### Installing Dependencies for DiffSync Example - Shell

Source: https://github.com/networktocode/diffsync/blob/develop/examples/03-remote-system/README.md

This command installs all necessary Python dependencies listed in the `requirements.txt` file. Running this ensures that the environment has all the prerequisite libraries for interacting with Nautobot and processing data as required by the DiffSync example.

```Shell
pip install -r requirements.txt
```

--------------------------------

### Defining Example Backend Data (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/examples/04-get-update-instantiate/README.md

Defines `BACKEND_DATA_A`, a list of dictionaries representing network device configurations. Each dictionary contains device name, role, interfaces, and site, serving as input for loading into the DiffSync adapter.

```python
BACKEND_DATA_A = [
    {
        "name": "nyc-spine1",
        "role": "spine",
        "interfaces": {"eth0": "Interface 0", "eth1": "Interface 1"},
        "site": "nyc"
    },
    {
        "name": "nyc-spine2",
        "role": "spine",
        "interfaces": {"eth0": "Interface 0", "eth1": "Interface 1"},
        "site": "nyc"
    }
]
```

--------------------------------

### Setting Up Local Docker Environment

Source: https://github.com/networktocode/diffsync/blob/develop/examples/05-nautobot-peeringdb/README.md

These commands set up and interact with a local Docker environment for the Nautobot-PeeringDB synchronization example. The first command starts the Docker containers in detached mode, building images if necessary. The second command provides an interactive Python shell within the running Docker container, allowing for direct execution of the synchronization script.

```bash
docker-compose -f examples/05-nautobot-peeringdb/docker-compose.yml up -d --build
```

```bash
docker exec -it 05-nautobot-peeringdb_example_1 python
```

--------------------------------

### Loading Data into DiffSync Adapter (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/examples/04-get-update-instantiate/README.md

Implements the `load` method for a `BackendA` object, demonstrating how to populate a DiffSync adapter using `get_or_instantiate` and `update_or_instantiate`. It iterates through `BACKEND_DATA_A` to create or update device, site, and interface objects, handling child relationships and avoiding `ObjectAlreadyExists` exceptions.

```python
    def load(self):
        """Initialize the BackendA Object by loading some site, device and interfaces from DATA."""
        for device_data in BACKEND_DATA_A:
            device, instantiated = self.get_or_instantiate(
                self.device, {"name": device_data["name"]}, {"role": device_data["role"]}
            )

            site, instantiated = self.get_or_instantiate(self.site, {"name": device_data["site"]})
            if instantiated:
                device.add_child(site)

            for intf_name, desc in device_data["interfaces"].items():
                intf, instantiated = self.update_or_instantiate(
                    self.interface, {"name": intf_name, "device_name": device_data["name"]}, {"description": desc}
                )
                if instantiated:
                    device.add_child(intf)
```

--------------------------------

### Copying PeeringDB Credentials Example File

Source: https://github.com/networktocode/diffsync/blob/develop/examples/05-nautobot-peeringdb/README.md

This command copies the example environment file for PeeringDB credentials to a new file, `creds.env`, where the user can then place their actual API key. This step is crucial for ensuring good performance and avoiding API rate limiting when interacting with the PeeringDB API.

```bash
cp examples/05-nautobot-peeringdb/creds.example.env examples/05-nautobot-peeringdb/creds.env
```

--------------------------------

### Installing Python Dependencies

Source: https://github.com/networktocode/diffsync/blob/develop/examples/06-ip-prefixes/README.md

Installs the necessary Python packages listed in `requirements.txt` to set up the project environment. It is recommended to perform this within a virtual environment.

```Shell
pip3 install -r requirements.txt
```

--------------------------------

### Installing DiffSync from PyPI (Shell)

Source: https://github.com/networktocode/diffsync/blob/develop/README.md

This shell command installs the DiffSync library from the Python Package Index (PyPI) using `pip`. This is the most common and recommended method for users to obtain the latest stable release of the library, ensuring all dependencies are correctly managed.

```shell
$ pip install diffsync
```

--------------------------------

### Using update_or_instantiate Helper Method (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/examples/04-get-update-instantiate/README.md

