matze/farmos.py-wagner
1
0
Fork 0
Code Issues 5 Pull Requests Actions Packages Projects Releases Wiki Activity

Details gefixt

Browse Source
This commit is contained in:
Wir
2024-11-05 15:58:42 +01:00
parent 775135e6b3
commit 17b64357a0
1 changed files with 349 additions and 74 deletions
Download Patch File Download Diff File Expand all files Collapse all files

417
reporting.ipynb
View File

@@ -16,13 +16,13 @@
"import importlib\n",
"importlib.reload(neo)\n",
"\n",
"plant = neo.Plant.from_id(\"76f89f82-1238-43bb-b34f-796a92d491a2\")\n",
"print(plant.name)\n",
"#plant = neo.Asset.Plant.from_id(\"76f89f82-1238-43bb-b34f-796a92d491a2\")\n",
"#print(plant.name)\n",
"\n",
"\n",
"seedings = neo.Seeding.get_list()\n",
"seedings = neo.Log.Seeding.get_list()\n",
"for seeding in seedings:\n",
" plant = seeding.getPlant()\n",
" plant = seeding.plant\n",
" equipment = seeding.equipment[0]\n",
" quantity1 = seeding.quantities[0]\n",
" quantity2 = seeding.quantities[1]\n",
@@ -45,6 +45,50 @@
" print(f\"Q2 units: {quantity2.units.name}\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c1bf2175-65f7-4704-8d39-15a08849c9ae",
"metadata": {
"jupyter": {
"source_hidden": true
}
},
"outputs": [],
"source": [
"import neofarm.lib as neo\n",
"import importlib\n",
"importlib.reload(neo)\n",
"\n",
"#plant = neo.Asset.Plant.from_id(\"76f89f82-1238-43bb-b34f-796a92d491a2\")\n",
"#print(plant.name)\n",
"\n",
"\n",
"seedings = neo.Log.Purchase.get_list()\n",
"for seeding in seedings:\n",
" plant = seeding.plant\n",
" #equipment = seeding.equipment[0]\n",
" quantity1 = seeding.quantities[0]\n",
" # quantity2 = seeding.quantities[1]\n",
" print(f\"name: {seeding.name}\")\n",
" print(f\"timestamp: {seeding.timestamp}\")\n",
" #print(f\"plant name: {plant.name}\")\n",
" #print(f\"plant crop: {plant.crop[0].name}\")\n",
" #print(f\"plant loc: {plant.location[0].name}\")\n",
" #print(f\"equipment: {equipment.name}\")\n",
" print(f\"isMovement: {seeding.isMovement}\")\n",
" print(f\"Q1 type: {quantity1.type}\")\n",
" print(f\"Q1 measure: {quantity1.measure}\")\n",
" print(f\"Q1 value: {quantity1.value}\")\n",
" print(f\"Q1 units: {quantity1.units.name}\")\n",
" print(f\"Q1 inv adj: {quantity1.inventory_adjustment}\")\n",
" print(f\"Q1 inv ass: {quantity1.inventory_asset.name}\")\n",
" print(f\"Q2 type: {quantity2.type}\")\n",
" print(f\"Q2 measure: {quantity2.measure}\")\n",
" print(f\"Q2 value: {quantity2.value}\")\n",
" print(f\"Q2 units: {quantity2.units.name}\")"
]
},
{
"cell_type": "code",
"execution_count": null,
@@ -158,8 +202,8 @@
" print(f\"quant_measure: {input.quantities[0].measure}\")\n",
" print(f\"quant_value: {input.quantities[0].value}\")\n",
" print(f\"quant_inventory_adjustment: {input.quantities[0].inventory_adjustment}\")\n",
" print(f\"quant_value: {input.quantities[0].unit_price}\")\n",
"\n",
" #print(f\"quant_value: {input.quantities[0].unit_price}\")\n",
" print(f\"unit_name: {input.quantities[0].units.name}\")\n",
" \t\n",
"#log Seeding \n",
" logs = asset.get_logs_of_type(neo.Log.Seeding)\n",
