Mastering SQLAlchemy (4 Part Series)

1 Databases in Python Made Easy with SQLAlchemy
2 Implement ORM Data Models with SQLAlchemy
3 Queries as Python Code with SQLAlchemy’s Expression Language
4 Define Relationships Between SQLAlchemy Data Models

Our SQLAlchemy journey thus far has covered managing database connections and model creation. Yet, how do we extract the data we want from our database?

SQLAlchemy’s ORM query API simplifies the way we write database queries. Instead of writing raw SQL queries, we can construct queries on our SQLAlchemy session by chaining together methods to retrieve data. We’re going to dive into SQLAlchemy’s extensive query API to get an idea of all the ways we can query our data.

Create a Session

We covered SQLAlchemy session creation in the previous post and explained the concept of engines in the post before that. If you skipped those posts, don’t. The below is copy+pasta courtesy:


<span>"""Database engine & session creation."""</span>
<span>from</span> <span>sqlalchemy</span> <span>import</span> <span>create_engine</span>
<span>from</span> <span>sqlalchemy.orm</span> <span>import</span> <span>sessionmaker</span>
<span>engine</span> <span>=</span> <span>create_engine</span><span>(</span>
    <span>'mysql+pymysql://user:password@host:3600/database'</span><span>,</span>
    <span>echo</span><span>=</span><span>True</span>
<span>)</span>
<span>Session</span> <span>=</span> <span>sessionmaker</span><span>(</span><span>bind</span><span>=</span><span>engine</span><span>)</span>
<span>session</span> <span>=</span> <span>Session</span><span>()</span>
<span>"""Database engine & session creation."""</span>
<span>from</span> <span>sqlalchemy</span> <span>import</span> <span>create_engine</span>
<span>from</span> <span>sqlalchemy.orm</span> <span>import</span> <span>sessionmaker</span>

<span>engine</span> <span>=</span> <span>create_engine</span><span>(</span>
    <span>'mysql+pymysql://user:password@host:3600/database'</span><span>,</span>
    <span>echo</span><span>=</span><span>True</span>
<span>)</span>
<span>Session</span> <span>=</span> <span>sessionmaker</span><span>(</span><span>bind</span><span>=</span><span>engine</span><span>)</span>
<span>session</span> <span>=</span> <span>Session</span><span>()</span>
"""Database engine & session creation."""
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker

engine = create_engine(
    'mysql+pymysql://user:password@host:3600/database',
    echo=True
)
Session = sessionmaker(bind=engine)
session = Session()

Enter fullscreen mode Exit fullscreen mode database.py

Basic Query Syntax

Let’s quickly become familiar with the basic structure of SQLAlchemy’s query API. SQLAlchemy session objects have a query() method which accepts the raw class of a data model we’ve previously defined. Below are the humble beginnings of a query to run on Customer model; or in other words, a query on the customers SQL table:


<span>"""Construct database queries from SQLAlchemy sessions."""</span>
<span>from</span> <span>.database</span> <span>import</span> <span>session</span>
<span>from</span> <span>.models</span> <span>import</span> <span>Customer</span>
<span># Example structure of an ORM query </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>Customer</span><span>)</span>
    <span>.</span><span>FUNCTION</span><span>()</span>
<span>"""Construct database queries from SQLAlchemy sessions."""</span>
<span>from</span> <span>.database</span> <span>import</span> <span>session</span>
<span>from</span> <span>.models</span> <span>import</span> <span>Customer</span>

<span># Example structure of an ORM query </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>Customer</span><span>)</span>
    <span>.</span><span>FUNCTION</span><span>()</span>
"""Construct database queries from SQLAlchemy sessions."""
from .database import session
from .models import Customer

# Example structure of an ORM query records = session
    .query(Customer)
    .FUNCTION()

Enter fullscreen mode Exit fullscreen mode Select records from a SQLAlchemy session

Calling .query(Customer) on our session isn’t a valid query until we add one more method to the chain. All session queries end with a final method to shape/anticipate the result(s) of our query:

all() will return all records which match our query as a list of objects. If we were to use all on the query above, we would receive all customer records with the Python data type List[Customer].
first() returns the first record matching our query, despite how many records match the query (what constitutes “first” depends on how your table is sorted). This is the equivalent of adding LIMIT 1 to a SQL query. As a result, the Python type to be returned would be Customer.
one() is extremely useful for cases where a maximum of one record should exist for the query we’re executing (think of querying by primary key). This syntax is notably useful when verifying whether or not a record exists prior to creating one.
scalar() returns a single value if one exists, None if no values exist, or raises an exception if multiple records are returned.
get([VALUE(S)]) searches against a model’s primary key to return rows where the primary key is equal to the value provided. get() also accepts tuples in the event that multiple foreign keys should be searched. Lastly, get() can also accept a dictionary and return rows where the columns (dictionary keys) match the values provided.

To create more complex queries, we’d add to our query by chaining methods on our original query:


<span>"""Construct database queries from SQLAlchemy sessions."""</span>
<span>from</span> <span>.database</span> <span>import</span> <span>session</span>
<span>from</span> <span>.models</span> <span>import</span> <span>Customer</span>
<span># Example structure of an ORM query </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>Customer</span><span>)</span>
    <span>.</span><span>METHOD_1</span><span>()</span>
    <span>.</span><span>METHOD_2</span><span>()</span>
    <span>.</span><span>FUNCTION</span><span>()</span>
<span>"""Construct database queries from SQLAlchemy sessions."""</span>
<span>from</span> <span>.database</span> <span>import</span> <span>session</span>
<span>from</span> <span>.models</span> <span>import</span> <span>Customer</span>

<span># Example structure of an ORM query </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>Customer</span><span>)</span>
    <span>.</span><span>METHOD_1</span><span>()</span>
    <span>.</span><span>METHOD_2</span><span>()</span>
    <span>.</span><span>FUNCTION</span><span>()</span>
"""Construct database queries from SQLAlchemy sessions."""
from .database import session
from .models import Customer

# Example structure of an ORM query records = session
    .query(Customer)
    .METHOD_1()
    .METHOD_2()
    .FUNCTION()

