diff --git a/pyzebra/load_1D.py b/pyzebra/load_1D.py
index 30ff5b8..cd1c75b 100644
--- a/pyzebra/load_1D.py
+++ b/pyzebra/load_1D.py
@@ -1,3 +1,4 @@
+import os
 import re
 from collections import defaultdict
 from decimal import Decimal
@@ -68,105 +69,113 @@ def load_1D(filepath):
     Names of these dictionaries are M + measurement number. They include HKL indeces, angles,
     monitors, stepsize and array of counts
     """
-    det_variables = {"file_type": str(filepath)[-3:], "meta": {}}
     with open(filepath, "r") as infile:
-        # read metadata
-        for line in infile:
-            det_variables["Measurements"] = {}
-            if "=" in line:
-                variable, value = line.split("=")
-                variable = variable.strip()
-                if variable in META_VARS_FLOAT:
-                    det_variables["meta"][variable] = float(value)
-                elif variable in META_VARS_STR:
-                    det_variables["meta"][variable] = str(value)[:-1].strip()
-                elif variable in META_UB_MATRIX:
-                    det_variables["meta"][variable] = re.findall(r"[-+]?\d*\.\d+|\d+", str(value))
-
-            if "#data" in line:
-                # this is the end of metadata and the start of data section
-                break
-
-        # read data
-        if det_variables["file_type"] == "ccl":
-            decimal = list()
-            data = infile.readlines()
-            position = -1
-            for lines in data:
-                position = position + 1
-                if (
-                    bool(re.match("(\s\s\s\d)", lines[0:4])) == True
-                    or bool(re.match("(\s\s\d\d)", lines[0:4])) == True
-                    or bool(re.match("(\s\d\d\d)", lines[0:4])) == True
-                    or bool(re.match("(\d\d\d\d)", lines[0:4])) == True
-                ):
-                    counts = []
-                    measurement_number = int(lines.split()[0])
-                    d = {}
-                    d["h_index"] = float(lines.split()[1])
-                    decimal.append(bool(Decimal(d["h_index"]) % 1 == 0))
-                    d["k_index"] = float(lines.split()[2])
-                    decimal.append(bool(Decimal(d["k_index"]) % 1 == 0))
-                    d["l_index"] = float(lines.split()[3])
-                    decimal.append(bool(Decimal(d["l_index"]) % 1 == 0))
-                    if det_variables["meta"]["zebra_mode"] == "bi":
-                        d["twotheta_angle"] = float(lines.split()[4])  # gamma
-                        d["omega_angle"] = float(lines.split()[5])  # omega
-                        d["chi_angle"] = float(lines.split()[6])  # nu
-                        d["phi_angle"] = float(lines.split()[7])  # doesnt matter
-                    elif det_variables["meta"]["zebra_mode"] == "nb":
-                        d["gamma_angle"] = float(lines.split()[4])  # gamma
-                        d["omega_angle"] = float(lines.split()[5])  # omega
-                        d["nu_angle"] = float(lines.split()[6])  # nu
-                        d["unkwn_angle"] = float(lines.split()[7])
-
-                    next_line = data[position + 1]
-                    d["number_of_measurements"] = int(next_line.split()[0])
-                    d["angle_step"] = float(next_line.split()[1])
-                    d["monitor"] = float(next_line.split()[2])
-                    d["unkwn1"] = float(next_line.split()[3])
-                    d["unkwn2"] = float(next_line.split()[4])
-                    d["date"] = str(next_line.split()[5])
-                    d["time"] = str(next_line.split()[6])
-                    d["scan_type"] = str(next_line.split()[7])
-                    for i in range(
-                        int(int(next_line.split()[0]) / 10) + (int(next_line.split()[0]) % 10 > 0)
-                    ):
-                        fileline = data[position + 2 + i].split()
-                        numbers = [int(w) for w in fileline]
-                        counts = counts + numbers
-                    d["om"] = np.linspace(
-                        float(lines.split()[5])
-                        - (int(next_line.split()[0]) / 2) * float(next_line.split()[1]),
-                        float(lines.split()[5])
-                        + (int(next_line.split()[0]) / 2) * float(next_line.split()[1]),
-                        int(next_line.split()[0]),
-                    )
-                    d["Counts"] = counts
-                    det_variables["Measurements"][str("M" + str(measurement_number))] = d
-
-                    if all(decimal):
-                        det_variables["meta"]["indices"] = "hkl"
-                    else:
-                        det_variables["meta"]["indices"] = "real"
-
-        elif det_variables["file_type"] == "dat":
-            # skip the first 2 rows, the third row contans the column names
-            next(infile)
-            next(infile)
-            row_names = next(infile).split()
-
-            data_cols = defaultdict(list)
