Unit 2: Getting Started With pysdmx

In this unit, we'll go over how to install pysdmx and how to verify installation once complete.

Installing pysdmx

You have two options for installing pysdmx. Let's look at each of them.

Select each option to learn more.

pip install pysdmx

pip install pysdmx[all]

pip install "pysdmx[all]"

Verifying pysdmx installation

To verify if everything is working correctly, let's connect to the SDMX Global Registry and retrieve some ESTAT metadata.

Call the SDMX Global Registry and retrieve ESTAT categories using an asynchronous API call:

import os
from pysdmx.api.fmr import AsyncRegistryClient

# A simple pysdmx example to call a registry.
endpoint = "https://registry.sdmx.org/sdmx/v2"      # SDMX global registry

client = AsyncRegistryClient(endpoint)
cs = await client.get_categories("ESTAT", "ESA2010TP")

Output:
NAMAIN_T0110_Q
NASU_1719PR_5
NAMAIN_T0101_Q
NASEC_T0621_A
NAMAIN_T0111_Q
NAMAIN_T0101_Q …

# Let's see the list of dataflows - the ID and Name
for flow in cs.dataflows:
    # os.mkdir(flow.id)
    print(flow.id, " : ", flow.name)

Output:
NAMAIN_T0110_Q : NAMAIN_T0110_Q
NASU_1719PR_5 : NASU_1719PR_5
NAMAIN_T0101_Q : NAMAIN_T0101_Q
NASEC_T0621_A : NASEC_T0621_A
NAMAIN_T0111_Q : NAMAIN_T0111_Q …

# Now, let's see the categories - both ID and DESCRIPTION
for category in cs.categories:
    print("\n", category.name, " : ", category.description)

Output:

Main aggregates  :  Table 1 — Main aggregates — quarterly and annual exercise
Table 3 — Tables by industry
Table 5 — Household final consumption expenditure
Table 20 — Cross classification of fixed assets by industry and by asset (stocks)
Table 22 — Cross classification of gross fixed capital formation (GFCF) by industry and by asset (transactions)
…

What do you know?

Now that you've completed our introduction and some information on getting started with pysdmx, try this question. Which of the following statements are true?

Select your answer and then select Submit.

Coming next

In this next unit, you'll learn about reading and writing SDMX datasets using pysdmx.