Enter fullscreen mode Exit fullscreen mode Complex SELECT query

Query Results

If we execute a query that returns multiple records, we’ll need to loop through them to see the results:


<span>"""Construct database queries from SQLAlchemy sessions."""</span>
<span>from</span> <span>.database</span> <span>import</span> <span>session</span>
<span>from</span> <span>.models</span> <span>import</span> <span>Customer</span>
<span># Fetch all customer records </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>Customer</span><span>)</span>
    <span>.</span><span>all</span><span>()</span>
<span># Loop over records </span><span>for</span> <span>record</span> <span>in</span> <span>records</span><span>:</span>
    <span>print</span><span>(</span><span>record</span><span>)</span>
<span>"""Construct database queries from SQLAlchemy sessions."""</span>
<span>from</span> <span>.database</span> <span>import</span> <span>session</span>
<span>from</span> <span>.models</span> <span>import</span> <span>Customer</span>

<span># Fetch all customer records </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>Customer</span><span>)</span>
    <span>.</span><span>all</span><span>()</span>

<span># Loop over records </span><span>for</span> <span>record</span> <span>in</span> <span>records</span><span>:</span>
    <span>print</span><span>(</span><span>record</span><span>)</span>
"""Construct database queries from SQLAlchemy sessions."""
from .database import session
from .models import Customer

# Fetch all customer records records = session
    .query(Customer)
    .all()

# Loop over records for record in records:
    print(record)

Enter fullscreen mode Exit fullscreen mode Fetch all customer records and print the output

The SQLAlchemy ORM will return an instance of a class by default, which means the above will result in the following output:


<Customer model 1>
<Customer model 2>
<Customer model 3>
<Customer model 4>
<Customer model 5>
<Customer model 6>
<Customer model 7>
<Customer model 8>
<Customer model 9>
<Customer model 10>
<Customer model 1>
<Customer model 2>
<Customer model 3>
<Customer model 4>
<Customer model 5>
<Customer model 6>
<Customer model 7>
<Customer model 8>
<Customer model 9>
<Customer model 10>
<Customer model 1>
<Customer model 2>
<Customer model 3>
<Customer model 4>
<Customer model 5>
<Customer model 6>
<Customer model 7>
<Customer model 8>
<Customer model 9>
<Customer model 10>

Enter fullscreen mode Exit fullscreen mode Output of a session query

If you’re looking to get dictionaries instead, use the built-in __dict__ method:


<span>...</span>
<span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>Customer</span><span>)</span>
    <span>.</span><span>all</span><span>()</span>
<span>for</span> <span>record</span> <span>in</span> <span>records</span><span>:</span>
    <span>pp</span><span>.</span><span>pprint</span><span>(</span><span>record</span><span>.</span> <span>__dict__</span> <span>)</span>
<span>...</span>

<span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>Customer</span><span>)</span>
    <span>.</span><span>all</span><span>()</span>

<span>for</span> <span>record</span> <span>in</span> <span>records</span><span>:</span>
    <span>pp</span><span>.</span><span>pprint</span><span>(</span><span>record</span><span>.</span> <span>__dict__</span> <span>)</span>
...

records = session
    .query(Customer)
    .all()

for record in records:
    pp.pprint(record. __dict__ )

Enter fullscreen mode Exit fullscreen mode View query results as dictionaries

This instead returns dictionary objects for each row:


<span>{</span> <span>'_sa_instance_state'</span>: <sqlalchemy.orm.state.InstanceState object at 0x7f98c8221748>,
    <span>'email'</span>: <span>'kpaladini5i@senate.gov'</span>,
    <span>'first_name'</span>: <span>'Kenna'</span>,
    <span>'id'</span>: 199,
    <span>'join_date'</span>: datetime.datetime<span>(</span>2019, 4, 19, 0, 0<span>)</span>,
    <span>'last_name'</span>: <span>'Paladini'</span>,
    <span>'preferred_language'</span>: <span>'Bulgarian'</span><span>}</span>
<span>{</span> <span>'_sa_instance_state'</span>: <sqlalchemy.orm.state.InstanceState object at 0x7f9918192d68>,
    <span>'email'</span>: <span>'rlebrun5j@narod.ru'</span>,
    <span>'first_name'</span>: <span>'Rriocard'</span>,
    <span>'id'</span>: 200,
    <span>'join_date'</span>: datetime.datetime<span>(</span>2015, 6, 8, 0, 0<span>)</span>,
    <span>'last_name'</span>: <span>'Le Brun'</span>,
    <span>'preferred_language'</span>: <span>'Khmer'</span><span>}</span>,
...
<span>{</span> <span>'_sa_instance_state'</span>: <sqlalchemy.orm.state.InstanceState object at 0x7f98c8221748>,
    <span>'email'</span>: <span>'kpaladini5i@senate.gov'</span>,
    <span>'first_name'</span>: <span>'Kenna'</span>,
    <span>'id'</span>: 199,
    <span>'join_date'</span>: datetime.datetime<span>(</span>2019, 4, 19, 0, 0<span>)</span>,
    <span>'last_name'</span>: <span>'Paladini'</span>,
    <span>'preferred_language'</span>: <span>'Bulgarian'</span><span>}</span>
<span>{</span> <span>'_sa_instance_state'</span>: <sqlalchemy.orm.state.InstanceState object at 0x7f9918192d68>,
    <span>'email'</span>: <span>'rlebrun5j@narod.ru'</span>,
    <span>'first_name'</span>: <span>'Rriocard'</span>,
    <span>'id'</span>: 200,
    <span>'join_date'</span>: datetime.datetime<span>(</span>2015, 6, 8, 0, 0<span>)</span>,
    <span>'last_name'</span>: <span>'Le Brun'</span>,
    <span>'preferred_language'</span>: <span>'Khmer'</span><span>}</span>,
...
{ '_sa_instance_state': <sqlalchemy.orm.state.InstanceState object at 0x7f98c8221748>,
    'email': 'kpaladini5i@senate.gov',
    'first_name': 'Kenna',
    'id': 199,
    'join_date': datetime.datetime(2019, 4, 19, 0, 0),
    'last_name': 'Paladini',
    'preferred_language': 'Bulgarian'}
{ '_sa_instance_state': <sqlalchemy.orm.state.InstanceState object at 0x7f9918192d68>,
    'email': 'rlebrun5j@narod.ru',
    'first_name': 'Rriocard',
    'id': 200,
    'join_date': datetime.datetime(2015, 6, 8, 0, 0),
    'last_name': 'Le Brun',
    'preferred_language': 'Khmer'},
...

