Update Getting Started guide, note WIP docs

README.md

@@ -18,19 +18,20 @@
 <details>
   <summary><strong>Table of contents</strong></summary>
 
-<!-- START doctoc generated TOC please keep comment here to allow auto update -->
+span
+
 <!-- DON'T EDIT THIS SECTION, INSTEAD RE-RUN doctoc TO UPDATE -->
 
-  - [💡 Why Redis OM?](#-why-redis-om)
-  - [📇 Modeling Your Data](#-modeling-your-data)
-  - [✓ Validating Data With Your Model](#-validating-data-with-your-model)
-  - [🔎 Rich Queries and Embedded Models](#-rich-queries-and-embedded-models)
-  - [💻 Installation](#-installation)
-  - [📚 Documentation](#-documentation)
-  - [⛏️ Troubleshooting](#-troubleshooting)
-  - [✨ So, How Do You Get RediSearch and RedisJSON?](#-so-how-do-you-get-redisearch-and-redisjson)
-  - [❤️ Contributing](#-contributing)
-  - [📝 License](#-license)
+- [💡 Why Redis OM?](#-why-redis-om)
+- [📇 Modeling Your Data](#-modeling-your-data)
+- [✓ Validating Data With Your Model](#-validating-data-with-your-model)
+- [🔎 Rich Queries and Embedded Models](#-rich-queries-and-embedded-models)
+- [💻 Installation](#-installation)
+- [📚 Documentation](#-documentation)
+- [⛏️ Troubleshooting](#-troubleshooting)
+- [✨ So, How Do You Get RediSearch and RedisJSON?](#-so-how-do-you-get-redisearch-and-redisjson)
+- [❤️ Contributing](#-contributing)
+- [📝 License](#-license)
 
 <!-- END doctoc generated TOC please keep comment here to allow auto update -->
 
@@ -58,9 +59,7 @@ from typing import Optional
 
 from pydantic import EmailStr
 
-from redis_om.model import (
-    HashModel,
-)
+from redis_om.model import HashModel
 
 
 class Customer(HashModel):
@@ -74,9 +73,25 @@ class Customer(HashModel):
 
 Now that we have a `Customer` model, let's use it to save customer data to Redis.
 
-First, we create a new `Customer` object:
-
 ```python
+import datetime
+from typing import Optional
+
+from pydantic import EmailStr
+
+from redis_om.model import HashModel
+
+
+class Customer(HashModel):
+    first_name: str
+    last_name: str
+    email: EmailStr
+    join_date: datetime.date
+    age: int
+    bio: Optional[str]
+
+
+# First, we create a new `Customer` object:
 andrew = Customer(
     first_name="Andrew",
     last_name="Brookins",
@@ -85,24 +100,17 @@ andrew = Customer(
     age=38,
     bio="Python developer, works at Redis, Inc."
 )
-```
-The model generates a globally unique primary key automatically without needing to talk to Redis.
 
-```python
+# The model generates a globally unique primary key automatically
+# without needing to talk to Redis.
 print(andrew.pk)
-'01FJM6PH661HCNNRC884H6K30C'
-```
+#> '01FJM6PH661HCNNRC884H6K30C'
 
-We can save the model to Redis by calling `save()`:
-
-```python
+# We can save the model to Redis by calling `save()`:
 andrew.save()
-```
 
-To retrieve this customer with its primary key, we use `Customer.get()`:
-
-```python
-other_andrew = Customer.get('01FJM6PH661HCNNRC884H6K30C')
+# To retrieve this customer with its primary key, we use `Customer.get()`:
+assert Customer.get(andrew.pk) == andrew
 ```
 
 **Ready to learn more?** Check out the [getting started](docs/getting_started.md) guide.
@@ -118,30 +126,45 @@ This validation ensures that fields like `first_name`, which the `Customer` mode
 For example, because we used the `EmailStr` type for the `email` field, we'll get a validation error if we try to create a `Customer` with an invalid email address:
 
 ```python
-Customer(
+import datetime
+from typing import Optional
+
+from pydantic import EmailStr, ValidationError
+
+from redis_om.model import HashModel
+
+
+class Customer(HashModel):
+    first_name: str
+    last_name: str
+    email: EmailStr
+    join_date: datetime.date
+    age: int
+    bio: Optional[str]
+
+
+try:
+    Customer(
         first_name="Andrew",
         last_name="Brookins",
         email="Not an email address!",
         join_date=datetime.date.today(),
         age=38,
         bio="Python developer, works at Redis, Inc."
-)
-```
-
-This code generates the following validation error:
-
-```
- Traceback:
+    )
+except ValidationError as e:
+    print(e)
+    """
     pydantic.error_wrappers.ValidationError: 1 validation error for Customer
      email
        value is not a valid email address (type=value_error.email)
+    """
 ```
 
 **Any existing Pydantic validator should work** as a drop-in type annotation with a Redis OM model. You can also write arbitrarily complex custom validations!
 
