another attempt at parsing RWA - seems to work better

original code is commented below, rows 517-545

.gitignore

@@ -1,6 +1,11 @@
-# ignora log di h5tojson e jsontoh5
+# ignores logs of h5tojson, jsontoh5
 *.log
 
+# ignores any output of main.py
+output/*.json
+output/*.h5
+output/*.nxs
+
 # ---> Python
 # Byte-compiled / optimized / DLL files
 __pycache__/

glossary.md

@@ -0,0 +1,39 @@
+## Scientific terms
+> Public service announcement: I'm not a physicist.
+
+* PLD deposition: fabrication method.
+* Sample: what is being produced by a deposition. A sample is made up of different stacked layers of material (target) deposited upon another material (substrate).
+* Target: material "consumed" during the deposition.
+* Substrate: material on which the target is deposited.
+* Compound: which material is a target or a substrate made of; substrates of the same batch are made of the same compound.
+* Layer: one of the layers of material of which a sample is composed; every layer can have different properties, both in the physical sense (i.e. shape, thickness...) and regarding their manufacturing process (i.e. frequency of pulses, deposition temperature and pressure...).
+
+## eLabFTW glossary
+> PSA: I'm not a Deltablot developer either.
+
+* Experiment: main type of entry on eLabFTW, used to store data related to the single experiment.
+* Resource or Item: secondary type of entry on eLabFTW, used to store data related to resources such as raw materials, instruments, machinery etc.
+* Elabid: unique ID used to identify a resource or an experiment; resources and experiments have different indexing and different API endpoints.
+* Categories: experiments or resources with common characteristics are associated by assigning them to the same category - e.g. experiments flagged as "PLD Deposition" contain data on a layer of a sample; categories also come with a mask of parameters (extra fields) which need to be compiled by the user.
+* Metadata: extra data; in eLabFTW it all falls under either the key "metadata" (as a single string of text) or the key "metadata_decoded". Metadata is then divided into "extra_fields" and "extra_fields_groups" - of which usually only the first one contains relevant metadata.
+* ReST API: [something I use to get my JSON files](https://www.redhat.com/en/topics/api/what-is-a-rest-api); endpoints are the URLs I point my requests to.
+* JSON: fancy dictionaries with important data.
+
+### Endpoints
+API URL: `https://{ELAB_BASE_URL}:{PORT}/api/v2`
+
+#### GET, PATCH, DELETE
+* `/items/{elabid}`: data on a resource identified by its elabid.
+* `/experiments/{elabid}`: data on an experiment identified by its elabid.
+
+## What is what
+At CNR-SPIN @Na we use eLabFTW resources to store:
+* Our samples;
+* Our instruments;
+* Our substrate batches and our PLD targets;
+* The compounds substrates and targets are made of (incl. chemical formula);
+* Other things.
+
+We use experiments to store:
+* Our laboratory journals;
+* The layers a sample is made up of.

requirements.txt

@@ -1 +1,3 @@
 requests
+asyncio
+h5py

src/APIHandler.py

@@ -0,0 +1,41 @@
+import requests
+
+class APIHandler:
+    '''
+    Class to standardize the format of the headers of our http requests.
+    '''
+    # TO-DO: remove static url.
+    def __init__(self, apikey="", ELABFTW_API_URL="https://elabftw.fisica.unina.it/api/v2"):
+        '''Init method, apikey suggested but not required (empty by default).'''
+        self.auth = {"Authorization" : apikey}
+        self.content = {"Content-Type" : "application/json"}
+        self.header = {**self.auth, **self.content}
+        self.elaburl = ELABFTW_API_URL
+    def get_entry_from_elabid(self, elabid, entryType="items"):
+        '''
+        Method which returns a resource's raw data (as dictionary) from its elabid and entry type.
+
+        Entry type can be either "experiments" or "items".
+        '''
+        # TO-DO: validation and error handling on entryType value.
+        header = self.header
+        response = requests.get(
+            headers = header,
+            url = f"{self.elaburl}/{entryType}/{elabid}",
+            verify=True
+        )
+        if response.status_code // 100 in [1,2,3]:
+            entry_data = response.json()
+            return entry_data
+        elif response.status_code // 100 == 4:
+            match response.status_code:
+                case 401|403:
+                    raise ConnectionError(f"Invalid API key or authentication method.")
+                case 404:
+                    raise ConnectionError(f"404: Not Found. This means there's no resource with this elabid (wrong elabid?) on your eLabFTW (wrong endpoint?).")
+                case 400:
+                    raise ConnectionError(f"400: Bad Request. This means the API endpoint you tried to reach is invalid. Did you tamper with the source code? If not, contact the developer.")
+                case _:
+                    raise ConnectionError(f"HTTP request failed with status code: {response.status_code} (NOTE: 4xx means user's fault).")
+        else:
+            raise ConnectionError(f"There's a problem on the server. Status code: {response.status_code}.")

