### Install SDMX from Source (Standard Install)

Source: https://github.com/khaeru/sdmx/blob/main/doc/install.md

Install the sdmx package from the source directory using setup.py. This performs a standard installation.

```bash
python setup.py install
```

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

### Install and Install Pre-commit Hooks

Source: https://github.com/khaeru/sdmx/blob/main/doc/dev.md

Install pre-commit and set up git hooks to ensure code style compliance on each commit.

```shell
pip install pre-commit
pre-commit install
```

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

### Install SDMX Package

Source: https://github.com/khaeru/sdmx/blob/main/doc/install.md

Install the sdmx package using pip. This is the standard method for installing Python packages.

```bash
pip install sdmx1
```

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

### Install SDMX from Source (Editable Mode)

Source: https://github.com/khaeru/sdmx/blob/main/doc/install.md

Install the sdmx package in editable mode from the source directory. This is recommended for development as changes to the code are reflected immediately.

```bash
pip install --editable .
```

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

### Install SDMX with Optional Dependencies

Source: https://github.com/khaeru/sdmx/blob/main/doc/install.md

Install the sdmx package along with optional dependencies for extra features like caching, documentation building, or testing. Use comma-separated values for multiple extras.

```bash
pip install sdmx1[cache]
```

```bash
pip install sdmx1[cache,docs,tests]
```

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

### Install SDMX from Source with Optional Dependencies (Editable)

Source: https://github.com/khaeru/sdmx/blob/main/doc/install.md

Install the sdmx package from source in editable mode, including optional dependencies. This allows for development with extra features enabled.

```bash
pip install --editable .[cache]
```

```bash
pip install --editable .[cache,docs,tests]
```

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

### Install SDMX-ML XML Schema Documents

Source: https://github.com/khaeru/sdmx/blob/main/doc/api.md

Installs SDMX-ML XML Schema documents required for XML validation. You can specify a directory for installation and the version of the schema to download.

```python
import sdmx
from sdmx.util import Version

sdmx.install_schemas(version=Version["3.0.0"])
```

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

### Install Official SDMX Schemas

Source: https://github.com/khaeru/sdmx/blob/main/doc/howto/validate.md

Installs the official SDMX schema files to a local cache for validation. This only needs to be run once per SDMX-ML version.

```python
import sdmx
sdmx.install_schemas()
```

```python
import sdmx
sdmx.install_schemas(version="3.0")
```

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

### BaseWriter Example

Source: https://github.com/khaeru/sdmx/blob/main/doc/api/writer.md

Demonstrates how to create a custom writer by subclassing BaseWriter and registering functions for specific model types.

```python
>>> MyWriter = BaseWriter('my')
```

```python
>>> @MyWriter.register
>>> def _(obj: sdmx.model.ItemScheme):
>>>     ... code to write an ItemScheme ...
>>>     return result
```

```python
>>> @MyWriter.register
>>> def _(obj: sdmx.model.Codelist):
>>>     ... code to write a Codelist ...
>>>     return result
```

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

### sdmx.install_schemas

Source: https://github.com/khaeru/sdmx/blob/main/doc/api.md

Installs SDMX-ML XML Schema documents, which are necessary for validating XML files using `validate_xml()`.

```APIDOC
## sdmx.install_schemas(schema_dir: Path | None = None, version: str | Version = Version.2.1) -> Path

### Description
Install SDMX-ML XML Schema documents for use with [`validate_xml()`](#sdmx.validate_xml).

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Request Example
None

### Response
#### Success Response (200)
* **Path** (Path) - The path containing the installed schemas. If schema_dir is given, the return value is identical to the parameter.

#### Response Example
None
```

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

### Get Dataflows for COMP Source

Source: https://github.com/khaeru/sdmx/blob/main/doc/sources.md

Instantiate the COMP client and retrieve available dataflows. This is useful for identifying available data within the Directorate General for Competition.

```python
COMP = sdmx.Client("COMP")
sm = COMP.dataflow()
print(sm.dataflow)
```

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

### Run SDMX Tests

Source: https://github.com/khaeru/sdmx/blob/main/doc/install.md

Run the test suite for the sdmx package after installing from source. This command executes the tests using pytest.

```bash
pytest
```