 To learn more, see the [documentation on data validation](docs/validation.md).
 
-
 ## 🔎 Rich Queries and Embedded Models
 
 Data modeling, validation, and saving models to Redis all work regardless of how you run Redis.
@@ -157,6 +180,18 @@ Redis OM comes with a rich query language that allows you to query Redis with Py
 To show how this works, we'll make a small change to the `Customer` model we defined earlier. We'll add `Field(index=True)` to tell Redis OM that we want to index the `last_name` and `age` fields:
 
 ```python
+import datetime
+from typing import Optional
+
+from pydantic import EmailStr
+
+from redis_om.model import (
+    Field,
+    HashModel,
+    Migrator
+)
+
+
 class Customer(HashModel):
     first_name: str
     last_name: str = Field(index=True)
@@ -164,11 +199,16 @@ class Customer(HashModel):
     join_date: datetime.date
     age: int = Field(index=True)
     bio: Optional[str]
-```
     
-Now, if we use this model with a Redis deployment that has the [RediSearch module][redisearch-url] installed, we can run queries like the following:
     
-```python
+# Now, if we use this model with a Redis deployment that has the
+# RediSearch module installed, we can run queries like the following.
+
+# Before running queries, we need to run migrations to set up the
+# indexes that Redis OM will use. You can also use the `migrate`
+# CLI tool for this!
+Migrator().run()
+
 # Find all customers with the last name "Brookins"
 Customer.find(Customer.last_name == "Brookins").all()
 
@@ -202,6 +242,7 @@ from redis_om.model import (
     EmbeddedJsonModel,
     JsonModel,
     Field,
+    Migrator
 )
 
 class Address(EmbeddedJsonModel):
@@ -224,11 +265,15 @@ class Customer(JsonModel):
 
     # Creates an embedded model.
     address: Address
-```
 
-With these two models and a Redis deployment with the RedisJSON module installed, we can run queries like the following:
+# With these two models and a Redis deployment with the RedisJSON 
+# module installed, we can run queries like the following.
+
+# Before running queries, we need to run migrations to set up the
+# indexes that Redis OM will use. You can also use the `migrate`
+# CLI tool for this!
+Migrator().run()
 
-```python
 # Find all customers who live in San Antonio, TX
 Customer.find(Customer.address.city == "San Antonio",
               Customer.address.state == "TX")
@@ -287,7 +332,6 @@ Redis OM uses the [BSD 3-Clause license][license-url].
 [ci-url]: https://github.com/redis-developer/redis-om-python/actions/workflows/ci.yml
 [license-image]: http://img.shields.io/badge/license-BSD_3--Clause-green.svg?style=flat-square
 [license-url]: LICENSE
-
 <!-- Links -->
 
 [redis-om-website]: https://developer.redis.com
@@ -299,4 +343,3 @@ Redis OM uses the [BSD 3-Clause license][license-url].
 [pydantic-url]: https://github.com/samuelcolvin/pydantic
 [ulid-url]: https://github.com/ulid/spec
 [redis-enterprise-url]: https://redis.com/try-free/
-

docs/connections.md

@@ -0,0 +1,3 @@
+# Managing Connections
+
+WIP!

docs/embedded_models.md

@@ -1,5 +1,7 @@
 # Embedded Models
 
+**NOTE:** This documentation is a stub, using the same embedded JSON model example as the README.
+
 Redis OM can store and query **nested models** like any document database, with the speed and power you get from Redis. Let's see how this works.
 
 In the next example, we'll define a new `Address` model and embed it within the `Customer` model.
@@ -12,6 +14,7 @@ from redis_om.model import (
     EmbeddedJsonModel,
     JsonModel,
     Field,
+    Migrator
 )
 
 class Address(EmbeddedJsonModel):
@@ -34,11 +37,15 @@ class Customer(JsonModel):
 
     # Creates an embedded model.
     address: Address
-```
 
-With these two models and a Redis deployment with the RedisJSON module installed, we can run queries like the following:
+# With these two models and a Redis deployment with the RedisJSON 
+# module installed, we can run queries like the following.
+
+# Before running queries, we need to run migrations to set up the
+# indexes that Redis OM will use. You can also use the `migrate`
+# CLI tool for this!
+Migrator().run()
 
-```python
 # Find all customers who live in San Antonio, TX
 Customer.find(Customer.address.city == "San Antonio",
               Customer.address.state == "TX")

docs/faq.md

@@ -0,0 +1,3 @@
+# Frequently Asked Questions (FAQ)
+
+WIP!

docs/getting_started.md

@@ -135,11 +135,8 @@ In this tutorial, we'll create a `Customer` model that validates and saves data.
 