Illustrates the use of `update_or_instantiate` to either update an existing `Interface` object or create a new one if it's not found. Similar to `get_or_instantiate`, it returns the object and a boolean indicating creation status, but it requires `attrs` for updates.

```python
obj, created = self.update_or_instantiate(Interface, {"device_name": "test100", "name": "eth0"}, {"description": "Test description"})
```

--------------------------------

### Setting Nautobot Environment Variables - Shell

Source: https://github.com/networktocode/diffsync/blob/develop/examples/03-remote-system/README.md

These commands set environment variables for the Nautobot URL and API token. By default, the example interacts with the public Nautobot sandbox, but these variables allow users to configure their own Nautobot instance for authentication and connection.

```Shell
export NAUTOBOT_URL = "https://demo.nautobot.com"
export NAUTOBOT_TOKEN = "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa"
```

--------------------------------

### Installing DiffSync from GitHub Branch (Shell)

Source: https://github.com/networktocode/diffsync/blob/develop/README.md

This shell command allows users to install the DiffSync library directly from a specific branch on its GitHub repository, such as the `main` branch. This method is useful for developers or users who need to access the latest development version or a specific commit that has not yet been released on PyPI.

```shell
$ pip install git+https://github.com/networktocode/diffsync.git@main
```

--------------------------------

### Using get_or_instantiate Helper Method (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/examples/04-get-update-instantiate/README.md

Demonstrates how to use `get_or_instantiate` to retrieve an existing `Interface` object or create a new one if it doesn't exist. It returns the object and a boolean indicating if it was newly created. This method is useful for preventing `ObjectAlreadyExists` errors when adding potentially duplicate objects.

```python
obj, created = self.get_or_instantiate(Interface, {"device_name": "test100", "name": "eth0"}, {"description": "Test description"})
```

--------------------------------

### Initializing and Loading DiffSync Backends in Python

Source: https://github.com/networktocode/diffsync/blob/develop/examples/01-multiple-data-sources/README.md

This snippet demonstrates how to import, instantiate, and load data into multiple DiffSync backend objects (BackendA, BackendB, BackendC). It then prints the string representation of each loaded backend to show their initial state. This is a prerequisite for comparing and synchronizing the data sources.

```python
from backend_a import BackendA
from backend_b import BackendB
from backend_c import BackendC

# Create each

a = BackendA()
a.load()
print(a.str())

b = BackendB()
b.load()
print(b.str())

c = BackendC()
c.load()
print(c.str())
```

--------------------------------

### Starting Python Interactive Session

Source: https://github.com/networktocode/diffsync/blob/develop/examples/06-ip-prefixes/README.md

Initiates a Python 3 interactive interpreter session, allowing for step-by-step execution of commands and immediate feedback.

```Shell
python3
```

--------------------------------

### Configuring DiffSync Adapter with RedisStore Backend (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/docs/source/core_engine/03-store.md

This example shows how to configure a DiffSync `Adapter` to use the `RedisStore` backend for distributed storage. It requires importing `RedisStore`, initializing it with the Redis host, and then passing the `store` instance to the `Adapter`'s `internal_storage_engine` argument. This setup enables scaling out tasks across different processes or workers.

```python
>>> from diffsync import Adapter
>>> from diffsync.store.redis import RedisStore
>>> store = RedisStore(host="redis host")
>>> adapter = Adapter(internal_storage_engine=store)
>>> type(adapter.store)
<
class 'diffsync.store.local.RedisStore'>
```

--------------------------------

### Defining a System Adapter with DiffSync (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/docs/source/getting_started/01-getting-started.md

This snippet illustrates how to define a system adapter by subclassing `Adapter`. It shows how to reference the top-level models available within the system (e.g., `site`, `device`) and how to define the `top_level` attribute to indicate which models should be the starting points for diff and synchronization operations.

```Python
from diffsync import Adapter


class BackendA(Adapter):
    site = Site
    device = Device

    top_level = ["site"]
```

--------------------------------

### Comparing Data with DiffSync - Python

Source: https://github.com/networktocode/diffsync/blob/develop/examples/03-remote-system/README.md

This command executes the `main.py` script with the `--diff` flag, initiating a comparison between the data in Nautobot and the local JSON file. It reports all differences without making any changes to the remote system, which is useful for previewing synchronization actions.

```Python
### DIFF Compare the data between Nautobot and the local JSON file.
python main.py --diff
```

