14. Change log/history

14.1. Contributors

Quick links:

14.2. Changes

14.2.1. 2015

2015-02-18

  • Started.

v0.03, 2015-03-19

v0.04, 2015-04-25

  • Whole bunch of stuff to cope with a limited computer talking to SQL Server with some idiosyncrasies.

v0.05, 2015-05-01

  • Ability to vary audit/secret map tablenames.
  • Made date element separators broader in anonymisation regex.
  • min_string_length_for_errors option
  • min_string_length_to_scrub_with option
  • words_not_to_scrub option
  • bugfix: date regex couldn’t cope with years prior to 1900
  • crate_anon.anonymise.patient.gen_all_values_for_patient() was inefficient in that it would process the same source table multiple times to retrieve different fields.
  • ddgen_index_fields option
  • simplification of crate_anon.anonymise.anonregex.get_anon_fragments_from_string()
  • SCRUBMETHOD.CODE, particularly for postcodes. (Not very different from SCRUBMETHOD.NUMERIC, but a little different.)
  • debug_row_limit applies to patient-based tables (as a per-thread limit); was previously implemented as a per-patient limit, which was silly.
  • Indirection step in config for destination/admin databases.
  • ddgen_allow_fulltext_indexing option, for old MySQL versions.

v0.06, 2015-06-25

  • Option: replace_nonspecific_info_with
  • Option: scrub_all_numbers_of_n_digits
  • Option: scrub_all_uk_postcodes

v0.06, 2015-07-14

  • bugfix: if a source scrub-from value was a number with value '.', the regex went haywire… so regex builders now check for blanks.

v0.07, 2015-07-16

  • regex.ENHANCEMATCH flag tried unsuccessfully (segmentation fault, i.e. internal error in regex module, likely because generated regular expressions got too complicated for it).

v0.08, 2015-07-20

  • SCRUBMETHOD.WORDS renamed SCRUBMETHOD.WORDS [? typo in changelog!]
  • SCRUBMETHOD.PHRASE added
  • ddgen_scrubmethod_phrase_fields added

v0.09, 2015-07-28

v0.10, 2015-09-02 to 2015-09-13

  • Opt-out mechanism.
  • Default hasher changed to SHA256.
  • Bugfix to datatypes in crate_anon.anonymise.delete_dest_rows_with_no_src_row().

v0.11, 2015-09-16

  • Split main source code for simplicity.

v0.12, 2015-09-21

  • Database interface renamed from mysqldb to mysql, to allow for PyMySQL support as well (backend details otherwise irrelevant to front-end application).

v0.13, 2015-10-06

  • Added TRID.

14.2.2. 2016

v0.14.0, 2016-03-10

  • Code cleanup.
  • HMAC for RID generation, replacing simpler hashes, for improved security. Default becomes HMAC_MD5.
  • New option: secret_trid_cache_tablename
  • Removed option: words_not_to_scrub
  • New options: whitelist_filenames (replaces words_not_to_scrub), blacklist_filenames.
  • Transition from cardinal_pythonlib.rnc_db to SQLAlchemy for anonymiser database interface.
  • Environment variable changed from CRATE_LOCAL_SETTINGS to CRATE_WEB_LOCAL_SETTINGS and coded into crate_anon.crateweb.config.constants.
  • Web front end now happy getting structure from SQL Server and PostgreSQL.
  • Windows support. Windows XP not supported as Erlang (and thus RabbitMQ) won’t run on it from the distributed binaries. Windows 10 works fine.
  • Semantic versioning.

v0.16.0, 2016-06-04

  • Fixes to work properly with SQL Server, including proper automatic conversion of VARCHAR(MAX) and NVARCHAR(MAX) to MySQL TEXT fields. Note: also needs SQLAlchemy 1.1 or higher [1], currently available only via (1) fetching source via git clone https://github.com/zzzeek/sqlalchemy and changing into the ‘sqlalchemy’ directory this will create; (2) activating your CRATE virtual environment; (3) pip install . to install SQLAlchemy from your source copy. Further note: as of v0.18.2, this is done via PyPI again.
  • Opt-out management (1) manually; (2) via disk file; (3) via database fields.