 ```python
 import datetime
-from typing import Optional
 
-from redis_om.model import (
-    HashModel,
-)
+from redis_om.model import HashModel
 
 
 class Customer(HashModel):
@@ -183,6 +180,20 @@ If you want to model fields with a list, set, or mapping type, or another model,
 Let's see what creating a model object looks like:
 
 ```python
+import datetime
+
+from redis_om.model import HashModel
+
+
+class Customer(HashModel):
+    first_name: str
+    last_name: str
+    email: str
+    join_date: datetime.date
+    age: int
+    bio: str
+    
+    
 andrew = Customer(
     first_name="Andrew",
     last_name="Brookins",
@@ -198,41 +209,88 @@ andrew = Customer(
 What would happen if we left out one of these fields, like `bio`?
 
 ```python
-Customer(
-    first_name="Andrew",
-    last_name="Brookins",
-    email="andrew.brookins@example.com",
-    join_date=datetime.date.today(),
-    age=38)
-```
+import datetime
 
-All fields are required because none of the fields are marked `Optional`, so we get a validation error:
+from redis_om.model import HashModel
+from pydantic import ValidationError
 
-```
-ValidationError: 1 validation error for Customer
-bio
-  field required (type=value_error.missing)
-```
 
-If we want the `bio` field to be optional, we need to change the type annotation:
-
-```python
 class Customer(HashModel):
     first_name: str
     last_name: str
     email: str
     join_date: datetime.date
     age: int
-    bio: Optional[str]
+    bio: str
+ 
+# All fields are required because none of the fields
+# are marked `Optional`, so we get a validation error:
+try:    
+    Customer(
+        first_name="Andrew",
+        last_name="Brookins",
+        email="andrew.brookins@example.com",
+        join_date=datetime.date.today(),
+        age=38   # <- We didn't pass in a bio!
+    )
+except ValidationError as e:
+    print(e)
+    """
+    ValidationError: 1 validation error for Customer
+    bio
+      field required (type=value_error.missing)
+    """
+```
+
+If we want the `bio` field to be optional, we need to change the type annotation to use `Optional`.
+
+```python
+import datetime
+from typing import Optional
+
+from redis_om.model import HashModel
+
+
+class Customer(HashModel):
+    first_name: str
+    last_name: str
+    email: str
+    join_date: datetime.date
+    age: int
+    bio: Optional[str]  # <- Now, bio is an Optional[str]
 ```
 
 Now we can create `Customer` objects with or without the `bio` field.
 
 ### Default Values
 
-Fields can have default values.
+Fields can have default values. You set them by assigning a value to a field.
 
 ```python
+import datetime
+from typing import Optional
+
+from redis_om.model import HashModel
+
+
+class Customer(HashModel):
+    first_name: str
+    last_name: str
+    email: str
+    join_date: datetime.date
+    age: int
+    bio: Optional[str] = "Super dope"  # <- We added a default here
+```
+
+Now, if we create a `Customer` object without a `bio` field, it will use the default value.
+
+```python
+import datetime
+from typing import Optional
+
+from redis_om.model import HashModel
+
+
 class Customer(HashModel):
     first_name: str
     last_name: str
@@ -240,20 +298,17 @@ class Customer(HashModel):
     join_date: datetime.date
     age: int
     bio: Optional[str] = "Super dope"
-```
 
-Now, if we create a `Customer` object without a `bio` field, it will use the default value.
     
-```python
 andrew = Customer(
     first_name="Andrew",
     last_name="Brookins",
     email="andrew.brookins@example.com",
     join_date=datetime.date.today(),
-    age=38)
+    age=38)  # <- Notice, we didn't give a bio!
 
-print(andrew.bio)
-'Super Dope'
+print(andrew.bio)  # <- So we got the default value.
+#> 'Super Dope'
 ```
 
 The model will then save this default value to Redis the next time you call `save()`.
@@ -263,29 +318,383 @@ The model will then save this default value to Redis the next time you call `sav
 Models generate a globally unique primary key automatically without needing to talk to Redis.
 