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

### Querying Data with Key and Time Period

Source: https://github.com/khaeru/sdmx/blob/main/doc/walkthrough.md

Demonstrates constructing a query for SDMX data by specifying dimension values for the 'CURRENCY' dimension and setting a start period to filter older data.

```python
from sdmx import Client

client = Client()

# Example 1: Key as a list of values for a dimension
client.get(resource_id='EXR', key=['USD', 'JPY'], params={'startPeriod': '2020-01-01'})

# Example 2: Key as a dictionary mapping dimension to value
client.get(resource_id='EXR', key={'CURRENCY': 'USD'}, params={'startPeriod': '2020-01-01'})

# Example 3: Key as a tuple of dimension-value pairs
client.get(resource_id='EXR', key=(('CURRENCY', 'USD'), ('FREQ', 'D')), params={'startPeriod': '2020-01-01'})

# Example 4: Key as a string (for a single dimension)
client.get(resource_id='EXR', key='USD', params={'startPeriod': '2020-01-01'})
```

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

### Clone SDMX Repository

Source: https://github.com/khaeru/sdmx/blob/main/doc/install.md

Clone the sdmx repository from Github to install from source. This is useful for development or accessing the latest code.

```bash
git clone git@github.com:khaeru/sdmx.git
```

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

### Configure HTTP Connection with Proxy

Source: https://github.com/khaeru/sdmx/blob/main/doc/walkthrough.md

Configure the HTTP connection for the SDMX client by passing keyword arguments recognized by requests.request(). This example shows how to specify a proxy server for all outgoing requests.

```python
from sdmx import Client

client = Client(
    'ecb',
    proxies={'http': 'http://user:pass@host:port'}
)

```

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

### Configure IMF SDMX Client for SDMX 3.0.0 API

Source: https://github.com/khaeru/sdmx/blob/main/doc/sources.md

This example demonstrates how to configure an SDMX client to use the SDMX 3.0.0 API provided by sdmxcentral.imf.org. It involves modifying the client's source URL and specifying the desired SDMX version.

```python
import sdmx
from sdmx.format import Version

client = sdmx.Client("IMF")
client.source.url = "https://sdmxcentral.imf.org/sdmx/v2"
client.source.versions = {Version["3.0.0"]}
```

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

### get

Source: https://github.com/khaeru/sdmx/blob/main/doc/api.md

Retrieves an SDMX resource. This method allows fetching specific resources by type and ID, with options for caching and dry runs.

```APIDOC
## get

### Description
Retrieves an SDMX resource by its type and ID. Supports caching and dry run options.

### Method
`get`

### Parameters
* **resource_type** (`str` or `sdmx.Resource` or `None`) - Optional - The type of the resource to retrieve.
* **resource_id** (`str` or `None`) - Optional - The ID of the resource to retrieve.
* **tofile** (`os.PathLike` or `IO` or `None`) - Optional - File path or IO object to save the resource to.
* **use_cache** (`bool`) - Optional - Whether to use the cache for retrieval. Defaults to `False`.
* **dry_run** (`bool`) - Optional - If `True`, returns a `requests.Request` object instead of the message. Defaults to `False`.
* **version** (`str`) - Optional - The version of the resource to retrieve. Defaults to 'latest'.

### Returns
* **`sdmx.message.Message` or `requests.Request`**: The requested SDMX message or a `Request` object if `dry_run` is `True`.

### Raises
* **NotImplementedError**: If the source does not support the given `resource_type` and `force` is not `True`.
```

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

### sdmx.model.common.ComponentList

Source: https://github.com/khaeru/sdmx/blob/main/doc/api/model.md

Represents a list of components, with methods to append, extend, get, and getdefault components. It also includes attributes for annotations, ID, URI, URN, and an auto-order counter.

```APIDOC
## class sdmx.model.common.ComponentList

Bases: [`IdentifiableArtefact`](#sdmx.model.common.IdentifiableArtefact), `Generic`[`CT`]

#### append(value: CT) → None

Append *value* to [`components`](#sdmx.model.common.ComponentList.components).

#### auto_order *= 1*

Counter used to automatically populate [`DimensionComponent.order`](#sdmx.model.common.DimensionComponent.order) values.

#### components *: list[CT]*

#### extend(values: Iterable[CT]) → None

Extend [`components`](#sdmx.model.common.ComponentList.components) with *values*.

#### get(id) → CT

Return the component with the given *id*.

#### getdefault(id, cls=None, **kwargs) → CT

Return or create the component with the given *id*.

If the component is automatically created, its `Dimension.order`
attribute is set to the value of [`auto_order`](#sdmx.model.common.ComponentList.auto_order), which is then incremented.

* **Parameters:**
  * **id** (`str`) – Component ID.
  * **cls** (`type`, *optional*) – Hint for the class of a new object.
  * **kwargs** – Passed to the constructor of [`Component`](#sdmx.model.common.Component), or a Component subclass if
    [`components`](#sdmx.model.common.ComponentList.components) is overridden in a subclass of ComponentList.

#### id *: str*

Unique identifier of the object.

#### uri *: str | None*

Universal resource identifier that may or may not be resolvable.

#### urn *: str | None*

Universal resource name. For use in SDMX registries; all registered objects have
a URN.
```

