The aim of our project is to create a simple software that behaves like a weather app. Our software will provide the user data about the current weather and much more for a given city.
Let's check in detail how it works!
To run the program, as a prerequisite you should have at least Python 3.5 version.
In order to start you have to install the required dependencies:
pip3 install -r requirements.txt
Now you are ready to try our program!
You can try using our software by writing:
python3 main.py Berlin
When the user has selected the city of interest, our software provides him with a user-friendly, easy readable and good looking table.
The table lists a lot of interesting information:
| OUTPUT | OUTPUT DESCRIPTION |
|---|---|
| CITY | City selected by the user |
| WEATHER | How is the current weather like |
| TEMPERATURE | Current temperature expressed in celsius degrees |
| DESCRIPTION | Weather broader description |
| ICON | Weather visual description |
| AIR QUALITY | Mean of the most recent air quality levels of the given city |
| ICON | Color describing the healthy level with respect to the air quality index |
Positional parameters:
- the chosen city.
Note: If you want to insert a city that has a space in the name, you must write for example
<"Abu Dhabi">.
Optional parameters:
- -v, --verbose : be more verbose;
- --version : show program's version number and exit;
- -h, --help : show this help message and exit;
- --history N : history of the previsions.
Note: --history N; the user would be able to specify the number of desired history rows.
Documentation can be opened with: open sphinx/_build/html/index.html.
Here you can find the information about the functions you can find in the various modules.
It has been made with Sphinx
The program based itself on two main API software:
- Opencage API: useful to get geographic coordinates (latitude and longitude) given a specific city name.
- Current Weather API: used to get current weather information given specific coordinates.
In oder to provide our users with further data about the city of interest, we have add a further dataset. The dataset includes data collected by the World Health Organization about the air quality mean per year for 10.075 cities around the world. When queried, it reports to the user a mean of air quality levels registered in the most recent year.
Note: If the city is not present in the database, it reports
<n.d.>.
The air quality is divided in different levels represented in the following table.
| AIR QUALITY INDEX | LEVELS OF HEALTH | COLORS |
|---|---|---|
| 0 to 49 | Healthy | Green |
| 50 to 150 | Moderate healthy | Orange |
| 151 to 300 | Unhealthy | Red |
| over 300 | Very unhealthy | Purple |
The software includes also a database, which keeps track of all the forecasts made by the program.
The database stored the following variables:
| VARIABLE | VARIABLE DESCRIPTION |
|---|---|
| Timestamp | When the research was done |
| City | The city on which the research has been conducted |
| Weather | The forecasted weather for the given city |
| Temperature | The forecasted temperature expressed in celsius degrees |
| Icon | The visual representation of the weather |
Note: The database is created automatically when the software is used.
We have tested our air_quality.py module (based on the air quality.csv )
and the open_cage.py module.
You can find both tests in our kronos_package/tests/.
To run them from the main folder use:
python3 -m unittest -v -b
All tests run correctly.
- Bagattin Enrico
- Bestetti Lucrezia Wally
- Doretto Alessandro
- Mosele Gianluigi
- Scarselli Lavinia