 ```python
+import datetime
+from typing import Optional
+
+from redis_om.model import HashModel
+
+
+class Customer(HashModel):
+    first_name: str
+    last_name: str
+    email: str
+    join_date: datetime.date
+    age: int
+    bio: Optional[str] = "Super dope"
+
+    
+andrew = Customer(
+    first_name="Andrew",
+    last_name="Brookins",
+    email="andrew.brookins@example.com",
+    join_date=datetime.date.today(),
+    age=38)
+
 print(andrew.pk)
-'01FJM6PH661HCNNRC884H6K30C'
+#> '01FJM6PH661HCNNRC884H6K30C'
 ```
 
 The ID is available *before* you save the model.
 
 The default ID generation function creates [ULIDs](https://github.com/ulid/spec), though you can change the function that generates the primary key for models if you'd like to use a different kind of primary key.
 
+## Validating Data
+
+Redis OM uses [Pydantic][pydantic-url] to validate data based on the type annotations you assign to fields in a model class.
+
+This validation ensures that fields like `first_name`, which the `Customer` model marked as a `str`, are always strings. **But every Redis OM model is also a Pydantic model**, so you can use Pydantic validators like `EmailStr`, `Pattern`, and many more for complex validations!
+
+For example, we defined the `join_date` for our `Customer` model earlier as a `datetime.date`. So, if we try to create a model with a `join_date` that isn't a date, we'll get a validation error.
+
+Let's try it now:
+
+```python
+import datetime
+from typing import Optional
+
+from redis_om.model import HashModel
+from pydantic import ValidationError
+
+
+class Customer(HashModel):
+    first_name: str
+    last_name: str
+    email: str
+    join_date: datetime.date
+    age: int
+    bio: Optional[str] = "Super dope"
+
+
+try:
+    Customer(
+        first_name="Andrew",
+        last_name="Brookins",
+        email="a@example.com",
+        join_date="not a date!",  # <- The problem line!
+        age=38
+    )
+except ValidationError as e:
+    print(e)
+    """
+    pydantic.error_wrappers.ValidationError: 1 validation error for Customer
+    join_date
+      invalid date format (type=value_error.date)
+    """
+```
+
+### Models Coerce Values By Default
+
+You might wonder what qualifies as a "date" in our last validation example. By default, Redis OM will try to coerce input values to the correct type. That means we can pass a date string for `join_date` instead of a `date` object:
+
+```python
+import datetime
+from typing import Optional
+
+from redis_om.model import HashModel
+
+
+class Customer(HashModel):
+    first_name: str
+    last_name: str
+    email: str
+    join_date: datetime.date
+    age: int
+
+
+andrew = Customer(
+    first_name="Andrew",
+    last_name="Brookins",
+    email="a@example.com",
+    join_date="2020-01-02",  # <- We're passing a YYYY-MM-DD date string now
+    age=38
+)
+
+print(andrew.join_date)
+#> 2021-11-02
+type(andrew.join_date)
+#> datetime.date  # The model parsed the string automatically!
+```
+
+This ability to combine parsing (in this case, a YYYY-MM-DD date string) with validation can save you a lot of work.
+
+However, you can turn off coercion -- check the next section on using strict validation.
+
+### Strict Validation
+
+You can turn on strict validation to reject values for a field unless they match the exact type of the model's type annotations.
+
+You do this by changing a field's type annotation to use one of the ["strict" types provided by Pydantic](https://pydantic-docs.helpmanual.io/usage/types/#strict-types).
+
+Redis OM supports all of Pydantic's strict types: `StrictStr`, `StrictBytes`, `StrictInt`, `StrictFloat`, and `StrictBool`.
+
+If we wanted to make sure that the `age` field only accepts integers and doesn't try to parse a string containing an integer, like "1", we'd use the `StrictInt` class.
+
+```python
+import datetime
+from typing import Optional
+
+from pydantic import StrictInt, ValidationError
+from redis_om.model import HashModel
+
+
+class Customer(HashModel):
+    first_name: str
+    last_name: str
+    email: str
+    join_date: datetime.date
+    age: StrictInt  # <- Instead of int, we use StrictInt
+    bio: Optional[str]
+
+# Now if we use a string instead of an integer for `age`,
+# we get a validation error:
+try:
+    Customer(
+        first_name="Andrew",
+        last_name="Brookins",
+        email="a@example.com",
+        join_date="2020-01-02",  # <- A date as a string shouldn't work now!
+        age="38"
+    )
+except ValidationError as e:
+    print(e)
+    """
+    pydantic.error_wrappers.ValidationError: 1 validation error for Customer
+    join_date
+      Value must be a datetime.date object (type=value_error)
+    """
+```
+
+Pydantic doesn't include a `StrictDate` class, but we can create our own. In this example, we create a `StrictDate` type that we'll use to validate that `join_date` is a `datetime.date` object.
+
+```python
+import datetime
+from typing import Optional
+
+from pydantic import ValidationError
+from redis_om.model import HashModel
+
+
+class StrictDate(datetime.date):
+    @classmethod
+    def __get_validators__(cls) -> 'CallableGenerator':
+        yield cls.validate
+
+    @classmethod
+    def validate(cls, value: datetime.date, **kwargs) -> datetime.date:
+        if not isinstance(value, datetime.date):
+            raise ValueError("Value must be a datetime.date object")
+        return value
+
+
+class Customer(HashModel):
+    first_name: str
+    last_name: str
+    email: str
+    join_date: StrictDate
+    age: int
+    bio: Optional[str]
+
+
+# Now if we use a string instead of a date object for `join_date`,
+# we get a validation error:
+try:
+    Customer(
+        first_name="Andrew",
+        last_name="Brookins",
+        email="a@example.com",
+        join_date="2020-01-02",  # <- A string shouldn't work now!
+        age="38"
+    )
+except ValidationError as e:
+    print(e)
+    """
+    pydantic.error_wrappers.ValidationError: 1 validation error for Customer
+    join_date
+      Value must be a datetime.date object (type=value_error)
+    """
+```
+
 ## Saving Models
 
 We can save the model to Redis by calling `save()`:
 
