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Icarus
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CLI tools for General Aviation
Download README (.md)
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Icarus
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# Icarus A suite of CLI tools for use in flight simulation.  ## How to Install 1) [Download and install the latest release of Python 3.](https://www.python.org/downloads/) 2) Download the [latest release of Icarus](https://github.com/musurca/Icarus/releases/latest) and unzip it to a directory of your choice, e.g. ```~/icarus```. 3) From the command line, change to your Icarus directory and run ```install``` to download the Icarus dependencies. *(If you'd rather do the last step manually, you can instead run* ```pip install numpy scipy wget beautifulsoup4 npyscreen rich requests```*.)* You're ready to use Icarus! ## The Tools ### airportinfo ``` airportinfo [ICAO] ex: > airportinfo KLAX ``` Displays useful information about an airport, including: * latitude / longitude and altitude * current METAR * nearest city * runway length, orientation, material, and suitability for night operations * published LOC/DME frequencies * relevant radio frequencies * nearby navaids * nearby airports NOTE: All headings are magnetic, calculated by magnetic declination at the airport on the current date via the IGRF-13 model. ### diagram ``` diagram [ICAO] ex: > diagram KJFK ``` Connects to the FAA database and downloads all available airport diagrams (PDF), approach/departure charts (PDF), and current remarks (TXT) to ./diagrams/[ICAO]. Remarks are also decoded/expanded where possible. If unable to find any current FAA charts, will scrape the web for any available Jeppesen charts. ### distance ``` distance [ICAO origin] [ICAO destination] ex: > distance KSBA TRM ``` Displays the distance and magnetic heading on a direct course from one ICAO location to another. Either origin or destination may be either an airport or a navaid. ### fuel ``` fuel [ICAO] [100LL OR JETA] [range] ex: > fuel KSAN JETA ``` Displays current avgas prices (either 100LL or Jet-A) at ICAO location, and within a desired range (100 nm by default). ### legs ``` legs [ICAO origin] [ICAO destination] [max range in nm] ex: > legs KBGR BGMQ 500 ``` Finds the shortest route between two airports using multiple stops, in which the length of each leg of the trip is less than the maximum range of your aircraft specified. NOTE: Due to the large number of possible airports to search, this command can be very slow to execute. ### metar ``` metar [ICAO code] ex: > metar KLAX ``` Finds the current METAR for an airport or weather station. ### updatedb ``` updatedb ``` Downloads most recent database of airports, navaids, and radio frequencies. ### vorpath ``` vorpath [ICAO origin] [ICAO destination] ex: > vorpath LFPG OMDB ``` Finds the shortest VOR-to-VOR route between two airports or navaids. You can filter by civilian, legacy, and military types. ### wind ``` wind ``` Estimates wind aloft by taking the results of two distance and bearing readings to a fixed reference point. The resulting information can be fed into an E6B to determine course correction to adjust for leeway. How to use: 1) Point your aircraft on a course exactly toward or exactly away from a fixed reference point with distance measuring equipment (e.g., a VOR), then set autopilot to maintain heading, altitude, and speed. 2) Record distance to reference point, start a timer, and wait for X seconds. Longer time intervals will produce more accurate results. An interval of 300-600 seconds (5-10 minutes) is ideal. 3) After X seconds, record the new distance to the reference point as well as its deviation from its original bearing to your plane in degrees. Use negative degrees if the reference point has slipped to the left, and positive degrees if it has slipped to the right. 4) Enter your recorded data into the wind program to estimate wind speed and direction. ## Dependencies * [Python 3](https://www.python.org/downloads/) * numpy * scipy * requests * wget * BeautifulSoup 4 * npyscreen * [rich](https://github.com/willmcgugan/rich) ## Acknowledgements * Airport/navaid data courtesy of [OurAirports](http://ourairports.com). * U.S. city data courtesy of [SimpleMaps](https://simplemaps.com/data/us-cities). * METAR data scraped from the [Aviation Weather Center](https://aviationweather.gov/). * Fuel prices scraped from [100LL.com - Aviation Fuel Price Search](http://www.100ll.com). * Some code based on the MIT-licensed [pyIGRF](https://github.com/zzyztyy/pyIGRF).