src/classes.py

@@ -1,17 +1,205 @@
-class Header:
+import os, json, requests
+from APIHandler import APIHandler
+
+class Layer:
     '''
-    Class to standardize the format of the headers of our http requests.
+    Layer(layer_data) - where layer_data is a Python dictionary.
+
+    Meant to be used for eLabFTW Experiments of the "PLD Deposition" category.
+
+    eLabFTW experiments contain most of the data required by the NeXus file - although every layer is on a different eLab entry;
+    unfortunately, some data like the target's chemical formula must be retrieved through additional HTTP requests.
+    Attributes 'target_elabid', 'rheed_system_elabid' and 'laser_system_elabid' contain elabid's for these resources, which are all items.
     '''
-    def __init__(self, apikey=""):
+    def __init__(self, layer_data):
-        '''Init method, apikey suggested but not required (empty by default).'''
+        try:
-        self.auth = {"Authorization" : apikey}
+            self.operator = layer_data["fullname"]
-        self.content = {"Content-Type" : "application/json"}
+            self.extra = layer_data["metadata_decoded"]["extra_fields"]
-    def dump(self):
+            self.layer_number = self.extra["Layer Progressive Number"]["value"] # integer
-        '''Dumps the header in form of a dictionary.'''
+            self.target_elabid = self.extra["Target"]["value"] # elabid
-        dump = {**self.auth, **self.content}
+            self.laser_system_elabid = self.extra["Laser System"]["value"] # elabid
-        return dump
+            self.chamber_elabid = self.extra["Chamber"]["value"] # elabid
+            self.rheed_system_elabid = self.extra["RHEED System"]["value"] # elabid
+            self.deposition_time = self.extra["Duration"]["value"]
+            self.deposition_time_unit = self.extra["Duration"]["unit"]
+            self.repetition_rate = self.extra["Repetition rate"]["value"]
+            self.repetition_rate_unit = self.extra["Repetition rate"]["unit"]
+            try:
+                self.number_of_pulses = (float(self.deposition_time) * float(self.repetition_rate)).__floor__()
+            except ValueError:
+                # Since number_of_pulses is required, if it can't be calculated raise error:
+                raise ValueError("""
+    Fatal: either Duration or Repetition Rate are empty or invalid.
+    This has to be an error, since these fields are required by the NeXus standard.
+    Please edit your eLabFTW entry and retry.
+                """)
+            self.temperature = self.extra["Heater temperature"]["value"] # Note: this field used to have a trailing space in its name
+            self.temperature_unit = self.extra["Heater temperature"]["unit"]
+            self.process_pressure = self.extra["Process pressure"]["value"] # Note: this field used to have a trailing space in its name
+            self.process_pressure_unit = self.extra["Process pressure"]["unit"]
+            self.heating_method = self.extra["Heating Method"]["value"]
+            self.layer_thickness = self.extra["Thickness"]["value"]
+            self.layer_thickness_unit = self.extra["Thickness"]["unit"]
+            self.buffer_gas = self.extra["Buffer gas"]["value"]
+            self.heater_target_distance = self.extra["Heater-target distance"]["value"]
+            self.heater_target_distance_unit = self.extra["Heater-target distance"]["unit"]
+            self.laser_fluence = self.extra["Laser Intensity"]["value"] # here fluence = intensity
+            self.laser_fluence_unit = "J/(s cm^2)"
+            self.laser_spot_area = self.extra["Spot Area"]["value"]
+            self.laser_spot_area_unit = "mm^2"
+            try:
+                self.laser_energy = ( float(self.laser_fluence) * float(self.laser_spot_area) / 100 ).__round__(3)
+                self.laser_energy_unit = "J/s"
+            except ValueError:
+                # Since laser_energy is NOT required, if it can't be calculated warn user but allow the software to continue execution:
+                print("""
+    Warning: either Laser Intensity or Spot Area are empty or invalid.
+    If you think this is an error, please edit your eLabFTW entry and retry.
+    Setting Laser Energy to NoneType.
+                """)
+                # Placeholder
+                self.laser_energy = None
+            # Laser rasternig section
+            self.laser_rastering_geometry = self.extra["Laser Rastering Geometry"]["value"]
+            self.laser_rastering_positions = self.extra["Laser Rastering Position"]["value"]
+            self.laser_rastering_velocities = self.extra["Laser Rastering Speed"]["value"]
+            # Pre annealing section
+            self.pre_annealing_ambient_gas = self.extra["Buffer gas Pre"]["value"]
+            self.pre_annealing_pressure = self.extra["Process pressure Pre"]["value"]
+            self.pre_annealing_temperature = self.extra["Heater temperature Pre"]["value"]
+            self.pre_annealing_duration = self.extra["Duration Pre"]["value"]
+            self.pre_annealing_pressure_unit = self.extra["Process pressure Pre"]["unit"]
+            self.pre_annealing_temperature_unit = self.extra["Heater temperature Pre"]["unit"]
+            self.pre_annealing_duration_unit = self.extra["Duration Pre"]["unit"]
+            # Post annealing section
+            self.post_annealing_ambient_gas = self.extra["Buffer gas PA"]["value"]
+            self.post_annealing_pressure = self.extra["Process pressure PA"]["value"]
+            self.post_annealing_temperature = self.extra["Heater temperature PA"]["value"]
+            self.post_annealing_duration = self.extra["Duration PA"]["value"]
+            self.post_annealing_pressure_unit = self.extra["Process pressure PA"]["unit"]
+            self.post_annealing_temperature_unit = self.extra["Heater temperature PA"]["unit"]
+            self.post_annealing_duration_unit = self.extra["Duration PA"]["unit"]
+
+            # Rejected but suggested by the NeXus standard:
+            #self.laser_rastering_coefficients = None
+        except KeyError as k:
+            # Some keys are not required and can be called through the .get() method - which is permissive and allows null values;
+            # Other keys are required so if they can't be called (invalid or null) raise error and stop execution of the program:
+            raise KeyError(f"The provided dictionary lacks a \"{k}\" key. Check the deposition layer entry on eLabFTW and make sure you used the correct Experiment template.")
+        # Optional
+        self.start_time = layer_data.get("created_at") or None
+        self.description = layer_data.get("body") or None
+    def get_instruments(self, apikey):
+        raw_lasersys_data = APIHandler(apikey).get_entry_from_elabid(self.laser_system_elabid, entryType="items")
+        raw_chamber_data = APIHandler(apikey).get_entry_from_elabid(self.chamber_elabid, entryType="items")
+        raw_rheedsys_data = APIHandler(apikey).get_entry_from_elabid(self.rheed_system_elabid, entryType="items")
+        instruments_used = {
+            "laser_system": raw_lasersys_data.get("title") or None,
+            "deposition_chamber": raw_chamber_data.get("title") or None,
+            "rheed_system": raw_rheedsys_data.get("title") or None,
+        }
+        return instruments_used
+
+class Entrypoint:
+    '''
+    Entrypoint(sample_data) - where sample_data is a Python dictionary.
+
+    Meant to be used for eLabFTW Resources of the "Sample" category.
+
+    The entrypoint is the starting point of the process of resolving the data chain.
+    The entrypoint must be a dictionary containing the data of a sample, created directly from the JSON of the item endpoint on eLabFTW - which can be done through the function get_entry_from_elabid.
+    '''
+    def __init__(self, sample_data):
+        try:
+            self.extra = sample_data["metadata_decoded"]["extra_fields"]
+            self.linked_items = sample_data["items_links"] # dict
+            self.batch_elabid = self.extra["Substrate batch"]["value"] # elabid
+            self.linked_experiments = sample_data["related_experiments_links"] # dict
+            self.linked_experiments_elabid = [ i["entityid"] for i in self.linked_experiments ] # list of elabid
+        except KeyError as k:
+            # Some keys are not required and can be called through the .get() method - which is permissive and allows null values;
+            # Other keys are required so if they can't be called (invalid or null) raise error and stop execution of the program:
+            raise KeyError(f"The provided dictionary lacks a \"{k}\" key. Check the sample entry on eLabFTW and make sure you used the correct Resource template.")
+        # Non-required attributes:
+        self.name = sample_data.get("title") or None # error prevention is more important than preventing empty fields here
+
+class Material:
+    '''
+    Material(material_data) - where material_data is a Python dictionary.
+
+    Meant to be used for eLabFTW Resources of either the "PLD Target" or the "Substrate" categories.
+
+    Both a PLD Target and a Substrate are materials made of a certain compound, of which we want to know:
+        * Name and formula;
+        * Shape and dimensions;
+        * Misc.
+    '''
+    def __init__(self, material_data):
+        try:
+            self.name = material_data["title"] # required
+            self.extra = material_data["metadata_decoded"]["extra_fields"]
+            self.compound_elabid = self.extra["Compound"]["value"]
+            self.dimensions = str(self.extra["Size"]["value"]) # strings have a .count() method
+            if self.dimensions.count("mm") == 2:
+                self.dimensions_unit = "mm x mm"
+            elif self.dimensions[-1] == '"':
+                self.dimensions_unit = "inches"
+            else:
+                self.dimensions_unit = None
+        except KeyError as k:
+            # Some keys are not required and can be called through the .get() method - which is permissive and allows null values;
+            # Other keys are required so if they can't be called (invalid or null) raise error and stop execution of the program:
+            raise KeyError(f"The provided dictionary lacks a \"{k}\" key. Check the target/substrate entry on eLabFTW and make sure you used the correct Resource template.")
+    def get_compound_data(self, apikey):
+        raw_compound_data = APIHandler(apikey).get_entry_from_elabid(self.compound_elabid, entryType="items")
+        name = raw_compound_data["title"]
+        extra = raw_compound_data["metadata_decoded"]["extra_fields"]
+        formula = extra.get("Chemical formula")
+        cas = extra.get("CAS number ") or { "value": None }
+        compound_data = {
+            "name" : name,
+            "chemical_formula" : formula.get("value"),
+            "cas_number" : cas.get("value")
+        }
+        return compound_data
+    def get_compound_formula(self, apikey):
+        formula = self.get_compound_data(apikey).get("chemical_formula")
+        return formula
+
+class Substrate(Material):
+    def __init__(self, material_data):
+        super().__init__(material_data)
+        try:
+            self.orientation = self.extra["Orientation"]["value"]
+            self.miscut_angle = self.extra["Miscut Angle"]["value"]
+            self.miscut_angle_unit = self.extra["Miscut Angle"]["unit"]
+            self.miscut_direction = self.extra["Miscut Direction"]["value"]
+            # Not present (yet) on eLabFTW for Substrates:
+            self.thickness = "" #self.extra["Thickness"]["value"]
+            self.thickness_unit = "μm" #self.extra["Thickness"]["unit"]
+            self.surface_treatment = self.extra["Surface treatment"]["value"]
+            self.manufacturer = self.extra["Supplier"]["value"]
+            self.batch_id = self.extra["Batch ID"]["value"]
+        except KeyError as k:
+            raise KeyError(f"The provided dictionary lacks a \"{k}\" key - which is specific for substrates. Check the {self.name} substrate entry on eLabFTW and make sure you used the correct Resource template.")
+
+class Target(Material):
+    def __init__(self, material_data):
+        super().__init__(material_data)
+        try:
+            self.thickness = self.extra["Thickness"]["value"]
+            self.thickness_unit = self.extra["Thickness"]["unit"]
+            self.shape = self.extra["shape"]["value"]
+            self.solid_form = self.extra["Solid form"]["value"]
+            self.manufacturer = self.extra["Supplier"]["value"]
+        except KeyError as k:
+            raise KeyError(f"The provided dictionary lacks a \"{k}\" key - which is specific for PLD targets. Check the {self.name} target entry on eLabFTW and make sure you used the correct Resource template.")
+        # Non-required attributes:
+        self.description = material_data.get("body") or ""
+
+
 
 if __name__=="__main__":
     head = Header("MyApiKey-123456789abcdef")
-    print(f"Example header: {head.dump()}")
+    print(f"Example header:\n\t{head.header}\n")
     print("Warning: you're not supposed to be running this as the main program.")