--------------------------------

### Executing PeeringDB to Nautobot Synchronization

Source: https://github.com/networktocode/diffsync/blob/develop/examples/05-nautobot-peeringdb/README.md

This Python script demonstrates the interactive execution of the PeeringDB to Nautobot synchronization process using the `diffsync` library. It initializes `RedisStore` for internal storage, sets up `PeeringDB` and `NautobotRemote` adapters, loads data from both sources, calculates the differences, and then synchronizes the data from PeeringDB to Nautobot, explicitly skipping deletions.

```python
from adapter_nautobot import NautobotRemote
from adapter_peeringdb import PeeringDB
from diffsync.enum import DiffSyncFlags
from diffsync.store.redis import RedisStore

store_one = RedisStore(host="redis")
store_two = RedisStore(host="redis")

# Initialize PeeringDB adapter, using CATNIX id for demonstration
peeringdb = PeeringDB(
    ix_id=62,
    internal_storage_engine=store_one
)

# Initialize Nautobot adapter, pointing to the demo instance (it's also the default settings)
nautobot = NautobotRemote(
    url="https://demo.nautobot.com",
    token="a" * 40,
    internal_storage_engine=store_two
)

# Load PeeringDB info into the adapter
peeringdb.load()

# We can check the data that has been imported, some as `site` and some as `region` (with the parent relationships)
peeringdb.dict()

# Load Nautobot info into the adapter
nautobot.load()

# Let's diffsync do it's magic
diff = nautobot.diff_from(peeringdb, flags=DiffSyncFlags.SKIP_UNMATCHED_DST)

# Quick summary of the expected changes (remember that delete ones are dry-run)
diff.summary()

# Execute the synchronization
nautobot.sync_from(peeringdb, flags=DiffSyncFlags.SKIP_UNMATCHED_DST)
```

--------------------------------

### Summarizing DiffSync Changes (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/examples/06-ip-prefixes/README.md

Calls the `summary()` method on the `diff` object to get a high-level overview of the proposed changes (creates, updates, deletes, no-changes, skips) that would occur if synchronization were enforced.

```Python
diff.summary()
```

--------------------------------

### Synchronizing Data with DiffSync - Python

Source: https://github.com/networktocode/diffsync/blob/develop/examples/03-remote-system/README.md

This command runs the `main.py` script with the `--sync` flag, which applies the identified differences to Nautobot, updating the remote system to match the local data. It ensures that the Nautobot instance reflects the desired state defined in the local JSON file, with subsequent runs showing no changes if data is consistent.

```Python
### SYNC Update the list of country in Nautobot.
python main.py --sync
```

--------------------------------

### Calculating Differences Between DiffSync Backends A and B in Python

Source: https://github.com/networktocode/diffsync/blob/develop/examples/01-multiple-data-sources/README.md

This snippet calculates and displays the differences between `BackendA` and `BackendB` using the `diff_to()` method. The `diff_to()` method compares the current object (`a`) against the target object (`b`) and returns a DiffSync `Diff` object, which is then printed to show the discrepancies.

```python
diff_a_b = a.diff_to(b)
print(diff_a_b.str())
```

--------------------------------

### Verifying No Differences After Synchronization in Python

Source: https://github.com/networktocode/diffsync/blob/develop/examples/01-multiple-data-sources/README.md

This snippet re-calculates and prints the differences between `BackendA` and `BackendB` after a synchronization operation. The expected output is an empty difference report, confirming that `BackendB` has been successfully updated to match the state of `BackendA`. This serves as a verification step for the synchronization process.

```python
diff_a_b = a.diff_to(b)
print(diff_a_b.str())
```

--------------------------------

### Calculating Differences Between DiffSync Backends B and C in Python

Source: https://github.com/networktocode/diffsync/blob/develop/examples/01-multiple-data-sources/README.md

This snippet calculates and displays the differences between `BackendB` and `BackendC` using the `diff_from()` method. The `diff_from()` method compares the current object (`c`) against the source object (`b`) and returns a DiffSync `Diff` object, which is then printed to show the discrepancies.

```python
diff_b_c = c.diff_from(b)
print(diff_b_c.str())
```

--------------------------------

### Initializing DiffSync Adapter with Default LocalStore Backend (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/docs/source/core_engine/03-store.md