v0.17.0, 2016-06-25

  • ONS Postcode Database.
  • RiO preprocessor.
  • Third-party patient cross-referencing for anonymisation.
  • The ‘required scrubber’ flag, as a safety measure.
  • Recordwise view of results in web interface.
  • Static type checking.

v0.18.0, 2016-09-29

  • Regular expression NLP tools for simple numerical results (CRP, ESR, WBC and differential, Na, MMSE).

v0.18.1, 2016-11-04

  • v0.18.1 (2016-11-04): new anonymise_numbers_at_numeric_boundaries_only option, to prevent e.g. ‘23’ being scrubbed from ‘1234’ unless you really want to.
  • More built-in NLP tools by now (height, weight, BMI, BP, TSH). MedEx support.

v0.18.2 to v0.18.8, 2016-11-11 to 2016-11-13

  • Too many version numbers here because git connection unavailable for remote development.
  • Requirement upgraded to SQLAlchemy 1.1.3, now SQLAlchemy 1.1 and higher are available from PyPI.
  • Support for non-integer PKs for NLP, to allow us to operate with tables we have only read-only access to. This is a bit tricky. To parallelize, it helps to be able to convert a non-integer to an integer for use with the modulo operator, %. In addition, we store PK values to speed up incremental updates. It becomes messy if we have to cope with lots and lots of types of PKs. Also, Python’s hash() function is inconsistent across invocations [2]. This is not a cryptographic application, so we can use anything simple and fast [3]. It looks like MurmurHash3 is suitable (hash DDoS attacks are not relevant here) [4]. However, the problem then is with collisions [5]. We want to ask “has this PK been processed before?” Realistically, the only types of PKs are integers and strings; it would be crazy to use floating-point numbers or BLOBs or something. So let’s put a cap at VARCHAR(n), where n comes from MAX_STRING_PK_LENGTH; store a 64-bit integer hash for speed, and then use the hash to say quickly “no, not processed” and check the original PK if processed. If the PK field is integer, we can just use the integer field for the PK itself. Note that the delete_where_no_source function may be imperfect now under hash collisions (and it may be imperfect in other ways too).
  • This system not implemented for anonymisation; it just gets too confusing (PIDs, MPIDs, uniqueness of PID for TRID generation, etc.).
  • However, mmh3 requires a Visual C++ 10.0 compiler for Windows. An alternative would be to require pymmh3 but load mmh3 if available, but pymmh3 isn’t on PyPI. Another is xxHash [6], but that also requires VC++ under Windows; pyhashxx installs but the interface isn’t fantastic. Others include FNV and siphash [7]. The xxHash page compares quality and speed and xxHash beats FNV for both (and MurmurHash for speed); siphash not listed. Installation of siphash is fine. Other comparisons at [8]. Let’s use xxhash (needs VC++) and pyhashxx as a fallback… only pyhashxx only supports 32-bit hashing. The pyhash module doesn’t install under Windows Server 2003, and nor does xxh, while lz4tools needs VC++. OK. Upshot: use mmh3 but fall back to some baked in Python implementations (from StackOverflow and pymmh3, with some bugfixes) if mmh3 not available.
  • NLP delete_where_no_source then failed as expected with large databases, so reworked to be OK regardless of size (using temporary tables).
  • Python 3.5 can handle circular imports (for type hints) that Python 3.4 can’t, so some delayed and version-conditional imports to sort that out in the NLP code.
  • Provide source/destination record counts from NLP manager, and better progress indicator for anonymiser.
  • Optional NLP record limit for debugging.
  • Speed increases by not requesting unnecessary ORDER BY conditions.
  • Commit-every options for NLP (every n bytes and/or every n rows).
  • Regex NLP for ACE, mini-ACE, MOCA.
  • Timing framework for NLP (for when it’s dreadfully slow and you think the problem might be the source database).
  • Significant NLP performance enhancement by altering progress DB lookup methods.

v0.18.9, 2016-12-02

  • Regex NLP: option in crate_anon.nlp_manager.regex_parser.SimpleNumericalResultParser to take absolute values, e.g. to deal with text like Na-142, K-4.1, CRP-97, which use - simply as punctuation, rather than as a minus sign. Failing to account for these would distort results.