src/main.py

@@ -0,0 +1,562 @@
+import os, json, requests, h5py
+import numpy as np
+from getpass import getpass
+from APIHandler import APIHandler
+from classes import *
+
+
+def call_entrypoint_from_elabid(elabid):
+    '''
+    Calls an entrypoint sample from eLabFTW using its elabid, then returns an object of the Entrypoint class.
+
+    If the entry is not a sample (category_title not matching exactly "Sample") returns ValueError.
+    '''
+    try: 
+        sample_data = APIHandler(apikey).get_entry_from_elabid(elabid, entryType="items")
+        if not sample_data.get("category_title") == "Sample":
+            raise ValueError("The resource you selected is not a sample, therefore it can't be used as an entrypoint.")
+        sample_object = Entrypoint(sample_data)
+    except ConnectionError as e:
+        raise ConnectionError(e)
+    return sample_object # Entrypoint-class object
+
+def call_material_from_elabid(elabid):
+    '''
+    Calls a material from eLabFTW using its elabid, then returns an object of the Material class.
+
+    If the entry is neither a PLD Target or a Substrate batch returns ValueError. Such entries always have a category_title key with its value matching exactly "PLD Target" or "Substrate".
+    Because of an old typo, the value "Subtrate" (second 's' is missing) is also accepted.
+    '''
+    try: 
+        material_data = APIHandler(apikey).get_entry_from_elabid(elabid, entryType="items")
+        material_category = material_data.get("category_title")
+        # TO-DO: correct this typo on elabftw: Subtrate → Substrate.
+        if not material_category in ["PLD Target", "Substrate", "Subtrate"]:
+            print(f"Category of the resource: {material_category}.")
+            raise ValueError(f"The referenced resource (elabid = {elabid}) is not a material.")
+        elif material_category == "PLD Target":
+            material_object = Target(material_data)
+        else:
+            material_object = Substrate(material_data)
+    except ConnectionError as e:
+        raise ConnectionError(e)
+    return material_object # Material-class object
+
+def call_layers_from_list(elabid_list):
+    '''
+    Calls a list of (PLD deposition) experiments from eLabFTW using their elabid - which means the input must be a list of integers instead of a single one - then returns a list of Layer-class objects.
+
+    If one of the entries is not related to a deposition layer (category_title not matching exactly "PLD Deposition") that entry is skipped, with no error raised.
+    '''
+    list_of_layers = []
+    for elabid in elabid_list:
+        try:
+            layer_data = APIHandler(apikey).get_entry_from_elabid(elabid, entryType="experiments")
+            if not layer_data.get("category_title") == "PLD Deposition":
+                continue
+            layer_object = Layer(layer_data)
+            list_of_layers.append(layer_object)        
+        except ConnectionError as e:
+            nums = [ layer.layer_number for layer in list_of_layers ]
+            nums.sort()
+            print(f"LIST OF THE LAYERS PROCESSED (unordered):\n" + str(nums))
+            raise ConnectionError(f"An error occurred while fetching the experiment with elabid = {elabid}:\n" +
+                str(e) + f"\nPlease solve the problem before retrying." + "\n\n" +
+                f"Last resource attempted to call: {ELABFTW_API_URL}/experiments/{elabid}"
+            )
+    return list_of_layers # list of Layer-class objects
+
+def chain_entrypoint_to_batch(sample_object):
+    '''
+    Takes an Entrypoint-class object, looks at its .batch_elabid attribute and returns a Material-class object containing data on the substrate batch associated to the starting sample.
+
+    Dependency: call_material_from_elabid.
+    '''
+    material_elabid = sample_object.batch_elabid
+    material_object = call_material_from_elabid(material_elabid)
+    return material_object
+
+def chain_entrypoint_to_layers(sample_object):
+    '''
+    Takes an Entrypoint-class object, looks at its .linked_experiments_elabid attribute (list) and returns a list of Layer-class objects containing data on the deposition layers associated to the starting sample - using the function call_layers_from_list.
+
+    The list is sorted by progressive layer number (layer_number attribute).
+
+    Dependency: call_layers_from_list.
+    '''
+    linked_experiments_elabid = sample_object.linked_experiments_elabid # list of elabid
+    layer_object_list = call_layers_from_list(linked_experiments_elabid)
+    layer_object_list.sort(key=lambda x: x.layer_number)
+    return layer_object_list
+
+def chain_layer_to_target(layer_object):
+    '''
+    Takes a Layer-class object, looks at its .target_elabid attribute and returns a Material-class object containing data on the PLD target used in the deposition of said layer.
+
+    Dependency: call_material_from_elabid.
+    '''
+    target_elabid = layer_object.target_elabid
+    material_object = call_material_from_elabid(target_elabid)
+    return material_object
+
+def deduplicate_instruments_from_layers(layers):
+    '''
+    Takes a list of Layer-class objects and for each layer gets the instruments used (laser, depo chamber and RHEED), returns dictionary with one item per category. This means that if more layers share the same instruments it returns a dictionary with just their names as strings (no lists or sub-dictionaries).
+    
+    If different layers have different instruments (e.g. laser systems) the user is prompted to only select one.
+    '''
+    lasers = []
+    chambers = []
+    rheeds = []
+    elegant_dict = {}
+    for lyr in layers:
+        instruments = lyr.get_instruments(apikey)
+        lasers.append(instruments["laser_system"])
+        chambers.append(instruments["deposition_chamber"])
+        rheeds.append(instruments["rheed_system"])
+        elegant_dict[f"layer_{lyr.layer_number}"] = {
+            "laser_system": instruments["laser_system"],
+            "deposition_chamber": instruments["deposition_chamber"],
+            "rheed_system": instruments["rheed_system"],
+        }
+    ded_lasers = list( set( lasers ) )
+    ded_chambers = list( set( chambers ) )
+    ded_rheeds = list( set( rheeds ) )
+    elegant_dict["multilayer"] = {
+        # Keep key names human readable since they're used in the messages of the following errors
+        "laser_system": ", ".join(ded_lasers),
+        "deposition_chamber": ", ".join(ded_chambers),
+        "rheed_system": ", ".join(ded_rheeds)
+    } # dictionary's name is a joke
+    # updated_dict = {} # use this for containing the final dataset
+    # for ded in elegant_dict:
+    #     if len(elegant_dict[ded]) == 0:
+    #         # if len of list is 0 - empty list - raise error
+    #         raise IndexError(f"Missing data: no Laser System, Chamber and/or RHEED System is specified in any of the Deposition-type experiments related to this sample. Fix this on eLabFTW before retrying. Affected list: {ded}.")
+    #     elif len(elegant_dict[ded]) > 1:
+    #         # if len of list is > 1 - too many values - allow the user to pick one
+    #         print("Warning: different instruments have been used for different layers - which is currently not allowed.")
+    #         # there's a better way to do this but I can't remember now for the life of me...
+    #         i = 0
+    #         while i < len(elegant_dict[ded]):
+    #             print(f"{i} - {elegant_dict[ded][i]}")
+    #             i += 1
+    #         ans = None
+    #         while not type(ans) == int or not ans in range(0, len(elegant_dict[ded])):
+    #             ans = input("Please pick one of the previous (0, 1, ...) [default = 0]: ") or "0"
+    #             if ans.isdigit():
+    #                 ans = int(ans)
+    #             continue # unnecessary?
+    #         updated_dict[ded] = elegant_dict[ded][ans]
+    #     elif elegant_dict[ded][0] in ["", 0, None]:
+    #         # if len is 1 BUT value is "", 0 or None raise error
+    #         raise ValueError(f"Missing data: a Laser System, Chamber and/or RHEED System which is specified across all the Deposition-type experiments related to this sample is either empty or invalid. Fix this on eLabFTW before retrying. Affected list: {ded}.")
+    #     else:
+    #         # if none of the previous (only 1 value), that single value is used
+    #         updated_dict[ded] = elegant_dict[ded][0]
+    # instruments_used_dict = {
+    #     "laser_system": updated_dict["Laser Systems"],
+    #     "deposition_chamber": updated_dict["Deposition Chamber"],
+    #     "rheed_system": updated_dict["RHEED Systems"],
+    # }
+    return elegant_dict
+    
+    ### OLD CODE
+    # if 0 in [ len(i) for i in elegant_list ]:
+    #     # i.e. if length of one of the lists in elegant_list is zero (missing data):
+    #     raise IndexError("Missing data: no Laser System, Chamber and/or RHEED System is specified in any of the Deposition-type experiments related to this sample.")
+    # if not all([ len(i) == 1 for i in elegant_list ]):
+    #     print("Warning: different instruments have been used for different layers - which is currently not allowed.")
+    #     # for every element in elegant list check if len > 1 and if it is 
+    #     print("Selecting the first occurence for every category...")
+    ###
+    # lasers = { f"layer_{lyr.layer_number}": lyr.laser_system for lyr in layers }
+    # chambers = { f"layer_{lyr.layer_number}": lyr.deposition_chamber for lyr in layers }
+    # rheeds = { f"layer_{lyr.layer_number}": lyr.rheed_system for lyr in layers }
+    # instruments_used_dict = {
+    #     "laser_system": lasers,
+    #     "deposition_chamber": chambers,
+    #     "rheed_system": rheeds,
+    # }
+
+def analyse_rheed_data(data):
+    '''
+    Takes the content of a tsv file and returns a dictionary with timestamps and intensities.
+    The file should contain a 2D array composed of 4 columns - where the first column is a timestamp and the other three are RHEED intensities - and an unspecified number of rows.
+    
+    -----
+    Time    Layer1_Int1     Layer1_Int2     Layer1_Int3
+    -----
+
+    Distinct ValueErrors are raised if:
+    - The array is not 2-dimensional;