This snippet demonstrates how to initialize a DiffSync `Adapter` instance without explicitly specifying an `internal_storage_engine`. By default, the adapter will use the `LocalStore` backend, which stores all loaded models in local memory. This setup is suitable for single-process operations where all steps share the same memory space.

```python
>>> from diffsync import Adapter
>>> adapter = Adapter()
>>> type(adapter.store)
<
class 'diffsync.store.local.LocalStore'>
```

--------------------------------

### Configuring DiffSync Console Logging Verbosity in Python

Source: https://github.com/networktocode/diffsync/blob/develop/examples/01-multiple-data-sources/README.md

This snippet shows how to configure the verbosity of DiffSync's structured console logging. By calling `enable_console_logging` with `verbosity=0`, only `WARNING` and `ERROR` level logs will be displayed, reducing output noise. Higher verbosity levels (1 for INFO, 2 for DEBUG) can be uncommented as needed for more detailed logging.

```python
from diffsync.logging import enable_console_logging
enable_console_logging(verbosity=0)  # Show WARNING and ERROR logs only
# enable_console_logging(verbosity=1)  # Also include INFO logs
# enable_console_logging(verbosity=2)  # Also include DEBUG logs
```

--------------------------------

### Synchronizing DiffSync Backend A to B in Python

Source: https://github.com/networktocode/diffsync/blob/develop/examples/01-multiple-data-sources/README.md

This snippet demonstrates how to synchronize `BackendB` with the contents of `BackendA` using the `sync_to()` method. After synchronization, it immediately calculates and prints the differences between `a` and `b` again, which should now show no differences if the sync was successful. An alternative approach of passing a pre-calculated diff object is also shown.

```python
a.sync_to(b)
print(a.diff_to(b).str())
# Alternatively you can pass in the diff object from above to prevent another diff calculation
# a.sync_to(b, diff=diff_a_b)
```

--------------------------------

### Synchronizing DiffSync Instances with Callback in Python

Source: https://github.com/networktocode/diffsync/blob/develop/examples/02-callback-function/README.md

This snippet demonstrates how to set up and synchronize two `DiffSync` instances (`ds1` and `ds2`) while utilizing a callback function (`print_callback`) to report progress. It initializes `DiffSync1` and `DiffSync2` with a specified number of records and then performs a `sync_to` operation, enabling console logging for warnings and errors. The `print_callback` function is invoked periodically during the diff and sync stages.

```python
from diffsync.logging import enable_console_logging
from main import DiffSync1, DiffSync2, print_callback

enable_console_logging(verbosity=0)  # Show WARNING and ERROR logs only

# Create a DiffSync1 instance and populate it with records numbered 1-100
ds1 = DiffSync1()
ds1.load(count=100)

# Create a DiffSync2 instance and populate it with 100 random records in the range 1-200
ds2 = DiffSync2()
ds2.load(count=100)

# Identify and attempt to resolve the differences between the two,
# periodically invoking print_callback() as DiffSync progresses
ds1.sync_to(ds2, callback=print_callback)
```

--------------------------------

### Applying Model Flags During Adapter Data Loading (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/docs/source/core_engine/01-flags.md

This example illustrates how to set model-specific flags during the data loading process within a DiffSync adapter. The `IGNORE` flag is applied to `MyDeviceModel` instances identified as 'firewall' devices, preventing DiffSync from rendering diffs or making changes to these specific models. This allows fine-grained control over individual model synchronization.

```python
from diffsync import Adapter
from diffsync.enum import DiffSyncModelFlags
from model import MyDeviceModel


class MyAdapter(Adapter):
    device = MyDeviceModel

    def load(self, data):
        """Load all devices into the adapter and add the flag IGNORE to all firewall devices."""
        for device in data.get("devices"):
            obj = self.device(name=device["name"])
            if "firewall" in device["name"]:
                obj.model_flags = DiffSyncModelFlags.IGNORE
            self.add(obj)
```

--------------------------------

### Initializing and Loading IPAM A Adapter (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/examples/06-ip-prefixes/README.md

Instantiates the `IpamA` DiffSync adapter and then calls its `load()` method to populate the adapter's internal data model with information from the simulated IPAM A system. This prepares the data for comparison.

```Python
ipam_a = IpamA()
ipam_a.load()
```