 ```python
+import datetime
+
+from redis_om.model import HashModel
+
+
+class Customer(HashModel):
+    first_name: str
+    last_name: str
+    email: str
+    join_date: datetime.date
+    age: int
+    
+
+andrew = Customer(
+    first_name="Andrew",
+    last_name="Brookins",
+    email="andrew.brookins@example.com",
+    join_date=datetime.date.today(),
+    age=38)
+
 andrew.save()
 ```
 
 ## Examining Your Data In Redis
 
-## Validating Data
+You can view the data stored in Redis for any Redis OM model.
+
+First, get the key of a model instance you want to inspect. The `key()` method will give you the exact Redis key used to store the model.
+
+**NOTE:** The naming of this method may be confusing. This is not the primary key, but is instead the Redis key for this model. For this reason, the method name may change.
+
+In this example, we're looking at the key created for the `Customer` model we've been building:
+
+```python
+import datetime
+from typing import Optional
+
+from redis_om.model import HashModel
+
+
+class Customer(HashModel):
+    first_name: str
+    last_name: str
+    email: str
+    join_date: datetime.date
+    age: int
+    bio: Optional[str] = "Super dope"
+
+andrew = Customer(
+    first_name="Andrew",
+    last_name="Brookins",
+    email="andrew.brookins@example.com",
+    join_date=datetime.date.today(),
+    age=38)
+
+andrew.save()
+andrew.key()
+#> 'mymodel.Customer:01FKGX1DFEV9Z2XKF59WQ6DC9T'
+```
+
+With the model's Redis key, you can start `redis-cli` and inspect the data stored under that key. Here, we run `JSON.GET` command with `redis-cli` using the running "redis" container that this project's Docker Compose file defines:
+
+```
+$ docker-compose exec -T redis redis-cli HGETALL mymodel.Customer:01FKGX1DFEV9Z2XKF59WQ6DC9r
+
+ 1) "pk"
+ 2) "01FKGX1DFEV9Z2XKF59WQ6DC9T"
+ 3) "first_name"
+ 4) "Andrew"
+ 5) "last_name"
+ 6) "Brookins"
+ 7) "email"
+ 8) "andrew.brookins@example.com"
+ 9) "join_date"
+10) "2021-11-02"
+11) "age"
+12) "38"
+13) "bio"
+14) "Super dope"
+```
+
+## Getting a Model
+
+If you have the primary key of a model, you can call the `get()` method on the model class to get the model's data.
+
+```python
+import datetime
+from typing import Optional
+
+from redis_om.model import HashModel
+
+
+class Customer(HashModel):
+    first_name: str
+    last_name: str
+    email: str
+    join_date: datetime.date
+    age: int
+    bio: Optional[str] = "Super dope"
+
+andrew = Customer(
+    first_name="Andrew",
+    last_name="Brookins",
+    email="andrew.brookins@example.com",
+    join_date=datetime.date.today(),
+    age=38)
+
+andrew.save()
+
+assert Customer.get(andrew.pk) == andrew
+```
+
+## Querying for Models With Expressions
+
+Redis OM comes with a rich query language that allows you to query Redis with Python expressions.
+
+To show how this works, we'll make a small change to the `Customer` model we defined earlier. We'll add `Field(index=True)` to tell Redis OM that we want to index the `last_name` and `age` fields:
+
+```python
+import datetime
+from typing import Optional
+
+from pydantic import EmailStr
+
+from redis_om.model import (
+    Field,
+    HashModel,
+    Migrator
+)
+
+
+class Customer(HashModel):
+    first_name: str
+    last_name: str = Field(index=True)
+    email: EmailStr
+    join_date: datetime.date
+    age: int = Field(index=True)
+    bio: Optional[str]
+    
+    
+# Now, if we use this model with a Redis deployment that has the
+# RediSearch module installed, we can run queries like the following.
+
+# Before running queries, we need to run migrations to set up the
+# indexes that Redis OM will use. You can also use the `migrate`
+# CLI tool for this!
+Migrator().run()
+
+# Find all customers with the last name "Brookins"
+Customer.find(Customer.last_name == "Brookins").all()
+
+# Find all customers that do NOT have the last name "Brookins"
+Customer.find(Customer.last_name != "Brookins").all()
+ 
+# Find all customers whose last name is "Brookins" OR whose age is 
+# 100 AND whose last name is "Smith"
+Customer.find((Customer.last_name == "Brookins") | (
+    Customer.age == 100
+) & (Customer.last_name == "Smith")).all()
+```
+
+Many more types of queries are possible. learn more about querying with Redis OM, see the [documentation on querying](docs/querying.md).
 
 ## Next Steps
 
-Now that you know the basics of working with Redis OM, continue on for all the nitty-gritty details about [models and fields](validation.md).
+Now that you know the basics of working with Redis OM, continue on for all the nitty-gritty details about [models and fields](models_and_fields.md).
 
 <!-- Links -->
 

docs/index.md

@@ -0,0 +1,3 @@
+# Redis OM Documentation
+
+WIP!

docs/integrating.md

@@ -0,0 +1,3 @@
+# Integration Redis OM With Popular Frameworks
+
+WIP!

docs/models_and_fields.md

@@ -1,5 +1,7 @@
 # Models and Fields
 
+**NOTE:** This documentation is a stub. Documentation for this project is a work in progress!
+
 ## Introduction
 
 ## Saving Data As Hashes With HashModel

docs/querying.md

@@ -1,15 +1,12 @@
 # Querying
-Querying uses a rich expression syntax inspired by the Django ORM, SQLAlchemy,  and Peewee.
 
-The example code defines `Address` and `Customer` models for use with a Redis database with the [RedisJSON](redis-json-url) module installed.
+**NOTE:** This documentation is a stub that uses examples from other documentation in this project (the README, the Getting Started guide, etc.). Detailed documentation on querying in a work in progress.
 
-With these two classes defined, you can now:
+Querying in Redis OM uses a rich expression syntax inspired by the Django ORM, SQLAlchemy,  and Peewee.
 
-* Validate data based on the model's type annotations using Pydantic 
-* Persist model instances to Redis as JSON
-* Instantiate model instances from Redis by primary key (a client-generated [ULID](ulid-url))
-* Query on any indexed fields in the models
+In the following example, we define `Address` and `Customer` models for use with a Redis database that has the [RedisJSON](redis-json-url) module installed.
 
+With these two classes defined, we can query on any indexed fields in the models -- including indexed fields within embedded models.
 