+    - The total number of columns does not equate exactly 1+3 (= 4).
+
+    Time is expressed in seconds, intensities are normalized (adimensional).
+
+    # TO-DO: complete this description...
+    Written with help from DeepSeek.
+    '''
+    # Verifying the format of the input file:
+    if data.ndim != 2:
+        raise ValueError(f"Unexpected trace format: expected 2D array, got ndim = {data.ndim}.")
+    n_cols = data.shape[1] # 0 = rows, 1 = columns
+    if n_cols > 4:
+        print(f"Warning! The input file (for Realtime Window Analysis) has {n_cols-4} more than needed.\nOnly 4 columns will be considered - with the first representing time and the others representing RHEED intensities.")
+    if n_cols < 4:
+        raise ValueError(f"Insufficient number of columns: expected 4, got n_cols = {n_cols}.")
+    n_time_points = data.shape[0]
+
+    # Get time (all rows of col 0) as Float64:
+    time = data[:, 0].astype(np.float64, copy=False) # copy=False suggested by LLM for mem. eff.
+
+    # Get intensities (all rows of cols 1,2,3) as Float32:
+    intensities = data[:, 1:4].astype(np.float32, copy=False)
+
+    return {
+        "time": time,
+        "intensity": intensities,
+    }
+
+
+def make_nexus_schema_dictionary(substrate_object, layers):
+    '''
+    Main function, takes all the other functions to reconstruct the full dataset. Takes a Substrate-class object (output of the chain_entrypoint_to_batch() function) and a list of Layer-class objects (output of the chain_entrypoint_to_layers() function), returns dictionary with the same schema as the NeXus standard for PLD fabrications.
+    '''
+    instruments = deduplicate_instruments_from_layers(layers)
+    pld_fabrication = {
+        "sample": {
+            "substrate": {
+                "name": substrate_object.name,
+                "chemical_formula" : substrate_object.get_compound_formula(apikey),
+                "orientation" : substrate_object.orientation,
+                "miscut_angle" : {
+                    "value": substrate_object.miscut_angle,
+                    "units": substrate_object.miscut_angle_unit
+                },
+                "miscut_direction" : substrate_object.miscut_direction,
+                "thickness" : {
+                    "value": substrate_object.thickness,
+                    "units": substrate_object.thickness_unit,
+                },
+                "dimensions" : substrate_object.dimensions,
+                "surface_treatment" : substrate_object.surface_treatment,
+                "manufacturer" : substrate_object.manufacturer,
+                "batch_id" : substrate_object.batch_id,
+            },
+            "multilayer": {},
+        },
+        "instruments_used": instruments["multilayer"],
+    }
+    multilayer = pld_fabrication["sample"]["multilayer"]
+    for layer in layers:
+        name = "layer_" + layer.layer_number
+        target_object = chain_layer_to_target(layer)
+        target_dict = {
+            "name": target_object.name,
+            "chemical_formula" : target_object.get_compound_formula(apikey),
+            "description" : target_object.description,
+            "shape" : target_object.shape,
+            "dimensions" : target_object.dimensions,
+            "thickness" : {
+                "value": target_object.thickness,
+                "units": target_object.thickness_unit,
+            },
+            "solid_form" : target_object.solid_form,
+            "manufacturer" : target_object.manufacturer,
+            "batch_id" : target_object.name,
+            # TO-DO: currently not available:
+        }
+        multilayer[name] = {
+            "target": target_dict,
+            "start_time": layer.start_time,
+            "operator": layer.operator,
+            "description": layer.description,
+            "number_of_pulses": layer.number_of_pulses,
+            "deposition_time": {
+                "value": layer.deposition_time,
+                "units": layer.deposition_time_unit,
+            },
+            "temperature": {
+                "value": layer.temperature,
+                "units": layer.temperature_unit,
+            },
+            "heating_method": layer.heating_method,
+            "layer_thickness": {
+                "value": layer.layer_thickness,
+                "units": layer.layer_thickness_unit,
+            },
+            "buffer_gas": layer.buffer_gas,
+            "process_pressure": {
+                "value": layer.process_pressure,
+                "units": layer.process_pressure_unit,
+            },
+            "heater_target_distance": {
+                "value": layer.heater_target_distance,
+                "units": layer.heater_target_distance_unit,
+            },
+            "repetition_rate": {
+                "value": layer.repetition_rate,
+                "units": layer.repetition_rate_unit,
+            },
+            "laser_fluence": {
+                "value": layer.laser_fluence,
+                "units": layer.laser_fluence_unit,
+            },
+            "laser_spot_area": {
+                "value": layer.laser_spot_area,
+                "units": layer.laser_spot_area_unit,
+            },
+            "laser_energy": {
+                "value": layer.laser_energy,
+                "units": layer.laser_energy_unit,
+            },
+            "laser_rastering": {
+                "geometry": layer.laser_rastering_geometry,
+                "positions": layer.laser_rastering_positions,
+                "velocities": layer.laser_rastering_velocities,
+            },
+            "pre_annealing": {
+                "ambient_gas": layer.pre_annealing_ambient_gas,
+                "pressure": {
+                    "value": layer.pre_annealing_pressure,
+                    "units": layer.pre_annealing_pressure_unit,
+                },
+                "temperature": {
+                    "value": layer.pre_annealing_temperature,
+                    "units": layer.pre_annealing_temperature_unit,
+                },
+                "duration": {
+                    "value": layer.pre_annealing_duration,
+                    "units": layer.pre_annealing_duration_unit,
+                },
+            },
+            "post_annealing": {
+                "ambient_gas": layer.post_annealing_ambient_gas,
+                "pressure": {
+                    "value": layer.post_annealing_pressure,
+                    "units": layer.post_annealing_pressure_unit,
+                },
+                "temperature": {
+                    "value": layer.post_annealing_temperature,
+                    "units": layer.post_annealing_temperature_unit,
+                },
+                "duration": {
+                    "value": layer.post_annealing_duration,
+                    "units": layer.post_annealing_duration_unit,
+                },
+            },
+            "instruments_used": instruments[name],
+        }
+    return pld_fabrication
+
+def build_nexus_file(pld_fabrication, output_path, rheed_osc=None):
+    # NOTE: look at the mail attachment from Emiliano...
+    with h5py.File(output_path, "w") as f:
+        nx_pld_entry = f.create_group("pld_fabrication")
+        nx_pld_entry.attrs["NX_class"] = "NXentry"
+
+        # Sample section
+        nx_sample = nx_pld_entry.create_group("sample")
+        nx_sample.attrs["NX_class"] = "NXsample"
+        sample_dict = pld_fabrication["sample"]
+
+        # Substrate sub-section
+        nx_substrate = nx_sample.create_group("substrate")
+        nx_substrate.attrs["NX_class"] = "NXsubentry"
+        substrate_dict = sample_dict["substrate"]
+        try:
+            # Substrate fields (datasets)
+            nx_substrate.create_dataset("name", data=substrate_dict["name"])
+            nx_substrate.create_dataset("chemical_formula", data=substrate_dict["chemical_formula"])
+            nx_substrate.create_dataset("orientation", data=substrate_dict["orientation"])
+            nx_substrate.create_dataset("miscut_angle", data=substrate_dict["miscut_angle"]["value"]) # float
+            nx_substrate["miscut_angle"].attrs["units"] = substrate_dict["miscut_angle"]["units"]
+            nx_substrate.create_dataset("miscut_direction", data=substrate_dict["miscut_direction"])
+            nx_substrate.create_dataset("thickness", data=substrate_dict["thickness"]["value"]) # float/int
+            nx_substrate["thickness"].attrs["units"] = substrate_dict["thickness"]["units"]
+            nx_substrate.create_dataset("dimensions", data=substrate_dict["dimensions"])
+            nx_substrate.create_dataset("surface_treatment", data=substrate_dict["surface_treatment"])
+            nx_substrate.create_dataset("manufacturer", data=substrate_dict["manufacturer"])
+            nx_substrate.create_dataset("batch_id", data=substrate_dict["batch_id"])
+        except TypeError as te:
+            # sooner or later I'll handle this too - not today tho
+            raise TypeError(te)
+
+        # Multilayer sub-section
+        nx_multilayer = nx_sample.create_group("multilayer")
+        nx_multilayer.attrs["NX_class"] = "NXsubentry"
+        multilayer_dict = sample_dict["multilayer"]
+        # Repeat FOR EACH LAYER:
+        for layer in multilayer_dict:
+            nx_layer = nx_multilayer.create_group(layer)
+            nx_layer.attrs["NX_class"] = "NXsubentry"
+            layer_dict = multilayer_dict[layer]
+            # Sub-groups of a layer
+            ## Target
+            nx_target = nx_layer.create_group("target")
+            nx_target.attrs["NX_class"] = "NXsample"
+            target_dict = layer_dict["target"]
+            ## Rastering and Annealing
+            nx_laser_rastering = nx_layer.create_group("laser_rastering")
+            nx_laser_rastering.attrs["NX_class"] = "NXprocess"
+            rastering_dict = layer_dict["laser_rastering"]
+            nx_pre_annealing = nx_layer.create_group("pre_annealing")
+            nx_pre_annealing.attrs["NX_class"] = "NXprocess"
+            pre_ann_dict = layer_dict["pre_annealing"]
+            nx_post_annealing = nx_layer.create_group("post_annealing")
+            nx_post_annealing.attrs["NX_class"] = "NXprocess"
+            post_ann_dict = layer_dict["post_annealing"]
+            nx_layer_instruments = nx_layer.create_group("instruments_used")
