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Python-Metar
============

Python-metar is a python package for interpreting METAR and SPECI coded
weather reports.

METAR and SPECI are coded aviation weather reports.  The official
coding schemes are specified in the World Meteorological Organization
(WMO) Manual on Codes, vol I.1, Part A (WMO-306 I.i.A).  US conventions
for METAR/SPECI reports vary in a number of ways from the international
standard, and are described in chapter 12 of the Federal Meteorological
Handbook No.1. (FMH-1 1995), issued by the National Oceanic and
Atmospheric Administration (NOAA).  General information about the
use and history of the METAR standard can be found [here](https://www.ncdc.noaa.gov/wdc/metar/).

This module extracts the data recorded in the main-body groups of
reports that follow the WMO spec or the US conventions, except for
the runway state and trend groups, which are parsed but ignored.
The most useful remark groups defined in the US spec are parsed,
as well, such as the cumulative precipitation, min/max temperature,
peak wind and sea-level pressure groups.  No other regional conventions
are formally supported, but a large number of variant formats found
in international reports are accepted.

Current METAR reports
---------------------

Current and historical METAR data can be obtained from various places.
The current METAR report for a given airport is available at the URL

    https://tgftp.nws.noaa.gov/data/observations/metar/stations/<station>.TXT

where `station` is the four-letter ICAO airport station code.  The
accompanying script get_report.py will download and decode the
current report for any specified station.

The METAR reports for all stations (worldwide) for any "cycle" (i.e., hour)
in the last 24 hours are available in a single file at the URL

    https://tgftp.nws.noaa.gov/data/observations/metar/cycles/<cycle>Z.TXT

where `cycle` is a 2-digit cycle number (`00` thru `23`).

METAR specifications
--------------------

The [Federal Meteorological Handbook No.1. (FMC-H1-2017)](http://www.ofcm.gov/publications/fmh/FMH1/FMH1.pdf) describes the U.S. standards for METAR. The [World Meteorological Organization (WMO) Manual on Codes](http://www.wmo.int/pages/prog/www/WMOCodes.html), vol I.1, Part A (WMO-306 I.i.A) is another good reference.

Author
------

The `metar` library was orignally authored by [Tom Pollard](https://github.com/tomp) in January 2005, and is now maintained by contributors on Github.

Installation
------------------------------------------------------------------------

Install this package in the usual way,

    python -m pip install .

    # to install test packages
    python -m pip install '.[test]'

The test suite can be run by:

    pytest

There are a couple of sample scripts, described briefly below.

There's no real documentation to speak of, yet, but feel free to
contact me with any questions you might have about how to use this package.

Current sources
---------------
You can always obtain the most recent version of this package using git, via

    git clone https://github.com/python-metar/python-metar.git

Contents
------------------------------------------------------------------------

File | Description
--- | ---
README | this file
parse_metar.py | a simple commandline driver for the METAR parser
get_report.py | a script to download and decode the current reports for one or more stations.
sample.py | a simple script showing how the decoded data can be accessed. (see metar/*.py sources and the test/test_*.py scripts for more examples.)
sample.metar | a sample METAR report (longer than most).  Try feeding this to the parse_metar.py script...
metar/Metar.py | the implementation of the Metar class.  This class parses and represents a single METAR report.
metar/Datatypes.py | a support module that defines classes representing different types of meteorological data, including temperature, pressure, speed, distance, direction and position.
test/test_*.py | individual test modules
setup.py  | installation script

Example
------------------------------------------------------------------------

See the sample.py script for an annonated demonstration of the use
of this code.  Just as an appetizer, here's an interactive example...

```python
>>> from metar import Metar
>>> obs = Metar.Metar('METAR KEWR 111851Z VRB03G19KT 2SM R04R/3000VP6000FT TSRA BR FEW015 BKN040CB BKN065 OVC200 22/22 A2987 RMK AO2 PK WND 29028/1817 WSHFT 1812 TSB05RAB22 SLP114 FRQ LTGICCCCG TS OHD AND NW -N-E MOV NE P0013 T02270215')
>>> print obs.string()
station: KEWR
type: routine report, cycle 19 (automatic report)
time: Tue Jan 11 18:51:00 2005
temperature: 22.7 C
dew point: 21.5 C
wind: variable at 3 knots, gusting to 19 knots
peak wind: WNW at 28 knots
visibility: 2 miles
visual range: runway 04R: 3000 meters to greater than 6000 meters feet
pressure: 1011.5 hPa
weather: thunderstorm with rain; mist
sky: a few clouds at 1500 feet
     broken cumulonimbus at 4000 feet
     broken clouds at 6500 feet
     overcast at 20000 feet
sea-level pressure: 1011.4 hPa
1-hour precipitation: 0.13in
remarks:
- Automated station (type 2)
- peak wind 28kt from 290 degrees at 18:17
- wind shift at 18:12
- frequent lightning (intracloud,cloud-to-cloud,cloud-to-ground)
- thunderstorm overhead and NW
- TSB05RAB22 -N-E MOV NE
METAR: METAR KEWR 111851Z VRB03G19KT 2SM R04R/3000VP6000FT TSRA BR FEW015 BKN040CB BKN065 OVC200 22/22 A2987 RMK AO2 PK WND 29028/1817 WSHFT 1812 TSB05RAB22 SLP114 FRQ LTGICCCCG TS OHD AND NW -N-E MOV NE P0013 T02270215
>>>>
```

Tests
------------------------------------------------------------------------

The library is tested against Python 3.10-3.14.

A [tox](https://tox.readthedocs.io/en/latest/)
configuration file is included to easily run tests against each of these
environments. To run tests against all environments, install tox and run:

    >>> tox

To run against a specific environment, use the `-e` flag:

    >>> tox -e py310