 ```python
 import datetime
@@ -19,6 +16,7 @@ from redis_om.model import (
     EmbeddedJsonModel,
     JsonModel,
     Field,
+    Migrator
 )
 
 class Address(EmbeddedJsonModel):
@@ -41,11 +39,15 @@ class Customer(JsonModel):
 
     # Creates an embedded model.
     address: Address
-```
 
-Here are a few example queries that use the models we defined earlier:
 
-```python
+# Before running queries, we need to run migrations to set up the
+# indexes that Redis OM will use. You can also use the `migrate`
+# CLI tool for this!
+Migrator().run() 
+    
+# Here are a few example queries that use these two models...
+
 # Find all customers with the last name "Brookins"
 Customer.find(Customer.last_name == "Brookins").all()
 

docs/redis_modules.md

@@ -25,6 +25,6 @@ You can use RediSearch and RedisJSON with your self-hosted Redis deployment. Jus
 - [RedisJSON Quick Start - Running Binaries](https://oss.redis.com/redisjson/#download-and-running-binaries)
 - [RediSearch Quick Start - Running Binaries](https://oss.redis.com/redisearch/Quick_Start/#download_and_running_binaries)
 
-**NOTE**: Both Quick Start Guides also have instructions on how to run these modules in Redis with Docker.
+**NOTE**: Both of these modules' Quick Start Guides also have instructions on how to run the modules in Redis with Docker.
 