--------------------------------

### Initializing and Loading IPAM B Adapter (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/examples/06-ip-prefixes/README.md

Instantiates the `IpamB` DiffSync adapter and loads its data from the simulated IPAM B system. This prepares the second dataset for comparison with IPAM A.

```Python
ipam_b = IpamB()
ipam_b.load()
```

--------------------------------

### Displaying Loaded Data from IPAM A (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/examples/06-ip-prefixes/README.md

Imports the `pprint` module for pretty-printing and then displays the dictionary representation of the data loaded into the `ipam_a` adapter. This shows how the original YAML data has been transformed into the DiffSync model.

```Python
import pprint
pprint.pprint(ipam_a.dict())
```

--------------------------------

### Displaying Loaded Data from IPAM B (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/examples/06-ip-prefixes/README.md

Uses `pprint` to display the dictionary representation of the data loaded into the `ipam_b` adapter, demonstrating its transformation into the DiffSync model, similar to IPAM A.

```Python
pprint.pprint(ipam_b.dict())
```

--------------------------------

### Importing DiffSync IPAM Adapters (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/examples/06-ip-prefixes/README.md

Imports the `IpamA` and `IpamB` classes, which are custom DiffSync adapters designed to interact with simulated IPAM systems A and B, respectively. These adapters facilitate data loading and synchronization.

```Python
from adapter_ipam_a import IpamA
from adapter_ipam_b import IpamB
```

--------------------------------

### Visualizing DiffSync Model Traversal Order (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/docs/source/getting_started/01-getting-started.md

This snippet illustrates how to use the Adapter.get_tree_traversal() class method to obtain a string representation of the model processing order. This helper method provides a clear visualization of the hierarchical traversal sequence, which is useful for understanding how models will be synchronized. It can also return a dictionary if as_dict=True is passed.

```Python
from nautobot_device_onboarding.network_importer.adapters.network_device.adapter import NetworkImporterAdapter
print(NetworkImporterAdapter.get_tree_traversal())
```

--------------------------------

### Comparing and Synchronizing Data with DiffSync (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/README.md

This Python snippet demonstrates the core functionality of DiffSync. It shows how to load data from two distinct systems (A and B), calculate the differences between them using `diff_from()`, and then apply synchronization changes in both directions using `sync_from()` and `sync_to()` methods. This process allows for identifying discrepancies and updating datasets to align with each other.

```python
A = DiffSyncSystemA()
B = DiffSyncSystemB()

A.load()
B.load()

# Show the difference between both systems, that is, what would change if we applied changes from System B to System A
diff_a_b = A.diff_from(B)
print(diff_a_b.str())

# Update System A to align with the current status of system B
A.sync_from(B)

# Update System B to align with the current status of system A
A.sync_to(B)
```

--------------------------------

### Validating Synchronization (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/examples/06-ip-prefixes/README.md

Reloads `ipam_b` into a new adapter instance (`new_ipam_b`) and then recalculates the differences between `ipam_a` and `new_ipam_b`. A successful synchronization is confirmed if the `diff.summary()` shows zero creates, updates, or deletes.

```Python
new_ipam_b = IpamB()
new_ipam_b.load()
diff = ipam_a.diff_to(new_ipam_b)
diff.summary()
```

--------------------------------

### Implementing Bulk Sync Completion Logic in DiffSync Adapter (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/docs/source/getting_started/01-getting-started.md

This snippet illustrates how to implement the `sync_complete()` callback method within a `DiffSync Adapter` class. This method is automatically invoked by DiffSync after all individual create/update/delete operations are performed, providing a convenient point for bulk updates to the remote system, such as writing to a file.

```python
class BackendA(Adapter):
    [...]

    def sync_complete(self, source: Adapter, diff: Diff, flags: DiffSyncFlags, logger: structlog.BoundLogger):
        ## TODO add your own logic to update the remote system now.
        # The various parameters passed to this method are for your convenience in implementing more complex logic, and
        # can be ignored if you do not need them.
        #
        # The default Adapter.sync_complete() method does nothing, but it's always a good habit to call super():
        super().sync_complete(source, diff, flags, logger)
```