  • No attempt is made to specify maximum or minimum values, which can easily be excluded as required from the resulting data set. One could of course use the SQL ABS() function to deal with negative values post hoc, but some things have no physical meaning when negative, such as a white cell count or CRP value, so it’s preferable to fix these at source to reduce the chance of user error through not noticing negative values.

  • The take_absolute option is applied to: CRP, sodium, TSH, BMI, MMSE, ACE, mini-ACE, MOCA, ESR, and white cell/differential counts. (NLP processors for height, BP already enforced positive values. Weight must be able to handle negatives, like “weight change –0.4kg”.)

  • Similarly, hyphen followed by whitespace treated as ignorable in regex NLP (e.g. in weight - 48 kg; though spaces are meaningful for mathematical operations (“a – b = c”), it is syntactically wrong to use - 4 as a unary minus sign to indicate a negative number (–4) and much more likely that this context means a dash.

  • En and em dashes, and a double-hyphen as a dash (--) treated as ignorables in regex NLP.

  • At present, Unicode minus signs () are not handled. For reference [9]:

    name character code handling
    hyphen-minus - Unicode 002D or ASCII 45 minus sign if context correct
    formal hyphen Unicode 2010 not handled at present
    minus sign Unicode 2212 not handled at present
    en dash Unicode 2013 treated as ignorable [10]
    em dash Unicode 2014 treated as ignorable
  • Improved regex self-testing, including new test framework in crate_anon.nlp_manager.test_all_regex.

v0.18.10, 2016-12-11

  • Full support for SQL Server as the backend.
  • Hot-swapping databases (compare MySQL [11]): you can rename databases, so this seems OK [12].
  • Full-text indexing: optional in SQL Server 2008, 2012, 2014 and 2016 [13]; basic SELECT syntax is WHERE CONTAINS(fieldname, "word"), and index creation with CREATE FULLTEXT INDEX ON table_name (column_name) KEY INDEX index_name .... Added to crate_anon.common.sqla.
  • Support for SQL query building, with user-configurable selector mechanism. See Transact-SQL syntax reference [14]. We use the Django setting settings.RESEARCH_DB_DIALECT to govern this.

v0.18.11, 2016-12-19

  • Tweaks/bugfixes for RiO preprocessor, and for anonymisation to SQL Server databases.
  • Local help HTML offered via web front end.

14.2.3. 2017

v0.18.12, 2017-02-26

  • More fixes for SQL Server, including full-text indexing.
  • Completed changes to CPFT consent materials to reflect ethics revision (Major Amendment 2, 12/EE/0407).

v0.18.13, 2017-03-04

  • Final update/PyPI push for CPFT consent materials.

v0.18.14, 2017-03-05

  • Extra debug options for consent-to-contact templates.
  • Multi-column FULLTEXT indexes under SQL Server.

v0.18.15-v0.18.16, 2017-03-06 to 2017-03-13

  • Full-text finder generates CONTAINS(column, 'word') properly for SQL Server.
  • Bugfix to Patient Explorer (wasn’t offering WHERE options always).
  • “Table browser” views in Patient Explorer
  • Bugfix to Windows service. Problem: a Python process was occasionally being “left over” by the Windows service, i.e. not being killed properly. Process Explorer indicated it was the one launched as python launch_cherrypy_server.py. The Windows event log has a message reading “Process 1/2 (Django/CherryPy) (PID=62516): Subprocess finished cleanly (return code 0).” The problem was probably that in crate_anon.crateweb.core.management.commands.runcpserver, the cherrypy.engine.stop() call was only made upon a KeyboardInterrupt exception, and not on other exceptions. Solution: broadened to all exceptions.

v0.18.17, 2017-03-17

  • Removed erroneous debugging code from crate_anon.nlp_manager.parse_medex.Medex.parse().
  • If you mis-configured the Java interface to a GATE application, it crashed quickly, which was helpful. If you mis-configured the Java interface to MedEx, it tried repeatedly. Now it crashes quickly.

v0.18.18 to v0.18.23, 2017-04-28

  • Paper published on 2017-04-26 as Cardinal (2017), BMC Medical Informatics and Decision Making 17:50; http://www.pubmed.com/28441940; https://doi.org/10.1186/s12911-017-0437-1.
  • Support for configurable paths for finding on-disk documents (e.g. from a combination of a fixed root directory, a patient ID, and a filename).