+            nx_layer_instruments.attrs["NX_class"] = "NXinstrument"
+            layer_instruments_dict = layer_dict["instruments_used"]
+
+            ## Target metadata
+            try:
+                nx_target.create_dataset("name", data = target_dict["name"])
+                nx_target.create_dataset("chemical_formula", data = target_dict["chemical_formula"])
+                nx_target.create_dataset("description", data = target_dict["description"])
+                nx_target.create_dataset("shape", data = target_dict["shape"])
+                nx_target.create_dataset("dimensions", data = target_dict["dimensions"])
+                nx_target.create_dataset("thickness", data = target_dict["thickness"]["value"]) # float/int
+                nx_target["thickness"].attrs["units"] = target_dict["thickness"]["units"]
+                nx_target.create_dataset("solid_form", data = target_dict["solid_form"])
+                nx_target.create_dataset("manufacturer", data = target_dict["manufacturer"])
+                nx_target.create_dataset("batch_id", data = target_dict["batch_id"])
+            except TypeError as te:
+                raise TypeError(te)
+            ## Other layer-specific metadata
+            try:
+                nx_layer.create_dataset("start_time", data = layer_dict["start_time"])
+                nx_layer.create_dataset("operator", data = layer_dict["operator"])
+                nx_layer.create_dataset("number_of_pulses", data = layer_dict["number_of_pulses"])
+                nx_layer.create_dataset("deposition_time", data = layer_dict["deposition_time"]["value"])
+                nx_layer["deposition_time"].attrs["units"] = layer_dict["deposition_time"]["units"]
+                nx_layer.create_dataset("repetition_rate", data = layer_dict["repetition_rate"]["value"])
+                nx_layer["repetition_rate"].attrs["units"] = layer_dict["repetition_rate"]["units"]
+                nx_layer.create_dataset("temperature", data = layer_dict["temperature"]["value"])
+                nx_layer["temperature"].attrs["units"] = layer_dict["temperature"]["units"]
+                nx_layer.create_dataset("heating_method", data = layer_dict["heating_method"])
+                nx_layer.create_dataset("layer_thickness", data = layer_dict["layer_thickness"]["value"])
+                nx_layer["layer_thickness"].attrs["units"] = layer_dict["layer_thickness"]["units"]
+                nx_layer.create_dataset("buffer_gas", data = layer_dict["buffer_gas"])
+                nx_layer.create_dataset("process_pressure", data = layer_dict["process_pressure"]["value"])
+                nx_layer["process_pressure"].attrs["units"] = layer_dict["process_pressure"]["units"]
+                nx_layer.create_dataset("heater_target_distance", data = layer_dict["heater_target_distance"]["value"])
+                nx_layer["heater_target_distance"].attrs["units"] = layer_dict["heater_target_distance"]["units"]
+                nx_layer.create_dataset("laser_fluence", data = layer_dict["laser_fluence"]["value"])
+                nx_layer["laser_fluence"].attrs["units"] = layer_dict["laser_fluence"]["units"]
+                nx_layer.create_dataset("laser_spot_area", data = layer_dict["laser_spot_area"]["value"])
+                nx_layer["laser_spot_area"].attrs["units"] = layer_dict["laser_spot_area"]["units"]
+                nx_layer.create_dataset("laser_energy", data = layer_dict["laser_energy"]["value"])
+                nx_layer["laser_energy"].attrs["units"] = layer_dict["laser_energy"]["units"]
+            except TypeError as te:
+                raise TypeError(te)
+            ## Rastering metadata
+            try:
+                nx_laser_rastering.create_dataset("geometry", data = rastering_dict["geometry"])
+                nx_laser_rastering.create_dataset("positions", data = rastering_dict["positions"])
+                nx_laser_rastering.create_dataset("velocities", data = rastering_dict["velocities"])
+            except TypeError as te:
+                raise TypeError(te)
+            ## Annealing metadata
+            try:
+                nx_pre_annealing.create_dataset("ambient_gas", data = pre_ann_dict["ambient_gas"])
+                nx_pre_annealing.create_dataset("pressure", data = pre_ann_dict["pressure"]["value"])
+                nx_pre_annealing["pressure"].attrs["units"] = pre_ann_dict["pressure"]["units"]
+                nx_pre_annealing.create_dataset("temperature", data = pre_ann_dict["temperature"]["value"])
+                nx_pre_annealing["temperature"].attrs["units"] = pre_ann_dict["temperature"]["units"]
+                nx_pre_annealing.create_dataset("duration", data = pre_ann_dict["duration"]["value"])
+                nx_pre_annealing["duration"].attrs["units"] = pre_ann_dict["duration"]["units"]
+            except TypeError as te:
+                raise TypeError(te)
+            try:
+                nx_post_annealing.create_dataset("ambient_gas", data = post_ann_dict["ambient_gas"])
+                nx_post_annealing.create_dataset("pressure", data = post_ann_dict["pressure"]["value"])
+                nx_post_annealing["pressure"].attrs["units"] = post_ann_dict["pressure"]["units"]
+                nx_post_annealing.create_dataset("temperature", data = post_ann_dict["temperature"]["value"])
+                nx_post_annealing["temperature"].attrs["units"] = post_ann_dict["temperature"]["units"]
+                nx_post_annealing.create_dataset("duration", data = post_ann_dict["duration"]["value"])
+                nx_post_annealing["duration"].attrs["units"] = post_ann_dict["duration"]["units"]
+            except TypeError as te:
+                raise TypeError(te)
+            try:
+                nx_layer_instruments.create_dataset("laser_system", data = layer_instruments_dict["laser_system"])
+                nx_layer_instruments.create_dataset("deposition_chamber", data = layer_instruments_dict["deposition_chamber"])
+                nx_layer_instruments.create_dataset("rheed_system", data = layer_instruments_dict["rheed_system"])
+            except TypeError as te:
+                raise TypeError(te)
+        
+        # Instruments used section
+        nx_instruments = nx_pld_entry.create_group("instruments_used")
+        nx_instruments.attrs["NX_class"] = "NXinstrument"
+        instruments_dict = pld_fabrication["instruments_used"]
+        try:
+            nx_instruments.create_dataset("laser_system", data = instruments_dict["laser_system"])
+            nx_instruments.create_dataset("deposition_chamber", data = instruments_dict["deposition_chamber"])
+            nx_instruments.create_dataset("rheed_system", data = instruments_dict["rheed_system"])
+        except TypeError as te:
+            raise TypeError(te)
+        
+        # RHEED data section
+        if rheed_osc is not None:
+            nx_rheed = nx_pld_entry.create_group("rheed_data")
+            nx_rheed.attrs["NX_class"] = "NXdata"
+
+            # Asse temporale
+            t_ds = nx_rheed.create_dataset("time", data=rheed_osc["time"])
+            t_ds.attrs["units"] = "s"
+            t_ds.attrs["long_name"] = "Time"
+
+            # Intensità: shape (n_layers, n_timepoints, 3)
+            i_ds = nx_rheed.create_dataset("intensity", data=rheed_osc["intensity"])
+            i_ds.attrs["units"] = "a.u."
+            i_ds.attrs["long_name"] = "RHEED Intensity"
+
+            # Attributi NXdata — notazione NeXus 3.x corretta
+            nx_rheed.attrs["signal"] = "intensity"
+            nx_rheed.attrs["axes"] = [".", "time", "."]   # solo l'asse 1 (time) è denominato
+            nx_rheed.attrs["time_indices"] = np.array([1], dtype=np.int32)
+            # ###########
+            # nx_rheed = nx_pld_entry.create_group("rheed_data")
+            # nx_rheed.attrs["NX_class"] = "NXdata"
+
+            # nx_rheed.create_dataset("time", data=rheed_osc["time"])
+            # nx_rheed["time"].attrs["units"] = "s"
+
+            # nx_rheed.create_dataset("intensity", data=rheed_osc["intensity"])
+            # #nx_rheed["intensity"].attrs["units"] = "counts"
+            # nx_rheed["intensity"].attrs["long_name"] = "RHEED intensity"
+            # nx_rheed.attrs["signal"] = "intensity"
+            # nx_rheed.attrs["axes"] = "layer:time:channel"
+            # nx_rheed.attrs["layer_indices"] = [0]  # asse layer
+            # nx_rheed.attrs["time_indices"] = [1]   # asse tempo
+            # nx_rheed.attrs["channel_indices"] = [2]
+    return
+
+if __name__=="__main__":
+    # TO-DO: place the API base URL somewhere else. 
+    ELABFTW_API_URL = "https://elabftw.fisica.unina.it/api/v2"
+    apikey = getpass("Paste API key here: ")
+    elabid = input("Enter elabid of your starting sample [default = 1111]: ") or 1111
+    data = APIHandler(apikey).get_entry_from_elabid(elabid)
+    sample = Entrypoint(data)
+    sample_name = sample.name.strip().replace(" ","_")
+    substrate_object = chain_entrypoint_to_batch(sample) # Substrate-class object
+    layers = chain_entrypoint_to_layers(sample) # list of Layer-class objects
+    n_layers = len(layers) # total number of layers on the sample
+    result = make_nexus_schema_dictionary(substrate_object, layers)
+    # print(make_nexus_schema_dictionary(substrate_object, layers)) # debug
+    with open (f"output/sample-{sample_name}.json", "w") as f:
+        json.dump(result, f, indent=3)
+    # TO-DO: remove the hard-coded path of the RWA file
+    # ideally the script should download a TXT/CSV file from each layer
+    # (IF PRESENT ←→ also handle missing file error)
+    # and merge all data in a single file to analyse it
+    with open(f"tests/Realtime_Window_Analysis.txt", "r") as o:
+        osc = np.loadtxt(o, delimiter="\t")
+    try:
+        rheed_osc = analyse_rheed_data(data=osc) or None # analyze rheed data first, build the file later
+    except ValueError as ve:
+        raise ValueError(f"Error with function analyse_rheed_data. {ve}\nPlease make sure the Realtime Window Analysis file is exactly 4 columns wide - where the first column represents time and the others are RHEED intensities.")
+    build_nexus_file(result, output_path=f"output/sample-{sample_name}-nexus.h5", rheed_osc=rheed_osc)