@@ -246,70 +290,214 @@
},
{
"cell_type": "code",
"execution_count": null,
"id": "ce30a9db-735e-4174-ad56-0f0079ab04c6",
"execution_count": 1,
"id": "649e4d8e-c3a9-4d5f-9bdf-9427f416fca9",
"metadata": {
"collapsed": true,
"jupyter": {
"outputs_hidden": true,
"source_hidden": true
}
},
"outputs": [],
"source": [
"#alle logs von einem Plant in Tabelle\n",
"import neofarm.lib as neo\n",
"import pandas as pd\n",
"from datetime import datetime\n",
"\n",
"if __name__ == \"__main__\":\n",
" asset = neo.Asset.Plant.from_id(\"76f89f82-1238-43bb-b34f-796a92d491a2\")\n",
" \n",
" # Definiere den Pflanzennamen\n",
" PlantName = \"W-Raps Helmacker Plant 24/25\"\n",
" print(f\"PlantName: {PlantName}\")\n",
" \n",
" # Erstelle eine Liste, in der die Log-Daten für die Tabelle gesammelt werden\n",
" data = []\n",
"\n",
" # Funktion, um die Logs zu verarbeiten und zur Tabelle hinzuzufügen\n",
" def process_logs(logs, log_type):\n",
" for log in logs:\n",
" formatted_date = datetime.fromisoformat(log.timestamp).strftime(\"%d.%m.%y %H:%M\")\n",
" equipment_name = log.equipment[0].name if log.equipment else \"\"\n",
" location_name = log.location[0].name if hasattr(log, 'location') and log.location else \"\"\n",
" data.append({\n",
" #\"PlantName\": PlantName,\n",
" \"LogType\": log_type,\n",
" \"Name\": log.name,\n",
" \"Timestamp\": formatted_date,\n",
" \"Equipment\": equipment_name,\n",
" \"Location\": location_name\n",
" })\n",
"\n",
" # Verarbeite die verschiedenen Log-Typen\n",
" process_logs(asset.get_logs_of_type(neo.Log.Maintenance), \"Maintenance\")\n",
" process_logs(asset.get_logs_of_type(neo.Log.Seeding), \"Seeding\")\n",
" process_logs(asset.get_logs_of_type(neo.Log.Input), \"Input\")\n",
" process_logs(asset.get_logs_of_type(neo.Log.Medical), \"Medical\")\n",
" process_logs(asset.get_logs_of_type(neo.Log.Harvest), \"Harvest\")\n",
" process_logs(asset.get_logs_of_type(neo.Log.Sale), \"Sale\")\n",
"\n",
" # Erstelle ein DataFrame aus den gesammelten Daten und zeige es an\n",
" df = pd.DataFrame(data)\n",
" display(df)\n"
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"PlantName: W-Raps Helmacker Plant 24/25\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "649e4d8e-c3a9-4d5f-9bdf-9427f416fca9",
"metadata": {
"jupyter": {
"source_hidden": true
}
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>PlantName</th>\n",
" <th>LogType</th>\n",
" <th>Name</th>\n",
" <th>Timestamp</th>\n",
" <th>Equipment</th>\n",
" <th>Location</th>\n",
" <th>QuantType</th>\n",
" <th>QuantMeasure</th>\n",
" <th>QuantValue</th>\n",
" <th>QuantInventoryAdjustment</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>W-Raps Helmacker Plant 24/25</td>\n",
" <td>Maintenance</td>\n",
" <td>Scheibeneggen Helmacker Maintenance 24/25</td>\n",
" <td>28.07.24 11:34</td>\n",
" <td>Scheibenegge Catros</td>\n",
" <td>None</td>\n",
" <td>quantity--price</td>\n",
" <td>time</td>\n",
" <td>2</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>W-Raps Helmacker Plant 24/25</td>\n",
" <td>Seeding</td>\n",