v0.18.23 to v0.18.33, 2017-05-02

  • NLP value_text field (FN_VALUE_TEXT in code) given maximum length, rather than 50, for the regex parsers, as it was overflowing (e.g. when a lot of whitespace was present). See crate_anon.nlp_manager.regex_parser.NumericalResultParser.dest_tables_columns().
  • Supports more simple text file types (.csv, .msg, .htm).
  • New option: ddgen_rename_tables_remove_suffixes.
  • Bugfix to CRATE GATE handler’s stdout-suppression switch.
  • New option: ddgen_extra_hash_fields.
  • PCMIS preprocessor.
  • Support non-integer PIDs and MPIDs. Note that the hashing is based on a string representation, so if you have one database using an integer NHS number, and another using a string NHS number, the same number will hash to the same result if you use the same key.
  • Hashing of additional fields, initially to support the PCMIS CaseNumber (as well as PatientId).

v0.18.34 to v0.18.39, 2017-06-05

  • For SLAM BRC GATE pharmacotherapy app: add support for output columns whose SQL column name is different to the GATE tag (e.g. when dose-value must be changed to dose_value); see ``renames`` option. GATE output fields now preserve case. Another option (null_literals) to allow GATE output of null to be changed to an SQL NULL. Also added _set column to GATE output.

v0.18.40, 2017-07-20

v0.18.41, 2017-07-21

To v0.18.46, 2017-07-28 to 2017-08-05

  • Fix to coerce_to_date (for date types), renamed to coerce_to_datetime.
  • NLP bug fixed relating to a missing pytz import.
  • Fixes to NLP, including accepting views (not just tables) as input. Note that under SQL Server, you should not have to specify ‘dbo’ anywhere in the config (but consider setting ALTER USER... WITH DEFAULT SCHEMA as above).
  • Manual and 2017 paper distributed with package.
  • Shift some core stuff to cardinal_pythonlib to reduce code duplication with other projects.

v0.18.48, 2017-11-06

  • Clinician view: find text across a database, for an identified patient. See crate_anon.crateweb.research.views.all_text_from_pid.
    • Rationale: Should privileged clinical queries be in any way integrated with CRATE? Advantages would include allowing the receiving user to run the query themselves without RDBM intervention and RDBM-to-recipient data transfer considerations, while ensuring the receiving user doesn’t have unrestricted access (e.g. via SQL Server Management Studio). Plus there may be a UI advantage.
  • Clinician view: look up (M)RIDs from (M)PIDs. Intended purpose for this and the preceding function: “My clinical front end won’t tell me if my patient’s ever had mirtazapine. I want to ask the research database.” (As per CO’L request 2017-05-04.) See crate_anon.crateweb.research.views.ridlookup.
  • Code to generate and test demonstration databases improved.

14.2.4. 2018

v0.18.49, 2018-01-07, 2018-03-21, 2018-03-27, published 2018-04-20

  • Use flashtext (rather than regex) for blacklisting words; this is much faster and allows large blacklists (e.g. a long list of all known forenames/surnames).
  • Provides the crate_fetch_wordlists tool to fetch names and English words (and perform in-A-not-B functions, e.g. to generate a list of names that are not English words).
  • Extend CRATE’s GATE pipeline to include or exclude GATE sets, since some applications produce results just in one set, and some produce them twice (e.g. in the unnamed set, named "", and in a specific named set).
  • Medical eponym list.

v0.18.50 to v0.18.51, 2018-05-04 to 2018-06-29

v0.18.52, 2018-07-02

  • NLP fields now support a standard _srcdatetime field; this can be NULL, but it’s normally specified as a defining DATETIME field from the source database (since most NLP needs an associated date and it’s far more convenient if this is in the destination database, along with patient ID). It’s specified directly to the crate_anon.nlp_manager.input_field_config.InputFieldConfig rather than via the copyfields, since we want a consistent date/time field name in the NLP output even if there is a lack of naming consistency in the source. Search for “new in v0.18.52”.
  • Possibly a bug fixed within the NLP manager, in relation to recording of hashed PKs from tables with non-integer PKs; see crate_anon.nlp_manager.input_field_config.InputFieldConfig.gen_text().

