km3db 0.9.0

KM3NeT database library

km3db is a lightweight library to access the web API of the KM3NeT Oracle database (https://km3netdbweb.in2p3.fr). It requires Python 2.7 or later and comes with a small set of command line utilities which can be used in shell scripts.

Installation

Tagged releases are available on the Python Package Index repository (https://pypi.org) and can easily be installed with the pip command:

pip install km3db

Python Classes

The three important classes are DBManager, StreamDS and CLBMap.

DBManager

The DBManager class manages the authentication and cookie management and low level access to the database:

>>> import km3db
>>> db = km3db.DBManager()

It tries to figure out the easiest way to authenticate with the database gateway. If launched on the Lyon CC, GitLab CI or the KM3NeT JupyterHub service, it will automatically use the corresponding session cookies. If not operating on whitelisted hosts, the environment variables KM3NET_DB_USERNAME and KM3NET_DB_PASSWORD will be used. If those are not set, it will look for a cookie in ~/.km3netdb_cookie. As a last resort, it will prompt the user to enter the username and password manually. After a successful authentication, a cookie file with the session cookie will be stored in the above mentioned file for future authentications.

StreamDS

The StreamDS class is specifically designed to access the Stream Data Service entrypoint of the database, which is meant to provide large datasets, potentially exceeding multiples of GB:

>>> import km3db
>>> sds = km3db.StreamDS()
>>> print(sds.detectors())
OID   SERIALNUMBER    LOCATIONID      CITY    FIRSTRUN        LASTRUN
D_DU1CPPM     2       A00070004       Marseille       2       10
A00350276     3       A00070003       Napoli  0       0
...
...
D1DU039CT     59      A02181273       Catania 408     480
D0DU040CE     60      A01288502       Caserta 0       0
>>> print(sds.get("detectors"))  # alternative way to call it
...

In km3pipe v8 and below, the StreamDS class always returned pandas.DataFrames by default. This has been changed in km3db and by default, only the raw ASCII output is returned, as delivered by the database.

One can however change the output container type back to pandas.DataFrame by passing container=”pd” to either the StreamDS() constructor or to the .get() function itself. Another supported container type is namedtuple from the Python standard library (collections.namedtuple), available via container=”nt”:

>>> sds = km3db.StreamDS(container="pd")
>>> type(sds.detectors())
pandas.core.frame.DataFrame

# pandas DataFrame only on a specific call
>>> sds = km3db.StreamDS()
>>> type(sds.get("detectors", container="pd"))
pandas.core.frame.DataFrame

# namedtuple
>>> sds.get("detectors", container="nt")[0]
Detectors(oid='D_DU1CPPM', serialnumber=2, locationid='A00070004', city='Marseille', firstrun=2, lastrun=10)

CLBMap

The CLBMap is a powerful helper class which makes it easy to query detector configurations and CLB:

>>> import km3db
>>> clbmap = km3db.CLBMap("D_ORCA003")
>>> clb = clbmap.omkeys[(1, 13)]
>>> clb
Clbmap(det_oid='D_ORCA003', du=1, floor=13, serial_number=374, upi='3.4.3.2/V2-2-1/2.374', dom_id=808949902)
>>> clb.dom_id
808949902
>>> clb.upi
'3.4.3.2/V2-2-1/2.374'

Command Line Utilities

The following command line utilities will be accessible after installing km3db.

detx

The detx command can be used to retrieve calibration information from the database formatted as DETX, which is its main offline representation format:

$ detx -h
Retrieves DETX files from the database.

Usage:
    detx [options] DET_ID
    detx DET_ID RUN
    detx (-h | --help)
    detx --version

Options:
    DET_ID        The detector ID (e.g. 49)
    RUN           The run ID.
    -c CALIBR_ID  Geometrical calibration ID (eg. A01466417)
    -t T0_SET     Time calibration ID (eg. A01466431)
    -o OUT        Output folder or filename.
    -h --help     Show this screen.

Example:

    detx 49 8220  # retrieve the calibrated DETX for run 8220 of ORCA6

streamds

The streamds command provides access to the “Stream Data Service” which was designed to deal with large datasets potentially exceeding multiple GB in size. The help output explains all the available functionality of the tool:

$ streamds -h
Access the KM3NeT StreamDS DataBase service.

Usage:
    streamds
    streamds list
    streamds info STREAM
    streamds get [-f FORMAT -o OUTFILE -g GROUPBY] STREAM [PARAMETERS...]
    streamds upload [-q -x] CSV_FILE
    streamds (-h | --help)
    streamds --version

Options:
    STREAM      Name of the stream.
    PARAMETERS  List of parameters separated by space (e.g. detid=29).
    CSV_FILE    Whitespace separated data for the runsummary tables.
    -f FORMAT   Usually 'txt' for ASCII or 'text' for UTF-8 [default: txt].
    -o OUTFILE  Output file: supported formats '.csv' and '.h5'.
    -g COLUMN   Group dataset by the name of the given row when writing HDF5.
    -q          Test run! When uploading, a TEST_ prefix will be added to the data.
    -x          Do not verify the SSL certificate.
    -h --help   Show this screen.

For example, a list of available detectors:

> streamds get detectors
OID   SERIALNUMBER    LOCATIONID      CITY    FIRSTRUN        LASTRUN
D_DU1CPPM     2       A00070004       Marseille       2       10
A00350276     3       A00070003       Napoli  0       0
D_DU2NAPO     5       A00070003       Napoli  98      428
D_TESTDET     6       A00070002       Fisciano        3       35
D_ARCA001     7       A00073795       Italy   1       2763
FR_INFRAS     8       A00073796       France  1600    3202
D_DU003NA     9       A00070003       Napoli  1       242
D_DU004NA     12      A00070003       Napoli  243     342
D_DU001MA     13      A00070004       Marseille       1       1922
D_ARCA003     14      A00073795       Italy   1       6465

To write the database output to a file, use the -o option, e.g. streamds get detectors -o detectors.csv. The currently supported filetypes are .csv and .h5. In case of .h5, the data can be grouped by providing -g COLUMN, which will split up the output and write distinct HDF5 dataset. It’s useful to group large datasets by e.g. RUN, however, only numerical datatypes are supported currently:

> streamds get toashort detid=D0ORCA010 minrun=13000 maxrun=13005 -g RUN -o KM3NeT_00000100_toashort.h5
Database output written to 'KM3NeT_00000100_toashort.h5'.

km3db

The km3db command gives direct access to database URLs and is mainly a debugging tool:

$ km3db -h
Command line access to the KM3NeT DB web API.

Usage:
    km3db URL
    km3db (-h | --help)
    km3db --version

Options:
    URL         The URL, starting from the database website's root.
    -h --help   Show this screen.

Example:

    km3db "streamds/runs.txt?detid=D_ARCA003"

The URL parameter is simply the string which comes right after https://km3netdbweb.in2p3.fr/.