"""
Using the ctapipe Provenance service
====================================

The provenance functionality is used automatically when you use most of
ctapipe functionality (particularly ``ctapipe.core.Tool`` and functions
in ``ctapipe.io`` and ``ctapipe.utils``), so normally you don’t have to
work with it directly. It tracks both input and output files, as well as
details of the machine and software environment on which a Tool
executed.

Here we show some very low-level functions of this system:

"""

from pprint import pprint

from ctapipe.core import Provenance

######################################################################
# Activities
# ----------
#
# The basis of Provenance is an *activity*, which is generally an
# executable or step in a script. Activities can be nested (e.g. with
# sub-activities), as shown below, but normally this is not required:
#

p = Provenance()  # note this is a singleton, so only ever one global provenence object
p.clear()
p.start_activity()
p.add_input_file("test.txt")

p.start_activity("sub")
p.add_input_file("subinput.txt")
p.add_input_file("anothersubinput.txt")
p.add_output_file("suboutput.txt")
p.finish_activity("sub")

p.start_activity("sub2")
p.add_input_file("sub2input.txt")
p.finish_activity("sub2")

p.finish_activity()

######################################################################
p.finished_activity_names


######################################################################
# Activities have associated input and output *entities* (files or other
# objects)
#

[(x["activity_name"], x["input"]) for x in p.provenance]


######################################################################
# Activities track when they were started and finished:
#

[(x["activity_name"], x["duration_min"]) for x in p.provenance]


######################################################################
# Full provenance
# ---------------
#
# The provenance object is a list of activities, and for each lots of
# details are collected:
#

p.provenance[0]


######################################################################
# This can be better represented in JSON:
#

print(p.as_json(indent=2))


######################################################################
# Storing provenance info in output files
# ---------------------------------------
#
# -  already this can be stored in something like an HDF5 file header,
#    which allows hierarchies.
# -  Try to flatted the data so it can be stored in a key=value header in
#    a **FITS file** (using the FITS extended keyword convention to allow
#    >8 character keywords), or as a table
#


def flatten_dict(y):
    out = {}

    def flatten(x, name=""):
        if isinstance(x, dict):
            for a in x:
                flatten(x[a], name + a + ".")
        elif isinstance(x, list):
            i = 0
            for a in x:
                flatten(a, name + str(i) + ".")
                i += 1
        else:
            out[name[:-1]] = x

    flatten(y)
    return out


######################################################################
d = dict(activity=p.provenance)

######################################################################
pprint(flatten_dict(d))