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Nexus Data writer implemented as a Tango Server

Project description

Authors: Jan Kotanski, Eugen Wintersberger, Halil Pasic


NXSDataWriter is a Tango server which allows to store NeXuS Data in H5 files.

The server provides storing data from other Tango devices, various databases as well as passed by a user client via JSON strings.

Tango Server API:


Install the dependencies:

pni-libraries, PyTango, numpy

From sources

Download the latest NexDaTaS version from

Extract sources and run

$ python install

Debian packages

Debian Jessie (and Wheezy) packages can be found in the HDRI repository.

To install the debian packages, add the PGP repository key

$ sudo su
$ wget -q -O - | apt-key add -

and then download the corresponding source list

$ cd /etc/apt/sources.list.d
$ wget


$ apt-get update
$ apt-get install python-nxswriter

To instal other NexDaTaS packages

$ apt-get install python-nxstools nxsconfigserver-db python-nxsconfigserver nxsconfigtool


$ apt-get install python-nxsrecselector nxselector python-sardana-nxsrecorder

for Component Selector and Sardana related packages.

From pip

To install it from pip you can

$ python3 -m venv myvenv
$ . myvenv/bin/activate

$ pip install nxswriter

Moreover it is also good to install

$ pip install pytango
$ pip install pymysqldb
$ pip install psycopg2-binary
$ pip install cx-oracle

Setting NeXus Writer Server

To set up NeXus Writer Server run

$ nxsetup -x NXSDataWriter

The nxsetup command comes from the python-nxstools package.

Client code

In order to use Nexus Data Server one has to write a client code. Some simple client codes are in the nexdatas repository. In this section we add some comments related to the client code.

# To use the Tango Server we must import the PyTango module and
# create DeviceProxy for the server.

import PyTango

device = "p09/tdw/r228"
dpx = PyTango.DeviceProxy(device)


# Here device corresponds to a name of our Nexus Data Server.
# The Init() method resets the state of the server.

dpx.FileName = "test.h5"

# We set the name of the output HDF5 file and open it.

# Now we are ready to pass the XML settings describing a structure of
# the output file as well as defining a way of data storing.
# Examples of the XMLSettings can be found in the XMLExamples directory.

xml = open("test.xml", 'r').read()
dpx.XMLSettings = xml

dpx.JSONRecord = '{"data": {"parameterA":0.2},


# We read our XML settings settings from a file and pass them to the server via
# the XMLSettings attribute. Then we open an entry group related to the XML
# configuration. Optionally, we can also set JSONRecord, i.e. an attribute
# which contains a global JSON string with data needed to store during opening
# the entry and also other stages of recording. If external decoder for
# DevEncoded data is need one can registred it passing its packages and
# class names in JSONRecord,
# e.g. "desy2d" class of "DESY2D" label in "desydecoders.desy2Ddec" package.
# Similarly making use of "datasources" records of the JSON string one can
# registred additional datasources. The OpenEntry method stores data defined
# in the XML string with strategy=INIT.
# The JSONRecord attribute can be changed during recording our data.

# After finalization of the configuration process we can start recording
# the main experiment data in a STEP mode.

dpx.Record('{"data": {"p09/counter/exp.01":0.1, "p09/counter/exp.02":1.1}}')

# Every time we call the Record method all nexus fields defined with
# strategy=STEP are extended by one record unit and the assigned to them data
# is stored. As the method argument we pass a local JSON string with the client
# data. To record the client data one can also use the global JSONRecord string.
# Contrary to the global JSON string the local one is only
# valid during one record step.

dpx.Record('{"data": {"emittance_x": 0.1},  "triggers":["trigger1", "trigger2"]  }')

# If you denote in your XML configuration string some fields by additional
# trigger attributes you may ask the server to store your data only in specific
# record steps. This can be helpful if you want to store your data in
# asynchronous mode. To this end you define in the local JSON string a list of
# triggers which are used in the current record step.

dpx.JSONRecord = '{"data": {"parameterB":0.3}}'

# After scanning experiment data in 'STEP' mode we close the entry.
# To this end we call the CloseEntry method which also stores data defined
# with strategy=FINAL. Since our HDF5 file can contain many entries we can again
# open the entry and repeat our record procedure. If we define more than one entry
# in one XML setting string the defined entries are recorded parallel
# with the same steps.

# Finally, we can close our output file by


Additionally, one can use asynchronous versions of OpenEntry, Record, CloseEntry, i.e. OpenEntryAsynch, RecordAsynch, CloseEntryAsynch. In this case data is stored in a background thread and during this writing Tango Data Server has a state RUNNING.

In order to build the XML configurations in the easy way the authors of the server provide for this purpose a specialized GUI tool, Component Designer. The attached to the server XML examples was created by XMLFile class defined in XMLCreator/

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