tests/chained_requests.py

@@ -0,0 +1,207 @@
+import os, json, requests
+from getpass import getpass
+
+class Header:
+    '''
+    Class to standardize the format of the headers of our http requests.
+    '''
+    def __init__(self, apikey=""):
+        '''Init method, apikey suggested but not required (empty by default).'''
+        self.auth = {"Authorization" : apikey}
+        self.content = {"Content-Type" : "application/json"}
+        self.header = {**self.auth, **self.content}
+
+def get_entry_from_elabid(elabid, entryType="items"):
+    '''
+    Function which returns entrypoint data (as dictionary) from its elabid.
+    '''
+    header = Header(apikey).header
+    response = requests.get(
+        headers = header,
+        url = f"{ELABFTW_API_URL}/{entryType}/{elabid}",
+        verify=True
+    )
+    if response.status_code // 100 in [2,3]:
+        entry_data = response.json()
+        return entry_data
+    else:
+        raise ConnectionError(f"HTTP request failed with status code: {response.status_code}.")
+
+
+
+class Layer:
+    '''
+    Layer(layer_data) - where layer_data is a Python dictionary.
+
+    Meant to be used for eLabFTW Experiments of the "PLD Deposition" category.
+
+    eLabFTW experiments contain most of the data required by the NeXus file - although every layer is on a different eLab entry;
+    unfortunately, some data like the target's chemical formula must be retrieved through additional HTTP requests.
+    Attributes 'target_elabid', 'rheed_system_elabid' and 'laser_system_elabid' contain elabid's for these resources, which are all items.
+    '''
+    def __init__(self, layer_data):
+        try:
+            self.extra = layer_data["metadata_decoded"]["extra_fields"]
+            self.layer_number = self.extra["Layer Progressive Number"]["value"] # integer
+            self.target_elabid = self.extra["Target"]["value"] # elabid
+            self.rheed_system_elabid = self.extra["RHEED System"]["value"] # elabid
+            self.laser_system_elabid = self.extra["Laser System"]["value"] # elabid
+            self.start_time = layer_data.get("created_at")
+            self.operator = layer_data.get("fullname")
+            self.description = layer_data.get("body")
+            self.deposition_time = self.extra["Duration"]["value"]
+            self.repetition_rate = self.extra["Repetition rate"]["value"]
+            try:
+                self.number_of_pulses = float(self.deposition_time) * float(self.repetition_rate)
+            except ValueError:
+                # Since number_of_pulses is required, if it can't be calculated raise error:
+                raise ValueError("""
+    Fatal: either Duration or Repetition Rate are empty or invalid.
+    This has to be an error, since these fields are required by the NeXus standard.
+    Please edit your eLabFTW entry and retry.
+                """)
+            self.temperature = self.extra["Heater temperature"]["value"] # Note: this field used to have a trailing space in its name
+            self.process_pressure = self.extra["Process pressure"]["value"] # Note: this field used to have a trailing space in its name
+            self.heating_method = self.extra["Heating Method"]["value"]
+            self.layer_thickness = self.extra["Thickness"]["value"]
+            self.buffer_gas = self.extra["Buffer gas"]["value"]
+            self.heater_target_distance = self.extra["Heater-target distance"]["value"]
+            self.laser_fluence = self.extra["Laser Intensity"]["value"] # here fluence = intensity
+            self.laser_spot_area = self.extra["Spot Area"]["value"]
+            try:
+                self.laser_energy = float(self.laser_fluence) * float(self.laser_spot_area)
+            except ValueError:
+                # Since laser_energy is NOT required, if it can't be calculated warn user but allow the software to continue execution:
+                print("""
+    Warning: either Laser Intensity or Spot Area are empty or invalid.
+    If you think this is an error, please edit your eLabFTW entry and retry.
+    Setting Laser Energy to NoneType.
+                """)
+                # Placeholder
+                self.laser_energy = None
+            # Laser rasternig section
+            self.laser_rastering_geometry = self.extra["Laser Rastering Geometry"]["value"]
+            self.laser_rastering_positions = self.extra["Laser Rastering Position"]["value"]
+            self.laser_rastering_velocities = self.extra["Laser Rastering Speed"]["value"]
+            # Pre annealing section
+            self.pre_annealing_ambient_gas = self.extra["Buffer gas Pre"]["value"]
+            self.pre_annealing_pressure = self.extra["Process pressure Pre"]["value"]
+            self.pre_annealing_temperature = self.extra["Heater temperature Pre"]["value"]
+            self.pre_annealing_duration = self.extra["Duration Pre"]["value"]
+            # Post annealing section
+            self.post_annealing_ambient_gas = self.extra["Buffer gas PA"]["value"]
+            self.post_annealing_pressure = self.extra["Process pressure PA"]["value"]
+            self.post_annealing_temperature = self.extra["Heater temperature PA"]["value"]
+            self.post_annealing_duration = self.extra["Duration PA"]["value"]
+            # Rejected but suggested by the NeXus standard:
+            #self.laser_rastering_coefficients = None
+        except KeyError as k:
+            # Some keys are not required and can be called through the .get() method - which is permissive and allows null values;
+            # Other keys are required so if they can't be called (invalid or null) raise error and stop execution of the program:
+            raise KeyError(f"The provided dictionary lacks a \"{k}\" key. Check the deposition layer entry on eLabFTW and make sure you used the correct Experiment template.")
+
+class Entrypoint:
+    '''
+    Entrypoint(sample_data) - where sample_data is a Python dictionary.
+
+    Meant to be used for eLabFTW Resources of the "Sample" category.
+
+    The entrypoint is the starting point of the process of resolving the data chain.
+    The entrypoint must be a dictionary containing the data of a sample, created directly from the JSON of the item endpoint on eLabFTW - which can be done through the function get_entry_from_elabid.
+    '''
+    def __init__(self, sample_data):
+        try:
+            self.extra = sample_data["metadata_decoded"]["extra_fields"]
+            self.linked_items = sample_data["items_links"]
+            self.batch_elabid = self.extra["Substrate batch"]["value"]
+            self.linked_experiments = sample_data["related_experiments_links"]
+            self.linked_experiments_elabid = [ i["entityid"] for i in self.linked_experiments ]
+        except KeyError as k:
+            # Some keys are not required and can be called through the .get() method - which is permissive and allows null values;
+            # Other keys are required so if they can't be called (invalid or null) raise error and stop execution of the program:
+            raise KeyError(f"The provided dictionary lacks a \"{k}\" key. Check the sample entry on eLabFTW and make sure you used the correct Resource template.")
+        # Non-required attributes:
+        self.name = sample_data.get("title") or None # error prevention is more important than preventing empty fields here
+
+class Material:
+    '''
+    Material(material_data) - where material_data is a Python dictionary.
+
+    Meant to be used for eLabFTW Resources of either the "PLD Target" or the "Substrate" categories.
+
+    Both a PLD Target and a Substrate are materials made of a certain compound, of which we want to know:
+        * Name and formula;
+        * Shape and dimensions;
+        * Misc.
+    '''
+    def __init__(self, material_data):
+        try:
+            self.extra = material_data["metadata_decoded"]["extra_fields"]
+            self.compound_elabid = self.extra["Compound"]["value"]
+        except KeyError as k:
+            # Some keys are not required and can be called through the .get() method - which is permissive and allows null values;
+            # Other keys are required so if they can't be called (invalid or null) raise error and stop execution of the program:
+            raise KeyError(f"The provided dictionary lacks a \"{k}\" key. Check the target/substrate entry on eLabFTW and make sure you used the correct Resource template.")
+    def get_compound_data(self):
+        raw_compound_data = get_entry_from_elabid(self.compound_elabid, entryType="items")
+        name = raw_compound_data["title"]
+        extra = raw_compound_data["metadata_decoded"]["extra_fields"]
+        formula = extra.get("Chemical formula")
+        cas = extra.get("CAS number ") or { "value": None }
+        compound_data = {
+            "name" : name,
+            "chemical_formula" : formula.get("value"),
+            "cas_number" : cas.get("value")
+        }
+        return compound_data
+    def get_compound_formula(self):
+        formula = self.get_compound_data().get("chemical_formula")
+        return formula
+
+
+
+if __name__=="__main__":
+    print(f"=======================\n===== DEBUG MODE! =====\n=======================\n")
+    ELABFTW_API_URL = "https://elabftw.fisica.unina.it/api/v2"
+    apikey = getpass("Paste API key here: ")
+    # TEST. In production the entryType will probably just be "items" since the entrypoint is an item (sample).
+    entryType = None
+    while entryType not in ["items", "experiments"]:
+        eT = input("Enter a valid entry type [items, experiments]: ")
+        # This allows for a shortcut: instead of prompting the type before and the elabid after I can just prompt both at the same time - e.g. e51 is exp. 51, i1108 is item 1108...
+        if eT[0] in ["e", "i"] and eT[-1].isnumeric():
+            try:
+                elabid = int(eT[1:])
+                eT = eT[0]
+            except Exception:
+                print("Usage: i|item|items|i[ELABID] for items, e|experiment|experiments|e[ELABID] for experiments.")
+                continue
+        match eT:
+            case "items" | "i" | "item":
+                entryType = "items"
+            case "experiments" | "e" | "exp" | "experiment":
+                entryType = "experiments"
+            case _:
+                continue
+    # This will probably be reworked in production
+    try:
+        elabid = elabid
+    except NameError:
+        elabid = input("Input elabid here [default = 1111]: ") or 1111
+    data = get_entry_from_elabid(elabid, entryType)
+    if entryType == "experiments":
+        layer = Layer(data)
+        result = layer.__dict__
+        result.pop("extra")
+        print(result)
+    elif entryType == "items":
+        if data.get("category_title") == "Sample":
+            item = Entrypoint(data)
+        elif data.get("category_title") in ["PLD Target", "Substrate"]:
+            item = Material(data)
+            print(item.get_compound_formula(apikey))
+        else:
+            raise Exception("The selected item or experiment is not in one of the following categories: [Sample, PLD Target, Substrate, PLD Deposition].")
+        result = item.__dict__
+        result.pop("extra")
+        print(result)

