Merge pull request #155 from CartoDB/do_integration
Data observatory integration
This commit is contained in:
@@ -89,3 +89,15 @@
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- { name: options, type: "text[]", default: 'ARRAY[]::text[]' }
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- { name: units, type: "text", default: "'kilometers'"}
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- name: obs_get_demographic_snapshot
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return_type: json
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params:
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- { name: geom, type: "geometry(Geometry, 4326)" }
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- { name: time_span, type: "text", default: "'2009 - 2013'::text" }
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- { name: geometry_level, type: text, default: "'\"us.census.tiger\".block_group'::text" }
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- name: obs_get_segment_snapshot
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return_type: json
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params:
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- { name: geom, type: "geometry(Geometry, 4326)" }
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- { name: geometry_level, type: text, default: "'\"us.census.tiger\".census_tract'::text" }
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@@ -1,5 +1,5 @@
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--
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-- Public geocoder API function
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-- Public dataservices API function
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--
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-- These are the only ones with permissions to publicuser role
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-- and should also be the only ones with SECURITY DEFINER
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42
client/test/expected/90_data_observatory_test.out
Normal file
42
client/test/expected/90_data_observatory_test.out
Normal file
@@ -0,0 +1,42 @@
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-- Add to the search path the schema
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SET search_path TO public,cartodb,cdb_dataservices_client;
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-- Mock the server functions
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CREATE OR REPLACE FUNCTION cdb_dataservices_server.obs_get_demographic_snapshot (username text, orgname text, geom geometry(Geometry, 4326), time_span text DEFAULT '2009 - 2013', geometry_level text DEFAULT '"us.census.tiger".block_group')
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RETURNS json AS $$
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DECLARE
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ret json;
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BEGIN
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RAISE NOTICE 'cdb_dataservices_server.obs_get_demographic_snapshot invoked with params (%, %, %, %, %)', username, orgname, geom, time_span, geometry_level;
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SELECT '{"total_pop":9516.27915900609,"male_pop":6152.51885204623,"female_pop":3363.76030695986,"median_age":28.8,"white_pop":5301.51624447348,"black_pop":149.500458087105,"asian_pop":230.000704749392,"hispanic_pop":3835.26175169611,"amerindian_pop":0,"other_race_pop":0,"two_or_more_races_pop":0,"not_hispanic_pop":5681.01740730998,"households":3323.51018362871,"pop_25_years_over":7107.02177675621,"high_school_diploma":1040.753188991,"less_one_year_college":69.0002114248176,"one_year_more_college":793.502431385402,"associates_degree":327.751004267883,"bachelors_degree":2742.7584041365,"masters_degree":931.502854235037,"median_income":66304,"gini_index":0.3494,"income_per_capita":28291,"housing_units":3662.76122313407,"vacant_housing_units":339.251039505353,"vacant_housing_units_for_rent":120.750369993431,"vacant_housing_units_for_sale":0,"median_rent":1764,"percent_income_spent_on_rent":35.3,"owner_occupied_housing_units":339.251039505353,"million_dollar_housing_units":0,"mortgaged_housing_units":224.250687130657,"commuters_16_over":6549.27006773893,"commute_less_10_mins":327.751004267883,"commute_10_14_mins":28.750088093674,"commute_15_19_mins":201.250616655718,"commute_20_24_mins":621.001902823358,"commute_25_29_mins":373.751145217762,"commute_30_34_mins":1851.5056732326,"commute_35_44_mins":1414.50433420876,"commute_45_59_mins":1115.50341803455,"commute_60_more_mins":615.251885204623,"aggregate_travel_time_to_work":null,"income_less_10000":57.500176187348,"income_10000_14999":0,"income_15000_19999":212.750651893187,"income_20000_24999":408.251250930171,"income_25000_29999":0,"income_30000_34999":155.25047570584,"income_35000_39999":109.250334755961,"income_40000_44999":92.0002818997568,"income_45000_49999":63.2501938060828,"income_50000_59999":184.000563799514,"income_60000_74999":621.001902823358,"income_75000_99999":552.001691398541,"income_100000_124999":327.751004267883,"income_125000_149999":333.501021886618,"income_150000_199999":126.500387612166,"income_200000_or_more":null,"land_area":null}'::json INTO ret;
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RETURN ret;
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END;
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$$ LANGUAGE 'plpgsql';
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CREATE OR REPLACE FUNCTION cdb_dataservices_server.obs_get_segment_snapshot (username text, orgname text, geom geometry(Geometry, 4326), geometry_level text DEFAULT '"us.census.tiger".census_tract')