Enter fullscreen mode Exit fullscreen mode Output of a session query as dictionaries

Of course, you could also create your own object instead to receive only the columns you want/need:


<span>...</span>
<span># Fetch all customers </span><span>records</span> <span>=</span> <span>session</span><span>.</span><span>query</span><span>(</span><span>Customer</span><span>).</span><span>all</span><span>()</span>
<span># Loop through records </span><span>for</span> <span>record</span> <span>in</span> <span>records</span><span>:</span>
    <span>recordObject</span> <span>=</span> <span>{</span>
        <span>'name'</span><span>:</span> <span>record</span><span>.</span><span>name</span><span>,</span>
        <span>'position'</span><span>:</span> <span>record</span><span>.</span><span>position</span><span>,</span>
        <span>'team_name'</span><span>:</span> <span>record</span><span>.</span><span>team</span><span>.</span><span>name</span><span>,</span>
        <span>'team_city'</span><span>:</span> <span>record</span><span>.</span><span>team</span><span>.</span><span>city</span>
    <span>}</span>
    <span>print</span><span>(</span><span>recordObject</span><span>)</span>
<span>...</span>

<span># Fetch all customers </span><span>records</span> <span>=</span> <span>session</span><span>.</span><span>query</span><span>(</span><span>Customer</span><span>).</span><span>all</span><span>()</span>

<span># Loop through records </span><span>for</span> <span>record</span> <span>in</span> <span>records</span><span>:</span>
    <span>recordObject</span> <span>=</span> <span>{</span>
        <span>'name'</span><span>:</span> <span>record</span><span>.</span><span>name</span><span>,</span>
        <span>'position'</span><span>:</span> <span>record</span><span>.</span><span>position</span><span>,</span>
        <span>'team_name'</span><span>:</span> <span>record</span><span>.</span><span>team</span><span>.</span><span>name</span><span>,</span>
        <span>'team_city'</span><span>:</span> <span>record</span><span>.</span><span>team</span><span>.</span><span>city</span>
    <span>}</span>
    <span>print</span><span>(</span><span>recordObject</span><span>)</span>
...

# Fetch all customers records = session.query(Customer).all()

# Loop through records for record in records:
    recordObject = {
        'name': record.name,
        'position': record.position,
        'team_name': record.team.name,
        'team_city': record.team.city
    }
    print(recordObject)

Enter fullscreen mode Exit fullscreen mode Deserialize results of a query

This outputs something a bit cleaner:


<span>{</span> <span>'email'</span>: <span>'kpaladini5i@senate.gov'</span>,
    <span>'first_name'</span>: <span>'Kenna'</span>,
    <span>'join_date'</span>: datetime.datetime<span>(</span>2019, 4, 19, 0, 0<span>)</span>,
    <span>'last_name'</span>: <span>'Paladini'</span>,
    <span>'preferred_language'</span>: <span>'Bulgarian'</span><span>}</span>
<span>{</span> <span>'email'</span>: <span>'rlebrun5j@narod.ru'</span>,
    <span>'first_name'</span>: <span>'Rriocard'</span>,
    <span>'join_date'</span>: datetime.datetime<span>(</span>2015, 6, 8, 0, 0<span>)</span>,
    <span>'last_name'</span>: <span>'Le Brun'</span>,
    <span>'preferred_language'</span>: <span>'Khmer'</span><span>}</span>,
...
<span>{</span> <span>'email'</span>: <span>'kpaladini5i@senate.gov'</span>,
    <span>'first_name'</span>: <span>'Kenna'</span>,
    <span>'join_date'</span>: datetime.datetime<span>(</span>2019, 4, 19, 0, 0<span>)</span>,
    <span>'last_name'</span>: <span>'Paladini'</span>,
    <span>'preferred_language'</span>: <span>'Bulgarian'</span><span>}</span>
<span>{</span> <span>'email'</span>: <span>'rlebrun5j@narod.ru'</span>,
    <span>'first_name'</span>: <span>'Rriocard'</span>,
    <span>'join_date'</span>: datetime.datetime<span>(</span>2015, 6, 8, 0, 0<span>)</span>,
    <span>'last_name'</span>: <span>'Le Brun'</span>,
    <span>'preferred_language'</span>: <span>'Khmer'</span><span>}</span>,
...
{ 'email': 'kpaladini5i@senate.gov',
    'first_name': 'Kenna',
    'join_date': datetime.datetime(2019, 4, 19, 0, 0),
    'last_name': 'Paladini',
    'preferred_language': 'Bulgarian'}
{ 'email': 'rlebrun5j@narod.ru',
    'first_name': 'Rriocard',
    'join_date': datetime.datetime(2015, 6, 8, 0, 0),
    'last_name': 'Le Brun',
    'preferred_language': 'Khmer'},
...

Enter fullscreen mode Exit fullscreen mode Output of query deserialization

Filtering Results

Probably the most common method you’ll use on a query is the filter() method. filter() is the equivalent of a SQL WHERE clause to return only rows that match the criteria we want:


<span>...</span>
<span># Fetch records where `first_name` is `Carl` </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>Customer</span><span>)</span>
    <span>.</span><span>filter</span><span>(</span><span>Customer</span><span>)</span>
    <span>.</span><span>first_name</span> <span>==</span> <span>'Carl'</span><span>)</span>
    <span>.</span><span>all</span><span>()</span>
<span>...</span>

<span># Fetch records where `first_name` is `Carl` </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>Customer</span><span>)</span>
    <span>.</span><span>filter</span><span>(</span><span>Customer</span><span>)</span>
    <span>.</span><span>first_name</span> <span>==</span> <span>'Carl'</span><span>)</span>
    <span>.</span><span>all</span><span>()</span>
...

