david-andrew

Results:
 [0](WorldEnergyOutlook2023.mmd ¶ 818): The World Energy Outlook 2023 provides insight analysis and strategic insights into every aspect of the global energy system. Against a package of geometrical tensors and flexible energy markets, this work report explores how structural shifts in economies and in energy. Use of shifts the way that the world meets rise demand for energy.

[1](WorldEnergyOutlook2023.mmd ¶ 702): The _World Energy Outlook-2023_ (_WEO-2023_) explores three main scenarios in the analysis in the chapters. These scenarios are not predictions - the IEA does not have a single view on the future of the energy system. The scenarios are:

[2](WorldEnergyOutlook2023.mmd ¶ 47): The topics included in this chapter represent key themes of the _World Energy Outlook 2023_. Further information and background on the IEA Net Zero Roadmap is in _Net Zero Roadmap: A Global Pathway to Keep the 1.5 "C Goal in Reach_ published in September 2023. In addition, a range of supply and demand issues for the oi

david-andrew

geo=[GeoAnnotation(name='iso', display_name=None, description='This dataset utilizes ISO 3166-1 numeric country codes to categorize incidents by country. The value "854" corresponds to Burkina Faso, indicating that the first five rows of data refer to events that occurred in Burkina Faso.', type=<ColumnType.GEO: 'geo'>, geo_type=<GeoType.COUNTRY: 'country'>, primary_geo=None, resolve_to_gadm=None, is_geo_pair=None, coord_format=None, qualifies=None, aliases={}, gadm_level=None), GeoAnnotation(name='region', display_name=None, description='This dataset categorizes various events by their geographical location within the continent of Africa, specifically focusing on the Western Africa region. This area includes countries such as Nigeria, Ghana, Senegal, and others, encompassing a diverse range of cultures, political landscapes, and socio-economic conditions. The data is structured to reflect the occurrences within this specific geographic region, highlighting the unique attributes and challenges faced by Wester

david-andrew

Meta(path=PosixPath('datasets/mock_aqi.csv'), name='Air Quality Index', description='This dataset represents daily air quality observations collected from various monitoring stations across different cities worldwide. Each row corresponds to a single observation with details about the date, time, and location of the observation, along with specific air quality metrics and conditions.')
LLM identified column "year" as a DATE
LLM identified column "month" as a DATE
LLM identified column "day" as a DATE
LLM identified column "time" as a DATE
LLM identified column "lat" as a GEO
LLM identified column "lon" as a GEO
LLM identified column "country" as a GEO
LLM identified column "admin1" as a GEO
LLM identified column "admin2" as a GEO

david-andrew

geo=[GeoAnnotation(name='iso', display_name=None, description='The values in the dataset represent the ISO 3166-1 numeric country codes, which are internationally recognized codes assigned to each country and certain territories. In this context, the number 854 corresponds to Burkina Faso. These codes are used for data exchange and to increase clarity and ensure unambiguity when identifying countries on a global scale.', type=<ColumnType.GEO: 'geo'>, geo_type=<GeoType.COUNTRY: 'country'>, primary_geo=None, resolve_to_gadm=None, is_geo_pair=None, coord_format=None, qualifies=None, aliases={}, gadm_level=None), GeoAnnotation(name='region', display_name=None, description='This dataset categorizes events based on their geographic location within the continent of Africa, specifically focusing on the sub-region of Western Africa. This area includes countries along the Atlantic coast, from the Sahara Desert in the north to the Gulf of Guinea in the south.', type=<ColumnType.GEO: 'geo'>, geo_type=<GeoType.COUNTRY: 'c

david-andrew

Meta(path=PosixPath('datasets/mock_aqi.csv'), name='Air Quality Index', description='This dataset represents daily air quality observations collected from various monitoring stations across different cities worldwide. Each row corresponds to a single observation with details about the date, time, and location of the observation, along with specific air quality metrics and conditions.')
LLM identified column "year" as a DATE
LLM identified column "month" as a DATE
LLM identified column "day" as a DATE
LLM identified column "time" as a DATE
LLM identified column "lat" as a GEO
LLM identified column "lon" as a GEO
LLM identified column "country" as a GEO
LLM identified column "admin1" as a GEO
LLM identified column "admin2" as a GEO

david-andrew

>>> how is climate change expected to affect flooding in ethiopia?
|||| Context free query: climate change impact on flooding in Ethiopia

Answer: Climate change is expected to affect flooding in Ethiopia in several ways. Primarily, it will likely lead to an increased frequency and intensity of extreme hydrologic events, causing more pronounced disastrous floods which can negatively impact the economy and society [0][7]. The country is susceptible to floods, and past events have shown considerable loss of life and property [1]. The median temperature increase for Africa is predicted to be 3-4°C by the end of the 21st century, possibly intensifying evapotranspiration, which may negate any benefits from increased rainfall, thus exacerbating drought and flood conditions [1].

Moreover, variability in rainfall is expected to increase due to climate change, resulting in more frequent droughts and floods [9]. These changes threaten the stability and transformation of Ethiopia's agricultural sector, which is heavily

david-andrew

43.19   Building wheel for GDAL (setup.py): started
45.54   Building wheel for GDAL (setup.py): finished with status 'error'
45.60   error: subprocess-exited-with-error
45.60   
45.60   × python setup.py bdist_wheel did not run successfully.
45.60   │ exit code: 1
45.60   ╰─> [782 lines of output]
45.60       running bdist_wheel
45.60       running build
45.60       running build_py

david-andrew

from typing import TypeVar
from typing_extensions import ParamSpec
_R_co = TypeVar("_R_co", covariant=True)
_P = ParamSpec("_P")

# decorated functions will mantain identical typing to their original form
def myDecorator(func: Callable[_P, _R_co]) -> Callable[_P, _R_co]:
    def wrapper(*args, **kwargs):
        # do wrapper stuff
        return func(*args, **kwargs)

david-andrew

(chatty) david@blade15:~/dev/askem/data-service$ sudo docker-compose logs
Attaching to data-service-api, data-service_graphdb_1, data-service-rdb, data-service_minio_1
data-service-api | Skipping virtualenv creation, as specified in config file.
data-service-api | 
data-service-api | tds is not a package.
data-service-api | Skipping virtualenv creation, as specified in config file.
data-service-api | 
data-service-api | tds is not a package.
data-service-api | Skipping virtualenv creation, as specified in config file.
data-service-api | 

david-andrew

---------------------------------------------------------
data/transition_reports/cb4410en.pdf
(page [0]) Food and Agriculture Organization
(page [0]) of the United Nations
(page [0]) FAOSTAT ANALYTICAL BRIEF 19
(page [0]) Temperature change statistics
(page [0]) 1961–2020
(page [0]) Global, regional and country trends
(page [0]) ISSN 2709-006X [Print] ISSN 2709-0078 [Online]
(page [1]) Temperature change statistics 1961 –2020 - Global, regional and country trends