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RETURNS json AS $$
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DECLARE
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ret json;
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BEGIN
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RAISE NOTICE 'cdb_dataservices_server.obs_get_segment_snapshot invoked with params (%, %, %, %)', username, orgname, geom, geometry_level;
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SELECT '{"total_pop":9516.27915900609,"male_pop":6152.51885204623,"female_pop":3363.76030695986,"median_age":28.8,"white_pop":5301.51624447348,"black_pop":149.500458087105,"asian_pop":230.000704749392,"hispanic_pop":3835.26175169611,"amerindian_pop":0,"other_race_pop":0,"two_or_more_races_pop":0,"not_hispanic_pop":5681.01740730998,"households":3323.51018362871,"pop_25_years_over":7107.02177675621,"high_school_diploma":1040.753188991,"less_one_year_college":69.0002114248176,"one_year_more_college":793.502431385402,"associates_degree":327.751004267883,"bachelors_degree":2742.7584041365,"masters_degree":931.502854235037,"median_income":66304,"gini_index":0.3494,"income_per_capita":28291,"housing_units":3662.76122313407,"vacant_housing_units":339.251039505353,"vacant_housing_units_for_rent":120.750369993431,"vacant_housing_units_for_sale":0,"median_rent":1764,"percent_income_spent_on_rent":35.3,"owner_occupied_housing_units":339.251039505353,"million_dollar_housing_units":0,"mortgaged_housing_units":224.250687130657,"commuters_16_over":6549.27006773893,"commute_less_10_mins":327.751004267883,"commute_10_14_mins":28.750088093674,"commute_15_19_mins":201.250616655718,"commute_20_24_mins":621.001902823358,"commute_25_29_mins":373.751145217762,"commute_30_34_mins":1851.5056732326,"commute_35_44_mins":1414.50433420876,"commute_45_59_mins":1115.50341803455,"commute_60_more_mins":615.251885204623,"aggregate_travel_time_to_work":null,"income_less_10000":57.500176187348,"income_10000_14999":0,"income_15000_19999":212.750651893187,"income_20000_24999":408.251250930171,"income_25000_29999":0,"income_30000_34999":155.25047570584,"income_35000_39999":109.250334755961,"income_40000_44999":92.0002818997568,"income_45000_49999":63.2501938060828,"income_50000_59999":184.000563799514,"income_60000_74999":621.001902823358,"income_75000_99999":552.001691398541,"income_100000_124999":327.751004267883,"income_125000_149999":333.501021886618,"income_150000_199999":126.500387612166,"income_200000_or_more":null,"land_area":null}'::json INTO ret;
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RETURN ret;
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END;
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$$ LANGUAGE 'plpgsql';
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-- Exercise the public and the proxied function
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SELECT obs_get_demographic_snapshot('POINT(-87.81406 41.89308)'::geometry);
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NOTICE: cdb_dataservices_client._obs_get_demographic_snapshot(5): [contrib_regression] REMOTE NOTICE: cdb_dataservices_server.obs_get_demographic_snapshot invoked with params (test_user, <NULL>, 0101000000D53E1D8F19F455C0185B087250F24440, 2009 - 2013, "us.census.tiger".block_group)
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CONTEXT: SQL statement "SELECT cdb_dataservices_client._obs_get_demographic_snapshot(username, orgname, geom, time_span, geometry_level)"
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PL/pgSQL function obs_get_demographic_snapshot(geometry,text,text) line 16 at SQL statement
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obs_get_demographic_snapshot
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-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
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{"total_pop":9516.27915900609,"male_pop":6152.51885204623,"female_pop":3363.76030695986,"median_age":28.8,"white_pop":5301.51624447348,"black_pop":149.500458087105,"asian_pop":230.000704749392,"hispanic_pop":3835.26175169611,"amerindian_pop":0,"other_race_pop":0,"two_or_more_races_pop":0,"not_hispanic_pop":5681.01740730998,"households":3323.51018362871,"pop_25_years_over":7107.02177675621,"high_school_diploma":1040.753188991,"less_one_year_college":69.0002114248176,"one_year_more_college":793.502431385402,"associates_degree":327.751004267883,"bachelors_degree":2742.7584041365,"masters_degree":931.502854235037,"median_income":66304,"gini_index":0.3494,"income_per_capita":28291,"housing_units":3662.76122313407,"vacant_housing_units":339.251039505353,"vacant_housing_units_for_rent":120.750369993431,"vacant_housing_units_for_sale":0,"median_rent":1764,"percent_income_spent_on_rent":35.3,"owner_occupied_housing_units":339.251039505353,"million_dollar_housing_units":0,"mortgaged_housing_units":224.250687130657,"commuters_16_over":6549.27006773893,"commute_less_10_mins":327.751004267883,"commute_10_14_mins":28.750088093674,"commute_15_19_mins":201.250616655718,"commute_20_24_mins":621.001902823358,"commute_25_29_mins":373.751145217762,"commute_30_34_mins":1851.5056732326,"commute_35_44_mins":1414.50433420876,"commute_45_59_mins":1115.50341803455,"commute_60_more_mins":615.251885204623,"aggregate_travel_time_to_work":null,"income_less_10000":57.500176187348,"income_10000_14999":0,"income_15000_19999":212.750651893187,"income_20000_24999":408.251250930171,"income_25000_29999":0,"income_30000_34999":155.25047570584,"income_35000_39999":109.250334755961,"income_40000_44999":92.0002818997568,"income_45000_49999":63.2501938060828,"income_50000_59999":184.000563799514,"income_60000_74999":621.001902823358,"income_75000_99999":552.001691398541,"income_100000_124999":327.751004267883,"income_125000_149999":333.501021886618,"income_150000_199999":126.500387612166,"income_200000_or_more":null,"land_area":null}
