o ;D©iø,ã@s¼ddlmZmZmZddlZddlmZddlmZddl m Z m Z m Z m Z mZdd„Zddd „Zee _dd d „Zee _dd d„Zee _ddd„Zee _ddd„Zee _ddd„Zee _dS)é)Úabsolute_importÚprint_functionÚdivisionN)Ú text_type)ÚDuplicateKeyError)ÚTableÚ asindicesÚasdictÚRecordÚ rowgetterc Cs t|ƒ}zt|ƒ}Wn tyg}Ynwt||ƒ}t|ƒdks%Jdƒ‚tj|Ž}|dur7ttt|ƒƒŽ}nt||ƒ}t|ƒdksFJdƒ‚tj|Ž}|||fS)Nrúno key selectedzno value selected) ÚiterÚnextÚ StopIterationrÚlenÚoperatorÚ itemgetterr Úrange) ÚtableÚkeyÚvalueÚitÚhdrÚ keyindicesÚgetkeyÚgetvalueÚ valueindices©rúJ/var/www/Datamplify/venv/lib/python3.10/site-packages/petl/util/lookups.pyÚ _setup_lookup s  ÿ     rc Csl|durtƒ}t|||ƒ\}}}|D]!}||ƒ}||ƒ} ||vr.||} |  | ¡| ||<q| g||<q|S)a¾ Load a dictionary with data from the given table. E.g.:: >>> import petl as etl >>> table1 = [['foo', 'bar'], ... ['a', 1], ... ['b', 2], ... ['b', 3]] >>> lkp = etl.lookup(table1, 'foo', 'bar') >>> lkp['a'] [1] >>> lkp['b'] [2, 3] >>> # if no value argument is given, defaults to the whole ... # row (as a tuple) ... lkp = etl.lookup(table1, 'foo') >>> lkp['a'] [('a', 1)] >>> lkp['b'] [('b', 2), ('b', 3)] >>> # compound keys are supported ... table2 = [['foo', 'bar', 'baz'], ... ['a', 1, True], ... ['b', 2, False], ... ['b', 3, True], ... ['b', 3, False]] >>> lkp = etl.lookup(table2, ('foo', 'bar'), 'baz') >>> lkp[('a', 1)] [True] >>> lkp[('b', 2)] [False] >>> lkp[('b', 3)] [True, False] >>> # data can be loaded into an existing dictionary-like ... # object, including persistent dictionaries created via the ... # shelve module ... import shelve >>> lkp = shelve.open('example1.dat', flag='n') >>> lkp = etl.lookup(table1, 'foo', 'bar', lkp) >>> lkp.close() >>> lkp = shelve.open('example1.dat', flag='r') >>> lkp['a'] [1] >>> lkp['b'] [2, 3] N)ÚdictrÚappend) rrrÚ dictionaryrrrÚrowÚkÚvÚlrrrÚlookup&s1   r'Fc Csb|durtƒ}t|||ƒ\}}}|D]}||ƒ} |r"| |vr"t| ƒ‚| |vr.||ƒ} | || <q|S)až Load a dictionary with data from the given table, assuming there is at most one value for each key. E.g.:: >>> import petl as etl >>> table1 = [['foo', 'bar'], ... ['a', 1], ... ['b', 2], ... ['b', 3]] >>> # if the specified key is not unique and strict=False (default), ... # the first value wins ... lkp = etl.lookupone(table1, 'foo', 'bar') >>> lkp['a'] 1 >>> lkp['b'] 2 >>> # if the specified key is not unique and strict=True, will raise ... # DuplicateKeyError ... try: ... lkp = etl.lookupone(table1, 'foo', strict=True) ... except etl.errors.DuplicateKeyError as e: ... print(e) ... duplicate key: 'b' >>> # compound keys are supported ... table2 = [['foo', 'bar', 'baz'], ... ['a', 1, True], ... ['b', 2, False], ... ['b', 3, True], ... ['b', 3, False]] >>> lkp = etl.lookupone(table2, ('foo', 'bar'), 'baz') >>> lkp[('a', 1)] True >>> lkp[('b', 2)] False >>> lkp[('b', 3)] True >>> # data can be loaded into an existing dictionary-like ... # object, including persistent dictionaries created via the ... # shelve module ... import shelve >>> lkp = shelve.open('example2.dat', flag='n') >>> lkp = etl.lookupone(table1, 'foo', 'bar', lkp) >>> lkp.close() >>> lkp = shelve.open('example2.dat', flag='r') >>> lkp['a'] 1 >>> lkp['b'] 2 N)r rr) rrrr"Ústrictrrrr#r$r%rrrÚ lookuponeos5 €r)c Cs¾|durtƒ}t|ƒ}zt|ƒ}Wn tyg}Ynwttt|ƒƒ}t||ƒ}t|ƒdks3Jdƒ‚t j |Ž}|D]"}||ƒ} t ||ƒ} | |vrW|| } |   | ¡| || <q:| g|| <q:|S)aÙ Load a dictionary with data from the given table, mapping to dicts. E.g.:: >>> import petl as etl >>> table1 = [['foo', 