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-rw-r--r--app/admin/datasets.py97
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diff --git a/app/admin/datasets.py b/app/admin/datasets.py
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+# -*- coding: utf-8 -*-
+
+"""
+Dataset handling
+
+The dataset model is a JSON object as follows:
+
+ {
+ "name": "name of the dataset",
+ "n_obs": number of observations,
+ "n_dim": number of dimensions,
+ "series": {
+ "V1": {
+ "type": "float",
+ "raw": [list of observations]
+ },
+ "V2": {
+ "type": "int",
+ "raw": [list of observations]
+ },
+ "V3": {
+ "type": "category",
+ "levels": ["A", "B", "C"],
+ "raw": [list of observations]
+ }
+ }
+ }
+
+Missing values must be denoted by 'NaN' (this is understood by the JSON
+decoder).
+
+Author: Gertjan van den Burg
+
+"""
+
+import json
+import hashlib
+
+
+def validate_dataset(filename):
+ """ Validate a dataset uploaded to the webapp
+ Return None on success and a string error on failure
+ """
+
+ with open(filename, "rb") as fid:
+ try:
+ data = json.load(fid)
+ except json.JSONDecoderError as err:
+ return "JSON decoding error: %s" % err.msg
+
+ required_keys = ["name", "n_obs", "n_dim", "series"]
+ for key in required_keys:
+ if not key in data:
+ return "Required key missing: %s" % key
+
+ if len(data["series"]) != data["n_dim"]:
+ return "Number of dimensions and number of series don't match"
+
+ required_keys = ["type", "raw"]
+ for idx, var in enumerate(data["series"]):
+ if not var == "V%i" % (idx + 1):
+ return "Unexpected variable name, expected 'V<int>', got %s" % var
+ vardict = data["series"][var]
+ for key in required_keys:
+ if not key in vardict:
+ return "Key '%s' missing for variable '%s'" % (key, var)
+ if vardict["type"] == "category":
+ if not "levels" in vardict:
+ return (
+ "Variable '%s' has categorical type but 'levels' is missing"
+ % (var)
+ )
+ if not len(vardict["raw"]) == data["n_obs"]:
+ return (
+ "Length of data for variable '%s' not equal to n_obs = %i"
+ % (var, data["n_obs"])
+ )
+
+ return None
+
+
+def get_name_from_dataset(filename):
+ with open(filename, "rb") as fid:
+ data = json.load(fid)
+ return data["name"]
+
+
+def md5sum(filename):
+ """ Compute the MD5 hash for a given filename """
+ blocksize = 65536
+ hasher = hashlib.md5()
+ with open(filename, "rb") as fid:
+ buf = fid.read(blocksize)
+ while len(buf) > 0:
+ hasher.update(buf)
+ buf = fid.read(blocksize)
+ return hasher.hexdigest()