--------------------------------

### Handling RedisStore Connection Errors in DiffSync (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/docs/source/core_engine/03-store.md

This snippet illustrates the exception raised when `RedisStore` fails to connect to the specified Redis host during initialization. It shows that a `redis.exceptions.ConnectionError` will occur, which is then re-raised as a `diffsync.exceptions.ObjectStoreException` indicating that the Redis store is unavailable. This highlights the importance of ensuring Redis host reachability before initializing the store.

```python
>>> from diffsync.store.redis import RedisStore
>>> store = RedisStore(host="redis host")
redis.exceptions.ConnectionError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/chadell/github.ntc/diffsync/diffsync/store/redis.py", line 34, in __init__
    raise ObjectStoreException("Redis store is unavailable.") from RedisConnectionError
diffsync.exceptions.ObjectStoreException: Redis store is unavailable.
```

--------------------------------

### Defining DiffSync Models and Adapter for Traversal Order (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/docs/source/getting_started/01-getting-started.md

This snippet demonstrates how to define DiffSyncModel classes with _children attributes to establish hierarchical relationships and how to configure an Adapter class with top_level models. These definitions dictate the "Preorder Tree Traversal" processing order for synchronization operations. It shows the structure for Site, Device, Vlan, Prefix, Interface, IPAddress, and Cable models, and their inclusion in the Nautobot adapter.

```Python
class Site(DiffSyncModel):
    _children = {"vlan": "vlans", "prefix": "prefixes"}
    [...]

class Device(DiffSyncModel):
    _children = {"interface": "interfaces"}
    [...]

class Vlan(DiffSyncModel):
    [...]

class Prefix(DiffSyncModel):
    [...]

class Interface(DiffSyncModel):
    _children = {"ip_address": "ip_addresses"}
    [...]

class IPAddress(DiffSyncModel):
    [...]

class Cable(DiffSyncModel):
    [...]


class Nautobot(Adapter):
    site = Site
    device = Device
    interface = Interface
    ip_address = IPAddress
    cable = Cable
    vlan = Vlan
    prefix = Prefix

    top_level = ["site", "device", "cable"]
    [...]
```

--------------------------------

### Defining a Data Model with DiffSyncModel (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/docs/source/getting_started/01-getting-started.md

This snippet demonstrates how to define a data model using `DiffSyncModel`. It shows the use of class-level attributes like `_modelname`, `_identifiers`, `_attributes`, and `_children` to specify the model's type, primary keys, comparable attributes, and child relationships. It also illustrates how fields not listed in these attributes are ignored during comparison.

```Python
from typing import List, Optional
from diffsync import DiffSyncModel

class Site(DiffSyncModel):
    _modelname = "site"
    _identifiers = ("name",)
    _shortname = ()
    _attributes = ("contact_phone",)
    _children = {"device": "devices"}

    name: str
    contact_phone: Optional[str]
    devices: List = list()
    database_pk: Optional[int]  # not listed in _identifiers/_attributes/_children as it's only locally significant
```

--------------------------------

### Adding and Relating DiffSync Models in Adapter Cache (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/docs/source/getting_started/01-getting-started.md

This snippet demonstrates how to populate an Adapter's local cache by adding DiffSyncModel objects using the self.add() method within the load() function. It shows two scenarios: adding an independent object (site) and adding a child object (device) while establishing its relationship to a parent (site) using add_child() and update(). This process prepares the in-memory data for synchronization.

```Python
class BackendA(Adapter):
    [...]

    def load(self):
        # Store an individual object
        site = self.site(name="nyc")
        self.add(site)

        # Store an object and define it as a child of another object
        device = self.device(name="rtr-nyc", role="router", site_name="nyc")
        self.add(device)
        site.add_child(device)
        site.update()
```

--------------------------------

### Calculating Differences with DiffSync (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/examples/06-ip-prefixes/README.md

Calculates the differences between `ipam_a` and `ipam_b` using `diff_to()`. This method determines what changes would be needed in `ipam_b` to match the state of `ipam_a`, from `ipam_a`'s perspective.

```Python
diff = ipam_a.diff_to(ipam_b)
```

--------------------------------

### Implementing CRUD Operations for DiffSyncModel in Python

Source: https://github.com/networktocode/diffsync/blob/develop/docs/source/getting_started/01-getting-started.md