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

### SDMX Version Patterns

Source: https://github.com/khaeru/sdmx/blob/main/doc/api/model.md

Defines regular expressions for parsing SDMX version strings for versions 2.1 and 3.0. Version 2.1 examples include '1.0', while 3.0 examples can include extensions like '1.0.0-draft'.

```python
import re

VERSION_PATTERNS = {
    '2_1': re.compile('^(?P<release>[0-9]+(?:\\.[0-9]+){1})$'),
    '3_0': re.compile('^(?P<release>[0-9]+(?:\\.[0-9]+){2})(-(?P<ext>.+))?$')
}
```

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

### Access SDMX Data via URL

Source: https://github.com/khaeru/sdmx/blob/main/doc/howto.md

Create an sdmx Client and use the get() method with a URL to access data from any SDMX 2.1 compliant web service.

```python
import sdmx
c = sdmx.Client()
c.get(url='https://sdmx.example.org/path/to/webservice', ...)
```

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

### Request Dataflow with All References

Source: https://github.com/khaeru/sdmx/blob/main/doc/howto.md

Example of requesting a dataflow and its associated objects (DSD, code lists, etc.) using the 'references' parameter set to 'all'. This is efficient for retrieving a complete set of related SDMX objects in a single request.

```python
response = some_agency.dataflow('SOME_ID', params={'references': 'all'})
```

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

### Structure-Specific Data Format Example

Source: https://github.com/khaeru/sdmx/blob/main/doc/walkthrough.md

Shows the more concise structure-specific XML format for SDMX-ML data, which omits explicit identification of dimensions and attributes for smaller message sizes.

```xml
<!-- NB. Other dimensions and attributes omitted: -->
<Obs CURRENCY_DENOM="EUR" OBS_VALUE="0.82363" OBS_STATUS="A" />
```

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

### Generic Data Format Example

Source: https://github.com/khaeru/sdmx/blob/main/doc/walkthrough.md

Illustrates the generic XML format for SDMX-ML data, where values associated with an Observation are explicitly identified as dimensions or attributes.

```xml
<generic:Obs>
    <generic:ObsKey>
      <!-- NB. Other dimensions omitted. -->
      <generic:Value value="EUR" id="CURRENCY_DENOM"/>
      <!-- … -->
    </generic:ObsKey>
    <generic:ObsValue value="0.82363"/>
    <generic:Attributes>
      <!-- NB. Other attributes omitted. -->
      <generic:Value value="A" id="OBS_STATUS"/>
      <!-- … -->
    </generic:Attributes>
  </generic:Obs>
```

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

### Querying UNICEF Data with Dataflow and DSD

Source: https://github.com/khaeru/sdmx/blob/main/doc/sources.md

This example demonstrates how to query data from UNICEF, first by obtaining the data structure definition (DSD) from a specific dataflow, and then using that DSD to query for a particular indicator.

```python
import sdmx

UNICEF = sdmx.Client("UNICEF")

# Use the dataflow ID to obtain the data structure definition
ds d = UNICEF.dataflow("CONSOLIDATED", provider="CD2030").structure[0]

# Use the DSD to construct a query for indicator D5 (“Births”)
client.data("CONSOLIDATED", key=dict(INDICATOR="D5"), dsd=dsd)
```