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(1 row)
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SELECT obs_get_segment_snapshot('POINT(-87.81406 41.89308)'::geometry);
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NOTICE: cdb_dataservices_client._obs_get_segment_snapshot(4): [contrib_regression] REMOTE NOTICE: cdb_dataservices_server.obs_get_segment_snapshot invoked with params (test_user, <NULL>, 0101000000D53E1D8F19F455C0185B087250F24440, "us.census.tiger".census_tract)
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CONTEXT: SQL statement "SELECT cdb_dataservices_client._obs_get_segment_snapshot(username, orgname, geom, geometry_level)"
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PL/pgSQL function obs_get_segment_snapshot(geometry,text) line 16 at SQL statement
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obs_get_segment_snapshot
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-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
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{"total_pop":9516.27915900609,"male_pop":6152.51885204623,"female_pop":3363.76030695986,"median_age":28.8,"white_pop":5301.51624447348,"black_pop":149.500458087105,"asian_pop":230.000704749392,"hispanic_pop":3835.26175169611,"amerindian_pop":0,"other_race_pop":0,"two_or_more_races_pop":0,"not_hispanic_pop":5681.01740730998,"households":3323.51018362871,"pop_25_years_over":7107.02177675621,"high_school_diploma":1040.753188991,"less_one_year_college":69.0002114248176,"one_year_more_college":793.502431385402,"associates_degree":327.751004267883,"bachelors_degree":2742.7584041365,"masters_degree":931.502854235037,"median_income":66304,"gini_index":0.3494,"income_per_capita":28291,"housing_units":3662.76122313407,"vacant_housing_units":339.251039505353,"vacant_housing_units_for_rent":120.750369993431,"vacant_housing_units_for_sale":0,"median_rent":1764,"percent_income_spent_on_rent":35.3,"owner_occupied_housing_units":339.251039505353,"million_dollar_housing_units":0,"mortgaged_housing_units":224.250687130657,"commuters_16_over":6549.27006773893,"commute_less_10_mins":327.751004267883,"commute_10_14_mins":28.750088093674,"commute_15_19_mins":201.250616655718,"commute_20_24_mins":621.001902823358,"commute_25_29_mins":373.751145217762,"commute_30_34_mins":1851.5056732326,"commute_35_44_mins":1414.50433420876,"commute_45_59_mins":1115.50341803455,"commute_60_more_mins":615.251885204623,"aggregate_travel_time_to_work":null,"income_less_10000":57.500176187348,"income_10000_14999":0,"income_15000_19999":212.750651893187,"income_20000_24999":408.251250930171,"income_25000_29999":0,"income_30000_34999":155.25047570584,"income_35000_39999":109.250334755961,"income_40000_44999":92.0002818997568,"income_45000_49999":63.2501938060828,"income_50000_59999":184.000563799514,"income_60000_74999":621.001902823358,"income_75000_99999":552.001691398541,"income_100000_124999":327.751004267883,"income_125000_149999":333.501021886618,"income_150000_199999":126.500387612166,"income_200000_or_more":null,"land_area":null}
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(1 row)
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31
client/test/sql/90_data_observatory_test.sql
Normal file
31
client/test/sql/90_data_observatory_test.sql
Normal file
@@ -0,0 +1,31 @@
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-- Add to the search path the schema
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SET search_path TO public,cartodb,cdb_dataservices_client;
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-- Mock the server functions
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CREATE OR REPLACE FUNCTION cdb_dataservices_server.obs_get_demographic_snapshot (username text, orgname text, geom geometry(Geometry, 4326), time_span text DEFAULT '2009 - 2013', geometry_level text DEFAULT '"us.census.tiger".block_group')
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RETURNS json AS $$
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DECLARE
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ret json;
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BEGIN
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RAISE NOTICE 'cdb_dataservices_server.obs_get_demographic_snapshot invoked with params (%, %, %, %, %)', username, orgname, geom, time_span, geometry_level;
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SELECT '{"total_pop":9516.27915900609,"male_pop":6152.51885204623,"female_pop":3363.76030695986,"median_age":28.8,"white_pop":5301.51624447348,"black_pop":149.500458087105,"asian_pop":230.000704749392,"hispanic_pop":3835.26175169611,"amerindian_pop":0,"other_race_pop":0,"two_or_more_races_pop":0,"not_hispanic_pop":5681.01740730998,"households":3323.51018362871,"pop_25_years_over":7107.02177675621,"high_school_diploma":1040.753188991,"less_one_year_college":69.0002114248176,"one_year_more_college":793.502431385402,"associates_degree":327.751004267883,"bachelors_degree":2742.7584041365,"masters_degree":931.502854235037,"median_income":66304,"gini_index":0.3494,"income_per_capita":28291,"housing_units":3662.76122313407,"vacant_housing_units":339.251039505353,"vacant_housing_units_for_rent":120.750369993431,"vacant_housing_units_for_sale":0,"median_rent":1764,"percent_income_spent_on_rent":35.3,"owner_occupied_housing_units":339.251039505353,"million_dollar_housing_units":0,"mortgaged_housing_units":224.250687130657,"commuters_16_over":6549.27006773893,"commute_less_10_mins":327.751004267883,"commute_10_14_mins":28.750088093674,"commute_15_19_mins":201.250616655718,"commute_20_24_mins":621.001902823358,"commute_25_29_mins":373.751145217762,"commute_30_34_mins":1851.5056732326,"commute_35_44_mins":1414.50433420876,"commute_45_59_mins":1115.50341803455,"commute_60_more_mins":615.251885204623,"aggregate_travel_time_to_work":null,"income_less_10000":57.500176187348,"income_10000_14999":0,"income_15000_19999":212.750651893187,"income_20000_24999":408.251250930171,"income_25000_29999":0,"income_30000_34999":155.25047570584,"income_35000_39999":109.250334755961,"income_40000_44999":92.0002818997568,"income_45000_49999":63.2501938060828,"income_50000_59999":184.000563799514,"income_60000_74999":621.001902823358,"income_75000_99999":552.001691398541,"income_100000_124999":327.751004267883,"income_125000_149999":333.501021886618,"income_150000_199999":126.500387612166,"income_200000_or_more":null,"land_area":null}'::json INTO ret;