tests/layer_A.json

@@ -0,0 +1,480 @@
+{
+	"access_key": null,
+	"body": "",
+	"body_html": "",
+	"canread": "{\"base\": 40, \"teams\": [], \"users\": [], \"teamgroups\": []}",
+	"canread_is_immutable": 0,
+	"canwrite": "{\"base\": 20, \"teams\": [], \"users\": [], \"teamgroups\": []}",
+	"canwrite_is_immutable": 0,
+	"category": 2,
+	"category_color": "8b8d43",
+	"category_title": "PLD Deposition",
+	"comments": [],
+	"compounds": [],
+	"containers": [],
+	"content_type": 1,
+	"created_at": "2026-02-09 09:53:50",
+	"custom_id": null,
+	"date": "2026-02-09",
+	"elabid": "20260209-8ba774f27896bbec37a7cc5eab18747dbac3a4fb",
+	"events_start": null,
+	"events_start_itemid": null,
+	"exclusive_edit_mode": null,
+	"experiments_links": [
+		{
+			"entityid": 59,
+			"title": "Na-26-015 lao on stocazzo",
+			"custom_id": null,
+			"elabid": "20260209-554888c7b8a17efd963fece04426f6ec5722fa8a",
+			"link_state": 1,
+			"page": "experiments.php",
+			"type": "experiments",
+			"category_title": "PLD Deposition",
+			"category_color": "8b8d43",
+			"status_title": null,
+			"status_color": null
+		}
+	],
+	"firstname": "Emiliano",
+	"fullname": "Emiliano Di Gennaro",
+	"id": 58,
+	"is_pinned": 0,
+	"items_links": [
+		{
+			"entityid": 1075,
+			"title": "ETO single crystal",
+			"custom_id": null,
+			"elabid": "20260126-6f77512fa5a3c5803fcfc64797ffa003429094dc",
+			"link_state": 1,
+			"is_bookable": 0,
+			"page": "database.php",
+			"type": "items",
+			"category_title": "PLD Target",
+			"category_color": "1a5fb4",
+			"status_title": null,
+			"status_color": null
+		},
+		{
+			"entityid": 1074,
+			"title": "LAO single crystal",
+			"custom_id": null,
+			"elabid": "20260126-2cef9e71c0ff4aa15062cb6562f64f6ac3a366fb",
+			"link_state": 1,
+			"is_bookable": 0,
+			"page": "database.php",
+			"type": "items",
+			"category_title": "PLD Target",
+			"category_color": "1a5fb4",
+			"status_title": null,
+			"status_color": null
+		},
+		{
+			"entityid": 1099,
+			"title": "Coherent Excimer Laser (KrF 248 nm)",
+			"custom_id": null,
+			"elabid": "20260126-9175c1674aef9947736fbc12447f912c8ea9bc81",
+			"link_state": 1,
+			"is_bookable": 0,
+			"page": "database.php",
+			"type": "items",
+			"category_title": "Process Instrument",
+			"category_color": "a51d2d",
+			"status_title": "Available",
+			"status_color": "6a7753"
+		},
+		{
+			"entityid": 1096,
+			"title": "PLD  Chamber I (small area)",
+			"custom_id": null,
+			"elabid": "20260126-19cf5d06fd119f841383f21db1c29eebfad550c5",
+			"link_state": 1,
+			"is_bookable": 1,
+			"page": "database.php",
+			"type": "items",
+			"category_title": "Process Instrument",
+			"category_color": "a51d2d",
+			"status_title": "Available",
+			"status_color": "6a7753"
+		},
+		{
+			"entityid": 1098,
+			"title": "STAIB RHEED 30",
+			"custom_id": null,
+			"elabid": "20260126-5df7738907b198451c19296ab07e5093d12a3ead",
+			"link_state": 1,
+			"is_bookable": 0,
+			"page": "database.php",
+			"type": "items",
+			"category_title": "Process Instrument",
+			"category_color": "a51d2d",
+			"status_title": "Available",
+			"status_color": "6a7753"
+		},
+		{
+			"entityid": 1111,
+			"title": "Na-26-015",
+			"custom_id": null,
+			"elabid": "20260209-6e19f19795b7ea79594a35d9a11da1896b13453e",
+			"link_state": 1,
+			"is_bookable": 0,
+			"page": "database.php",
+			"type": "items",
+			"category_title": "Sample",
+			"category_color": "ffbe6f",
+			"status_title": null,
+			"status_color": null
+		}
+	],
+	"lastchangeby": 2,
+	"lastname": "Di Gennaro",
+	"locked": 0,
+	"locked_at": null,
+	"lockedby": null,
+	"metadata": "{\"elabftw\": {\"extra_fields_groups\": [{\"id\": 1, \"name\": \"Process\"}, {\"id\": 2, \"name\": \"Laser\"}, {\"id\": 3, \"name\": \"Pre Annealing\"}, {\"id\": 4, \"name\": \"Post Annealing\"}, {\"id\": 5, \"name\": \"Instruments\"}]}, \"extra_fields\": {\"Sample\": {\"type\": \"items\", \"value\": 1111, \"group_id\": 1, \"position\": 0, \"required\": true}, \"Target\": {\"type\": \"items\", \"value\": 1075, \"group_id\": 1, \"position\": 2, \"required\": true}, \"Chamber\": {\"type\": \"items\", \"value\": 1096, \"group_id\": 5, \"position\": 0, \"required\": true}, \"Duration\": {\"type\": \"number\", \"unit\": \"s\", \"units\": [\"s\", \"min\"], \"value\": \"45\", \"group_id\": 1, \"position\": 3, \"required\": true}, \"Spot Area\": {\"type\": \"number\", \"unit\": \"mm^2\", \"units\": [\"mm^2\"], \"value\": \"0.8\", \"group_id\": 2, \"position\": 2}, \"Thickness\": {\"type\": \"number\", \"unit\": \"u.c.\", \"units\": [\"u.c.\", \"nm\"], \"value\": \"3\", \"group_id\": 1, \"position\": 4}, \"Buffer gas\": {\"type\": \"select\", \"value\": \"O2\", \"options\": [\"O2\", \"N2\", \"Ar\", \"\"], \"group_id\": 1, \"position\": 5}, \"Duration PA\": {\"type\": \"number\", \"unit\": \"s\", \"units\": [\"s\", \"min\"], \"value\": \"\", \"group_id\": 4, \"position\": 0}, \"Duration Pre\": {\"type\": \"number\", \"unit\": \"s\", \"units\": [\"s\", \"min\"], \"value\": \"\", \"group_id\": 3, \"position\": 0}, \"Laser System\": {\"type\": \"items\", \"value\": 1099, \"group_id\": 5, \"position\": 1}, \"RHEED System\": {\"type\": \"items\", \"value\": 1098, \"group_id\": 5, \"position\": 2}, \"Buffer gas PA\": {\"type\": \"select\", \"value\": \"O2\", \"options\": [\"O2\", \"N2\", \"Ar\", \"\"], \"group_id\": 4, \"position\": 1}, \"Buffer gas Pre\": {\"type\": \"select\", \"value\": \"O2\", \"options\": [\"O2\", \"N2\", \"Ar\", \"\"], \"group_id\": 3, \"position\": 1}, \"Heating Method\": {\"type\": \"select\", \"value\": \"Radiative Heater\", \"options\": [\"Radiative Heater\", \"Laser Heater\"], \"group_id\": 1, \"position\": 9}, \"Laser Intensity\": {\"type\": \"number\", \"unit\": \"J/(s cm^2)\", \"units\": [\"J/(s cm^2)\"], \"value\": \"1.5\", \"group_id\": 2, \"position\": 0}, \"Repetition rate\": {\"type\": \"number\", \"unit\": \"Hz\", \"units\": [\"Hz\"], \"value\": \"1\", \"group_id\": 2, \"position\": 1}, \"Process pressure\": {\"type\": \"number\", \"unit\": \"mbar\", \"units\": [\"mbar\"], \"value\": \"1e-3\", \"group_id\": 1, \"position\": 6}, \"Heater