v0.18.53, to 2018-10-24

  • Added Client_Demographic_Details.National_Insurance_Number and ClientOtherDetail.NINumber to RiO automatic data dictionary generator as a sensitive (scrub-source) field; they were marked for code anonymisation but not flagged as scrub-source automatically.
  • Removed full stop from end of sentence in email_clinician.html beginning “If you’d like help, please telephone the Research Database Manager…”, since some users copied/pasted the full stop as part of the final e-mail address, which bounced. Clarity more important than grammar in this case.
  • NLP adds CRATE version column, _crate_version.
  • NLP adds “when fetched from database” column, _when_fetched_utc.
  • NLP supports “cmm” as an abbreviation for cubic mm (seen in CPFT and as per https://medical-dictionary.thefreedictionary.com/cmm).
  • To cardinal_pythonlib==1.0.25 with updates to document_to_text() parameter handling, then to 1.0.32.
    • Note that cardinal_pythonlib==1.0.25 also fixes a bug related to SQLAlchemy that manifested as AttributeError: module 'sqlalchemy.sql.sqltypes' has no attribute '_DateAffinity'.
  • NLPRP draft to 0.1.0.
  • django==2.0.6 to django==2.1.2 given security vulnerabilities reported in Django versions [2.0, 2.0.8).
  • Bugfix: mark_safe decorator added to all Django admin site parts with allow_tags = True set (for embedded URLs).
  • django-debug-toolbar==1.9.1 to django-debug-toolbar==1.10.1
  • Improved docstrings.
  • Minor bugfixes in crate_anon.anonymise.anonymise for fetching values from files.
  • _addition_only DDR flag only permitted on PK fields. (Was only attended to for them in any case!)
  • Bugfix to crate_anon.crateweb.consent.views.validate_email_request() and crate_anon.crateweb.consent.views.validate_letter_request(); these were returning rather than raising. Testing showed that something else was also blocking permission to access such things inappropriately, but fixed anyway!
  • Renamed generate_fake_nhs to generate_random_nhs to emphasize what this does.
  • crate_anon.crateweb.consent.models.Study.html_summary()
  • Sitewide queries, editable by RDBM.
  • Restrict anonymiser to specific patient IDs (for subset generation +/- custom pseudonyms).

v0.18.54, 2018-10-26

  • Deferred load of clinical team info. (Main research database structure is still loaded at the start; I think my intention was to fail as early as possible if it’s going to fail, and/or ensure that “filling the cache” time is not experienced by the end user).

  • Fixed packaging bug in setup.py.

  • 2018-10-21: Fixed bug in RDBM admin ‣ Studies:

    OperationalError at /mgr_admin/consent/study/
    
    (1054, "Unknown column 'consent_study.p_summary' in 'field list'")
    

    Changed p_summary to a property.

v0.18.55, 2018-11-02

  • In crate_anon.anonymise.altermethod.AlterMethod._extract_text_func(), pre-check that a file exists (to save time if it doesn’t).
  • Bugfix to cardinal_pythonlib (now v1.0.33) in the autotranslation of SQL Server TIMESTAMP fields.
  • Changed caching for crate_anon.crateweb.research.research_db_info.SingleResearchDatabase to make command-line startup faster (at the expense of first-fetch speed).

v0.18.56, 2018-11-02

  • cardinal_pythonlib==1.0.36
  • Bugfix to setup.py; Java files were not being distributed properly.
  • Performance optimization to query “column filtering” for “show only columns containing no NULL values”, and more generally optimized; should run queries only once per web session.
  • Bugfix to crate_anon.crateweb.research.models.get_executed_researchdb_cursor(), which was double-wrapping a database cursor incorrectly.

v0.18.57, 2018-12-11

v0.18.58, 2018-12-23

v0.18.59, 2018-12-24

  • Bugfix to clinician_initiated_contact_request(). Now checks that patient’s consent mode is green or yellow before confirming request.

v0.18.60, 2018-12-27

  • New look of website.
  • Bugfix to clinician requests. Also now sends a more appropriate email in these cases.

