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biotrade-0.0.23
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مشاهده بیشترتوضیحات
Agriculture and forestry statistics.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | biotrade-0.0.23 |
| نام | biotrade |
| نسخه کتابخانه | 0.0.23 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Paul Rougieux, Selene Patani |
| ایمیل نویسنده | paul.rougieux@gmail.com |
| آدرس صفحه اصلی | https://gitlab.com/bioeconomy/forobs/biotrade/ |
| آدرس اینترنتی | https://pypi.org/project/biotrade/ |
| مجوز | MIT |
The `biotrade` package analyses international trade of bio-based products. It focuses on
the agriculture and forestry sectors, from primary production to secondary products
transformation. It loads bilateral trade data from UN Comtrade, production and trade
data from FAOSTAT and socio-economic indicators from the World Bank.
Extraction rates and waste of supply are taken from the FAO, technical conversion
factors for agricultural commodities available at:
https://www.fao.org/economic/the-statistics-division-ess/methodology/methodology-systems/technical-conversion-factors-for-agricultural-commodities/ar/
# Installation
## Base installation
Install from the main branch of a private repo on gitlab using an
[authentication
token](https://docs.gitlab.com/ee/user/project/deploy_tokens/index.html). The tokens
will not be necessary once biotrade becomes publicly available.
pip install git+https://<token>@gitlab.com/bioeconomy/forobs/biotrade.git@main
To install a previous version specify the git tag, for example v0.0.1
pip install git+https://<token>@gitlab.com/bioeconomy/forobs/biotrade.git@v0.0.1
To install the latest development version, use also the `--upgrade` flag:
pip install --upgrade --force-reinstall git+https://<token>@gitlab.com/bioeconomy/forobs/biotrade.git@dev
## Installation for contributors
If you plan to contribute to the development of the biotrade package, clone the
repository and tell python where it is located by adding it to your PYTHONPATH. You can
do this by changing the environment variables or by adding the following line to your
shell configuration file such as `.bash_aliases`:
export PYTHONPATH="$HOME/repos/biotrade/":$PYTHONPATH
Specify where you want to store the data by adding the following environment variable:
export BIOTRADE_DATA="$HOME/repos/biotrade_data/"
Dependencies are listed in the `install_requires` argument of [setup.py](setup.py).
# Usage
The biotrade package can download data from FAOSTAT and UN Comtrade and store it inside
a database. By default it will use an SQLite database stored locally in the folder
defined by the environment variable `BIOTRADE_DATA`. Alternatively, a PostGRESQL
database can be used if a connection string is defined in the environment variable
`BIOTRADE_DATABASE_URL`, for example by adding the following to your .bash_aliases or
.bash_rc:
export BIOTRADE_DATABASE_URL="postgresql://user@localhost/biotrade"
Note that database queries are abstracted with [SQL
Alchemy](https://www.sqlalchemy.org/) which is what makes it possible to use different
database engines. SQLite is convenient for data analysis on laptops. PostGreSQL can be
used on servers.
## FAOSTAT
Faostat provides agriculture and forestry data on their website https://www.fao.org/faostat/en/#data/
The biotrade package has a `faostat.pump` object that loads a selection of datasets. The
list of downloaded datasets is visible in `faostat.pump.datasets`. Column names and
product descriptions are reformatted to snake case in a way that is convenient for
analysis. The data is then stored into an SQLite database (or PostgreSQL). The following
commands download and transfer the given datasets to the database:
>>> from biotrade.faostat import faostat
>>> faostat.pump.update(["crop_production", "crop_trade"])
>>> faostat.pump.update(["forestry_production", "forestry_trade", "forest_land"])
>>> faostat.pump.update(["food_balance"])
>>> faostat.pump.update(["land_use", "land_cover"])
List available datasets and metadata links:
>>> faostat.pump.datasets
>>> faostat.pump.metadata_link
Once the data has been loaded into the database, you can query it. For example select
crop production data for 2 countries
>>> from biotrade.faostat import faostat
>>> db = faostat.db_sqlite
>>> cp2 = db.select(table="crop_production",
>>> reporter=["Portugal", "Estonia"])
Select forestry trade flows data reported by all countries, with
Austria as a partner country:
>>> ft_aut = db.select(table="forestry_trade",
>>> partner=["Austria"])
Select crop trade flows reported by the Netherlands where Brazil was a
partner
>>> ct_nel_bra = db.select(table="crop_trade",
>>> reporter="Netherlands",
>>> partner="Brazil")
Select the mirror flows reported by Brazil, where the Netherlands was a partner
>>> ct_bra_bel = db.select(table="crop_trade",
>>> reporter="Brazil",
>>> partner="Netherlands")
Select land use and land cover data
>>> lu = faostat.db.select("land_use")
>>> lc = faostat.db.select("land_cover")
## Comtrade
See the documentation of the various methods. As an example here is how to download
trade data from the Comtrade API and return a data frame, for debugging purposes:
>>> from biotrade.comtrade import comtrade
>>> # Other sawnwood
>>> swd99 = comtrade.pump.download(cc = "440799")
>>> # Soy
>>> soy = comtrade.pump.download(cc = "120190")
Display information on column names used for renaming
and dropping less important columns:
>>> comtrade.column_names
Get the list of products from the Comtrade API
>>> hs = comtrade.pump.get_parameter_list("classificationHS.json")
Get the list of reporter and partner countries
>>> comtrade.pump.get_parameter_list("reporterAreas.json")
>>> comtrade.pump.get_parameter_list("partnerAreas.json")
# Metadata and configuration data
## Release dates
FAOSTAT release dates are available at :
https://fenixservices.fao.org/faostat/static/releasecalendar/Default.aspx
## Variable definitions and harmonization
Column names and product descriptions are reformatted to snake case in a way that is
convenient for analysis. See example below.