'bar'], ... ['a', 1], ... ['b', 2], ... ['b', 3]] >>> lkp = etl.dictlookup(table1, 'foo') >>> lkp['a'] [{'foo': 'a', 'bar': 1}] >>> lkp['b'] [{'foo': 'b', 'bar': 2}, {'foo': 'b', 'bar': 3}] >>> # compound keys are supported ... table2 = [['foo', 'bar', 'baz'], ... ['a', 1, True], ... ['b', 2, False], ... ['b', 3, True], ... ['b', 3, False]] >>> lkp = etl.dictlookup(table2, ('foo', 'bar')) >>> lkp[('a', 1)] [{'foo': 'a', 'bar': 1, 'baz': True}] >>> lkp[('b', 2)] [{'foo': 'b', 'bar': 2, 'baz': False}] >>> lkp[('b', 3)] [{'foo': 'b', 'bar': 3, 'baz': True}, {'foo': 'b', 'bar': 3, 'baz': False}] >>> # data can be loaded into an existing dictionary-like ... # object, including persistent dictionaries created via the ... # shelve module ... import shelve >>> lok = shelve.open('example3.dat', flag='n') >>> lok = etl.dictlookup(table1, 'foo', lok) >>> lok.close() >>> lup = shelve.open('example3.dat', flag='r') >>> lup['a'] [{'foo': 'a', 'bar': 1}] >>> lup['b'] [{'foo': 'b', 'bar': 2}, {'foo': 'b', 'bar': 3}] Nrr ) r r rrÚlistÚmaprrrrrr r!© rrr"rrÚfldsrrr#r$Úrecr&rrrÚ dictlookup¹s**  ÿ      r/c Cs´|durtƒ}t|ƒ}zt|ƒ}Wn tyg}Ynwttt|ƒƒ}t||ƒ}t|ƒdks3Jdƒ‚t j |Ž}|D]} || ƒ} |rJ| |vrJt | ƒ‚| |vrWt || ƒ} | || <q:|S)aZ Load a dictionary with data from the given table, mapping to dicts, assuming there is at most one row for each key. E.g.:: >>> import petl as etl >>> table1 = [['foo', 'bar'], ... ['a', 1], ... ['b', 2], ... ['b', 3]] >>> # if the specified key is not unique and strict=False (default), ... # the first value wins ... lkp = etl.dictlookupone(table1, 'foo') >>> lkp['a'] {'foo': 'a', 'bar': 1} >>> lkp['b'] {'foo': 'b', 'bar': 2} >>> # if the specified key is not unique and strict=True, will raise ... # DuplicateKeyError ... try: ... lkp = etl.dictlookupone(table1, 'foo', strict=True) ... except etl.errors.DuplicateKeyError as e: ... print(e) ... duplicate key: 'b' >>> # compound keys are supported ... table2 = [['foo', 'bar', 'baz'], ... ['a', 1, True], ... ['b', 2, False], ... ['b', 3, True], ... ['b', 3, False]] >>> lkp = etl.dictlookupone(table2, ('foo', 'bar')) >>> lkp[('a', 1)] {'foo': 'a', 'bar': 1, 'baz': True} >>> lkp[('b', 2)] {'foo': 'b', 'bar': 2, 'baz': False} >>> lkp[('b', 3)] {'foo': 'b', 'bar': 3, 'baz': True} >>> # data can be loaded into an existing dictionary-like ... # object, including persistent dictionaries created via the ... # shelve module ... import shelve >>> lkp = shelve.open('example4.dat', flag='n') >>> lkp = etl.dictlookupone(table1, 'foo', lkp) >>> lkp.close() >>> lkp = shelve.open('example4.dat', flag='r') >>> lkp['a'] {'foo': 'a', 'bar': 1} >>> lkp['b'] {'foo': 'b', 'bar': 2} Nrr ) r r rrr*r+rrrrrrr © rrr"r(rrr-rrr#r$ÚdrrrÚ dictlookuponeÿs*5  ÿ    €r2c Cs¾|durtƒ}t|ƒ}zt|ƒ}Wn tyg}Ynwttt|ƒƒ}t||ƒ}t|ƒdks3Jdƒ‚t j |Ž}|D]"}||ƒ} t ||ƒ} | |vrW|| } |   | ¡| || <q:| g|| <q:|S)zW Load a dictionary with data from the given table, mapping to record objects. Nrr ) r r rrr*r+rrrrrr r!r,rrrÚ recordlookupMs*  ÿ      r3c Cs´|durtƒ}t|ƒ}zt|ƒ}Wn tyg}Ynwttt|ƒƒ}t||ƒ}t|ƒdks3Jdƒ‚t j |Ž}|D]} || ƒ} |rJ| |vrJt | ƒ‚| |vrWt | |ƒ} | || <q:|S)z‹ Load a dictionary with data from the given table, mapping to record objects, assuming there is at most one row for each key. Nrr ) r r rrr*r+rrrrrrr r0rrrÚrecordlookuponeos*  ÿ    €r4)NN)NNF)N)NF)Ú __future__rrrrÚ petl.compatrÚ petl.errorsrÚpetl.util.baserrr r r rr'r)r/r2r3r4rrrrÚs$   F G C K