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Jorge Fernandez HernandezJorge Fernandez Hernandez
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EUCLIDSWRQ-247 New remote tests for euclid
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CHANGES.rst

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@@ -48,7 +48,6 @@ esa.euclid
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- New method, get_scientific_product_list, to retrieve scientific LE3
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products. [#3313]
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- New cross-match method [#3386]
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- New remote tests [#3407]
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gaia
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^^^^

astroquery/esa/euclid/tests/test_euclid_remote.py

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@@ -15,6 +15,7 @@ def test_query_object_columns_with_radius():
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@pytest.mark.remote_data
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@pytest.mark.filterwarnings("ignore::astropy.units.UnitsWarning")
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def test_query_object_row_limit():
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euclid = EuclidClass()
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coord = SkyCoord(ra=265.8, dec=64.1, unit=(u.degree, u.degree), frame='icrs')

docs/esa/euclid/euclid.rst

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@@ -150,8 +150,29 @@ To load only table names metadata (TAP+ capability):
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>>> from astroquery.esa.euclid import Euclid
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>>> tables = Euclid.load_tables(only_names=True, include_shared_tables=True)
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INFO: Retrieving tables... [astroquery.utils.tap.core]
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INFO: Parsing tables... [astroquery.utils.tap.core]
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INFO: Done. [astroquery.utils.tap.core]
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>>> print("Found", len(tables), "tables") # doctest: +IGNORE_OUTPUT
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Found 34 tables
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>>> print(*(table.name for table in tables), sep="\n") # doctest: +IGNORE_OUTPUT
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ivoa.obscore
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public.dual
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sedm.raw_detector
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sedm.raw_frame
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sedm.raw_quadrant
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sedm.aux_calibrated
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sedm.aux_mosaic
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sedm.aux_stacked
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sedm.basic_download_data
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sedm.calibrated_detectors
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sedm.calibrated_frame
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sedm.column_values
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sedm.combined_spectra
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...
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tap_config.coord_sys
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tap_config.properties
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...
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To load all table metadata (TAP compatible):
@@ -160,8 +181,14 @@ To load all table metadata (TAP compatible):
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>>> from astroquery.esa.euclid import Euclid
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>>> tables = Euclid.load_tables()
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INFO: Retrieving tables... [astroquery.utils.tap.core]
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INFO: Parsing tables... [astroquery.utils.tap.core]
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INFO: Done. [astroquery.utils.tap.core]
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>>> print(tables[0]) # doctest: +IGNORE_OUTPUT
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TAP Table name: ivoa.obscore
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Description: None
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Size (bytes): 0
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Num. columns: 34
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To load only a table (TAP+ capability) and inspect its columns:
@@ -171,8 +198,23 @@ To load only a table (TAP+ capability) and inspect its columns:
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>>> from astroquery.esa.euclid import Euclid
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>>> raw_detector_table = Euclid.load_table('sedm.raw_detector')
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>>> print(raw_detector_table) # doctest: +SKIP
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TAP Table name: sedm.raw_detector
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Description: None
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Size (bytes): 0
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Num. columns: 12
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>>> print(*(column.name for column in raw_detector_table.columns), sep="\n") # doctest: +IGNORE_OUTPUT
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crpix1
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crpix2
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crval1
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crval2
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detector_id
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detector_oid
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l1_raw_frame_oid
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q1_oid
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q2_oid
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q3_oid
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q4_oid
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to_be_published
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To get the list of products associated with a given Euclid observation_id or tile_index (for mosaic):
@@ -249,9 +291,20 @@ This query performs a cone search centered at the specified ra/dec coordinates w
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>>> coord = SkyCoord("17h51m07.4s +65d31m50.8s", frame='icrs')
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>>> radius = u.Quantity(0.5, u.deg)
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>>> job = Euclid.cone_search(coordinate=coord, radius=radius, table_name="sedm.mosaic_product", ra_column_name="ra", dec_column_name="dec", columns="*", async_job=True)
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INFO: Query finished. [astroquery.utils.tap.core]
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>>> cone_results = job.get_results()
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>>> print("Found", len(cone_results), "results")
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Found 27 results
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>>> cone_results['tile_index', 'creation_date', 'ra', 'dec', 'file_name', 'file_path', 'datalabs_path', 'filter_name', 'dist'][:5]
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<Table length=5>
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tile_index creation_date ra dec file_name file_path datalabs_path filter_name dist
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int64 str23 float64 float64 str88 str55 str43 str11 float64
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---------- ----------------------- ----------- ------- ------------------------------------------------------------------------------------- ------------------------------------------------------- ------------------------------------------- ----------- -------------------
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102158889 2024-10-26T14:01:21.038 267.3807789 65.4983 EUC_MER_BGSUB-MOSAIC-CFIS-R_TILE102158889-4366B7_20241024T203624.450577Z_00.00.fits /euclid/repository_idr/iqr1/Q1_R1/MER/102158889/MEGACAM /data/euclid_q1/Q1_R1/MER/102158889/MEGACAM MEGACAM_r 0.16895922479034217
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102158889 2024-10-26T13:50:13.676 267.3807789 65.4983 EUC_MER_BGSUB-MOSAIC-WISHES-G_TILE102158889-3DC3C3_20241024T205647.635112Z_00.00.fits /euclid/repository_idr/iqr1/Q1_R1/MER/102158889/HSC /data/euclid_q1/Q1_R1/MER/102158889/HSC HSC_g 0.16895922479034217
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102158889 2024-10-26T13:37:09.628 267.3807789 65.4983 EUC_MER_BGSUB-MOSAIC-NIR-Y_TILE102158889-AC6585_20241024T225321.344048Z_00.00.fits /euclid/repository_idr/iqr1/Q1_R1/MER/102158889/NISP /data/euclid_q1/Q1_R1/MER/102158889/NISP NIR_Y 0.16895922479034217