" <td>W-Raps Otello KWS Helmacker Seeding 24/25</td>\n",
" <td>22.08.24 22:00</td>\n",
" <td>Sähmaschine Cataya</td>\n",
" <td>Helmacker</td>\n",
" <td>quantity--standard</td>\n",
" <td>weight</td>\n",
" <td>50</td>\n",
" <td>decrement</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>W-Raps Helmacker Plant 24/25</td>\n",
" <td>Seeding</td>\n",
" <td>W-Raps Otello KWS Helmacker Seeding 24/25</td>\n",
" <td>22.08.24 22:00</td>\n",
" <td>Sähmaschine Cataya</td>\n",
" <td>Helmacker</td>\n",
" <td>quantity--standard</td>\n",
" <td>area</td>\n",
" <td>3.02</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>W-Raps Helmacker Plant 24/25</td>\n",
" <td>Input</td>\n",
" <td>Innovert Raps Input 24/25</td>\n",
" <td>12.10.24 13:18</td>\n",
" <td>Spritze</td>\n",
" <td>None</td>\n",
" <td>quantity--standard</td>\n",
" <td>volume</td>\n",
" <td>10</td>\n",
" <td>decrement</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>W-Raps Helmacker Plant 24/25</td>\n",
" <td>Input</td>\n",
" <td>Innovert Raps Input 24/25</td>\n",
" <td>03.11.24 23:00</td>\n",
" <td>Spritze</td>\n",
" <td>None</td>\n",
" <td>quantity--standard</td>\n",
" <td>volume</td>\n",
" <td>10</td>\n",
" <td>decrement</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>W-Raps Helmacker Plant 24/25</td>\n",
" <td>Medical</td>\n",
" <td>Schneckenkorn Medical 24/25</td>\n",
" <td>30.08.24 06:42</td>\n",
" <td>Schneckenkornstreuer Leinfelder</td>\n",
" <td>None</td>\n",
" <td>quantity--standard</td>\n",
" <td>weight</td>\n",
" <td>10</td>\n",
" <td>decrement</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>W-Raps Helmacker Plant 24/25</td>\n",
" <td>Harvest</td>\n",
" <td>W-Raps Helmacker Harvest 24/25</td>\n",
" <td>20.10.24 10:11</td>\n",
" <td>Mähdrescher Leinfelder</td>\n",
" <td>None</td>\n",
" <td>quantity--standard</td>\n",
" <td>weight</td>\n",
" <td>5</td>\n",
" <td>increment</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>W-Raps Helmacker Plant 24/25</td>\n",
" <td>Sale</td>\n",
" <td>W-Raps Sale 24/25</td>\n",
" <td>28.10.24 07:54</td>\n",
" <td>None</td>\n",
" <td>None</td>\n",
" <td>quantity--price</td>\n",
" <td>weight</td>\n",
" <td>5</td>\n",
" <td>decrement</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" PlantName LogType \\\n",
"0 W-Raps Helmacker Plant 24/25 Maintenance \n",
"1 W-Raps Helmacker Plant 24/25 Seeding \n",
"2 W-Raps Helmacker Plant 24/25 Seeding \n",
"3 W-Raps Helmacker Plant 24/25 Input \n",
"4 W-Raps Helmacker Plant 24/25 Input \n",
"5 W-Raps Helmacker Plant 24/25 Medical \n",
"6 W-Raps Helmacker Plant 24/25 Harvest \n",
"7 W-Raps Helmacker Plant 24/25 Sale \n",
"\n",
" Name Timestamp \\\n",
"0 Scheibeneggen Helmacker Maintenance 24/25 28.07.24 11:34 \n",
"1 W-Raps Otello KWS Helmacker Seeding 24/25 22.08.24 22:00 \n",
"2 W-Raps Otello KWS Helmacker Seeding 24/25 22.08.24 22:00 \n",
"3 Innovert Raps Input 24/25 12.10.24 13:18 \n",
"4 Innovert Raps Input 24/25 03.11.24 23:00 \n",
"5 Schneckenkorn Medical 24/25 30.08.24 06:42 \n",