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

### get(resource_type, resource_id, tofile, use_cache, dry_run, **kwargs)

Source: https://github.com/khaeru/sdmx/blob/main/doc/api.md

Retrieves SDMX data or metadata from the client's source. Resources can be specified by type and ID, or by a resource object. The method supports various options for constraining data, handling files, caching, and dry runs.

```APIDOC
## get(resource_type, resource_id, tofile, use_cache, dry_run, **kwargs)

### Description
Retrieve SDMX data or metadata. (Meta)data is retrieved from the [`source`](sources.md#module-sdmx.source) of the current Client. The item(s) to retrieve can be specified in one of two ways: 1. resource_type, resource_id: These give the type (see [`Resource`](#sdmx.Resource)) and, optionally, ID of the item(s). If the resource_id is not given, all items of the given type are retrieved. 2. a resource object, i.e. a [`MaintainableArtefact`](api/model.md#sdmx.model.common.MaintainableArtefact): resource_type and resource_id are determined by the object’s class and [`id`](api/model.md#sdmx.model.common.IdentifiableArtefact.id) attribute, respectively.

### Method
GET (implied by retrieval operation)

### Endpoint
Not explicitly defined, operates on the client's configured source.

### Parameters
#### Path Parameters
None

#### Query Parameters
* **resource_type** (`str` or [`Resource`](#sdmx.Resource), *optional*) – Type of resource to retrieve.
* **resource_id** (`str`, *optional*) – ID of the resource to retrieve.
* **tofile** (`str` or `PathLike` or file-like object, *optional*) – File path or file-like to write SDMX data as it is received.
* **use_cache** (`bool`, *optional*) – If `True`, return a previously retrieved [`Message`](#sdmx.message.Message) from `cache`, or update the cache with a newly-retrieved Message.
* **dry_run** (`bool`, *optional*) – If `True`, prepare and return a `requests.Request` object, but do not execute the query. The prepared URL and headers can be examined by inspecting the returned object.
* **dsd** ([`DataStructureDefinition`](api/model.md#sdmx.model.common.BaseDataStructureDefinition)) – Existing object used to validate the key argument. If not provided, an additional query executed to retrieve a DSD in order to validate the key.
* **force** (`bool`) – If `True`, execute the query even if the [`source`](sources.md#module-sdmx.source) does not support queries for the given resource_type. Default: `False`.
* **headers** (`dict`) – HTTP headers. Given headers will overwrite instance-wide headers passed to the constructor. Default: `None` to use the default headers of the [`source`](sources.md#module-sdmx.source).
* **key** (`str` or `dict`) – For queries with resource_type=’data’. `str` values are not validated; `dict` values are validated using `make_constraint()`.
* **params** (`dict`) – Query parameters. The [SDMX REST web service guidelines](https://github.com/sdmx-twg/sdmx-rest/tree/master/v2_1/ws/rest/docs) describe parameters and allowable values for different queries. params is not validated before the query is executed.
* **provider** (`str`) – ID of the agency providing the data or metadata. Default: ID of the [`source`](sources.md#module-sdmx.source) agency.
* **resource** ([`MaintainableArtefact`](api/model.md#sdmx.model.common.MaintainableArtefact) subclass) – Object to retrieve. If given, resource_type and resource_id are ignored.

### Request Example
```python
# Example for specifying resource_type and resource_id
client.get(resource_type='data', resource_id='ABS_QGDP_AUS')

# Example for specifying key for data retrieval
client.get(resource_type='data', key={'GEO': ['EL', 'ES', 'IE']})

# Example for specifying key as a string
client.get(resource_type='data', key='....EL+ES+IE')

# Example for specifying optional parameters
client.get(resource_type='metadata', resource_id='CL_ABS', params={'references': 'parentsandsiblings'})
```

### Response
#### Success Response (200)
Returns an SDMX [`Message`](#sdmx.message.Message) object or a `requests.Request` object if `dry_run` is True.

#### Response Example
```json
{
  "message": "SDMX Message Object or Request Object"
}
```
```

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

### Configure HTTP Caching with SQLite

Source: https://github.com/khaeru/sdmx/blob/main/doc/walkthrough.md

Enable and configure HTTP response caching using requests_cache. This example demonstrates how to force requests_cache to use SQLite for storing cached data and set a cache expiration time.

```python
from sdmx import Client

client = Client(
    'ecb',
    use_requests_cache=True,
    cache_name='sdmx-cache',
    expire_after=600,
    fast_save=True
)

```

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

### Convert SDMX to Pandas and then to Excel

Source: https://github.com/khaeru/sdmx/blob/main/doc/howto.md

This snippet shows how to read an SDMX file into a pandas DataFrame and then export it to an Excel file. Ensure you have the necessary libraries (sdmx, pandas, openpyxl) installed.

```python
msg = sdmx.read_sdmx('data.xml')
sdmx.to_pandas(msg).to_excel('data.xlsx')
```

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

### Inspect Code Lists

Source: https://github.com/khaeru/sdmx/blob/main/doc/example.md

Retrieve and inspect code lists from a StructureMessage. This example shows how to get a specific code list and convert it to a pandas Series for easier examination.

```python
from sdmx import Client
from sdmx.message import StructureMessage
from sdmx.util import to_pandas

client = Client("ESTAT")
msg = client.get_structure("UNE_RT_A", idtype="dataflow")

# Get the code list for dimensions like 'GEO'
geo_codelist = msg.get("codelist", "GEO")
print(to_pandas(geo_codelist))

# Get the code list for dimensions like 'UNIT'
unit_codelist = msg.get("codelist", "UNIT")
print(to_pandas(unit_codelist))
```