 Don't want to run Redis yourself? RediSearch and RedisJSON are also available on Redis Cloud. [Get started here.](https://redis.com/try-free/)

docs/testing.md

@@ -1 +1,5 @@
 # Testing Your Models
+
+**NOTE:** This documentation is a Work in Progress.
+
+Writing tests that use a Redis OM model requires some setup. For now, review the tests in the redis-om-python project for examples.

poetry.lock

@@ -23,7 +23,7 @@ python-versions = "*"
 
 [[package]]
 name = "astroid"
-version = "2.8.3"
+version = "2.8.4"
 description = "An abstract syntax tree for Python with inference support."
 category = "dev"
 optional = false
@@ -36,11 +36,14 @@ wrapt = ">=1.11,<1.14"
 
 [[package]]
 name = "async-timeout"
-version = "3.0.1"
+version = "4.0.0"
 description = "Timeout context manager for asyncio programs"
 category = "main"
 optional = false
-python-versions = ">=3.5.3"
+python-versions = ">=3.6"
+
+[package.dependencies]
+typing-extensions = ">=3.6.5"
 
 [[package]]
 name = "atomicwrites"
@@ -101,7 +104,7 @@ stevedore = ">=1.20.0"
 
 [[package]]
 name = "black"
-version = "21.9b0"
+version = "21.10b0"
 description = "The uncompromising code formatter."
 category = "dev"
 optional = false
@@ -121,9 +124,9 @@ typing-extensions = [
 
 [package.extras]
 colorama = ["colorama (>=0.4.3)"]
-d = ["aiohttp (>=3.6.0)", "aiohttp-cors (>=0.4.0)"]
+d = ["aiohttp (>=3.7.4)"]
 jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
-python2 = ["typed-ast (>=1.4.2)"]
+python2 = ["typed-ast (>=1.4.3)"]
 uvloop = ["uvloop (>=0.15.2)"]
 
 [[package]]
@@ -190,7 +193,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
 
 [[package]]
 name = "coverage"
-version = "6.0.2"
+version = "6.1.1"
 description = "Code coverage measurement for Python"
 category = "dev"
 optional = false
@@ -254,7 +257,7 @@ trio = ["trio (>=0.14.0)", "sniffio (>=1.1)"]
 
 [[package]]
 name = "docutils"
-version = "0.17.1"
+version = "0.18"
 description = "Docutils -- Python Documentation Utilities"
 category = "dev"
 optional = false
@@ -285,7 +288,7 @@ testing = ["pre-commit"]
 
 [[package]]
 name = "filelock"
-version = "3.3.1"
+version = "3.3.2"
 description = "A platform independent file lock."
 category = "dev"
 optional = false
@@ -310,14 +313,14 @@ pyflakes = ">=2.4.0,<2.5.0"
 
 [[package]]
 name = "gitdb"
-version = "4.0.7"
+version = "4.0.9"
 description = "Git Object Database"
 category = "dev"
 optional = false
-python-versions = ">=3.4"
+python-versions = ">=3.6"
 
 [package.dependencies]
-smmap = ">=3.0.1,<5"
+smmap = ">=3.0.1,<6"
 
 [[package]]
 name = "gitpython"
@@ -378,7 +381,7 @@ toml = {version = ">=0.10.2", markers = "python_version > \"3.6\""}
 
 [[package]]
 name = "ipython"
-version = "7.28.0"
+version = "7.29.0"
 description = "IPython: Productive Interactive Computing"
 category = "dev"
 optional = false
@@ -521,14 +524,14 @@ python-versions = "*"
 
 [[package]]
 name = "packaging"
-version = "21.0"
+version = "21.2"
 description = "Core utilities for Python packages"
 category = "dev"
 optional = false
 python-versions = ">=3.6"
 
 [package.dependencies]
-pyparsing = ">=2.0.2"
+pyparsing = ">=2.0.2,<3"
 
 [[package]]
 name = "parso"
@@ -622,7 +625,7 @@ python-versions = "*"
 
 [[package]]
 name = "prompt-toolkit"
-version = "3.0.20"
+version = "3.0.21"
 description = "Library for building powerful interactive command lines in Python"
 category = "dev"
 optional = false
@@ -849,7 +852,7 @@ hiredis = ["hiredis (>=0.1.3)"]
 
 [[package]]
 name = "regex"
-version = "2021.10.8"
+version = "2021.11.2"
 description = "Alternative regular expression module, to replace re."
 category = "dev"
 optional = false
@@ -917,11 +920,11 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
 
 [[package]]
 name = "smmap"
-version = "4.0.0"
+version = "5.0.0"
 description = "A pure Python implementation of a sliding window memory map manager"
 category = "dev"
 optional = false
-python-versions = ">=3.5"
+python-versions = ">=3.6"
 
 [[package]]
 name = "stevedore"
@@ -944,7 +947,7 @@ python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
 