# Fetch records where `first_name` is `Carl` records = session
    .query(Customer)
    .filter(Customer)
    .first_name == 'Carl')
    .all()

Enter fullscreen mode Exit fullscreen mode Select all customers named Carl

filter_by()

We could write the above query using the filter_by() method instead like so:


<span>...</span>
<span># Fetch records where `first_name` is `Carl` </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>Customer</span><span>)</span>
    <span>.</span><span>filter_by</span><span>(</span><span>first_name</span><span>=</span><span>"Carl"</span><span>)</span>
    <span>.</span><span>all</span><span>()</span>
<span>...</span>

<span># Fetch records where `first_name` is `Carl` </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>Customer</span><span>)</span>
    <span>.</span><span>filter_by</span><span>(</span><span>first_name</span><span>=</span><span>"Carl"</span><span>)</span>
    <span>.</span><span>all</span><span>()</span>
...

# Fetch records where `first_name` is `Carl` records = session
    .query(Customer)
    .filter_by(first_name="Carl")
    .all()

Enter fullscreen mode Exit fullscreen mode Filter with
filter_by

Unlike filter(), filter_by() accepts keyword arguments (note the difference in syntax here: filter() checks a conditional against a column object whereas filter_by() finds columns that match the arguments we pass). filter_by() can only search for exact values and serves as a kind of shorthand for simple filtering queries.

like()

We can do more than filter on simple conditionals. SQLAlchemy has a like() method which works in an equivalent manner to SQL’s LIKE:


<span>...</span>
<span># Fetch records where `first_name` begins with the letter `J` </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>Customer</span><span>)</span>
    <span>.</span><span>filter</span><span>(</span><span>Customer</span><span>.</span><span>first_name</span><span>.</span><span>like</span><span>(</span><span>'J%'</span><span>))</span>
    <span>.</span><span>all</span><span>()</span>
<span>...</span>

<span># Fetch records where `first_name` begins with the letter `J` </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>Customer</span><span>)</span>
    <span>.</span><span>filter</span><span>(</span><span>Customer</span><span>.</span><span>first_name</span><span>.</span><span>like</span><span>(</span><span>'J%'</span><span>))</span>
    <span>.</span><span>all</span><span>()</span>
...

# Fetch records where `first_name` begins with the letter `J` records = session
    .query(Customer)
    .filter(Customer.first_name.like('J%'))
    .all()

Enter fullscreen mode Exit fullscreen mode Select customer records where first names begin with “J”

As expected, this will give us all rows where the customer’s first name starts with a J :


<span>{</span> <span>'email'</span>: <span>'jpugsley9@netvibes.com'</span>,
    <span>'first_name'</span>: <span>'Jarid'</span>,
    <span>'join_date'</span>: datetime.datetime<span>(</span>2017, 10, 11, 0, 0<span>)</span>,
    <span>'last_name'</span>: <span>'Pugsley'</span>,
    <span>'preferred_language'</span>: <span>'Burmese'</span><span>}</span>
<span>{</span> <span>'email'</span>: <span>'jdymockek@is.gd'</span>,
    <span>'first_name'</span>: <span>'Jeanna'</span>,
    <span>'join_date'</span>: datetime.datetime<span>(</span>2017, 11, 13, 0, 0<span>)</span>,
    <span>'last_name'</span>: <span>'Dymocke'</span>,
    <span>'preferred_language'</span>: <span>'Malayalam'</span><span>}</span>
...
<span>{</span> <span>'email'</span>: <span>'jpugsley9@netvibes.com'</span>,
    <span>'first_name'</span>: <span>'Jarid'</span>,
    <span>'join_date'</span>: datetime.datetime<span>(</span>2017, 10, 11, 0, 0<span>)</span>,
    <span>'last_name'</span>: <span>'Pugsley'</span>,
    <span>'preferred_language'</span>: <span>'Burmese'</span><span>}</span>
<span>{</span> <span>'email'</span>: <span>'jdymockek@is.gd'</span>,
    <span>'first_name'</span>: <span>'Jeanna'</span>,
    <span>'join_date'</span>: datetime.datetime<span>(</span>2017, 11, 13, 0, 0<span>)</span>,
    <span>'last_name'</span>: <span>'Dymocke'</span>,
    <span>'preferred_language'</span>: <span>'Malayalam'</span><span>}</span>
...
{ 'email': 'jpugsley9@netvibes.com',
    'first_name': 'Jarid',
    'join_date': datetime.datetime(2017, 10, 11, 0, 0),
    'last_name': 'Pugsley',
    'preferred_language': 'Burmese'}
{ 'email': 'jdymockek@is.gd',
    'first_name': 'Jeanna',
    'join_date': datetime.datetime(2017, 11, 13, 0, 0),
    'last_name': 'Dymocke',
    'preferred_language': 'Malayalam'}
...

Enter fullscreen mode Exit fullscreen mode Output

High-level Query Methods

In addition to filter(), there are a few basic methods we should be familiar with. Each of these corresponds to SQL keywords you’re probably familiar with:

limit([INTEGER]): Limits the number of rows to a maximum of the number provided.
order_by([COLUMN]): Sorts results by the provided column.
offset([INTEGER]): Begins the query at row n.

This next part involves executing JOIN queries between models, which requires us to define relationships on our models first. Things are a bit out of order at the moment, as I actually don’t cover this until the next post. Sorry for the mess, I’m working on it!