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

### Create SDMX Client

Source: https://github.com/khaeru/sdmx/blob/main/doc/example.md

Instantiate an SDMX client to interact with a specific data provider's web service. This is the first step for making multiple queries.

```python
from sdmx import Client
client = Client("ESTAT")
```

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

### Example XML Structure Message from UNICEF

Source: https://github.com/khaeru/sdmx/blob/main/doc/sources.md

This is an example of an XML structure message returned by the UNICEF API. It illustrates the format of the structureID and namespace, and the reference to the dataflow.

```xml
<mes:Structure structureID="UNICEF_GLOBAL_DATAFLOW_1_0" namespace="urn:sdmx:org.sdmx.infomodel.datastructure.Dataflow=UNICEF:GLOBAL_DATAFLOW(1.0):ObsLevelDim:TIME_PERIOD" dimensionAtObservation="TIME_PERIOD">
    <com:StructureUsage>
      <Ref agencyID="UNICEF" id="GLOBAL_DATAFLOW" version="1.0"/>
    </com:StructureUsage>
  </mes:Structure>
```

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

### Create and Access Key Values

Source: https://github.com/khaeru/sdmx/blob/main/doc/api/model.md

Demonstrates how to create a Key object with dimension values and access them using dictionary-like syntax.

```python
>>> k = Key(foo=1, bar=2)
>>> k.values['foo']
1
>>> k['foo']
1
```

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

### sdmx.util.requests.save_response

Source: https://github.com/khaeru/sdmx/blob/main/doc/dev.md

Stores a response in the cache of a given session. If requests_cache is not installed, this function has no effect.

```APIDOC
## sdmx.util.requests.save_response(session: [Session], method: str, url: str, content: bytes, headers: dict) -> None

### Description
Store a response in the cache of session.
If `requests_cache` is not available, this has no effect.

### Parameters
#### Path Parameters
- **session** (Session) - Required - The session object to cache the response in.
- **method** (str) - Required - The HTTP method of the request.
- **url** (str) - Required - The URL of the request.
- **content** (bytes) - Required - The content of the response.
- **headers** (dict) - Required - The headers of the response.
```

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

### Query Data Directly via URL

Source: https://github.com/khaeru/sdmx/blob/main/doc/sources.md

This snippet demonstrates querying data directly from a URL using a generic sdmx Client, bypassing source-specific initialization. This is useful when the source does not offer a dedicated client or for direct file access.

```python
c = sdmx.Client()
dm = c.get(url="https://sdds.indec.gob.ar/files/data/IND.XML")
```

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

### sdmx.model.v30.RangePeriod

Source: https://github.com/khaeru/sdmx/blob/main/doc/api/model.md

Represents a time range period in SDMX v3.0, defined by a start and end period.

```APIDOC
## sdmx.model.v30.RangePeriod

### Description
Represents a time range period in SDMX v3.0, defined by a start and end period.

### Attributes
- **valid_from** (str | None): The date from which the period is valid.
- **valid_to** (str | None): The date until which the period is valid.
- **start** ([sdmx.model.common.StartPeriod](#sdmx.model.common.StartPeriod) | None): The start period.
- **end** ([sdmx.model.common.EndPeriod](#sdmx.model.common.EndPeriod) | None): The end period.
```

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

### sdmx.session.Session

Source: https://github.com/khaeru/sdmx/blob/main/doc/api.md

Custom requests.Session with optional caching. Inherits from requests_cache.CacheMixin if requests_cache is installed, otherwise inherits from requests_cache.RequestsSession.

```APIDOC
## sdmx.session.Session

### Description
Custom `requests.Session` with optional caching. If `requests_cache` is installed, this class inherits from `CacheMixin` and caches responses. Otherwise, it inherits only from the `requests_cache`.

### Parameters
* **timeout** (`float`) – Timeout in seconds, used for every request.
* **kwargs** –
  These may include:
  1. Values for any attributes of `requests.Session`, such as `proxies`, `stream`, or `verify`. These are set on the created Session.
  2. Keyword arguments to `CacheMixin` or any `requests_cache` backend. Note that:
     - Unlike `requests_cache`, you must supply `backend="sqlite"` explicitly; otherwise [`sdmx`](#module-sdmx) uses `backend="memory"`.
     - These classes will silently ignore any other/unrecognized keyword arguments.

### Raises
**TypeError** – if `requests_cache` is *not* installed and any parameters are passed except for timeout.
```