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RETURN ret;
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END;
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$$ LANGUAGE 'plpgsql';
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CREATE OR REPLACE FUNCTION cdb_dataservices_server.obs_get_segment_snapshot (username text, orgname text, geom geometry(Geometry, 4326), geometry_level text DEFAULT '"us.census.tiger".census_tract')
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RETURNS json AS $$
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DECLARE
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ret json;
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BEGIN
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RAISE NOTICE 'cdb_dataservices_server.obs_get_segment_snapshot invoked with params (%, %, %, %)', username, orgname, geom, geometry_level;
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SELECT '{"total_pop":9516.27915900609,"male_pop":6152.51885204623,"female_pop":3363.76030695986,"median_age":28.8,"white_pop":5301.51624447348,"black_pop":149.500458087105,"asian_pop":230.000704749392,"hispanic_pop":3835.26175169611,"amerindian_pop":0,"other_race_pop":0,"two_or_more_races_pop":0,"not_hispanic_pop":5681.01740730998,"households":3323.51018362871,"pop_25_years_over":7107.02177675621,"high_school_diploma":1040.753188991,"less_one_year_college":69.0002114248176,"one_year_more_college":793.502431385402,"associates_degree":327.751004267883,"bachelors_degree":2742.7584041365,"masters_degree":931.502854235037,"median_income":66304,"gini_index":0.3494,"income_per_capita":28291,"housing_units":3662.76122313407,"vacant_housing_units":339.251039505353,"vacant_housing_units_for_rent":120.750369993431,"vacant_housing_units_for_sale":0,"median_rent":1764,"percent_income_spent_on_rent":35.3,"owner_occupied_housing_units":339.251039505353,"million_dollar_housing_units":0,"mortgaged_housing_units":224.250687130657,"commuters_16_over":6549.27006773893,"commute_less_10_mins":327.751004267883,"commute_10_14_mins":28.750088093674,"commute_15_19_mins":201.250616655718,"commute_20_24_mins":621.001902823358,"commute_25_29_mins":373.751145217762,"commute_30_34_mins":1851.5056732326,"commute_35_44_mins":1414.50433420876,"commute_45_59_mins":1115.50341803455,"commute_60_more_mins":615.251885204623,"aggregate_travel_time_to_work":null,"income_less_10000":57.500176187348,"income_10000_14999":0,"income_15000_19999":212.750651893187,"income_20000_24999":408.251250930171,"income_25000_29999":0,"income_30000_34999":155.25047570584,"income_35000_39999":109.250334755961,"income_40000_44999":92.0002818997568,"income_45000_49999":63.2501938060828,"income_50000_59999":184.000563799514,"income_60000_74999":621.001902823358,"income_75000_99999":552.001691398541,"income_100000_124999":327.751004267883,"income_125000_149999":333.501021886618,"income_150000_199999":126.500387612166,"income_200000_or_more":null,"land_area":null}'::json INTO ret;
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RETURN ret;
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||||
END;
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$$ LANGUAGE 'plpgsql';
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-- Exercise the public and the proxied function
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SELECT obs_get_demographic_snapshot('POINT(-87.81406 41.89308)'::geometry);
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SELECT obs_get_segment_snapshot('POINT(-87.81406 41.89308)'::geometry);
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@@ -25,7 +25,7 @@ RETURNS cdb_dataservices_server.simple_route AS $$
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quota_service = QuotaService(user_routing_config, redis_conn)
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if not quota_service.check_user_quota():
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plpy.error('You have reach the limit of your quota')
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plpy.error('You have reached the limit of your quota')
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try:
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client = MapzenRouting(user_routing_config.mapzen_api_key)
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76
server/extension/sql/110_data_observatory.sql
Normal file
76
server/extension/sql/110_data_observatory.sql
Normal file
@@ -0,0 +1,76 @@
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CREATE OR REPLACE FUNCTION cdb_dataservices_server.obs_get_demographic_snapshot(
|
||||
username TEXT,
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||||
orgname TEXT,
|
||||
geom geometry(Geometry, 4326),
|
||||
time_span TEXT DEFAULT '2009 - 2013',
|
||||
geometry_level TEXT DEFAULT '"us.census.tiger".block_group')
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||||
RETURNS json AS $$
|
||||