- Variables are defined and compared between the data sources in a notebook called
[definitions_and_harmonization](notebooks/definitions_and_harmonization.md)
- Variable names are harmonized between the different sources using a mapping table
defined in
[biotrade/config_data/column_names.csv](https://gitlab.com/bioeconomy/biotrade/-/blob/main/biotrade/config_data/column_names.csv)
See for example how the `product_code` column is called `PRODUCT_NC` in Eurostat Comext,
`commodity_code` or `cmdcode` in UN Comtrade and `item_code` in FAOSTAT.
- `snake_case` is the preferred way of naming files and variables in the code. This
follows the R [tidyverse style guide for object
names](https://style.tidyverse.org/syntax.html) and the python [PEP
8](https://www.python.org/dev/peps/pep-0008/#function-and-variable-names) style guide
for function and variable names.
To illustrate the advantage of using snake case for data exploration, compare the use of
column names with space which have to be quoted. Python
>>> df["Product Code"]
>>> df.product_code
R
R> df["Product Code"]
R> df$`Product Code`
R> df$product_code
## Configuration data
The `biotrade` package stores a small amount of configuration data such as country and
product mapping tables and conversion coefficients in the `biotrade/config_data` folder.
- FAOSTAT country and product mapping tables are accessible under the FAO Creative
Commons 3.0 Intergovernmental Organization (IGO) licence mentionned in the FAO open
access policy https://www.fao.org/3/I9461EN/I9461en.pdf
- The Table "Extraction rates and value shares of major oil crops" comes from a JRC
technical report: Cuypers, Dieter, Theo Geerken, Leen Gorissen, Arnoud Lust, Glen
Peters, Jonas Karstensen, Sylvia Prieler, G. Fischer, Eva Hizsnyik, and Harrij Van
Velthuizen. "The impact of EU consumption on deforestation: Comprehensive analysis of
the impact of EU consumption on deforestation." (2013).
https://ec.europa.eu/environment/forests/pdf/1.%20Report%20analysis%20of%20impact.pdf
# Licence
This software is licenced under the MIT licence.
See the [LICENCE.md](LICENCE.md) file.
# Similar projects
- The python package [pandas-datareader](https://pydata.github.io/pandas-datareader/)
- The R packages FAOSTAT and WDI
# Tests
This package uses pytest for unit testing. Run the test suite with
pytest
Run pytest with code coverage
cd python_project_dir
coverage run --source=. -m pytest
Followed by
coverage html
To generate a report.
These tests are run as part of the Continuous Integration.
# Acknowledgements
The authors would like to acknowledge ideas and feedback received from the following
persons: Lucas Sinclair, Roberto Pilli, Mirco Migliavacca, Giovanni Bausano.
Noemi Cazzaniga's package [eurostat](https://pypi.org/project/eurostat/) was taken as an
inspiration to load Eurostat data from the bulk download repository.
نیازمندی
| مقدار | نام |
|---|---|
| - | pandas |
| - | sqlalchemy |
| - | sqlalchemy-utils |
| - | psycopg2 |
| - | requests |
| - | fastapi |
| - | uvicorn |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.7 | Python |
نحوه نصب
نصب پکیج whl biotrade-0.0.23:
pip install biotrade-0.0.23.whl
نصب پکیج tar.gz biotrade-0.0.23:
pip install biotrade-0.0.23.tar.gz