Added carbon API!

api/carbon.py

@@ -0,0 +1,80 @@
+import requests
+import numpy as np 
+import matplotlib.pyplot as plt
+import datetime
+from util import logging
+
+def current_level() -> []:
+    url = "https://api.carbonintensity.org.uk/intensity"
+    response = requests.get(url)
+
+    if not response.ok:
+        logging.error(f"Failed to access Carbon API: {response.status_code} [{url}]")
+
+    data = response.json()["data"][0]
+    return [data["from"], data["intensity"]["forecast"], data["intensity"]["actual"], data["intensity"]["index"]]
+
+def level_at(date: str) -> []:
+    url = f"https://api.carbonintensity.org.uk/intensity/date/{date}"
+    response = requests.get(url)
+
+    if not response.ok:
+        logging.error(f"Failed to access Carbon API: {response.status_code} [{url}]")
+        return []
+
+    if len(response.json()["data"]) == 0:
+        return []
+
+    data = response.json()["data"][0]
+    return [data["from"], data["intensity"]["forecast"], data["intensity"]["actual"], data["intensity"]["index"]]
+
+def level_from_to(start: str, stop: str) -> str:
+    url = f"https://api.carbonintensity.org.uk/intensity/{start}/{stop}"
+    response = requests.get(url)
+
+    if not response.ok:
+        logging.error(f"Failed to access Carbon API: {response.status_code} [{url}]")
+        return ""
+
+    if len(response.json()["data"]) == 0:
+        return []
+
+    data = response.json()["data"]
+
+    x = []
+    measured = []
+    indices = []
+
+    for i in range(len(data)):
+        intensity = data[i]["intensity"]
+        x.append(datetime.datetime.strptime(data[i]["from"], "%Y-%m-%dT%H:%MZ"))
+        measured.append(intensity["actual"])
+        indices.append(intensity["index"])
+
+    curr_color = indices[0]
+    curr_color_index = 0
+    for i in range(len(measured)):
+        if indices[i] != curr_color:
+            color = ""
+            if curr_color == "very low":
+                color = "#5bcc32"
+            if curr_color == "low":
+                color = "#87cc32"
+            if curr_color == "moderate":
+                color = "#ccc932"
+            if curr_color == "high":
+                color = "#cc8e32"
+            if curr_color == "very high":
+                color = "#cc4f32"
+
+            plt.plot(x[curr_color_index:i+1], measured[curr_color_index:i+1], color)
+            curr_color_index = i
+            curr_color = indices[i]
+
+    plt.xlabel("Time & Date")
+    plt.ylabel("Carbon Intensity [gCO2/kWh]")
+    plt.xticks(rotation=45)
+    plt.gcf().subplots_adjust(bottom=0.2)
+    plt.savefig("plot.png")
+    plt.clf()
+    return "plot.png"