from cartodb_services.metrics import QuotaService
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import json
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||||
|
||||
plpy.execute("SELECT cdb_dataservices_server._connect_to_redis('{0}')".format(username))
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||||
redis_conn = GD["redis_connection_{0}".format(username)]['redis_metrics_connection']
|
||||
plpy.execute("SELECT cdb_dataservices_server._get_data_observatory_config({0}, {1})".format(plpy.quote_nullable(username), plpy.quote_nullable(orgname)))
|
||||
user_data_observatory_config = GD["user_data_observatory_config_{0}".format(username)]
|
||||
|
||||
quota_service = QuotaService(user_data_observatory_config, redis_conn)
|
||||
if not quota_service.check_user_quota():
|
||||
plpy.error('You have reached the limit of your quota')
|
||||
|
||||
try:
|
||||
obs_plan = plpy.prepare("SELECT cdb_observatory.OBS_GetDemographicSnapshot($1, $2, $3) as snapshot;", ["geometry(Geometry, 4326)", "text", "text"])
|
||||
result = plpy.execute(obs_plan, [geom, time_span, geometry_level])
|
||||
if result:
|
||||
quota_service.increment_success_service_use()
|
||||
return result[0]['snapshot']
|
||||
else:
|
||||
quota_service.increment_empty_service_use()
|
||||
return None
|
||||
except BaseException as e:
|
||||
import sys, traceback
|
||||
type_, value_, traceback_ = sys.exc_info()
|
||||
quota_service.increment_failed_service_use()
|
||||
error_msg = 'There was an error trying to use get_geographic_snapshot: {0}'.format(e)
|
||||
plpy.notice(traceback.format_tb(traceback_))
|
||||
plpy.error(error_msg)
|
||||
finally:
|
||||
quota_service.increment_total_service_use()
|
||||
$$ LANGUAGE plpythonu;
|
||||
|
||||
CREATE OR REPLACE FUNCTION cdb_dataservices_server.obs_get_segment_snapshot(
|
||||
username TEXT,
|
||||
orgname TEXT,
|
||||
geom geometry(Geometry, 4326),
|
||||
geometry_level TEXT DEFAULT '"us.census.tiger".block_group')
|
||||
RETURNS json AS $$
|
||||
from cartodb_services.metrics import QuotaService
|
||||
import json
|
||||
|
||||
plpy.execute("SELECT cdb_dataservices_server._connect_to_redis('{0}')".format(username))
|
||||
redis_conn = GD["redis_connection_{0}".format(username)]['redis_metrics_connection']
|
||||
plpy.execute("SELECT cdb_dataservices_server._get_data_observatory_config({0}, {1})".format(plpy.quote_nullable(username), plpy.quote_nullable(orgname)))
|
||||
user_data_observatory_config = GD["user_data_observatory_config_{0}".format(username)]
|
||||
|
||||
quota_service = QuotaService(user_data_observatory_config, redis_conn)
|
||||
if not quota_service.check_user_quota():
|
||||
plpy.error('You have reached the limit of your quota')
|
||||
|
||||
try:
|
||||
obs_plan = plpy.prepare("SELECT cdb_observatory.OBS_GetSegmentSnapshot($1, $2) as snapshot;", ["geometry(Geometry, 4326)", "text"])
|
||||
result = plpy.execute(obs_plan, [geom, geometry_level])
|
||||
if result:
|
||||
quota_service.increment_success_service_use()
|
||||
return result[0]['snapshot']
|
||||
else:
|
||||
quota_service.increment_empty_service_use()
|
||||
return None
|
||||
except BaseException as e:
|
||||
import sys, traceback
|
||||
type_, value_, traceback_ = sys.exc_info()
|
||||
quota_service.increment_failed_service_use()
|
||||
error_msg = 'There was an error trying to use get_segment_snapshot: {0}'.format(e)
|
||||
plpy.notice(traceback.format_tb(traceback_))
|
||||
plpy.error(error_msg)
|
||||
finally:
|
||||
quota_service.increment_total_service_use()
|
||||
$$ LANGUAGE plpythonu;
|
||||
@@ -1,4 +1,3 @@
|
||||
-- Get the Redis configuration from the _conf table --
|
||||
CREATE OR REPLACE FUNCTION cdb_dataservices_server._get_geocoder_config(username text, orgname text)
|
||||
RETURNS boolean AS $$
|
||||
cache_key = "user_geocoder_config_{0}".format(username)
|
||||
@@ -13,7 +12,6 @@ RETURNS boolean AS $$
|
||||
return True
|
||||
$$ LANGUAGE plpythonu SECURITY DEFINER;
|
||||
|
||||
-- Get the Redis configuration from the _conf table --
|
||||
CREATE OR REPLACE FUNCTION cdb_dataservices_server._get_internal_geocoder_config(username text, orgname text)
|
||||
RETURNS boolean AS $$
|
||||
cache_key = "user_internal_geocoder_config_{0}".format(username)
|
||||
@@ -28,7 +26,6 @@ RETURNS boolean AS $$
|
||||
return True
|
||||
$$ LANGUAGE plpythonu SECURITY DEFINER;
|
||||
|
||||
-- Get the Redis configuration from the _conf table --
|
||||
CREATE OR REPLACE FUNCTION cdb_dataservices_server._get_isolines_routing_config(username text, orgname text)
|
||||
RETURNS boolean AS $$
|
||||
cache_key = "user_isolines_routing_config_{0}".format(username)
|
||||
@@ -43,7 +40,6 @@ RETURNS boolean AS $$
|
||||
return True
|
||||
$$ LANGUAGE plpythonu SECURITY DEFINER;
|
||||
|
||||
-- Get the Redis configuration from the _conf table --
|
||||
CREATE OR REPLACE FUNCTION cdb_dataservices_server._get_routing_config(username text, orgname text)
|
||||
RETURNS boolean AS $$
|
||||
cache_key = "user_routing_config_{0}".format(username)
|
||||
@@ -57,3 +53,17 @@ RETURNS boolean AS $$
|
||||
GD[cache_key] = routing_config
|
||||
return True
|
||||
$$ LANGUAGE plpythonu SECURITY DEFINER;
|
||||
|
||||
CREATE OR REPLACE FUNCTION cdb_dataservices_server._get_data_observatory_config(username text, orgname text)
|
||||
RETURNS boolean AS $$
|
||||
cache_key = "user_data_observatory_config_{0}".format(username)
|
||||
if cache_key in GD:
|
||||
return False
|
||||
else:
|
||||
from cartodb_services.metrics import DataObservatoryConfig
|
||||
plpy.execute("SELECT cdb_dataservices_server._connect_to_redis('{0}')".format(username))
|
||||
redis_conn = GD["redis_connection_{0}".format(username)]['redis_metadata_connection']
|
||||
data_observatory_config = DataObservatoryConfig(redis_conn, plpy, username, orgname)
