Quick start

The csv2bufr Python module contains both a command line interface and an API to convert data stored in a CSV file to the WMO BUFR data format. For example, the command line interface reads in data from a CSV file, converts it to BUFR and writes out the data to the specified directory. e.g.:

csv2bufr data transform <my-csv-file.csv> \
    --bufr-template <csv-to-bufr-mapping.json> \
    --station-metadata <oscar-metadata-file.json> \
    --output <output-directory-path>

This command is explained in more detail below.

Command line interface

The following example transforms the data in file my-csv-file.csv to BUFR using template csv-to-bufr-mapping.json and writes the output to directory output-directory-path:

csv2bufr data transform <my-csv-file.csv> \
    --bufr-template <csv-to-bufr-mapping.json> \
    --station-metadata <oscar-metadata-file.json> \
    --output-dir <output-directory-path>

The command is built on the Python Click module and is formed of three components (csv2bufr data transform), 1 argument and 3 options (specified by –). The argument specifies the file to process and the options various configuration files to use.

  1. my-csv-file.csv: argument specifying the CSV data file to process

  2. --bufr-template csv-to-bufr-mapping.json: option followed by the bufr mapping template to use

  3. --station-metadata oscar-metadata-file.json: option followed by name of json file containing the station metadata

  4. --output-dir output-directory-path: option followed by output directory to write BUFR file to. The output filename is set using the md5 checksum of the BUFR data to ensure uniqueness, future versions will use the WIGOS ID and timestamp of the data to set the filename.

The output BUFR files can be validated using a tool such as the ECMWF BUFR validator.

Input CSV file

Currently, a single station per file is supported with each row treated as a separate record and one BUFR file per record created. The format of the input CSV file has a few requirements:

  • A comma (i.e. ,) must be used as the delimiter.

  • Strings must be quoted.

  • Missing values must be encoded as “None”.

  • The final row in the file must contain data and not be a new line.

  • The timestamp of the records must be separated into components, i.e. year, month, day etc must each be in a separate column.

  • The date/time elements should be in Universal Time Coordinated (UTC).

BUFR mapping template (--bufr-template)

The mapping from CSV to BUFR is specified in a JSON file (see the BUFR template mapping page).

Station metadata (--station-metadata)

In addition to the input CSV data file and BUFR template file a json file containing the station metadata is also required. At a minimum this file must contain the WIGOS station identifier as per the example below:

    "wigosIds": [
            "wid": "<series>-<issuer>-<issue-number>-<local-identifier>"

Where the parameters in brackets (<>) are replaced with their respective values. More information on the WIGOS identifiers can also be found in the Guide to the WMO Integrated Observing System, section 2 (WMO-No. 1165).

If the station has been registered within the WMO OSCAR/Surface database the metadata file can be downloaded using the pyoscar Python package. For example, to download station metadata for the station on Bird Island, South Georgia, with the WIGOS station identifier “0-20008-0-SGI” the following would be used:

pyoscar station --identifier 0-20008-0-SGI > 0-20008-0-SGI.json

This writes the output to the file 0-20008-0-SGI.json as specified by the redirect (>).


The command line interface uses the transform function from the csv2bufr module. This can be used directly, e.g.:

# import modules
import json
from csv2bufr import transform

# load data from file
with open("my-csv-file.csv") as fh:
    data = fh.read()

# load mapping
with open("csv-to-bufr-mapping.json") as fh:
    mapping = json.load(fh)

# load metadata
with open("oscar-metadata-file.json") as fh:
    metadata = json.load(fh)

# call transform function
result = transform(data, metadata, mapping)

# iterate over items
for item in result:
    # get id and phenomenon time to use in output filename
    wsid = item["_meta"]["wigos_station_identifier"]  # WIGOS station ID
    geometry = item["_meta"]["geometry"]  # GeoJSON geometry object
    timestamp = item["_meta"]["data_date"]  # phenomenonTime as datetime object
    timestamp = timestamp.strftime("%Y%m%dT%H%MZ")  # convert to string
    # set filename
    output_file = f"{wsid}_{timestamp}.bufr4"
    # save to file
    with open(output_file, "wb") as fh:  # note binary write mode

The transform function returns an iterator that can be used to iterate over each line in the data file. Each item returned contains a dictionary with the following elements:

  • item["bufr4"] binary BUFR data

  • item["_meta"] dictionary containing metadata elements

  • item["_meta"]["md5"] the md5 checksum of the encoded BUFR data

  • item["_meta"]["identifier"] identifier for result (set combination of wigos_station_identifier and data_date)

  • item["_meta"]["geometry"] GeoJSON geometry object of location of data

  • item["_meta"]["wigos_station_identifier"] WIGOS station identifier

  • item["_meta"]["data_date"] characteristic date of data contained in result (from BUFR)

  • item["_meta"]["originating_centre"] originating centre for data (from BUFR)

  • item["_meta"]["data_category"] data category (from BUFR)