Performing Joins & Unions

We’ve touched on JOINs a bit previously, but we’re about to kick it up a notch. We have two data models we’re working with: one for customers, and one for orders. Each customer


<span>...</span>
<span>import</span> <span>pprint</span>
<span>from</span> <span>.models</span> <span>import</span> <span>Order</span><span>,</span> <span>Customer</span>
<span>pp</span> <span>=</span> <span>pprint</span><span>.</span><span>PrettyPrinter</span><span>(</span><span>indent</span><span>=</span><span>4</span><span>)</span>
<span># Execute a SELECT query on JOINed tables </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>Customer</span><span>)</span>
    <span>.</span><span>join</span><span>(</span><span>Order</span><span>,</span> <span>Order</span><span>.</span><span>customer_id</span> <span>==</span> <span>Customer</span><span>.</span><span>id</span><span>)</span>
    <span>.</span><span>all</span><span>()</span>
<span># Loop through results </span><span>for</span> <span>record</span> <span>in</span> <span>records</span><span>:</span>
    <span>record_object</span> <span>=</span> <span>{</span>
        <span>'first_name'</span><span>:</span> <span>record</span><span>.</span><span>first_name</span><span>,</span>
        <span>'last_name'</span><span>:</span> <span>record</span><span>.</span><span>last_name</span><span>,</span>
        <span>'email'</span><span>:</span> <span>record</span><span>.</span><span>email</span><span>,</span>
        <span>'preferred_language'</span><span>:</span> <span>record</span><span>.</span><span>preferred_language</span><span>,</span>
        <span>'join_date'</span><span>:</span> <span>record</span><span>.</span><span>join_date</span><span>,</span>
        <span>'orders'</span><span>:</span> <span>[]</span>
    <span>}</span>
    <span>for</span> <span>order</span> <span>in</span> <span>record</span><span>.</span><span>order</span><span>:</span>
        <span>order</span> <span>=</span> <span>{</span>
            <span>'order_price'</span><span>:</span> <span>order</span><span>.</span><span>price</span><span>,</span>
            <span>'currency'</span><span>:</span> <span>order</span><span>.</span><span>currency</span><span>,</span>
            <span>'purchase_date'</span><span>:</span> <span>order</span><span>.</span><span>purchase_date</span><span>,</span>
            <span>'product'</span><span>:</span> <span>order</span><span>.</span><span>product</span>
        <span>}</span>
        <span>record_object</span><span>[</span><span>'orders'</span><span>].</span><span>append</span><span>(</span><span>order</span><span>)</span>
        <span>pp</span><span>.</span><span>pprint</span><span>(</span><span>record_object</span><span>)</span>
<span>...</span>
<span>import</span> <span>pprint</span>
<span>from</span> <span>.models</span> <span>import</span> <span>Order</span><span>,</span> <span>Customer</span>

<span>pp</span> <span>=</span> <span>pprint</span><span>.</span><span>PrettyPrinter</span><span>(</span><span>indent</span><span>=</span><span>4</span><span>)</span>

<span># Execute a SELECT query on JOINed tables </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>Customer</span><span>)</span>
    <span>.</span><span>join</span><span>(</span><span>Order</span><span>,</span> <span>Order</span><span>.</span><span>customer_id</span> <span>==</span> <span>Customer</span><span>.</span><span>id</span><span>)</span>
    <span>.</span><span>all</span><span>()</span>

<span># Loop through results </span><span>for</span> <span>record</span> <span>in</span> <span>records</span><span>:</span>
    <span>record_object</span> <span>=</span> <span>{</span>
        <span>'first_name'</span><span>:</span> <span>record</span><span>.</span><span>first_name</span><span>,</span>
        <span>'last_name'</span><span>:</span> <span>record</span><span>.</span><span>last_name</span><span>,</span>
        <span>'email'</span><span>:</span> <span>record</span><span>.</span><span>email</span><span>,</span>
        <span>'preferred_language'</span><span>:</span> <span>record</span><span>.</span><span>preferred_language</span><span>,</span>
        <span>'join_date'</span><span>:</span> <span>record</span><span>.</span><span>join_date</span><span>,</span>
        <span>'orders'</span><span>:</span> <span>[]</span>
    <span>}</span>
    <span>for</span> <span>order</span> <span>in</span> <span>record</span><span>.</span><span>order</span><span>:</span>
        <span>order</span> <span>=</span> <span>{</span>
            <span>'order_price'</span><span>:</span> <span>order</span><span>.</span><span>price</span><span>,</span>
            <span>'currency'</span><span>:</span> <span>order</span><span>.</span><span>currency</span><span>,</span>
            <span>'purchase_date'</span><span>:</span> <span>order</span><span>.</span><span>purchase_date</span><span>,</span>
            <span>'product'</span><span>:</span> <span>order</span><span>.</span><span>product</span>
        <span>}</span>
        <span>record_object</span><span>[</span><span>'orders'</span><span>].</span><span>append</span><span>(</span><span>order</span><span>)</span>
        <span>pp</span><span>.</span><span>pprint</span><span>(</span><span>record_object</span><span>)</span>
...
import pprint
from .models import Order, Customer

pp = pprint.PrettyPrinter(indent=4)

# Execute a SELECT query on JOINed tables records = session
    .query(Customer)
    .join(Order, Order.customer_id == Customer.id)
    .all()

# Loop through results for record in records:
    record_object = {
        'first_name': record.first_name,
        'last_name': record.last_name,
        'email': record.email,
        'preferred_language': record.preferred_language,
        'join_date': record.join_date,
        'orders': []
    }
    for order in record.order:
        order = {
            'order_price': order.price,
            'currency': order.currency,
            'purchase_date': order.purchase_date,
            'product': order.product
        }
        record_object['orders'].append(order)
        pp.pprint(record_object)

Enter fullscreen mode Exit fullscreen mode Join records from different tables and deserialize records

We perform our JOIN using the join() method. The first parameter we pass is the data model we’ll be joining with on the “right.” We then specify what we’ll be joining “on”: the customer_id column of our order model, and the id column of our customer model.

