_name", lockmode=LOCKMODE_WAIT)
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return bucket
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class User(BaseModel):
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username: str
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email: Optional[str] = None
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full_name: Optional[str] = None
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disabled: Optional[bool] = None
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class UserInDB(User):
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type: str = USERPROFILE_DOC_TYPE
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hashed_password: str
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class Meta:
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key: Optional[str] = None
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def get_user(bucket: Bucket, username: str):
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doc_id = f"userprofile::{username}"
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result = bucket.get(doc_id, quiet=True)
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if not result.value:
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return None
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user = UserInDB(**result.value)
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user.Meta.key = result.key
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return user
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# FastAPI specific code
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app = FastAPI()
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@app.get("/users/{username}", response_model=User)
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def read_user(username: str):
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bucket = get_bucket()
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user = get_user(bucket=bucket, username=username)
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return user
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@ -12,6 +12,7 @@ db_session = scoped_session(
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sessionmaker(autocommit=False, autoflush=False, bind=engine)
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)
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class CustomBase:
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# Generate __tablename__ automatically
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@declared_attr
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@ -42,6 +42,7 @@ nav:
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- First Steps: 'tutorial/dependencies/first-steps.md'
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- Second Steps: 'tutorial/dependencies/second-steps.md'
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- SQL (Relational) Databases: 'tutorial/sql-databases.md'
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- NoSQL (Distributed / Big Data) Databases: 'tutorial/nosql-databases.md'
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- Concurrency and async / await: 'async.md'
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- Deployment: 'deployment.md'
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