 [[package]]
 name = "tomli"
-version = "1.2.1"
+version = "1.2.2"
 description = "A lil' TOML parser"
 category = "dev"
 optional = false
@@ -1001,7 +1004,7 @@ telegram = ["requests"]
 
 [[package]]
 name = "traitlets"
-version = "5.1.0"
+version = "5.1.1"
 description = "Traitlets Python configuration system"
 category = "dev"
 optional = false
@@ -1068,7 +1071,7 @@ socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 
 [[package]]
 name = "virtualenv"
-version = "20.9.0"
+version = "20.10.0"
 description = "Virtual Python Environment builder"
 category = "dev"
 optional = false
@@ -1082,7 +1085,7 @@ platformdirs = ">=2,<3"
 six = ">=1.9.0,<2"
 
 [package.extras]
-docs = ["proselint (>=0.10.2)", "sphinx (>=3)", "sphinx-argparse (>=0.2.5)", "sphinx-rtd-theme (>=0.4.3)", "towncrier (>=19.9.0rc1)"]
+docs = ["proselint (>=0.10.2)", "sphinx (>=3)", "sphinx-argparse (>=0.2.5)", "sphinx-rtd-theme (>=0.4.3)", "towncrier (>=21.3)"]
 testing = ["coverage (>=4)", "coverage-enable-subprocess (>=1)", "flaky (>=3)", "pytest (>=4)", "pytest-env (>=0.6.2)", "pytest-freezegun (>=0.4.1)", "pytest-mock (>=2)", "pytest-randomly (>=1)", "pytest-timeout (>=1)", "packaging (>=20.0)"]
 
 [[package]]
@@ -1103,7 +1106,7 @@ python-versions = "*"
 
 [[package]]
 name = "wrapt"
-version = "1.13.2"
+version = "1.13.3"
 description = "Module for decorators, wrappers and monkey patching."
 category = "dev"
 optional = false
@@ -1123,8 +1126,8 @@ testing = ["pytest (>=4.6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytes
 
 [metadata]
 lock-version = "1.1"
-python-versions = "^3.9"
-content-hash = "fb8766fad12a5598ff95e95e96feae984d7cc64e3ce31eb8d3ad9dfd8b39d621"
+python-versions = "^3.8"
+content-hash = "1447e711408fe0aecd3bc17697456f773472a131ce2834b7fa09464f21144c37"
 
 [metadata.files]
 aioredis = [
@@ -1136,12 +1139,12 @@ appnope = [
     {file = "appnope-0.1.2.tar.gz", hash = "sha256:dd83cd4b5b460958838f6eb3000c660b1f9caf2a5b1de4264e941512f603258a"},
 ]
 astroid = [
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+    {file = "astroid-2.8.4-py3-none-any.whl", hash = "sha256:0755c998e7117078dcb7d0bda621391dd2a85da48052d948c7411ab187325346"},
+    {file = "astroid-2.8.4.tar.gz", hash = "sha256:1e83a69fd51b013ebf5912d26b9338d6643a55fec2f20c787792680610eed4a2"},
 ]
 async-timeout = [
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+    {file = "async-timeout-4.0.0.tar.gz", hash = "sha256:7d87a4e8adba8ededb52e579ce6bc8276985888913620c935094c2276fd83382"},
+    {file = "async_timeout-4.0.0-py3-none-any.whl", hash = "sha256:f3303dddf6cafa748a92747ab6c2ecf60e0aeca769aee4c151adfce243a05d9b"},
 ]
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@@ -1164,8 +1167,8 @@ bandit = [
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 ]
 black = [
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-    {file = "black-21.9b0.tar.gz", hash = "sha256:7de4cfc7eb6b710de325712d40125689101d21d25283eed7e9998722cf10eb91"},
+    {file = "black-21.10b0-py3-none-any.whl", hash = "sha256:6eb7448da9143ee65b856a5f3676b7dda98ad9abe0f87fce8c59291f15e82a5b"},
+    {file = "black-21.10b0.tar.gz", hash = "sha256:a9952229092e325fe5f3dae56d81f639b23f7131eb840781947e4b2886030f33"},
 ]
 bleach = [
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@@ -1240,39 +1243,55 @@ colorama = [
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 zipp = [
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pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "redis-om"
-version = "0.0.1"
+version = "0.0.2"
 description = "A high-level library containing useful Redis abstractions and tools, like an ORM and leaderboard."
 authors = ["Andrew Brookins <andrew.brookins@redis.com>"]
 maintainers = ["Andrew Brookins <andrew.brookins@redis.com>"]

redis_om/model/__init__.py

@@ -1 +1,2 @@
+from .migrations.migrator import MigrationError, Migrator
 from .model import EmbeddedJsonModel, Field, HashModel, JsonModel, RedisModel