Our outer loop gives us each customer, and our inner loop adds each order to the appropriate customer. Check out an example record:


<span>{</span> <span>'email'</span>: <span>'jtinline16@arizona.edu'</span>,
    <span>'first_name'</span>: <span>'Jerry'</span>,
    <span>'join_date'</span>: datetime.datetime<span>(</span>2016, 10, 27, 0, 0<span>)</span>,
    <span>'last_name'</span>: <span>'Tinline'</span>,
    <span>'preferred_language'</span>: <span>'Icelandic'</span>,
    <span>'orders'</span>: <span>[{</span><span>'currency'</span>: <span>'IDR'</span>,
                <span>'order_price'</span>: 34.24,
                <span>'product'</span>: <span>'Beer - Corona'</span>,
                <span>'purchase_date'</span>: datetime.datetime<span>(</span>2019, 5, 5, 0, 0<span>)}</span>,
               <span>{</span><span>'currency'</span>: <span>'GEL'</span>,
                <span>'order_price'</span>: 25.75,
                <span>'product'</span>: <span>'Creamers - 10%'</span>,
                <span>'purchase_date'</span>: datetime.datetime<span>(</span>2019, 1, 27, 0, 0<span>)}]}</span>
<span>{</span> <span>'email'</span>: <span>'jtinline16@arizona.edu'</span>,
    <span>'first_name'</span>: <span>'Jerry'</span>,
    <span>'join_date'</span>: datetime.datetime<span>(</span>2016, 10, 27, 0, 0<span>)</span>,
    <span>'last_name'</span>: <span>'Tinline'</span>,
    <span>'preferred_language'</span>: <span>'Icelandic'</span>,
    <span>'orders'</span>: <span>[{</span><span>'currency'</span>: <span>'IDR'</span>,
                <span>'order_price'</span>: 34.24,
                <span>'product'</span>: <span>'Beer - Corona'</span>,
                <span>'purchase_date'</span>: datetime.datetime<span>(</span>2019, 5, 5, 0, 0<span>)}</span>,
               <span>{</span><span>'currency'</span>: <span>'GEL'</span>,
                <span>'order_price'</span>: 25.75,
                <span>'product'</span>: <span>'Creamers - 10%'</span>,
                <span>'purchase_date'</span>: datetime.datetime<span>(</span>2019, 1, 27, 0, 0<span>)}]}</span>
{ 'email': 'jtinline16@arizona.edu',
    'first_name': 'Jerry',
    'join_date': datetime.datetime(2016, 10, 27, 0, 0),
    'last_name': 'Tinline',
    'preferred_language': 'Icelandic',
    'orders': [{'currency': 'IDR',
                'order_price': 34.24,
                'product': 'Beer - Corona',
                'purchase_date': datetime.datetime(2019, 5, 5, 0, 0)},
               {'currency': 'GEL',
                'order_price': 25.75,
                'product': 'Creamers - 10%',
                'purchase_date': datetime.datetime(2019, 1, 27, 0, 0)}]}

Enter fullscreen mode Exit fullscreen mode Output

Our friend Jerry here has two orders: one for some Coronas, and another for creamers. Get at it, Jerry.

Outer JOINs

In addition to simple JOINs, we can perform outer JOINs using the same syntax:


<span>...</span>
<span>from</span> <span>.models</span> <span>import</span> <span>ExampleModel1</span><span>,</span> <span>ExampleModel2</span>
<span># Execute an outer JOIN </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>ExampleModel1</span><span>)</span>
    <span>.</span><span>outerjoin</span><span>(</span><span>ExampleModel2</span><span>)</span>
    <span>.</span><span>all</span><span>()</span>
<span>...</span>
<span>from</span> <span>.models</span> <span>import</span> <span>ExampleModel1</span><span>,</span> <span>ExampleModel2</span>

<span># Execute an outer JOIN </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>ExampleModel1</span><span>)</span>
    <span>.</span><span>outerjoin</span><span>(</span><span>ExampleModel2</span><span>)</span>
    <span>.</span><span>all</span><span>()</span>
...
from .models import ExampleModel1, ExampleModel2

# Execute an outer JOIN records = session
    .query(ExampleModel1)
    .outerjoin(ExampleModel2)
    .all()

Enter fullscreen mode Exit fullscreen mode Perform an outer join

Unions

We can perform UNIONs and UNION ALLs as well:


<span>...</span>
<span>from</span> <span>.models</span> <span>import</span> <span>ExampleModel1</span><span>,</span> <span>ExampleModel2</span>
<span># Execute a UNION </span><span>records</span> <span>=</span> <span>ExampleModel1</span><span>.</span><span>union</span><span>(</span><span>ExampleModel2</span><span>)</span>
<span>...</span>
<span>from</span> <span>.models</span> <span>import</span> <span>ExampleModel1</span><span>,</span> <span>ExampleModel2</span>

<span># Execute a UNION </span><span>records</span> <span>=</span> <span>ExampleModel1</span><span>.</span><span>union</span><span>(</span><span>ExampleModel2</span><span>)</span>
...
from .models import ExampleModel1, ExampleModel2

# Execute a UNION records = ExampleModel1.union(ExampleModel2)

Enter fullscreen mode Exit fullscreen mode Perform a union

To perform a union all, simply replace union() with union_all()!

Aggregate Functions and Stats

As with all SQL-like query languages, we can perform some aggregate stats as well. The following are available to us:

count([COLUMN]): Counts the number of records in a column.
count(distinct([COLUMN])): Counts the distinct number of records in a column.
sum([COLUMN]): Adds the numerical values in a column.

Here’s how we’d perform a query that counts the values in a column:


<span>...</span>
<span>from</span> <span>sqlalchemy</span> <span>import</span> <span>func</span>
<span># Count number of records with a `first_name` value </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>func</span><span>.</span><span>count</span><span>(</span><span>Customer</span><span>.</span><span>first_name</span><span>))</span>
    <span>.</span><span>all</span><span>()</span>   
<span>for</span> <span>record</span> <span>in</span> <span>records</span><span>:</span>
    <span>print</span><span>(</span><span>record</span><span>)</span>
<span>...</span>
<span>from</span> <span>sqlalchemy</span> <span>import</span> <span>func</span>

<span># Count number of records with a `first_name` value </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>func</span><span>.</span><span>count</span><span>(</span><span>Customer</span><span>.</span><span>first_name</span><span>))</span>
    <span>.</span><span>all</span><span>()</span>   

<span>for</span> <span>record</span> <span>in</span> <span>records</span><span>:</span>
    <span>print</span><span>(</span><span>record</span><span>)</span>
...
from sqlalchemy import func

# Count number of records with a `first_name` value records = session
    .query(func.count(Customer.first_name))
    .all()   

for record in records:
    print(record)

Enter fullscreen mode Exit fullscreen mode Aggregate queries

Which outputs:


<span>(</span>200,<span>)</span>
<span>(</span>200,<span>)</span>
(200,)

Enter fullscreen mode Exit fullscreen mode Output

This query can easily be modified to only count distinct values:


