mappings/VegCore-VegBIEN.csv: taxonomic terms: Remapped the concatenated taxonomic name to new identifyingtaxonomicname to use it directly to match up with the TNRS submitted name. Continue to map scientificNameWithAuthorship to taxonomicnamewithauthor.
schemas/vegbien.sql: taxonpath: Renamed plantcode to identifyingtaxonomicname so that it can be used to store the concatenated taxonomicname that gets scrubbed. This enables ignoring the name components when the full name is specified, so that when a TNRS submitted name's matched components are included in its taxonpath, this will not prevent a datasource's concatenated name (without the matched components) from matching up with the corresponding TNRS submitted name.
schemas/vegbien.sql: taxonpath: Made taxonomicnamewithauthor optional again and include all columns in the taxonpath_unique_within_datasource_by_name unique index so that the original name components can be stored in a separate taxonpath from the taxonpath with the concatenated taxonomic name. (The datasource's taxonpath would not always contain an entry for taxonomicnamewithauthor, so the other columns also need to be used in the unique index.)
schemas/vegbien.sql: taxonpath: Added back datasource_id, plantcode to make taxonpath datasource-specific again. This way, the original name components can still be stored in taxonpath, in addition to storing the concatenated name in a datasource-general taxonpath for use by TNRS.
inputs/.TNRS/tnrs/map.csv: Mapped columns for components of original, submitted name
mappings/VegCore-VegBIEN.csv, VegCore.csv: Removed no longer used verbatimScientificNameWithAuthorship. Use scientificNameWithAuthorship instead, and map accepted (scrubbed) names to acceptedScientificNameWithAuthorship to create the canon_taxonpath_id link.
inputs/.TNRS/tnrs/map.csv: Remapped to new accepted* taxonomic terms
mappings/VegCore-VegBIEN.csv: Mapped accepted* taxonomic terms
sql_io.py: cleanup_table(): Don't clean up the pkey, because the canonicalization involved may produce collisions (as it does for TNRS.tnrs)
sql.py: Added pkey_col_()
tnrs.py: tnrs_request(): Added comment that names containing only whitespace characters are ignored by TNRS and do not receive a response row. Our tnrs_db and reimport pipeline handles the necessary re-matching-up by just creating taxonpaths for each Name_submitted, and then letting the data import process on the following import attach to the prepopulated taxonpaths.
tnrs_db: Exclude taxonomic names which have already been scrubbed, by using a filter-out LEFT JOIN on TNRS.tnrs
tnrs.py: max_pause: Changed to 30 min because TNRS sometimes freezes for ~10 min. The freezing usually happens while the data is being uploaded rather than when it's being retrieved, so that the max_pause would not apply, but to be on the safe side, requests should not time out unnecessarily.
tnrs_db: tnrs_profiler: Use iter_text='name' for consistency with tnrs.tnrs_request()'s own profiler's iter_text
tnrs_db: Print cumulative profiling information after every TNRS request, rather than just at the end
inputs/.TNRS/tnrs/tnrs.make: Append to the log file instead of overwriting it, so that the TNRS scrubbing of each import's new taxonomic names can be included in one log file. Echo the command to the log file to identify separate runs.
TNRS-related programs: Use "names" instead of "taxons" for variable names because what's being submitted are actually verbatim taxonomic names, not official references to specific taxa
tnrs.py: tnrs_request(): Profile the TNRS request
tnrs.py: tnrs_request(): Fixed bug where initial_headers needed to be copied instead of just assigned to headers, because initial_headers is a global constant and should not be changed when the Cookie header is added
mappings/VegCore.csv: originalTaxonRank, acceptedTaxonRank: Fixed sources to use verbatimTaxonRank, not taxonRank
mappings/VegCore.csv: originalTaxonRank: Added source of the original* prefix
mappings/VegCore.csv: acceptedTaxonRank: Added source of the accepted prefix
mappings/VegCore.csv: accepted* taxonomic terms: Fixed sources of the accepted prefix to use acceptedNameUsage, not acceptedNameUsageID
mappings/VegCore.csv: original* taxonomic terms: Source the original prefix to DwC originalNameUsage, which is a more offical source than SALVIAS orig_species
mappings/VegCore.csv: Added accepted* taxonomic terms to store the scrubbed name
import_all: Clean up any new TNRS.tnrs entries before importing the TNRS data
inputs/.TNRS/tnrs/: Create using datasource schema.sql file instead of text header and postprocess.sql, for clarity and to enable using `make inputs/.TNRS/tnrs/install` to clean up the tnrs entries populated by tnrs_db
mappings/VegCore-VegBIEN.csv: Don't combine taxonRank with infraspecificEpithet if there is no infraspecificEpithet, because the taxonRank is only the infraspecificEpithet's prefix when there is an actual infraspecificEpithet. Often, taxonRank contains values like "genus" or "species" which cannot be used for this purpose.