"6 W-Raps Helmacker Harvest 24/25 20.10.24 10:11 \n",
"7 W-Raps Sale 24/25 28.10.24 07:54 \n",
"\n",
" Equipment Location QuantType \\\n",
"0 Scheibenegge Catros None quantity--price \n",
"1 Sähmaschine Cataya Helmacker quantity--standard \n",
"2 Sähmaschine Cataya Helmacker quantity--standard \n",
"3 Spritze None quantity--standard \n",
"4 Spritze None quantity--standard \n",
"5 Schneckenkornstreuer Leinfelder None quantity--standard \n",
"6 Mähdrescher Leinfelder None quantity--standard \n",
"7 None None quantity--price \n",
"\n",
" QuantMeasure QuantValue QuantInventoryAdjustment \n",
"0 time 2 None \n",
"1 weight 50 decrement \n",
"2 area 3.02 None \n",
"3 volume 10 decrement \n",
"4 volume 10 decrement \n",
"5 weight 10 decrement \n",
"6 weight 5 increment \n",
"7 weight 5 decrement "
]
},
"outputs": [],
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#Alle logs zu plant mit quantities untereinander\n",
"#Alle logs zu plant mit quantities untereinander tabelle\n",
"import neofarm.lib as neo\n",
"import pandas as pd\n",
"from datetime import datetime\n",
@@ -385,7 +573,7 @@
},
"outputs": [],
"source": [
"#Alle logs zu plant mit quantities nebeneinander\n",
"#Alle logs zu plant mit quantities nebeneinander tabelle\n",
"import neofarm.lib as neo\n",
"import pandas as pd\n",
"from datetime import datetime\n",
@@ -465,7 +653,11 @@
"cell_type": "code",
"execution_count": null,
"id": "c1b73098-08f3-43fd-9bf0-d3d628b15e0d",
"metadata": {},
"metadata": {
"jupyter": {
"source_hidden": true
}
},
"outputs": [],
"source": [
"#Alle logs zu plant mit quantities nebeneinander in Excel exportiert\n",
@@ -481,12 +673,16 @@
"downloads_folder = os.path.join(os.path.expanduser(\"~\"), \"Downloads\")\n",
"file_path = os.path.join(downloads_folder, \"PlantLogs.xlsx\")\n",
"\n",
"if __name__ == \"__main__\":\n",
" asset = neo.Asset.Plant.from_id(\"76f89f82-1238-43bb-b34f-796a92d491a2\")\n",
"\n",
" # Definiere den Pflanzennamen\n",
" PlantName = \"W-Raps Helmacker Plant 24/25\"\n",
" print(f\"PlantName: {PlantName}\")\n",
"# Definiere den Pflanzennamen\n",
"PlantName = \"W-Raps Helmacker Plant 24/25\"\n",
"PlantId = \"76f89f82-1238-43bb-b34f-796a92d491a2\"\n",
"print(f\"PlantName: {PlantName}\")\n",
"\n",
"\n",
"if __name__ == \"__main__\":\n",
" asset = neo.Asset.Plant.from_id(PlantId)\n",
"\n",
"\n",
" data = []\n",
"\n",
@@ -573,7 +769,7 @@
" cell.number_format = 'DD.MM.YYYY' # Setze das Datumsformat\n",
" \n",
" max_length = max(max_length, len(str(cell.value)) if cell.value else 0)\n",
" adjusted_width = (max_length + 2) * 1.2 # Extra Puffer hinzufügen\n",
" adjusted_width = (max_length + 2) * 1.0 # Extra Puffer hinzufügen\n",
" worksheet.column_dimensions[col_letter].width = adjusted_width\n",
"\n",
" # Speichern Sie die Datei\n",
@@ -585,9 +781,88 @@
"cell_type": "code",
"execution_count": null,
"id": "ebcc62d0-4334-4c61-aaa2-14cd96e8a6f0",
"metadata": {},
"metadata": {
"jupyter": {
"source_hidden": true
}
},
"outputs": [],
"source": []
"source": [
"#Alle logs zu plant mit quantities nebeneinander tabelle\n",