<span>...</span>
<span>from</span> <span>sqlalchemy</span> <span>import</span> <span>func</span>
<span>from</span> <span>sqlalchemy</span> <span>import</span> <span>distinct</span>
<span># Count number of DISTINCT `first_name` values </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>func</span><span>.</span><span>count</span><span>(</span><span>distinct</span><span>(</span><span>Customer</span><span>.</span><span>first_name</span><span>)))</span>
    <span>.</span><span>all</span><span>()</span>
<span>for</span> <span>record</span> <span>in</span> <span>records</span><span>:</span>
    <span>print</span><span>(</span><span>record</span><span>)</span>
<span>...</span>
<span>from</span> <span>sqlalchemy</span> <span>import</span> <span>func</span>
<span>from</span> <span>sqlalchemy</span> <span>import</span> <span>distinct</span>

<span># Count number of DISTINCT `first_name` values </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>func</span><span>.</span><span>count</span><span>(</span><span>distinct</span><span>(</span><span>Customer</span><span>.</span><span>first_name</span><span>)))</span>
    <span>.</span><span>all</span><span>()</span>

<span>for</span> <span>record</span> <span>in</span> <span>records</span><span>:</span>
    <span>print</span><span>(</span><span>record</span><span>)</span>
...
from sqlalchemy import func
from sqlalchemy import distinct

# Count number of DISTINCT `first_name` values records = session
    .query(func.count(distinct(Customer.first_name)))
    .all()

for record in records:
    print(record)

Enter fullscreen mode Exit fullscreen mode Query to aggregate distinct results

Using Group_by()

Of course, we can use the group_by() method on queries based around aggregates as well. group_by() works similarly to what we’d expect from SQL and Pandas:


<span>...</span>
<span># Execute a `GROUP BY` aggregation query </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>func</span><span>.</span><span>count</span><span>(</span><span>Customer</span><span>.</span><span>first_name</span><span>))</span>
    <span>.</span><span>group_by</span><span>(</span><span>Customer</span><span>.</span><span>first_name</span><span>)</span>
    <span>.</span><span>all</span><span>()</span>
<span>...</span>

<span># Execute a `GROUP BY` aggregation query </span><span>records</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>func</span><span>.</span><span>count</span><span>(</span><span>Customer</span><span>.</span><span>first_name</span><span>))</span>
    <span>.</span><span>group_by</span><span>(</span><span>Customer</span><span>.</span><span>first_name</span><span>)</span>
    <span>.</span><span>all</span><span>()</span>
...

# Execute a `GROUP BY` aggregation query records = session
    .query(func.count(Customer.first_name))
    .group_by(Customer.first_name)
    .all()

Enter fullscreen mode Exit fullscreen mode “Group by” aggregation

Mutations

We’ve spent an awful lot of time going over how to extract data from our database, but haven’t talked about modifying our data yet! The last item on our agenda today is looking at how to add, remove, and change records using the SQLAlchemy ORM.

Inserting Rows

The first way we can add data is by using the add() method. add() expects an instance of a class (data model specifically) to be passed, and will create a new database row as a result:


<span>from</span> <span>.database</span> <span>import</span> <span>session</span>
<span>from</span> <span>.models</span> <span>import</span> <span>Customer</span>
<span># Inserting records via data models </span><span>customer</span> <span>=</span> <span>Customer</span><span>(</span>
    <span>first_name</span><span>=</span><span>'Todd'</span><span>,</span>
    <span>last_name</span><span>=</span><span>'Birchard'</span><span>,</span>
    <span>email</span><span>=</span><span>'fake@example.com'</span><span>,</span>
    <span>preferred_language</span><span>=</span><span>'English'</span><span>,</span>
    <span>join_date</span><span>=</span><span>datetime</span><span>.</span><span>now</span><span>()</span>
<span>)</span>
<span>session</span><span>.</span><span>add</span><span>(</span><span>customer</span><span>)</span>
<span>session</span><span>.</span><span>commit</span><span>()</span>
<span>from</span> <span>.database</span> <span>import</span> <span>session</span>
<span>from</span> <span>.models</span> <span>import</span> <span>Customer</span>

<span># Inserting records via data models </span><span>customer</span> <span>=</span> <span>Customer</span><span>(</span>
    <span>first_name</span><span>=</span><span>'Todd'</span><span>,</span>
    <span>last_name</span><span>=</span><span>'Birchard'</span><span>,</span>
    <span>email</span><span>=</span><span>'fake@example.com'</span><span>,</span>
    <span>preferred_language</span><span>=</span><span>'English'</span><span>,</span>
    <span>join_date</span><span>=</span><span>datetime</span><span>.</span><span>now</span><span>()</span>
<span>)</span>
<span>session</span><span>.</span><span>add</span><span>(</span><span>customer</span><span>)</span>
<span>session</span><span>.</span><span>commit</span><span>()</span>
from .database import session
from .models import Customer

# Inserting records via data models customer = Customer(
    first_name='Todd',
    last_name='Birchard',
    email='fake@example.com',
    preferred_language='English',
    join_date=datetime.now()
)
session.add(customer)
session.commit()

Enter fullscreen mode Exit fullscreen mode Insert records via ORM

An alternative way to add data is by using the insert() method. Unlike add(), insert() is called on an SQLAlchemy Table object and doesn’t rely on receiving a data model. insert() is not part of the ORM:


<span>...</span>
<span># Inserting records via SQLAlchemy `Table` objects </span><span>insert</span> <span>=</span> <span>[</span><span>TABLE</span><span>]</span>
    <span>.</span><span>insert</span><span>()</span>
    <span>.</span><span>values</span><span>(</span>
        <span>first_name</span><span>=</span><span>'Todd'</span><span>,</span>
        <span>last_name</span><span>=</span><span>'Jack Jones'</span><span>,</span>
        <span>email</span><span>=</span><span>'fake@example.com'</span><span>,</span>
        <span>preferred_language</span><span>=</span><span>'English'</span><span>,</span>
        <span>join_date</span><span>=</span><span>datetime</span><span>.</span><span>now</span><span>()</span>
    <span>)</span>
<span>...</span>

<span># Inserting records via SQLAlchemy `Table` objects </span><span>insert</span> <span>=</span> <span>[</span><span>TABLE</span><span>]</span>
    <span>.</span><span>insert</span><span>()</span>
    <span>.</span><span>values</span><span>(</span>
        <span>first_name</span><span>=</span><span>'Todd'</span><span>,</span>
        <span>last_name</span><span>=</span><span>'Jack Jones'</span><span>,</span>
        <span>email</span><span>=</span><span>'fake@example.com'</span><span>,</span>
        <span>preferred_language</span><span>=</span><span>'English'</span><span>,</span>
        <span>join_date</span><span>=</span><span>datetime</span><span>.</span><span>now</span><span>()</span>
    <span>)</span>
...