temperature\": {\"type\": \"number\", \"unit\": \"\u00b0C\", \"units\": [\"\u00b0C\"], \"value\": \"650\", \"group_id\": 1, \"position\": 7}, \"Process pressure PA\": {\"type\": \"number\", \"unit\": \"mbar\", \"units\": [\"mbar\"], \"value\": \"\", \"group_id\": 4, \"position\": 2}, \"Process pressure Pre\": {\"type\": \"number\", \"unit\": \"mbar\", \"units\": [\"mbar\"], \"value\": \"\", \"group_id\": 3, \"position\": 2}, \"Heater temperature PA\": {\"type\": \"number\", \"unit\": \"\u00b0C\", \"units\": [\"\u00b0C\"], \"value\": \"\", \"group_id\": 4, \"position\": 3}, \"Laser Rastering Speed\": {\"type\": \"number\", \"unit\": \"\", \"units\": [], \"value\": \"\", \"group_id\": 2, \"position\": 4}, \"Heater temperature Pre\": {\"type\": \"number\", \"unit\": \"\u00b0C\", \"units\": [\"\u00b0C\"], \"value\": \"\", \"group_id\": 3, \"position\": 3}, \"Heater-target distance\": {\"type\": \"number\", \"unit\": \"mm\", \"units\": [\"mm\"], \"value\": \"45\", \"group_id\": 1, \"position\": 8}, \"Laser Rastering Geometry\": {\"type\": \"select\", \"value\": \"none\", \"options\": [\"none\", \"on a square\", \"on a rectangle\", \"on a line\", \"other\"], \"group_id\": 2, \"position\": 3}, \"Laser Rastering Position\": {\"type\": \"number\", \"unit\": \"\", \"units\": [], \"value\": \"\", \"group_id\": 2, \"position\": 5}, \"Layer Progressive Number\": {\"type\": \"number\", \"unit\": \"\", \"units\": [], \"value\": \"2\", \"group_id\": 1, \"position\": 1, \"required\": true}}}",
+	"metadata_decoded": {
+		"elabftw": {
+			"extra_fields_groups": [
+				{
+					"id": 1,
+					"name": "Process"
+				},
+				{
+					"id": 2,
+					"name": "Laser"
+				},
+				{
+					"id": 3,
+					"name": "Pre Annealing"
+				},
+				{
+					"id": 4,
+					"name": "Post Annealing"
+				},
+				{
+					"id": 5,
+					"name": "Instruments"
+				}
+			]
+		},
+		"extra_fields": {
+			"Sample": {
+				"type": "items",
+				"value": 1111,
+				"group_id": 1,
+				"position": 0,
+				"required": true
+			},
+			"Target": {
+				"type": "items",
+				"value": 1075,
+				"group_id": 1,
+				"position": 2,
+				"required": true
+			},
+			"Chamber": {
+				"type": "items",
+				"value": 1096,
+				"group_id": 5,
+				"position": 0,
+				"required": true
+			},
+			"Duration": {
+				"type": "number",
+				"unit": "s",
+				"units": [
+					"s",
+					"min"
+				],
+				"value": "69",
+				"group_id": 1,
+				"position": 3,
+				"required": true
+			},
+			"Spot Area": {
+				"type": "number",
+				"unit": "mm^2",
+				"units": [
+					"mm^2"
+				],
+				"value": "0.8",
+				"group_id": 2,
+				"position": 2
+			},
+			"Thickness": {
+				"type": "number",
+				"unit": "u.c.",
+				"units": [
+					"u.c.",
+					"nm"
+				],
+				"value": "3",
+				"group_id": 1,
+				"position": 4
+			},
+			"Buffer gas": {
+				"type": "select",
+				"value": "O2",
+				"options": [
+					"O2",
+					"N2",
+					"Ar",
+					""
+				],
+				"group_id": 1,
+				"position": 5
+			},
+			"Duration PA": {
+				"type": "number",
+				"unit": "s",
+				"units": [
+					"s",
+					"min"
+				],
+				"value": "",
+				"group_id": 4,
+				"position": 0
+			},
+			"Duration Pre": {
+				"type": "number",
+				"unit": "s",
+				"units": [
+					"s",
+					"min"
+				],
+				"value": "",
+				"group_id": 3,
+				"position": 0
+			},
+			"Laser System": {
+				"type": "items",
+				"value": 1099,
+				"group_id": 5,
+				"position": 1
+			},
+			"RHEED System": {
+				"type": "items",
+				"value": 1098,
+				"group_id": 5,
+				"position": 2
+			},
+			"Buffer gas PA": {
+				"type": "select",
+				"value": "O2",
+				"options": [
+					"O2",
+					"N2",
+					"Ar",
+					""
+				],
+				"group_id": 4,
+				"position": 1
+			},
+			"Buffer gas Pre": {
+				"type": "select",
+				"value": "O2",
+				"options": [
+					"O2",
+					"N2",
+					"Ar",
+					""
+				],
+				"group_id": 3,
+				"position": 1
+			},
+			"Heating Method": {
+				"type": "select",
+				"value": "Radiative Heater",
+				"options": [
+					"Radiative Heater",
+					"Laser Heater"
+				],
+				"group_id": 1,
+				"position": 9
+			},
+			"Laser Intensity": {
+				"type": "number",
+				"unit": "J/(s cm^2)",
+				"units": [
+					"J/(s cm^2)"
+				],
+				"value": "1.5",
+				"group_id": 2,
+				"position": 0
+			},
+			"Repetition rate": {
+				"type": "number",
+				"unit": "Hz",
+				"units": [
+					"Hz"
+				],
+				"value": "1",
+				"group_id": 2,
+				"position": 1
+			},
+			"Process pressure": {
+				"type": "number",
+				"unit": "mbar",
+				"units": [
+					"mbar"
+				],
+				"value": "1e-3",
+				"group_id": 1,
+				"position": 6
+			},
+			"Heater temperature": {
+				"type": "number",
+				"unit": "\u00b0C",
+				"units": [
+					"\u00b0C"
+				],
+				"value": "650",
+				"group_id": 1,
+				"position": 7
+			},
+			"Process pressure PA": {
+				"type": "number",
+				"unit": "mbar",
+				"units": [
+					"mbar"
+				],
+				"value": "",
+				"group_id": 4,
+				"position": 2
+			},
+			"Process pressure Pre": {
+				"type": "number",
+				"unit": "mbar",
+				"units": [
+					"mbar"
+				],
+				"value": "",
+				"group_id": 3,
+				"position": 2
+			},
+			"Heater temperature PA": {
+				"type": "number",
+				"unit": "\u00b0C",
+				"units": [
+					"\u00b0C"
+				],
+				"value": "",
+				"group_id": 4,
+				"position": 3
+			},
+			"Laser Rastering Speed": {
+				"type": "number",
+				"unit": "",
+				"units": [],
+				"value": "",
+				"group_id": 2,
+				"position": 4
+			},
+			"Heater temperature Pre": {
+				"type": "number",
+				"unit": "\u00b0C",
+				"units": [
+					"\u00b0C"
+				],
+				"value": "",
+				"group_id": 3,
+				"position": 3
+			},
+			"Heater-target distance": {
+				"type": "number",
+				"unit": "mm",
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+	"userid": 2
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+				"unit": "\u00b0C",
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+				"type": "select",
+				"value": "none",
+				"options": [
+					"none",
+					"on a square",
+					"on a rectangle",
+					"on a line",
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tests/layer_C.json

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