This snippet demonstrates how to extend a `DiffSyncModel` class to define custom `create`, `update`, and `delete` methods. These methods are responsible for interacting with the remote system to persist changes, while also calling their `super()` counterparts to maintain the in-memory DiffSyncModel instance.

```python
class Device(DiffSyncModel):
    [...]

    @classmethod
    def create(cls, adapter, ids, attrs):
        ## TODO add your own logic here to create the device on the remote system
        # Call the super().create() method to create the in-memory DiffSyncModel instance
        return super().create(ids=ids, adapter=adapter, attrs=attrs)

    def update(self, attrs):
        ## TODO add your own logic here to update the device on the remote system
        # Call the super().update() method to update the in-memory DiffSyncModel instance
        return super().update(attrs)

    def delete(self):
        ## TODO add your own logic here to delete the device on the remote system
        # Call the super().delete() method to remove the DiffSyncModel instance from its parent DiffSync adapter
        super().delete()
        return self
```

--------------------------------

### Defining Python Project Dependencies

Source: https://github.com/networktocode/diffsync/blob/develop/docs/requirements.txt

This snippet lists the Python packages and their exact versions required for the project. It ensures that all developers and deployment environments use the same dependency versions, preventing compatibility issues and ensuring consistent builds.

```Python
m2r2==0.3.3.post2
mistune==0.8.4
sphinx==6.2.1
toml==0.10.2
sphinx-rtd-theme==2.0.0
```

--------------------------------

### Displaying Detailed DiffSync Changes (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/examples/06-ip-prefixes/README.md

Uses `pprint` to show the granular details of the differences found by DiffSync. The `'+'` symbol indicates additions or changes from the source, while `'-'` indicates deletions or changes in the target, highlighting specific attribute modifications.

```Python
pprint.pprint(diff.dict())
```

--------------------------------

### Enforcing Synchronization with DiffSync (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/examples/06-ip-prefixes/README.md

Applies the calculated differences from `ipam_a` to `ipam_b` using `sync_to()`. This operation modifies the state of the destination target (`ipam_b`) to match the source (`ipam_a`).

```Python
ipam_a.sync_to(ipam_b)
```

--------------------------------

### Enabling DiffSync Flags using Bitwise OR in Python

Source: https://github.com/networktocode/diffsync/blob/develop/docs/source/core_engine/01-flags.md

This snippet demonstrates how to enable a flag using the bitwise OR (`|=`) operator. This method ensures that other flags' values remain unchanged while adding a new flag. It shows how to initialize flags and then add `SKIP_UNMATCHED_DST` to `CONTINUE_ON_FAILURE`.

```Python
from diffsync.enum import DiffSyncFlags
flags = DiffSyncFlags.CONTINUE_ON_FAILURE
flags
bin(flags.value)
flags |= DiffSyncFlags.SKIP_UNMATCHED_DST
flags
bin(flags.value)
```

--------------------------------

### Handling Optional Fields with Pydantic v2 in DiffSync Models (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/docs/source/upgrading/01-upgrading-to-2.0.md

This snippet illustrates the change required for `Optional` fields when upgrading to Pydantic v2. Previously, `Optional[int]` was sufficient, but now an explicit `None` default (`Optional[int] = None`) is required for such fields in `DiffSyncModel` definitions. This ensures compatibility with Pydantic's stricter validation rules.

```Python
from typing import Optional

from diffsync import DiffSyncModel

# Before
class Person(DiffSyncModel):
    _identifiers = ("name",)
    _attributes = ("age",)

    name: str
    age: Optional[int]

# After
class BetterPerson(DiffSyncModel):
    _identifiers = ("name",)
    _attributes = ("age",)

    name: str
    age: Optional[int] = None
```

--------------------------------

### Checking DiffSync Flag Status using Bitwise AND in Python

Source: https://github.com/networktocode/diffsync/blob/develop/docs/source/core_engine/01-flags.md

This snippet illustrates how to check if a specific flag is enabled using the bitwise AND (`&`) operator. The result of the AND operation can be wrapped in `bool()` to convert it into a true/false conditional, useful for control flow. It demonstrates checking a flag before and after it's set.

```Python
from diffsync.enum import DiffSyncFlags
flags = DiffSyncFlags.NONE
bool(flags & DiffSyncFlags.CONTINUE_ON_FAILURE)
flags |= DiffSyncFlags.CONTINUE_ON_FAILURE
bool(flags & DiffSyncFlags.CONTINUE_ON_FAILURE)
```