# Inserting records via SQLAlchemy `Table` objects insert = [TABLE]
    .insert()
    .values(
        first_name='Todd',
        last_name='Jack Jones',
        email='fake@example.com',
        preferred_language='English',
        join_date=datetime.now()
    )

Enter fullscreen mode Exit fullscreen mode Insert records

Updating

Building on the syntax of insert(), we can drop in the update() method to change an existing record’s values. We chain in the where() method to specify which rows should be updated:


<span>...</span>
<span># Updating records via SQLAlchemy `Table` objects </span><span>result</span> <span>=</span> <span>[</span><span>TABLE</span><span>]</span>
    <span>.</span><span>update</span><span>()</span>
    <span>.</span><span>where</span><span>([</span><span>TABLE</span><span>].</span><span>c</span><span>.</span><span>name</span> <span>==</span> <span>'Todd'</span><span>)</span>
    <span>.</span><span>values</span><span>(</span><span>email</span><span>=</span><span>'newemail@example.com'</span><span>)</span>
<span>...</span>

<span># Updating records via SQLAlchemy `Table` objects </span><span>result</span> <span>=</span> <span>[</span><span>TABLE</span><span>]</span>
    <span>.</span><span>update</span><span>()</span>
    <span>.</span><span>where</span><span>([</span><span>TABLE</span><span>].</span><span>c</span><span>.</span><span>name</span> <span>==</span> <span>'Todd'</span><span>)</span>
    <span>.</span><span>values</span><span>(</span><span>email</span><span>=</span><span>'newemail@example.com'</span><span>)</span>
...

# Updating records via SQLAlchemy `Table` objects result = [TABLE]
    .update()
    .where([TABLE].c.name == 'Todd')
    .values(email='newemail@example.com')

Enter fullscreen mode Exit fullscreen mode Update records

Deleting

On any query we execute, we can append the delete() method to delete all rows which are contained in that query (be careful!). The below deletes all records where the first_name column contains a value of “Carl”:


<span>...</span>
<span># Delete records where `first_name` is `Carl` </span><span>result</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>Customer</span><span>)</span>
    <span>.</span><span>filter</span><span>(</span><span>Customer</span><span>.</span><span>first_name</span> <span>==</span> <span>'Carl'</span><span>)</span>
    <span>.</span><span>delete</span><span>()</span>
<span>...</span>

<span># Delete records where `first_name` is `Carl` </span><span>result</span> <span>=</span> <span>session</span>
    <span>.</span><span>query</span><span>(</span><span>Customer</span><span>)</span>
    <span>.</span><span>filter</span><span>(</span><span>Customer</span><span>.</span><span>first_name</span> <span>==</span> <span>'Carl'</span><span>)</span>
    <span>.</span><span>delete</span><span>()</span>
...

# Delete records where `first_name` is `Carl` result = session
    .query(Customer)
    .filter(Customer.first_name == 'Carl')
    .delete()

Enter fullscreen mode Exit fullscreen mode Delete records

delete() accepts the synchronize_session parameter, which determines how deletions should be handled:

False won’t perform the delete until the session is committed.
'fetch' selects all rows to be deleted and removes matched rows.
'evaluate' will evaluate the objects in the current session to determine which rows should be removed.

Never Stop Exploring™

There’s a lot we’ve left out for the sake of simplicity. There are plenty of cool methods left to explore, like the correlate() method, for instance. You’re armed with enough to be dangerous in SQLAlchemy now, but I encourage anybody to look over the query documentation and find the cool things we didn’t speak to in detail here.

I’m still working on throwing together the source code for this post in the Github repo below. Source for the previous chapters can be found there as well. In the meantime, I apologize for being a bit of a shit show:

hackersandslackers / sqlalchemy-tutorial

🧪 Use SQLAlchemy to connect, query, and interact with relational databases.

SQLAlchemy Tutorial

This repository contains the source code for a four-part tutorial series on SQLAlchemy:

Getting Started

Get set up locally in two steps:

Environment Variables

Replace the values in .env.example with your values and rename this file to .env:

SQLALCHEMY_DATABASE_URI: Connection URI of a SQL database.
SQLALCHEMY_DATABASE_PEM (Optional): PEM key for databases requiring an SSL connection.

Remember never to commit secrets saved in .env files to Github.

Installation

Get up and running with make deploy:

$ git clone https://github.com/hackersandslackers/sqlalchemy-tutorial.git
$ cd sqlalchemy-tutorial
$ make deploy

Enter fullscreen mode Exit fullscreen mode

Hackers and Slackers tutorials are free of charge. If you found this tutorial helpful, a small donation would be greatly appreciated to keep us in business. All proceeds go towards coffee, and all coffee goes towards more content.

View on GitHub

Mastering SQLAlchemy (4 Part Series)

原文链接：Queries as Python Code with SQLAlchemy’s Expression Language

展开阅读全文

文章版权声明 1、本网站名称：拾光赋
2、本站永久网址：https://www.blogs.ink
3、本网站的文章部分内容可能来源于网络，仅供大家学习与参考，如有侵权，请联系站长QQ：805375623进行删除处理。
4、本站一切资源不代表本站立场，并不代表本站赞同其观点和对其真实性负责。
5、本站一律禁止以任何方式发布或转载任何违法的相关信息，访客发现请向站长举报
6、本站资源大多存储在云盘，如发现链接失效，请联系我们我们会第一时间更新。

THE END