tnrs.py: repeated_tnrs_request(): Just retry the request once with with debug turned on, to avoid cluttering the log output with the verbose debug info of multiple failed requests if the error is not resolved on retry
tnrs.py: tnrs_request(): repeated_tnrs_request(): Print all suppressed exceptions to stderr
tnrs.py: tnrs_request(): parse_response(): Include both the response headers and the response body in the InvalidResponse message
inputs/import.stats.xls: Updated import times
profiling.py: Profiler: Fixed bug where instance variable start had the same name as method start()
mappings/VegCore-VegBIEN.csv: verbatimScientificNameWithAuthorship: Set canon_taxonpath_id to 0 on the first, scrubbed taxonpath to auto-create the self reference that indicates a scrubbed taxonpath
mappings/VegCore-VegBIEN.csv: Don't forward scientificName to taxonoccurrence.authortaxoncode when importing just taxonpaths, as for TNRS
tnrs_db: Moved lower max_taxons limit to tnrs.py because it's really required to avoid crashing the TNRS server and should apply to all callers
tnrs_db: Print log message with # of taxonpaths being sent to TNRS
tnrs_db: Fixed bug where InvalidResponse was missing module name
tnrs_db: Profile the TNRS requests. This involves using a finally block to ensure that the profiling stats are printed even if the program exits with an error.
tnrs_db: Reduced the chunk size to avoid slowing down the TNRS server
inputs/.TNRS/tnrs/tnrs.make: Added log option which outputs to the terminal instead when set to ""
tnrs_db: Added log messages for Making TNRS request and Storing TNRS response data so that if the TNRS daemon pauses, it's obvious which step it's waiting on
sql.py: insert(): ignore optimization: Fixed bug where needed to run insert_select() recoverably so that the aborted transaction is rolled back after a DuplicateKeyException or NullValueException
tnrs_db: If tnrs.repeated_tnrs_request() stil throws InvalidResponse, skip the current set in case its data caused the error. Note that it will still be tried again the next time tnrs_db is run.
repeated_tnrs_request(): When retrying after an invalid response, output protocol info for debugging
inputs/Makefile: Import logs: Don't download .TNRS/tnrs/tnrs.make.log by default because it changes each time `make inputs/.TNRS/tnrs/tnrs-remake` is run, and any version downloaded for debugging should be preserved. It can still be downloaded by setting the tnrs_log env var.
tnrs_client, tnrs_db: Use new tnrs.repeated_tnrs_request()
tnrs.py: Added repeated_tnrs_request() to retry a TNRS request which returned an invalid response
db_xml.py: put_table(): Fixed bug where pkeys_loc needed to be initialized. Note that this bug was only triggered when importing a table with zero rows (in this case, the initial empty TNRS.tnrs table), because otherwise it would be set in the loop.
inputs/Makefile: Import logs: Also download inputs/.TNRS/tnrs/tnrs.make.log
inputs/Makefile: Import logs: Use new $(rsync*) to also sync datasources starting with ., such as .TNRS
lib/common.Makefile: rsync: Added $(rsync*) to rsync all files, including those starting with "."
tnrs.py: parse_response(): Raise custom InvalidResponse exception instead of SystemExit, so callers can catch the exception and respond to it
mappings/VegCore-VegBIEN.csv: taxonpath.taxonomicnamewithauthor _join_words mappings: Added space after taxon rank prefix (var., etc.) for infraspecific ranks
import_all: Start the tnrs daemon using `make inputs/.TNRS/tnrs/tnrs-remake &`
Added inputs/.TNRS/tnrs/tnrs.make to run tnrs_db on VegBIEN
Added tnrs_db to scrub the taxonpaths in VegBIEN using TNRS
Regenerated vegbien.ERD exports
schemas/vegbien.sql: taxonpath: Made it datasource-general and uniquely identified only by its taxonomicnamewithauthor so that the taxonpaths imported by the TNRS datasource will be matched and used directly when the other datasources are imported
schemas/vegbien.sql: taxonpath: taxonpath_unique_within_datasource_by_name unique index: Just do duplicate elimination on the taxonomicnamewithauthor, since that is now a required field and is generated by concatenating all the other fields. Note that the inserted row counts change slightly because the concatenation makes some names equal that are split among the fields differently, such as when the genus is included in the species field.
db_xml.py: put(): Added _alt optimization that just returns the first arg if it's non-NULL
sql_gen.py: Added is_nullable()
schemas/vegbien.sql: taxonpath.taxonomicnamewithauthor: Made it NOT NULL, so that all taxonpaths would have a concatenated name to feed to TNRS
mappings/VegCore-VegBIEN.csv: taxonomic terms: Changed _first to _alt because some datasources have NULL values in scientificNameWithAuthorship or scientificName, so it can't just be used in place of the joined-together taxonomic ranks
db_xml.py: put(): Parse input columns and process values in separate loops, so that structural XML function optimization code can be inserted between them
sql_io.py: put_table(): Removed comment that can support in_tables of any fixed-size iterable type, because the iterable must be ordered so that the first table can be treated specially
sql_io.py: put_table(): Support in_tables of any fixed-size iterable type
mappings/Veg+-VegCore.csv: cationExchangeCapacity->cationExchangeCapacity_cmol_kg mapping: Removed ? prefix because a mapping to only one set of units is unambiguous (if additional units for cationExchangeCapacity are found, this will become an ambiguous mapping). Note that canon automatically removes punctuation from VegCore terms, so this mapping would previously have had the ? prefix autoremoved anyway (both in inputs/*/*/map.csv and recently also in Veg+-VegCore.csv).
