from collections import ChainMap
from functools import lru_cache
from typing import List
import click
import pycountry
from sdmx.model import Annotation, Code
from message_ix_models.util import as_codes, load_package_data
[docs]@lru_cache()
def get_codes(name: str) -> List[Code]:
"""Return codes for the set `name` in MESSAGE-GLOBIOM scenarios.
The information is read from :file:`data/{name}.yaml`, e.g.
:file:`data/technology.yaml`.
When `name` includes "node", then child codes are automatically populated from the
ISO 3166 database via :mod:`pycountry`. For instance:
.. code-block:: yaml
myregion:
name: Custom region
child: [AUT, SCG]
…results in a region with child codes for Austria (a current country) and the
formerly-existing country Serbia and Montenegro.
Parameters
----------
name : :class:`str`
Any :file:`.yaml` file in the folder :file:`message_ix_models/data/`.
Returns
-------
list of :class:`~sdmx.model.Code`
Every Code has :attr:`id`, :attr:`name`, :attr:`description`, and
:attr:`annotations` attributes. Calling :func:`str` on a code returns its
:attr:`id`.
"""
# Raw contents of the config file
config = load_package_data(name)
if "node" in name:
# Automatically add information for countries within regions in the node
# codelists. Use a ChainMap to combine a the `config` loaded from file and then
# fall back to contents of the pycountry databases.
config = ChainMap(
config,
# Create codes using the ISO database via pycountry
{c.alpha_3: dict(id=c.alpha_3, name=c.name) for c in pycountry.countries},
# Also include historic countries
{
c.alpha_3: dict(id=c.alpha_3, name=c.name)
for c in pycountry.historic_countries
},
)
# Convert to codes
data = as_codes(config)
if name == "technology":
for code in data:
try:
anno = code.pop_annotation(id="vintaged")
except KeyError:
# Default value for 'vintaged'
anno = Annotation(id="vintaged", text=repr(False))
code.annotations.append(anno)
return data
@click.command(name="techs")
@click.pass_obj
def cli(ctx):
"""Export metadata to technology.csv.
This command transforms the technology metadata from the YAML file to CSV format.
"""
import pandas as pd
# Convert each code to a pd.Series
data = []
for code in get_codes("technology"):
# Base attributes
d = dict(id=code.id, name=str(code.name), description=str(code.description))
# Annotations
for anno in ("type", "vintaged", "sector", "input", "output"):
try:
d[anno] = str(code.get_annotation(id=anno).text)
except KeyError:
pass
data.append(pd.Series(d))
# Combine series to a data frame
techs = pd.DataFrame(data)
# Write to file
dest = ctx.get_local_path("technology.csv")
print(f"Write to {dest}")
techs.to_csv(dest, index=None, header=True)
# Print the first few items of the data frame
print(techs.head())