--------------------------------

### Setting Global Flags for DiffSync Operations (Python)

Source: https://github.com/networktocode/diffsync/blob/develop/docs/source/core_engine/01-flags.md

This snippet demonstrates how to define and apply a global flag, `SKIP_UNMATCHED_DST`, when performing a `diff_from` operation using DiffSync. The flag instructs the engine to ignore objects that only exist in the target adapter, preventing their deletion. This is useful for controlling synchronization behavior at a global level.

```python
from diffsync.enum import DiffSyncFlags
flags = DiffSyncFlags.SKIP_UNMATCHED_DST
diff = nautobot.diff_from(local, flags=flags)
```

--------------------------------

### Customizing Diff Element Processing Order in DiffSync with Python

Source: https://github.com/networktocode/diffsync/blob/develop/docs/source/core_engine/02-customize-diff-class.md

This Python class, `MixedOrderingDiff`, extends the base `Diff` class to provide custom ordering logic for diff elements. It defines `order_children_default` to sort all children alphabetically and `order_children_device` to specifically sort device objects by their CRUD action (create, update, delete) before alphabetical sorting, ensuring a predictable processing sequence.

```Python
class MixedOrderingDiff(Diff):
    """Alternate diff class to list children in alphabetical order, except devices to be ordered by CRUD action."""

    @classmethod
    def order_children_default(cls, children):
        """Simple diff to return all children in alphabetical order."""
        for child_name, child in sorted(children.items()):
            yield children[child_name]

    @classmethod
    def order_children_device(cls, children):
        """Return a list of device sorted by CRUD action and alphabetically."""
        children_by_type = defaultdict(list)

        # Organize the children's name by action create, update or delete
        for child_name, child in children.items():
            action = child.action or "skip"
            children_by_type[action].append(child_name)

        # Create a global list, organized per action
        sorted_children = sorted(children_by_type["create"])
        sorted_children += sorted(children_by_type["update"])
        sorted_children += sorted(children_by_type["delete"])
        sorted_children += sorted(children_by_type["skip"])

        for name in sorted_children:
            yield children[name]
```

--------------------------------

### Using a Custom Diff Class with DiffSync Operations in Python

Source: https://github.com/networktocode/diffsync/blob/develop/docs/source/core_engine/02-customize-diff-class.md

This snippet demonstrates how to pass a custom `Diff` class, `AlphabeticalOrderDiff`, to DiffSync operations like `diff_from`. By specifying `diff_class` during the call, the generated diff object will be an instance of the provided custom class, allowing for customized behavior such as element ordering.

```Python
from diffsync.enum import DiffSyncFlags
from diff import AlphabeticalOrderDiff
diff = remote_adapter.diff_from(local_adapter, diff_class=AlphabeticalOrderDiff)
type(diff)
<class 'AlphabeticalOrderDiff'>
```

--------------------------------

### Disabling DiffSync Flags using Bitwise AND NOT in Python

Source: https://github.com/networktocode/diffsync/blob/develop/docs/source/core_engine/01-flags.md

This snippet shows how to disable an enabled flag using the bitwise AND NOT (`&= ~`) operator. This operation effectively unsets a specific flag while preserving the state of other flags. It demonstrates setting multiple flags, then unsetting one and verifying the change.

```Python
from diffsync.enum import DiffSyncFlags
flags = DiffSyncFlags.NONE
# Setting the flags SKIP_UNMATCHED_DST and CONTINUE_ON_FAILURE
flags |= DiffSyncFlags.SKIP_UNMATCHED_DST | DiffSyncFlags.CONTINUE_ON_FAILURE
flags
bool(flags & DiffSyncFlags.SKIP_UNMATCHED_DST)
# Unsetting the flag SKIP_UNMATCHED_DST; CONTINUE_ON_FAILURE remains set
flags &= ~DiffSyncFlags.SKIP_UNMATCHED_DST
flags
bool(flags & DiffSyncFlags.SKIP_UNMATCHED_DST)
```

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