-            for line in infile:
-                if "END-OF-DATA" in line:
-                    # this is the end of data
-                    break
-
-                for name, val in zip(row_names, line.split()):
-                    data_cols[name].append(float(val))
-
-            det_variables["Measurements"] = dict(data_cols)
-        else:
-            print("Unknown file extention")
+        _, ext = os.path.splitext(filepath)
+        det_variables = parse_1D(infile, data_type=ext)
 
     return det_variables
+
+
+def parse_1D(fileobj, data_type):
+    # read metadata
+    metadata = {}
+    for line in fileobj:
+        if "=" in line:
+            variable, value = line.split("=")
+            variable = variable.strip()
+            if variable in META_VARS_FLOAT:
+                metadata[variable] = float(value)
+            elif variable in META_VARS_STR:
+                metadata[variable] = str(value)[:-1].strip()
+            elif variable in META_UB_MATRIX:
+                metadata[variable] = re.findall(r"[-+]?\d*\.\d+|\d+", str(value))
+
+        if "#data" in line:
+            # this is the end of metadata and the start of data section
+            break
+
+    # read data
+    if data_type == ".ccl":
+        measurements = {}
+        decimal = list()
+        data = fileobj.readlines()
+        position = -1
+        for lines in data:
+            position = position + 1
+            if (
+                bool(re.match("(\s\s\s\d)", lines[0:4])) == True
+                or bool(re.match("(\s\s\d\d)", lines[0:4])) == True
+                or bool(re.match("(\s\d\d\d)", lines[0:4])) == True
+                or bool(re.match("(\d\d\d\d)", lines[0:4])) == True
+            ):
+                counts = []
+                measurement_number = int(lines.split()[0])
+                d = {}
+                d["h_index"] = float(lines.split()[1])
+                decimal.append(bool(Decimal(d["h_index"]) % 1 == 0))
+                d["k_index"] = float(lines.split()[2])
+                decimal.append(bool(Decimal(d["k_index"]) % 1 == 0))
+                d["l_index"] = float(lines.split()[3])
+                decimal.append(bool(Decimal(d["l_index"]) % 1 == 0))
+                if metadata["zebra_mode"] == "bi":
+                    d["twotheta_angle"] = float(lines.split()[4])  # gamma
+                    d["omega_angle"] = float(lines.split()[5])  # omega
+                    d["chi_angle"] = float(lines.split()[6])  # nu
+                    d["phi_angle"] = float(lines.split()[7])  # doesnt matter
+                elif metadata["zebra_mode"] == "nb":
+                    d["gamma_angle"] = float(lines.split()[4])  # gamma
+                    d["omega_angle"] = float(lines.split()[5])  # omega
+                    d["nu_angle"] = float(lines.split()[6])  # nu
+                    d["unkwn_angle"] = float(lines.split()[7])
+
+                next_line = data[position + 1]
+                d["number_of_measurements"] = int(next_line.split()[0])
+                d["angle_step"] = float(next_line.split()[1])
+                d["monitor"] = float(next_line.split()[2])
+                d["unkwn1"] = float(next_line.split()[3])
+                d["unkwn2"] = float(next_line.split()[4])
+                d["date"] = str(next_line.split()[5])
+                d["time"] = str(next_line.split()[6])
+                d["scan_type"] = str(next_line.split()[7])
+                for i in range(
+                    int(int(next_line.split()[0]) / 10) + (int(next_line.split()[0]) % 10 > 0)
+                ):
+                    fileline = data[position + 2 + i].split()
+                    numbers = [int(w) for w in fileline]
+                    counts = counts + numbers
+                d["om"] = np.linspace(
+                    float(lines.split()[5])
+                    - (int(next_line.split()[0]) / 2) * float(next_line.split()[1]),
+                    float(lines.split()[5])
+                    + (int(next_line.split()[0]) / 2) * float(next_line.split()[1]),
+                    int(next_line.split()[0]),
+                )
+                d["Counts"] = counts
+                measurements[str("M" + str(measurement_number))] = d
+
+                if all(decimal):
+                    metadata["indices"] = "hkl"
+                else:
+                    metadata["indices"] = "real"
+
+    elif data_type == ".dat":
+        # skip the first 2 rows, the third row contans the column names
+        next(fileobj)
+        next(fileobj)
+        col_names = next(fileobj).split()
+
+        data_cols = defaultdict(list)
+        for line in fileobj:
+            if "END-OF-DATA" in line:
+                # this is the end of data
+                break
+
+            for name, val in zip(col_names, line.split()):
+                data_cols[name].append(float(val))
+
+        measurements = dict(data_cols)
+
+    else:
+        print("Unknown file extention")
+
+    return {"meta": metadata, "Measurements": measurements}