#!/usr/bin/env python
# coding: utf-8

# # Parallel Jobs
# 
# ## Example: Airport monitoring
# 
# - Get a Sentinel-2 clipped image for 10 airports in a country. 
# - Run all jobs in parallel
# - Visualize the results

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import up42
import pandas as pd
import geopandas as gpd
from pathlib import Path


# ### Random airports in Spain

# Airport locations scrapped from: https://raw.githubusercontent.com/jpatokal/openflights/master/data/airports.dat

# In[2]:


country = "Spain"

dat = "https://raw.githubusercontent.com/jpatokal/openflights/master/data/airports.dat"
airports = pd.read_table(dat, 
                         sep=",", 
                         usecols=[0, 1, 3, 6, 7], 
                         names=["uid",'airport', "country", "lat", "lon"])
airports = airports[airports.country==country]
airports = gpd.GeoDataFrame(airports, geometry=gpd.points_from_xy(airports.lon, airports.lat))

world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
world = world[world.name == country]
airports = airports[airports.within(world.iloc[0].geometry)]

display(airports.head())


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airports=airports.sample(6)


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# Visualize locations
ax = world.plot(figsize=(10,10), color='white', edgecolor='black')
airports.plot(markersize=20, ax=ax, color="r")


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# Buffer airport point locations by roughly 100m
airports.geometry = airports.geometry.buffer(0.001)


# ### Prepare UP42 workflows

# Create a new project on UP42 or use an existing one.

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# Authenticate with UP42
up42.authenticate(project_id="123", project_api_key="456")
#up42.authenticate(cfg_file="config.json")

project = up42.initialize_project()


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# Increase the parallel job limit for the project.
# Only works when you have added your credit card information to the UP42 account.
project.update_project_settings(max_concurrent_jobs=10)


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workflow = project.create_workflow("workflow_airports", use_existing=True)


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# Fill the workflow with tasks

#blocks = up42.get_blocks(basic=True)
selected_block = "sobloo-s2-l1c-aoiclipped"
workflow.add_workflow_tasks([selected_block])

workflow.get_workflow_tasks(basic=True)


# ### Run jobs in parallel
# 
# Queries & downloads one image per airport in parallel.
# 
# Crude, this will soon be available in the API in one simple command!

# In[11]:


# Run jobs in parallel
up42.settings(log=False)

input_parameters_list = workflow.construct_parameters_parallel(geometries=airports.geometry.to_list(),
                                                               interval_dates=[("2018-01-01","2020-12-31")], 
                                                               geometry_operation="bbox")
# Adjust cloud cover parameter
for params in input_parameters_list:
    params[f"{selected_block}:1"]["max_cloud_cover"] = 10


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real_jobs = workflow.run_jobs_parallel(input_parameters_list=input_parameters_list)


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real_jobs.download_results()


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# Visualize downloaded results
real_jobs.plot_results()


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