14.2.5. 2019

v0.18.61, 2019-01-15

  • Updated version of Django in setup.py.
  • Flag on website to check if query has been run since last database update.
  • Option of column in anonymiser output specifying when processed.

v0.18.62, 2019-02-09

  • Improved the crate_test_extract_text command (crate_anon.anonymise.test_extract_text), including errorlevel/return codes to detect text presence.
  • Bump to cardinal_pythonlib==1.0.47. Note that this now raises an exception from cardinal_pythonlib.extract_text.document_to_text() if a filename is passed and the file doesn’t exist.

v0.18.63, 2019-02-12

  • NLP web server based on the NLPRP API.
  • Bugfix to the website string finder - ‘text fields’ now includes ‘NVARCHAR(-1)’.

v0.18.64, 2019-02-21

  • NLP for glucose cholesterol (LDL, HDL, total), triglycerides, HbA1c (still need external validation).

v0.18.65, 2019-03-04 to 2019-03-25

  • NLP for potassium, urea, creatinine, haemoglobin, haematocrit (still need external validation).
  • At some point before this: SQL helpers to find drug classes/types (e.g. “atypical antipsychotics”, “SSRIs”), as per JL’s idea of 2018-01-08.
  • At some point before this: research query options to show a subset of columns.
  • At some point before this: “Clinician asks for a study pack” – create a contact request that’s pre-authorized by a clinician (who might want to pass on the pack themselves or delegate the RDBM to do it).
  • Standard site queries now handle the following problem:
    • With regular data updates there might be problems with queries returning different results if rerun a week later, so might be worth returning a timestamp of some type, like: MAX(DATE_CREATED) FROM RIO.DBO.Clinical_Documents + MAX(whenprocessedutc)) FROM [RiONLP].[dbo].[crate_nlp_progress] +

v0.18.66, 2019-03-29

  • Update to CrateGatePipeline.java to support an option to continue after GATE crashes.

v0.18.67, 2019-03-30 to 2019-03-31

  • semver to semantic_version; consistent with CamCOPS and better (and not actually used hitherto by CRATE!)
  • NLPRP constants and core API.
  • Move to Python 3.6 (already the minimum in CPFT), allowing f-strings.
  • f-strings. (Note: use Alt-Enter in PyCharm.)
  • CrateGatePipeline.java supports continuation after a Java RuntimeException (“bug in GATE code”).

v0.18.68, 2019-04-09

v0.18.70, 2019-04-17

  • PyPI distribution properly contains nlprp directory.

v0.18.71, 2019-05-13

  • Bugfix to nlp incremental mode.
  • Use of tokens in cloud NLP and option not to verify SSL.

v0.18.72, 2019-05-16

  • Bugfix to crate_anon.nlp_manager.cloud_parser.CloudRequest to convert string datetime back to datetime object. (MySQL automatically converts when writing to the database, but MSSQL doesn’t.)

v0.18.73, 2019-05-21

  • Only do nlp processing on records with alphanumeric characters.
  • Do highlighting only once per query, then save the highlighted version in an attribute of the crate_anon.crateweb.Query class.

v0.18.74, 2019-05-21

  • Changed migrations to make them compatible with SQL Server.

v0.18.75, 2019-06-06

  • Long queries are now hidden on website in order to avoid long render time.
  • crate_anon.nlp_manager.cloud_parser.CloudRequest now extracts content from GATE processors based on the start and end indexes.

v0.18.76, 2019-06-12

  • Option to truncate source data in nlp and to mark truncated records as processed or not.
  • Upgrade to SQLAlchemy==1.3.0 and django==2.2.2.
  • Bugfix to crate_anon.nlp_webserver.views - include_text and client_job_id are obtained from args rather than top-level of the request.
  • In crate_anon.nlp_manager.nlp_manager, open file to write after completing retrieval of requests so if there is a problem you don’t lose all your queue_ids.
  • Records will not be sent with no word character.
  • session.remove() has been added to to crate_anon.nlp_webserver.views.

v0.18.77, 2019-06-12

v0.18.78, 2019-06-12

v0.18.79, 2019-06-13

  • Downgraded to SQLAlchemy==1.2.8, which it was before and django==2.1.9, which is higher than it was before, because the updates where causing clashes with django-pyodbc-azure.
  • Log error messages from server in crate_anon.nlp_manager.cloud_parser.CloudRequest.list_processors().

