In order to enable an iCal export link, your account needs to have an API key created. This key enables other applications to access data from within Indico even when you are neither using nor logged into the Indico system yourself with the link provided. Once created, you can manage your key at any time by going to 'My Profile' and looking under the tab entitled 'HTTP API'. Further information about HTTP API keys can be found in the Indico documentation.
Additionally to having an API key associated with your account, exporting private event information requires the usage of a persistent signature. This enables API URLs which do not expire after a few minutes so while the setting is active, anyone in possession of the link provided can access the information. Due to this, it is extremely important that you keep these links private and for your use only. If you think someone else may have acquired access to a link using this key in the future, you must immediately create a new key pair on the 'My Profile' page under the 'HTTP API' and update the iCalendar links afterwards.
Permanent link for public information only:
Permanent link for all public and protected information:
The Flask library for Python is a fantastic tool for building lightweight web services and applications. It is currently used at numerous places around the Synchrotron including the DNS Manager, Experiment Changeovers, IMBL data management, MX autoprocessing and sample shipping.
This workshop will cover how to use Flask to make simple user interfaces as well as how to create APIs to trigger tasks on a server.
Monitoring and controlling devices with PyEPICS2h
PyEPICS makes it easy to interact with any device with an EPICS IOC. This workshop will cover writing simple scripts to monitor or capture EPICS PVs as well as building more advanced applications for controlling a device.
Processing and visualising data with Numpy, Pandas, Matplotlib and Plotly2h
Python has become an indispensable tool in the scientific community. This is in large part due to the high performance numeric library numpy, the analysis package pandas and the plotting packages such as Matplotlib and Plotly.
In this workshop you will learn how to read data from image files, csv/Excel and hdf5 and then visualise the data by creating beautiful, interactive charts.