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102158889 2024-10-26T14:05:09.98 267.3807789 65.4983 EUC_MER_BGSUB-MOSAIC-CFIS-U_TILE102158889-9E97F_20241024T204431.839748Z_00.00.fits /euclid/repository_idr/iqr1/Q1_R1/MER/102158889/MEGACAM /data/euclid_q1/Q1_R1/MER/102158889/MEGACAM MEGACAM_u 0.16895922479034217
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102158889 2024-10-26T13:10:32.453 267.3807789 65.4983 EUC_MER_BGSUB-MOSAIC-NIR-H_TILE102158889-ED035A_20241024T212936.705156Z_00.00.fits /euclid/repository_idr/iqr1/Q1_R1/MER/102158889/NISP /data/euclid_q1/Q1_R1/MER/102158889/NISP NIR_H 0.16895922479034217
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@@ -263,6 +316,7 @@ Queries return a limited number of rows controlled by ``Euclid.ROW_LIMIT``. To c
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>>> job = Euclid.cone_search(coordinate=coord, radius=radius, table_name="sedm.mosaic_product", ra_column_name="ra", dec_column_name="dec", columns="*", async_job=True)
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>>> cone_results = job.get_results()
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>>> print("Found", len(cone_results), "results")
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Found 2 results
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To return an unlimited number of rows set ``Euclid.ROW_LIMIT`` to -1.
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>>> coord = SkyCoord(ra=60.3372780005097, dec=-49.93184727724773, unit=(u.degree, u.degree), frame='icrs')
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>>> table = Euclid.query_object(coordinate=coord, width=u.Quantity(0.1, u.deg), height= u.Quantity(0.1, u.deg))
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>>> print("Found a total of", len(table), "query results")
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Found a total of 2000 query results
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>>> print(table)
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dist avg_trans_wave_g_ext_decam avg_trans_wave_g_ext_hsc avg_trans_wave_g_ext_jpcam avg_trans_wave_g_ext_lsst avg_trans_wave_h avg_trans_wave_i_ext_decam ... sersic_fract_z_ext_panstarrs_disk_sersic sersic_fract_z_ext_panstarrs_disk_sersic_err she_flag spurious_flag spurious_prob variable_flag vis_det
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--------------------- -------------------------- ------------------------ -------------------------- ------------------------- ---------------- -------------------------- ... ---------------------------------------- -------------------------------------------- -------- ------------- ---------------------- ------------- -------
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3.566798805594703e-06 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.15743961930274963 -- 1
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0.0004459918667892947 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.004427384119480848 -- 1
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0.0011813971416470212 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.1833316683769226 -- 1
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0.0015542789169486976 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.12239421904087067 -- 0
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0.0015885047273778879 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.00021384040883276612 -- 1
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... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
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0.03958455791235079 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.1343534141778946 -- 0
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0.03958823626200475 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.00015592691488564014 -- 1
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0.03959898295410331 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.0365927591919899 -- 1
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0.039605684988334174 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.0831669270992279 -- 0
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0.03960602180308949 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 1 0.6376287937164307 -- 1
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0.039606556762811496 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.012528697960078716 -- 1
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0.03962541836711639 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.003399776993319392 -- 1
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Length = 2000 rows
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Synchronous queries like this one return a limited number of rows -> 2000
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>>> width=u.Quantity(0.1, u.deg)
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>>> height= u.Quantity(0.1, u.deg)
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>>> table_async = Euclid.query_object(coordinate=coord, width=width, height=height, async_job=True)
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INFO: Query finished. [astroquery.utils.tap.core]
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>>> print("Found a total of", len(table_async), "query results")
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Found a total of 2895 query results
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>>> print(table_async)
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dist avg_trans_wave_g_ext_decam avg_trans_wave_g_ext_hsc avg_trans_wave_g_ext_jpcam avg_trans_wave_g_ext_lsst avg_trans_wave_h avg_trans_wave_i_ext_decam ... sersic_fract_z_ext_panstarrs_disk_sersic sersic_fract_z_ext_panstarrs_disk_sersic_err she_flag spurious_flag spurious_prob variable_flag vis_det
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--------------------- -------------------------- ------------------------ -------------------------- ------------------------- ---------------- -------------------------- ... ---------------------------------------- -------------------------------------------- -------- ------------- ---------------------- ------------- -------
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3.566798805594703e-06 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.15743961930274963 -- 1
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0.0004459918667892947 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.004427384119480848 -- 1
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0.0011813971416470212 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.1833316683769226 -- 1
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0.0015542789169486976 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.12239421904087067 -- 0
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0.0015885047273778879 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.00021384040883276612 -- 1
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... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
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0.03958455791235079 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.1343534141778946 -- 0
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0.03958823626200475 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.00015592691488564014 -- 1
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0.03959898295410331 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.0365927591919899 -- 1
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0.039605684988334174 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.0831669270992279 -- 0
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0.03960602180308949 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 1 0.6376287937164307 -- 1
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0.039606556762811496 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.012528697960078716 -- 1
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0.03962541836711639 4826.7998046875 -- -- -- -- 7826.669921875 ... -- -- -- 0 0.003399776993319392 -- 1
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Length = 2000 rows
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1.4. Synchronous query
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>>> Euclid.login()
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>>> job_1 = Euclid.launch_job_async("select top 10 * from catalogue.mer_catalogue")
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>>> Euclid.upload_table_from_job(job=job_1)
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Created table 't1539932994481O' from job: '1539932994481O'.
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Now, you can query your table as follows (a full qualified table name must be provided,
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i.e.: *user_<your_login_name>."t<job_id>"*. Note that the previous table name must be

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