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

### Querying Data in Generic Format

Source: https://github.com/khaeru/sdmx/blob/main/doc/walkthrough.md

Demonstrates a basic query to retrieve data in the generic SDMX-ML format.

```python
from sdmx import Client

client = Client()
data_message = client.get(resource_id='EXR', format='xml', params={'startPeriod': '2020-01-01'})
print(data_message.text)
```

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

### ItemScheme Initialization and Item Manipulation

Source: https://github.com/khaeru/sdmx/blob/main/doc/api/model.md

Demonstrates how to initialize an ItemScheme, add items to it, and access them using various methods including direct attribute access, dictionary-like indexing, and the 'in' operator.

```python
>>> foo = ItemScheme(id='foo')
>>> bar = Item(id='bar')
>>> foo.append(bar)
>>> foo
<ItemScheme: 'foo', 1 items>
>>> (foo.bar is bar) and (foo['bar'] is bar) and (bar in foo)
True
```

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

### sdmx.list_sources

Source: https://github.com/khaeru/sdmx/blob/main/doc/api.md

Returns a sorted list of all valid source IDs that can be used to create `Client` instances.

```APIDOC
## sdmx.list_sources()

### Description
Return a sorted list of valid source IDs.

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Request Example
None

### Response
#### Success Response (200)
* **List[str]** - A sorted list of valid source IDs.

#### Response Example
None
```

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

### Get Data Flow Definitions

Source: https://github.com/khaeru/sdmx/blob/main/doc/walkthrough.md

Retrieves definitions for all data flows from a chosen source using the sdmx library. The query returns a Message instance.

```python
from sdmx import Client

client = Client()
flow_msg = client.get("dataflow")
```

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

### sdmx.compare.Options

Source: https://github.com/khaeru/sdmx/blob/main/doc/api.md

Options for a comparison. Configures how two SDMX artefacts are compared, including strictness and handling of implied URNs.

```APIDOC
## sdmx.compare.Options

### Description
Options for a comparison. Configures how two SDMX artefacts are compared, including strictness and handling of implied URNs.

### Attributes
* **allow_implied_urn** (bool) – Objects compare equal even if [`IdentifiableArtefact.urn`](api/model.md#sdmx.model.common.IdentifiableArtefact.urn) is `None` for either or both, so long as the URNs implied by their other attributes—that is, returned by [`sdmx.urn.make()`](#sdmx.urn.make)—are the same. Defaults to `True`.
* **base** (Any) – Base object for a recursive comparison. Used internally for memoization/to improve performance.
* **log_level** (int) – Level for log messages. Defaults to `0`.
* **strict** (bool) – if `True` (the default), then attributes and associated objects must compare exactly equal. If `False`, then `None` values on either side are permitted. Defaults to `True`.
* **verbose** (bool) – Continue comparing even after reaching a definitive `False` result. If [`log_level`](#sdmx.compare.Options.log_level) is not set, `verbose = True` implies `log_level = logging.DEBUG`. Defaults to `False`.

### Methods
#### log(message: str, level: int = 20) → None
Log message on level. level must be at least [`log_level`](#sdmx.compare.Options.log_level).

#### visited(obj) → bool
Return `True` if obj has already be compared.
```

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

### get

Source: https://github.com/khaeru/sdmx/blob/main/doc/api.md

Retrieves an IdentifiableArtefact from the StructureMessage by its ID or object reference. It supports various string formats for IDs, including exact matches, partial URNs, and full URNs.

```APIDOC
## get(obj_or_id: str | IdentifiableArtefact) -> IdentifiableArtefact | None

### Description
Retrieve an IdentifiableArtefact from the StructureMessage using its ID or object reference. This method can handle string inputs that are exact ID matches, partial SDMX URNs, or full SDMX URNs.

### Method
get

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Parameters
- **obj_or_id** (`str` or `IdentifiableArtefact`) - Required - The ID of the artefact as a string or an IdentifiableArtefact object.
  - If an `IdentifiableArtefact` is provided, an object of the same class with a matching ID is returned.
  - If a `str` is provided, it can be an exact match for an `IdentifiableArtefact.id`, part of an SDMX URN (e.g., “FOO(1.2.3)”), or a full SDMX URN.

### Returns
- [`IdentifiableArtefact`](api/model.md#sdmx.model.common.IdentifiableArtefact) - The retrieved IdentifiableArtefact or None if no match is found.

### Raises
- **ValueError** – If there are two or more objects with the same obj_or_id (e.g., two objects of different classes, or two objects of the same class with different maintainer or version).

### Request Example
None provided in source.

### Response
#### Success Response (200)
- **IdentifiableArtefact** - The retrieved artefact.

#### Response Example
None provided in source.
```

