cmutel

from flowmapper.transformation_mapping import prepare_transformations
from flowmapper import Flow
from flowmapper.utils import load_standard_transformations

our_transform = [{
    "update": [{
        "source":
        {
            "name": "2,4-D",
            "context": "Emissions to air/"

cmutel

{
  "source": {
    "name": "Zinc",
    "context": "water/groundwater, long-term"
  },
  "target": {
    "name": "Zinc, ion",
    "context": ["water", "ground-, long-term"]
  }
}

cmutel

import bw2data as bd
db = bd.Database("Transport routes")
# Compatible with legacy - "new_node" is 2.5 only
my_route = bd.new_activity(
    name="Transport from CN to EU",
    unit="trip",
    code="surf-practice"
)
my_route.save()

cmutel

import csv
import bw2data as bd

bio_db_name = 'ecoinvent-3.10-biosphere'
new_method = ("Something", "Something", "Danger zone")


# Writing
with open(f'{bio_db_name}.csv', 'w', encoding='utf-8') as csvfile:
    fieldnames = ['id', 'name', 'categories', 'unit', 'cf']

cmutel

from typing import List, Optional
from enum import IntEnum
from datetime import datetime

from pydantic import BaseModel, Json, HttpUrl, Field


class BrightwayBase(BaseModel):
    id: int
    name: str

cmutel

import os
import sys
from pathlib import Path
from typing import Union

from lxml import etree, objectify


def fix_version(
    filepath: Union[str, Path],

cmutel

import bw2data as bd
import bw2calc as bc

bd.projects.set_current("ghg-scores")

db = bd.Database("eg")
db.register()

a = db.new_node(code="a", name="a")
a.save()

cmutel

The aim of bw_projects is relatively simple - we want to store data in a SQLite file and in a few subdirectories, and we want to be able to do switch this SQLite file and associated subdirectories whenever we want.

To do this we use peewee as an ORM to SQLite, and its ability to bind ORM tables to a database object after initial import:

    def _create_database(self):
        db = SqliteDatabase(self._filepath)
        for model in self._tables:
            model.bind(db, bind_refs=False, bind_backrefs=False)
 db.connect()

cmutel

#!/usr/bin/env python
from collections import defaultdict
from pathlib import Path
import bw2data as bd
import bw2io as bi
import functools
import pandas as pd
import requests
import tempfile

cmutel

# Reset min/max
for ds in bd.Database("swiss consumption 1.0"):
    for exc in ds.technosphere():
        if exc.get('uncertainty type') == 0 or exc.get('uncertainty_type') == 0:
            exc['minimum'] = exc['maximum'] = np.NaN
            exc.save()

# Get functional unit
ave_hh = bd.get_node(name='ch hh average consumption disaggregated, years 151617')