v0.18.80, 2019-06-13

  • Sending requests to the cloud servers is broken up into blocks so that the database can be written to periodically.
  • New sessions for each request on the server-side.

v0.18.81, 2019-06-17

  • Microsoft specific bugfix in cloud nlp.
  • Commit every n records, where n is specified by the user, in retrieval of cloud requests.

v0.18.82, 2019-06-17

  • Used rate limiter.

v0.18.83, 2019-06-23

  • Bugfix to crate_anon.nlp_manager.cloud_parser.CloudRequest.get_nlp_values_gate() and crate_anon.nlp_manager.cloud_parser.CloudRequest.get_nlp_values_internal() so that they don’t try to fish out results for a processor when there are errors.
  • Retry after connection failure in crate_anon.nlp_manager.cloud_parser.

v0.18.85, 2019-07-21

v0.18.86, 2019-08-06

v0.18.87, 2019-09-30

  • NLP web server performance tweaks; database structure changes.
  • Remove dependence on cardinal_pythonlib.rnc_db, which is trivial but gives a warning.
  • cardinal_pythonlib==1.0.65
  • readthedocs.org problems fixed; see
    • environment variable _SPHINX_AUTODOC_IN_PROGRESS (re errors from docs build environment)
    • readthedocs.yml (re resource usage)
    • all .ini files were being ignored (despite being fine on a local Sphinx build) – this was a .gitignore bug.

v0.18.88 to 0.18.91, 2019-10-06 to 2019-10-07

v0.18.92, 2019-10-10

  • Bugfix: tools that were unrelated to the NLP web server were importing its settings (so requiring a dummy config file).
  • crate_email_rdbm tool
  • Bugfix in the way that postcodes.py imported from cardinal_pythonlib.extract_text.
  • cardinal_pythonlib==1.0.73

Footnotes

[1]https://bitbucket.org/zzzeek/sqlalchemy/issues/3504; http://docs.sqlalchemy.org/en/latest/changelog/migration_11.html#change-3504; http://docs.sqlalchemy.org/en/latest/changelog/changelog_11.html#change-1.1.0b1
[2]https://docs.python.org/3/reference/datamodel.html#object.__hash__; http://stackoverflow.com/questions/27522626/hash-function-in-python-3-3-returns-different-results-between-sessions
[3]See also http://stackoverflow.com/questions/5400275/fast-large-width-non-cryptographic-string-hashing-in-python
[4]https://pypi.python.org/pypi/mmh3/2.2; https://en.wikipedia.org/wiki/MurmurHash; see how it works using the less fast Python version at https://github.com/wc-duck/pymmh3
[5]http://preshing.com/20110504/hash-collision-probabilities/
[6]https://cyan4973.github.io/xxHash/
[7]https://www.131002.net/siphash/
[8]https://github.com/rurban/perl-hash-stats#number-of-collisions-with-crc32; http://fastcompression.blogspot.co.uk/2012/04/selecting-checksum-algorithm.html; http://softwareengineering.stackexchange.com/questions/49550/which-hashing-algorithm-is-best-for-uniqueness-and-speed; http://aras-p.info/blog/2016/08/02/Hash-Functions-all-the-way-down/
[9]https://www.cs.tut.fi/~jkorpela/dashes.html
[10]Possible that we may need to treat this as a minus sign in some contexts later, but this is not implemented yet.
[11]http://stackoverflow.com/questions/67093/how-do-i-quickly-rename-a-mysql-database-change-schema-name
[12]https://msdn.microsoft.com/en-GB/library/ms345378.aspx; https://www.mssqltips.com/sqlservertip/1891/best-practice-for-renaming-a-sql-server-database/
[13]https://technet.microsoft.com/en-us/library/cc721269(v=sql.100).aspx; https://msdn.microsoft.com/en-us/library/ms142571(v=sql.120).aspx
[14]https://msdn.microsoft.com/en-us/library/bb510741.aspx
[15]https://stackoverflow.com/questions/28837057/pandas-writing-an-excel-file-containing-unicode-illegalcharactererror; https://openpyxl.readthedocs.io/en/2.5/_modules/openpyxl/utils/exceptions.html; in particular, see check_string() in http://openpyxl.readthedocs.io/en/stable/_modules/openpyxl/cell/cell.html