|
||||
GD[cache_key] = data_observatory_config
|
||||
return True
|
||||
$$ LANGUAGE plpythonu SECURITY DEFINER;
|
||||
|
||||
@@ -31,7 +31,7 @@ RETURNS Geometry AS $$
|
||||
# -- Check the quota
|
||||
quota_service = QuotaService(user_geocoder_config, redis_conn)
|
||||
if not quota_service.check_user_quota():
|
||||
plpy.error('You have reach the limit of your quota')
|
||||
plpy.error('You have reached the limit of your quota')
|
||||
|
||||
try:
|
||||
geocoder = HereMapsGeocoder(user_geocoder_config.heremaps_app_id, user_geocoder_config.heremaps_app_code)
|
||||
@@ -96,7 +96,7 @@ RETURNS Geometry AS $$
|
||||
user_geocoder_config = GD["user_geocoder_config_{0}".format(username)]
|
||||
quota_service = QuotaService(user_geocoder_config, redis_conn)
|
||||
if not quota_service.check_user_quota():
|
||||
plpy.error('You have reach the limit of your quota')
|
||||
plpy.error('You have reached the limit of your quota')
|
||||
|
||||
try:
|
||||
geocoder = MapzenGeocoder(user_geocoder_config.mapzen_api_key)
|
||||
|
||||
@@ -13,7 +13,7 @@ RETURNS SETOF cdb_dataservices_server.isoline AS $$
|
||||
# -- Check the quota
|
||||
quota_service = QuotaService(user_isolines_routing_config, redis_conn)
|
||||
if not quota_service.check_user_quota():
|
||||
plpy.error('You have reach the limit of your quota')
|
||||
plpy.error('You have reached the limit of your quota')
|
||||
|
||||
try:
|
||||
client = HereMapsRoutingIsoline(user_isolines_routing_config.heremaps_app_id, user_isolines_routing_config.heremaps_app_code, base_url = HereMapsRoutingIsoline.PRODUCTION_ROUTING_BASE_URL)
|
||||
|
||||
@@ -4,6 +4,7 @@ CREATE EXTENSION schema_triggers;
|
||||
CREATE EXTENSION plpythonu;
|
||||
CREATE EXTENSION cartodb;
|
||||
CREATE EXTENSION cdb_geocoder;
|
||||
CREATE EXTENSION observatory VERSION 'dev';
|
||||
-- Install the extension
|
||||
CREATE EXTENSION cdb_dataservices_server;
|
||||
-- Mock the redis server connection to point to this very test db
|
||||
@@ -37,6 +38,12 @@ SELECT cartodb.cdb_conf_setconf('logger_conf', '{"geocoder_log_path": "/dev/null
|
||||
|
||||
(1 row)
|
||||
|
||||
SELECT cartodb.cdb_conf_setconf('data_observatory_conf', '{"monthly_quota": 10000}');
|
||||
cdb_conf_setconf
|
||||
------------------
|
||||
|
||||
(1 row)
|
||||
|
||||
-- Mock the varnish invalidation function
|
||||
-- (used by cdb_geocoder tests)
|
||||
CREATE OR REPLACE FUNCTION public.cdb_invalidate_varnish(table_name text) RETURNS void AS $$
|
||||
|
||||
22
server/extension/test/expected/100_data_observatory_test.out
Normal file
22
server/extension/test/expected/100_data_observatory_test.out
Normal file
@@ -0,0 +1,22 @@
|
||||
SELECT exists(SELECT *
|
||||
FROM pg_proc p
|
||||
INNER JOIN pg_namespace ns ON (p.pronamespace = ns.oid)
|
||||
WHERE ns.nspname = 'cdb_dataservices_server'
|
||||
AND proname = 'obs_get_demographic_snapshot'
|
||||
AND oidvectortypes(p.proargtypes) = 'text, text, geometry, text, text');
|
||||
exists
|
||||
--------
|
||||
t
|
||||
(1 row)
|
||||
|
||||
SELECT exists(SELECT *
|
||||
FROM pg_proc p
|
||||
INNER JOIN pg_namespace ns ON (p.pronamespace = ns.oid)
|
||||
WHERE ns.nspname = 'cdb_dataservices_server'
|
||||
AND proname = 'obs_get_segment_snapshot'
|
||||
AND oidvectortypes(p.proargtypes) = 'text, text, geometry, text');
|
||||
exists
|
||||
--------
|
||||
t
|
||||
(1 row)
|
||||
|
||||
@@ -4,6 +4,7 @@ CREATE EXTENSION schema_triggers;
|
||||
CREATE EXTENSION plpythonu;
|
||||
CREATE EXTENSION cartodb;
|
||||
CREATE EXTENSION cdb_geocoder;
|
||||
CREATE EXTENSION observatory VERSION 'dev';
|
||||
|
||||
-- Install the extension
|
||||
CREATE EXTENSION cdb_dataservices_server;
|
||||
@@ -14,6 +15,7 @@ SELECT cartodb.cdb_conf_setconf('redis_metadata_config', '{"redis_host": "localh
|
||||
SELECT cartodb.cdb_conf_setconf('heremaps_conf', '{"geocoder": {"app_id": "dummy_id", "app_code": "dummy_code", "geocoder_cost_per_hit": 1}, "isolines": {"app_id": "dummy_id", "app_code": "dummy_code"}}');
|
||||
SELECT cartodb.cdb_conf_setconf('mapzen_conf', '{"routing": {"api_key": "routing_dummy_api_key", "monthly_quota": 1500000}, "geocoder": {"api_key": "geocoder_dummy_api_key", "monthly_quota": 1500000}}');
|
||||
SELECT cartodb.cdb_conf_setconf('logger_conf', '{"geocoder_log_path": "/dev/null"}');
|
||||
SELECT cartodb.cdb_conf_setconf('data_observatory_conf', '{"monthly_quota": 10000}');
|
||||
|
||||
-- Mock the varnish invalidation function
|
||||
-- (used by cdb_geocoder tests)
|
||||
|
||||
13
server/extension/test/sql/100_data_observatory_test.sql
Normal file
13
server/extension/test/sql/100_data_observatory_test.sql
Normal file
@@ -0,0 +1,13 @@
|
||||
SELECT exists(SELECT *
|
||||
FROM pg_proc p
|
||||
INNER JOIN pg_namespace ns ON (p.pronamespace = ns.oid)
|
||||
WHERE ns.nspname = 'cdb_dataservices_server'
|
||||
AND proname = 'obs_get_demographic_snapshot'
|
||||
AND oidvectortypes(p.proargtypes) = 'text, text, geometry, text, text');
|
||||
|
||||
SELECT exists(SELECT *
|
||||
FROM pg_proc p
|
||||
INNER JOIN pg_namespace ns ON (p.pronamespace = ns.oid)
|
||||
WHERE ns.nspname = 'cdb_dataservices_server'
|
||||
AND proname = 'obs_get_segment_snapshot'
|
||||
AND oidvectortypes(p.proargtypes) = 'text, text, geometry, text');
|
||||
@@ -1,3 +1,3 @@
|
||||
from config import GeocoderConfig, IsolinesRoutingConfig, InternalGeocoderConfig, RoutingConfig, ConfigException
|
||||
from config import GeocoderConfig, IsolinesRoutingConfig, InternalGeocoderConfig, RoutingConfig, ConfigException, DataObservatoryConfig
|
||||
from quota import QuotaService
|
||||
from user import UserMetricsService
|
||||
|
||||
@@ -32,6 +32,28 @@ class ServiceConfig(object):
|
||||
def organization(self):
|
||||
return self._orgname
|
||||
|
||||