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

### Query Data Set with Key and Time Period

Source: https://github.com/khaeru/sdmx/blob/main/doc/example.md

Download a data set for specific countries (Greece, Ireland, Spain) and a specified time period. This uses the 'GEO' dimension key and the 'startPeriod' query parameter.

```python
from sdmx import Client
from sdmx.message import DataMessage

client = Client("ESTAT")

data_key = {
    "geo": ["EL", "IE", "ES"],
    "age": "Y15-74",
    "sex": "T",
    "unit": "PC_ACT",
    "TIME_PERIOD": "2020"
}

dm = client.get_data("UNE_RT_A", key=data_key, params={"startPeriod": "2020"})
assert isinstance(dm, DataMessage)
```

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

### Preview Data and Count Series Keys

Source: https://github.com/khaeru/sdmx/blob/main/doc/api.md

Use preview_data to get a list of SeriesKeys for a given flow_id. The length of this list can be used to count the total number of series.

```python
keys = sdmx.Client('PROVIDER').preview_data('flow')
len(keys)
```

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

### Create Key Instance

Source: https://github.com/khaeru/sdmx/blob/main/doc/api/model.md

Creates an instance of a Key class (e.g., Key, SeriesKey, GroupKey) using provided values. Can optionally extend with missing dimensions.

```python
key = dsd.make_key(sdmx.model.common.Key, {'dim1': 'val1', 'dim2': 'val2'})
```

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

### Select Cross-Section using Pandas xs()

Source: https://github.com/khaeru/sdmx/blob/main/doc/example.md

Use pandas' `xs()` method to select a cross-section of the data based on specific dimension values. This example selects data for 'geo' dimension.

```python
from sdmx import Client
from sdmx.message import DataMessage
from sdmx.util import to_pandas

client = Client("ESTAT")
data_key = {
    "geo": ["EL", "IE", "ES"],
    "age": "Y15-74",
    "sex": "T",
    "unit": "PC_ACT",
    "TIME_PERIOD": "2020"
}
dm = client.get_data("UNE_RT_A", key=data_key, params={"startPeriod": "2020"})
data = to_pandas(dm)

# Select data for Ireland ('IE') from the 'geo' dimension
print(data.xs("IE", level="geo"))
```

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

### Read SDMX from Local File

Source: https://github.com/khaeru/sdmx/blob/main/doc/walkthrough.md

Use sdmx.read_sdmx to load SDMX messages from local files. Ensure the file path is correctly specified.

```python
from sdmx.testing import SpecimenCollection

specimen = SpecimenCollection("/path/to/sdmx-test-data")

with specimen("ECB_EXR/ng-ts.xml") as f:
    sdmx.read_sdmx(f)
```

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

### Record HTTP Responses for Testing

Source: https://github.com/khaeru/sdmx/blob/main/doc/dev.md

Use requests_cache to record HTTP responses from SDMX-REST web services for testing purposes. This example shows how to set up a CachedSession and make a client request to record its response.

```python
from requests_cache import CachedSession
from sdmx import Client

session = CachedSession(
    "./recorded",  # or other path to sdmx-test-data/recorded/
    backend="filesystem",
    serializer="json",
)

# Exactly the client and request to be used in a test/cached
client = sdmx.Client("ISTAT", session=session)
client.dataflow("47_850", params={"references": "datastructure"})
```

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

### sdmx.model.common.BaseContentConstraint

Source: https://github.com/khaeru/sdmx/blob/main/doc/api/model.md

Abstract base class for SDMX 2.1 and 3.0 ContentConstraints.

```APIDOC
## sdmx.model.common.BaseContentConstraint

### Description
Abstract base class for SDMX 2.1 and 3.0 ContentConstraints.

### Class Signature
```python
class BaseContentConstraint
```

### Attributes
This class does not explicitly define attributes in the provided source, but serves as an abstract base for content constraint objects.
```