mappings/Makefile: .Veg+-VegCore.csv.last_cleanup: Translate VegCore terms using itself so that any mapping to another Veg+ term automatically becomes a mapping to a VegCore term. .VegX-VegCore.csv.last_cleanup: Translate VegCore terms using Veg+-VegCore.csv to keep the terms up to date.
mappings/VegX-VegCore.csv: Translated VegCore terms using Veg+-VegCore.csv
mappings/Makefile: .VegCore.csv.last_cleanup, .VegCore-VegBIEN.csv.last_cleanup: Apply Veg+-VegCore.csv so that terms can easily be renamed just by adding a mapping in Veg+-VegCore.csv, which will auto-translate all places that use the term. .VegCore-VegBIEN.csv.last_cleanup: Canonicalize to VegCore.csv so case changes in VegCore terms will automatically propagate to VegCore-VegBIEN.csv.
mappings/VegCore-VegBIEN.csv: Mapped verbatimScientificNameWithAuthorship, so that it links a verbatim taxonpath to the scrubbed taxonpath created from the primary taxonomic terms
mappings/VegCore.csv: Renamed unscrubbedScientificNameWithAuthorship to the more standard verbatimScientificNameWithAuthorship, which is available now that the original taxondetermination terms use the original* prefix
mappings/VegCore.csv: Renamed verbatim* taxonomic terms to original* because in most datasources, they are in fact for the original taxon determination of the organism (which can be a completely different name than the primary determination), rather than merely unscrubbed versions of the primary taxonomic name elements. Note that SALVIAS's orig_* terms do appear to be merely unscrubbed versions, but it's not a problem to add an additional taxon determination for them.
sql.py: pkey(): Get the table's actual primary key column, rather than just using the first column in the table. Continue to return the first column in the table if the table has no primary key.
inputs/.TNRS/tnrs/postprocess.sql: Use :table var instead of hardcoding the table name
inputs/.TNRS/tnrs/postprocess.sql: Also add a primary key on Name_submitted, to prevent duplicate entries
inputs/.TNRS/tnrs/: Added postprocess.sql which makes Name_submitted NOT NULL
sql.py: insert(): ignore mode: Also ignore NullValueException
input.Makefile: Staging tables installation: %/install: Support custom postprocess.sql which specifies commands to run after the table is imported
import_all: Added import of .TNRS datasource, which happens synchronously before other datasources are imported
Moved tnrs table from public (schemas/vegbien.sql) to its own TNRS schema, which is created by a new .TNRS datasource. Note that .TNRS is included in the automated testing, but not yet in the import.
mappings/VegCore-VegBIEN.csv: Restored subplotID -> if subplot cond mapping, which had been overwritten
inputs/ACAD/Specimen/map.csv: Remapped scientificName to scientificNameWithAuthorship
sql_io.py: append_csv(): Using INSERT: Use ignore mode to support inserting rows into a table with a unique constraint
sql.py: insert(): Added ignore optimization that just suppresses any DuplicateKeyException on the client side, to avoid needing to create a wrapper function just to insert-ignore one row
mappings/VegCore-VegBIEN.csv: Synchronized verbatim* and non-verbatim taxonomic terms' mappings
mappings/VegCore.csv: Added special term unscrubbedScientificNameWithAuthorship
mappings/VegCore.csv: Added verbatimSubspecies, verbatimVariety, verbatimForma, verbatimCultivar (already mapped in VegCore-VegBIEN.csv)
mappings/Makefile: .VegCore.csv.last_cleanup: Also remake VegCore-VegBIEN.unsourced_terms.csv here, not just in .VegCore-VegBIEN.csv.last_cleanup, so that the unsourced_terms.csv will be remade if the user adds the missing sources to VegCore.csv
mappings/Makefile: VegCore-VegBIEN.unsourced_terms.csv: Factored remake code into its own make target
mappings/VegCore-VegBIEN.csv: verbatim* taxonomic terms: Added taxonomicnamewithauthor mappings analogous to those for the non-verbatim taxonomic terms
mappings/VegCore.csv: Added verbatimScientificNameWithAuthorship
Added inputs/.public/, which stores mappings that manipulate VegBIEN itself
forwarding.Makefile: Differentiate between subdirs which can be sent a command and subdirs which will receive a command broadcast to "all" subdirs
README.TXT: Data import: Starting column-based import: Use import_all, which now supports passing custom vars like by_col=1
import_all: Pass any args, such as vars, through to with_all
with_all: Support additional command-line args for the make target, such as vars