class DataObservatoryConfig(ServiceConfig):
|
||||
|
||||
PERIOD_END_DATE = 'period_end_date'
|
||||
|
||||
def __init__(self, redis_connection, db_conn, username, orgname=None):
|
||||
super(DataObservatoryConfig, self).__init__(redis_connection, db_conn,
|
||||
username, orgname)
|
||||
self._monthly_quota = self._db_config.data_observatory_monthly_quota
|
||||
self._period_end_date = date_parse(self._redis_config[self.PERIOD_END_DATE])
|
||||
|
||||
@property
|
||||
def service_type(self):
|
||||
return 'data_observatory'
|
||||
|
||||
@property
|
||||
def monthly_quota(self):
|
||||
return self._monthly_quota
|
||||
|
||||
@property
|
||||
def period_end_date(self):
|
||||
return self._period_end_date
|
||||
|
||||
|
||||
class RoutingConfig(ServiceConfig):
|
||||
|
||||
@@ -315,6 +337,7 @@ class ServicesDBConfig:
|
||||
self._get_here_config()
|
||||
self._get_mapzen_config()
|
||||
self._get_logger_config()
|
||||
self._get_data_observatory_config()
|
||||
|
||||
def _get_here_config(self):
|
||||
heremaps_conf_json = self._get_conf('heremaps_conf')
|
||||
@@ -340,6 +363,14 @@ class ServicesDBConfig:
|
||||
self._mapzen_geocoder_api_key = mapzen_conf['geocoder']['api_key']
|
||||
self._mapzen_geocoder_quota = mapzen_conf['geocoder']['monthly_quota']
|
||||
|
||||
def _get_data_observatory_config(self):
|
||||
do_conf_json = self._get_conf('data_observatory_conf')
|
||||
if not do_conf_json:
|
||||
raise ConfigException('Data Observatory configuration missing')
|
||||
else:
|
||||
do_conf = json.loads(do_conf_json)
|
||||
self._data_observatory_monthly_quota = do_conf['monthly_quota']
|
||||
|
||||
def _get_logger_config(self):
|
||||
logger_conf_json = self._get_conf('logger_conf')
|
||||
if not logger_conf_json:
|
||||
@@ -396,6 +427,10 @@ class ServicesDBConfig:
|
||||
def geocoder_log_path(self):
|
||||
return self._geocoder_log_path
|
||||
|
||||
@property
|
||||
def data_observatory_monthly_quota(self):
|
||||
return self._data_observatory_monthly_quota
|
||||
|
||||
|
||||
class ServicesRedisConfig:
|
||||
|
||||
|
||||
@@ -73,6 +73,9 @@ class QuotaChecker:
|
||||
elif re.match('routing_mapzen',
|
||||
self._user_service_config.service_type) is not None:
|
||||
return self.__check_routing_quota()
|
||||
elif re.match('data_observatory',
|
||||
self._user_service_config.service_type) is not None:
|
||||
return self.__check_data_observatory_quota()
|
||||
else:
|
||||
return False
|
||||
|
||||
@@ -114,3 +117,14 @@ class QuotaChecker:
|
||||
return True
|
||||
else:
|
||||
return False
|
||||
|
||||
def __check_data_observatory_quota(self):
|
||||
user_quota = self._user_service_config.monthly_quota
|
||||
today = date.today()
|
||||
service_type = self._user_service_config.service_type
|
||||
current_used = self._user_service.used_quota(service_type, today)
|
||||
|
||||
if (user_quota > 0 and current_used <= user_quota):
|
||||
return True
|
||||
else:
|
||||
return False
|
||||
|
||||
@@ -10,7 +10,7 @@ from setuptools import setup, find_packages
|
||||
setup(
|
||||
name='cartodb_services',
|
||||
|
||||
version='0.4.5',
|
||||
version='0.5.0',
|
||||
|
||||
description='CartoDB Services API Python Library',
|
||||
|
||||
|
||||
@@ -51,3 +51,5 @@ def _plpy_execute_side_effect(*args, **kwargs):
|
||||
return [{'conf': '{"routing": {"api_key": "valhalla-Z61FWEs", "monthly_quota": 1500000}, "geocoder": {"api_key": "search-d744tp0", "monthly_quota": 1500000}}'}]
|
||||
elif args[0] == "SELECT cartodb.CDB_Conf_GetConf('logger_conf') as conf":
|
||||
return [{'conf': '{"geocoder_log_path": "/dev/null"}'}]
|
||||
elif args[0] == "SELECT cartodb.CDB_Conf_GetConf('data_observatory_conf') as conf":
|
||||
return [{'conf': '{"monthly_quota": 100000}'}]
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
import test_helper
|
||||
from mockredis import MockRedis
|
||||
from cartodb_services.metrics import QuotaService
|
||||
from cartodb_services.metrics import GeocoderConfig, RoutingConfig
|
||||
from cartodb_services.metrics import GeocoderConfig, RoutingConfig, DataObservatoryConfig
|
||||
from unittest import TestCase
|
||||
from nose.tools import assert_raises
|
||||
from datetime import datetime, date
|
||||
@@ -109,6 +109,20 @@ class TestQuotaService(TestCase):
|
||||
qs.increment_success_service_use(amount=1500000)
|
||||
assert qs.check_user_quota() is False
|
||||
|
||||
def test_should_check_user_data_observatory_quota_correctly(self):
|
||||
qs = self.__build_data_observatory_quota_service('test_user')
|
||||
qs.increment_success_service_use()
|
||||
assert qs.check_user_quota() is True
|
||||
qs.increment_success_service_use(amount=100000)
|
||||
assert qs.check_user_quota() is False
|
||||
|
||||
def test_should_check_org_data_observatory_quota_correctly(self):
|
||||
qs = self.__build_data_observatory_quota_service('test_user', orgname='testorg')
|
||||
qs.increment_success_service_use()
|
||||
assert qs.check_user_quota() is True
|
||||
qs.increment_success_service_use(amount=100000)
|
||||
assert qs.check_user_quota() is False
|
||||
|
||||
def __prepare_quota_service(self, username, quota, service, orgname,
|
||||
soft_limit, end_date):
|
||||
test_helper.build_redis_user_config(self.redis_conn, username,
|
||||
@@ -139,3 +153,13 @@ class TestQuotaService(TestCase):
|
||||
routing_config = RoutingConfig(self.redis_conn, self._plpy_mock,
|
||||
username, orgname)
|
||||
return QuotaService(routing_config, redis_connection=self.redis_conn)
|
||||
|
||||
def __build_data_observatory_quota_service(self, username, quota=100,
|
||||
service='data_observatory', orgname=None,
|
||||
soft_limit=False,
|
||||
end_date=datetime.today()):
|
||||
self.__prepare_quota_service(username, quota, service, orgname,
|
||||
soft_limit, end_date)
|
||||
do_config = DataObservatoryConfig(self.redis_conn, self._plpy_mock,