"import neofarm.lib as neo\n",
"import pandas as pd\n",
"from datetime import datetime\n",
"\n",
"if __name__ == \"__main__\":\n",
" asset = neo.Asset.Plant.from_id(\"\")\n",
"\n",
" # Definiere den Pflanzennamen\n",
" PlantName = \"W-Raps Helmacker Plant 24/25\"\n",
" print(f\"PlantName: {PlantName}\")\n",
"\n",
" # Erstelle eine Liste zur Sammlung der Daten\n",
" data = []\n",
"\n",
" # Funktion, um Logs zu verarbeiten und die Daten zur Liste hinzuzufügen\n",
" def process_logs(logs, log_type):\n",
" for log in logs:\n",
" formatted_date = datetime.fromisoformat(log.timestamp).strftime(\"%d.%m.%y %H:%M\")\n",
" equipment_name = log.equipment[0].name if log.equipment else \"None\"\n",
" location_name = log.location[0].name if hasattr(log, 'location') and log.location else \"\"\n",
"\n",
" # Menge und weitere Details (bis zu zwei Mengen)\n",
" quantities = getattr(log, 'quantities', [])\n",
" \n",
" # Initialisiere Standardwerte für die zweite Menge\n",
" quant_type_2 = quant_measure_2 = quant_value_2 = quant_inventory_adjustment_2 = \"\"\n",
"\n",
" if len(quantities) > 0:\n",
" # Erste Menge vorhanden\n",
" quant_type_1 = quantities[0].type\n",
" quant_measure_1 = quantities[0].measure\n",
" quant_value_1 = quantities[0].value\n",
" quant_inventory_adjustment_1 = quantities[0].inventory_adjustment\n",
" else:\n",
" # Keine Mengenangaben vorhanden\n",
" quant_type_1 = quant_measure_1 = quant_value_1 = quant_inventory_adjustment_1 = \"\"\n",
" \n",
" if len(quantities) > 1:\n",
" # Zweite Menge vorhanden\n",
" quant_type_2 = quantities[1].type\n",
" quant_measure_2 = quantities[1].measure\n",
" quant_value_2 = quantities[1].value\n",
" quant_inventory_adjustment_2 = quantities[1].inventory_adjustment\n",
"\n",
" # Daten zur Tabelle hinzufügen\n",
" data.append({\n",
" \"PlantName\": PlantName,\n",
" \"LogType\": log_type,\n",
" \"Name\": log.name,\n",
" \"Timestamp\": formatted_date,\n",
" \"Equipment\": equipment_name,\n",
" \"Location\": location_name,\n",
" \"QuantType_1\": quant_type_1,\n",
" \"QuantMeasure_1\": quant_measure_1,\n",
" \"QuantValue_1\": quant_value_1,\n",
" \"QuantInventoryAdjustment_1\": quant_inventory_adjustment_1,\n",
" \"QuantType_2\": quant_type_2,\n",
" \"QuantMeasure_2\": quant_measure_2,\n",
" \"QuantValue_2\": quant_value_2,\n",
" \"QuantInventoryAdjustment_2\": quant_inventory_adjustment_2\n",
" })\n",
"\n",
" # Verarbeite die verschiedenen Log-Typen\n",
" process_logs(asset.get_logs_of_type(neo.Log.Maintenance), \"Maintenance\")\n",
" process_logs(asset.get_logs_of_type(neo.Log.Seeding), \"Seeding\")\n",
" process_logs(asset.get_logs_of_type(neo.Log.Input), \"Input\")\n",
" process_logs(asset.get_logs_of_type(neo.Log.Medical), \"Medical\")\n",
" process_logs(asset.get_logs_of_type(neo.Log.Harvest), \"Harvest\")\n",
" process_logs(asset.get_logs_of_type(neo.Log.Sale), \"Sale\")\n",
"\n",
" # Erstelle ein DataFrame aus den gesammelten Daten und zeige es an\n",
" df = pd.DataFrame(data)\n",
" display(df)\n"
]
},
{
"cell_type": "code",