Certainly, coffee is a soft commodity (meaning it’s not storable for long periods of time). This product is taken from plants that grow in tropical-friendy climates.
Coffee is such a significant part of people’s diets around the world that it has developed its own business. Coffee roasters, packers, growers, marketers, and coffee equipment manufacturers.
Top 5
With about 2.600.000 annual metric tonnes, Brazil is the biggest coffee producer. Followed by Vietnam, Colombia, Indonesia, and Ethiopia, these nations integrate the Top 5 exporting countries.
Price
Besides, coffee prices, as any other commodity, are influenced by multiple factors such as:
- Geopolitics: political crises and instability affect the market.
- Climate: plants, where cherry coffee grows, are extremely sensitive to weather conditions.
- Demand: as this is not exactly a basic need, the consumption fluctuates with the economy and the ability to purchase and spend money on this.
- Transportation and oil prices: as we mentioned before, grains are exported all over the world so fuel has an impact too.
Tracking prices and fluctuations of this raw material and its stock is highly important to market players. Fortunately, this can be done by using automated systems combined with software to do it in a more efficient way
Python
Firstly, let’s define this as a programming language used to build websites and apps, automate tasks, and perform data analysis.
Its design philosophy places a strong emphasis on code readability, with a lot of underlining. It also has language features that help programmers write concise, logical code for both small and large-scale projects.
Also, it is commonly used in the development of software, as well as task automation, data analysis, and data visualization. However, many non-programmers, such as accountants and scientists chose Python for a variety of common tasks.
Python, on the other hand, needs to be supplied by another program that gives real-time data on commodity rates in a variety of currencies. There are numerous internet resources available.
Mix Technology
Consequently, a python-developed software can be easily combined with an API to boost its features by adding immediateness and accuracy.
Python (using Request module)
import requests
base_currency = 'USD'
symbol = 'COFFEE'
endpoint = 'latest'
access_key = 'API_KEY'
resp = requests.get(
'https://commodities-api.com/api/'+endpoint+'?access_key='+access_key+'&base='+base_currency+'&symbols='+symbol)
if resp.status_code != 200:
# This means something went wrong.
raise ApiError('GET /'+endpoint+'/ {}'.format(resp.status_code))
print(resp.json())
Commodities-api.com, on the other hand, is almost always the better choice. This is a website where you can keep track of the prices of a variety of commodities. Finally, you’ll be able to forecast prices and convert them to your preferred currency.
Commodities-API
This online API delivers precise rate data in a variety of currencies for a large range of commodities.
Commodities-API began as a simple, minimalist Open-Source API for recent and historical commodity prices from financial institutions.
Accuracy
The API can offer real-time commodity data with a precision of two decimal points and a pace of up to every 60 seconds. Commodities-API is built on a strong back-end architecture that ensures high availability and response times of less than 50 milliseconds for defined API calls. Delivering commodities exchange rates, converting single currencies, and returning Time-Series and Fluctuation data are only a few of the functions.
Encrypted
The Commodities-API uses bank-grade 256-bit SSL security to protect your connection.
Thousands of developers, small enterprises, and large corporations use Commodities-API on a daily basis. This API is the most popular site for commodity rates because of its reliable data sources and 6+ years of experience.
Also published on Medium.