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

### Select Specific Data Subset

Source: https://github.com/khaeru/sdmx/blob/main/doc/example.md

Select a specific subset of the data based on dimension values. This example filters for aggregate unemployment rates across ages and sexes, expressed as a percentage of the active population.

```python
from sdmx import Client
from sdmx.message import DataMessage
from sdmx.util import to_pandas

client = Client("ESTAT")
data_key = {
    "geo": ["EL", "IE", "ES"],
    "age": "Y15-74",
    "sex": "T",
    "unit": "PC_ACT",
    "TIME_PERIOD": "2020"
}
dm = client.get_data("UNE_RT_A", key=data_key, params={"startPeriod": "2020"})
data = to_pandas(dm)

# Select aggregate unemployment rates
subset = data.loc[("Y15-74", "T", "PC_ACT"), :]
print(subset)
```

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

### Converting Daily Exchange Rate Data to Pandas DataFrame

Source: https://github.com/khaeru/sdmx/blob/main/doc/walkthrough.md

Demonstrates how to select only daily data from a dataset and convert it into a pandas DataFrame using the to_pandas() function.

```python
from sdmx import Client
from sdmx.util import to_pandas

client = Client()
dsd = client.get(resource_id='EXR', resource_type='datastructure')
data_message = client.get(resource_id='EXR', dsd=dsd, params={'startPeriod': '2020-01-01'})

# Select only daily data series
daily_data = [series for series in data_message.series if series.FREQ == 'D']

df = to_pandas(data_message, series_keys=daily_data)
print(df.head())
```

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

### sdmx.urn.make

Source: https://github.com/khaeru/sdmx/blob/main/doc/api.md

Creates an SDMX URN for a given object.

```APIDOC
## sdmx.urn.make

### Description
Create an SDMX URN for obj.

If obj is not [`MaintainableArtefact`](api/model.md#sdmx.model.common.MaintainableArtefact), then maintainable_parent must be supplied in order to construct the URN. If kwargs are supplied, they must be fields/attributes of [`URN`](#sdmx.urn.URN), and override values derived from obj and/or maintainable_parent.

### Returns
String representation of the URN.

### Return type
`str`
```

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

### Expand SDMX URN

Source: https://github.com/khaeru/sdmx/blob/main/doc/api.md

Use this function to get the full URN for a given value. It accepts either a partial URN or a full URN and returns the complete URN string. If the input is not a URN, it is returned unchanged.

```python
>>> expand("Code=BAZ:FOO(1.2.3).BAR")
"urn:sdmx:org.sdmx.infomodel.codelist.Code=BAZ:FOO(1.2.3).BAR"
```

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

### Build SDMX-REST API v2.1.0 URLs

Source: https://github.com/khaeru/sdmx/blob/main/doc/api.md

Utility class for constructing SDMX-REST API v2.1.0 URLs. It provides methods to handle specific parameters for different endpoint types like data, metadata, and structure.

```python
class sdmx.rest.v30.URL(source: [sdmx.source.Source](sources.md#sdmx.source.Source), resource_type: [Resource](#sdmx.Resource), **kwargs)
```

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

### Handle URL Parameters for Registration Endpoints

Source: https://github.com/khaeru/sdmx/blob/main/doc/api.md

Specific method within the URL class to manage parameters tailored for registration endpoints in the SDMX-REST API.

```python
handle_registration()
```

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

### Query Data from AR1 Source

Source: https://github.com/khaeru/sdmx/blob/main/doc/sources.md

This snippet shows how to query data from the AR1 source using its specific resource ID. It demonstrates using a Client initialized with the source ID.

```python
c = sdmx.Client("AR1")
# The URL https://sdds.indec.gob.ar/files/data/IND.XML
dm = c.data("IND.XML")
```

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

### Query Data from a Dataflow

Source: https://github.com/khaeru/sdmx/blob/main/doc/walkthrough.md

Initiates a data query for a dataflow using the Client.get() method with resource_type set to 'data'.

```python
data_msg = client.get("data", dataflow="EXR")
```

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

### Import Annotation from sdmx.model.v21

Source: https://github.com/khaeru/sdmx/blob/main/doc/whatsnew.md

In v2.22.0, Annotation should be imported from sdmx.model.v21. This snippet shows the new way.

```python
from sdmx.model.v21 import Annotation

a = Annotation(id="FOO", ...)
```

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

### Import Annotation from sdmx.model.common

Source: https://github.com/khaeru/sdmx/blob/main/doc/whatsnew.md

Before v2.22.0, Annotation was imported from sdmx.model.common. This snippet shows the old way.

```python
from sdmx.model.common import Annotation

a = Annotation(id="FOO", ...)
```

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

### Run SDMX Source Tests

Source: https://github.com/khaeru/sdmx/blob/main/doc/install.md

Run the sdmx tests, including those that involve retrieving data over a network connection. This is done using the '-m source' flag with pytest.

```bash
pytest -m source
```