|
||||
username, orgname)
|
||||
return QuotaService(do_config, redis_connection=self.redis_conn)
|
||||
|
||||
@@ -8,7 +8,7 @@ class TestAdmin0Functions(TestCase):
|
||||
|
||||
def setUp(self):
|
||||
self.env_variables = IntegrationTestHelper.get_environment_variables()
|
||||
self.sql_api_url = "https://{0}.{1}/api/v2/sql".format(
|
||||
self.sql_api_url = "https://{0}.{1}/api/v1/sql".format(
|
||||
self.env_variables['username'],
|
||||
self.env_variables['host'],
|
||||
self.env_variables['api_key']
|
||||
|
||||
@@ -8,7 +8,7 @@ class TestAdmin1Functions(TestCase):
|
||||
|
||||
def setUp(self):
|
||||
self.env_variables = IntegrationTestHelper.get_environment_variables()
|
||||
self.sql_api_url = "https://{0}.{1}/api/v2/sql".format(
|
||||
self.sql_api_url = "https://{0}.{1}/api/v1/sql".format(
|
||||
self.env_variables['username'],
|
||||
self.env_variables['host'],
|
||||
self.env_variables['api_key']
|
||||
|
||||
45
test/integration/test_data_observatory_functions.py
Normal file
45
test/integration/test_data_observatory_functions.py
Normal file
@@ -0,0 +1,45 @@
|
||||
from unittest import TestCase
|
||||
from nose.tools import assert_raises
|
||||
from nose.tools import assert_not_equal, assert_equal
|
||||
from ..helpers.integration_test_helper import IntegrationTestHelper
|
||||
|
||||
|
||||
class TestDataObservatoryFunctions(TestCase):
|
||||
|
||||
def setUp(self):
|
||||
self.env_variables = IntegrationTestHelper.get_environment_variables()
|
||||
self.sql_api_url = "https://{0}.{1}/api/v1/sql".format(
|
||||
self.env_variables['username'],
|
||||
self.env_variables['host'],
|
||||
self.env_variables['api_key']
|
||||
)
|
||||
|
||||
def test_if_get_demographic_snapshot_is_ok(self):
|
||||
query = "SELECT duration, length, shape as the_geom " \
|
||||
"FROM cdb_do_get_demographic_snapshot(CDB_LatLng(40.704512, -73.936669))".format(
|
||||
self.env_variables['api_key'])
|
||||
routing = IntegrationTestHelper.execute_query(self.sql_api_url, query)
|
||||
assert_not_equal(routing['the_geom'], None)
|
||||
|
||||
def test_if_get_demographic_snapshot_without_api_key_raise_error(self):
|
||||
query = "SELECT duration, length, shape as the_geom " \
|
||||
"FROM cdb_do_get_demographic_snapshot(CDB_LatLng(40.704512, -73.936669))"
|
||||
try:
|
||||
IntegrationTestHelper.execute_query(self.sql_api_url, query)
|
||||
except Exception as e:
|
||||
assert_equal(e.message[0], "The api_key must be provided")
|
||||
|
||||
def test_if_get_segment_snapshot_is_ok(self):
|
||||
query = "SELECT duration, length, shape as the_geom " \
|
||||
"FROM cdb_do_get_segment_snapshot(CDB_LatLng(40.704512, -73.936669))".format(
|
||||
self.env_variables['api_key'])
|
||||
routing = IntegrationTestHelper.execute_query(self.sql_api_url, query)
|
||||
assert_not_equal(routing['the_geom'], None)
|
||||
|
||||
def test_if_get_segment_snapshot_without_api_key_raise_error(self):
|
||||
query = "SELECT duration, length, shape as the_geom " \
|
||||
"FROM cdb_do_get_segment_snapshot(CDB_LatLng(40.704512, -73.936669))"
|
||||
try:
|
||||
IntegrationTestHelper.execute_query(self.sql_api_url, query)
|
||||
except Exception as e:
|
||||
assert_equal(e.message[0], "The api_key must be provided")
|
||||
@@ -8,7 +8,7 @@ class TestPostalcodeFunctions(TestCase):
|
||||
|
||||
def setUp(self):
|
||||
self.env_variables = IntegrationTestHelper.get_environment_variables()
|
||||
self.sql_api_url = "https://{0}.{1}/api/v2/sql".format(
|
||||
self.sql_api_url = "https://{0}.{1}/api/v1/sql".format(
|
||||
self.env_variables['username'],
|
||||
self.env_variables['host'],
|
||||
self.env_variables['api_key']
|
||||
|
||||
@@ -8,7 +8,7 @@ class TestIsolinesFunctions(TestCase):
|
||||
|
||||
def setUp(self):
|
||||
self.env_variables = IntegrationTestHelper.get_environment_variables()
|
||||
self.sql_api_url = "https://{0}.{1}/api/v2/sql".format(
|
||||
self.sql_api_url = "https://{0}.{1}/api/v1/sql".format(
|
||||
self.env_variables['username'],
|
||||
self.env_variables['host'],
|
||||
self.env_variables['api_key']
|
||||
|
||||
@@ -8,7 +8,7 @@ class TestNameplaceFunctions(TestCase):
|
||||
|
||||
def setUp(self):
|
||||
self.env_variables = IntegrationTestHelper.get_environment_variables()
|
||||
self.sql_api_url = "https://{0}.{1}/api/v2/sql".format(
|
||||
self.sql_api_url = "https://{0}.{1}/api/v1/sql".format(
|
||||
self.env_variables['username'],
|
||||
self.env_variables['host'],
|
||||
self.env_variables['api_key']
|
||||
|
||||
@@ -8,7 +8,7 @@ class TestPostalcodeFunctions(TestCase):
|
||||
|
||||
def setUp(self):
|
||||
self.env_variables = IntegrationTestHelper.get_environment_variables()
|
||||
self.sql_api_url = "https://{0}.{1}/api/v2/sql".format(
|
||||
self.sql_api_url = "https://{0}.{1}/api/v1/sql".format(
|
||||
self.env_variables['username'],
|
||||
self.env_variables['host'],
|
||||
self.env_variables['api_key']
|
||||
|
||||
@@ -8,7 +8,7 @@ class TestRoutingFunctions(TestCase):
|
||||
|
||||
def setUp(self):
|
||||
self.env_variables = IntegrationTestHelper.get_environment_variables()
|
||||
self.sql_api_url = "https://{0}.{1}/api/v2/sql".format(
|
||||
self.sql_api_url = "https://{0}.{1}/api/v1/sql".format(
|
||||
self.env_variables['username'],
|
||||
self.env_variables['host'],
|
||||
self.env_variables['api_key']
|
||||
|
||||
@@ -8,7 +8,7 @@ class TestStreetFunctions(TestCase):
|
||||
|
||||
def setUp(self):
|
||||
self.env_variables = IntegrationTestHelper.get_environment_variables()
|
||||
self.sql_api_url = "https://{0}.{1}/api/v2/sql".format(
|
||||
self.sql_api_url = "https://{0}.{1}/api/v1/sql".format(
|
||||
self.env_variables['username'],
|
||||
self.env_variables['host'],
|
||||
self.env_variables['api_key']
|
||||
|
||||
Reference in New Issue
Block a user