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add-license-header | add-license-headerA tool for automatically adding your license as a header in your source code.Template OptionsYou can use template markers to dynamically change your license.Template MarkerDefaultCLI Flag${start_year}Current Year--start-year${end_year}Current Year--end-year${author_name}Empty String--author-nameFor example:MIT License
Copyright (c) ${start_year} ${author_name}
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.What does it do?$catexample.py
print("Hello World")$add-license-header\--licenseMIT-LICENSE.template\--author'Arkin Modi'\--start-year2023\example.py
updatinglicenseinexample.py
$catexample.py# LICENSE HEADER MANAGED BY add-license-header## MIT License## Copyright (c) 2023 Arkin Modi## Permission is hereby granted, free of charge, to any person obtaining a copy# of this software and associated documentation files (the "Software"), to deal# in the Software without restriction, including without limitation the rights# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell# copies of the Software, and to permit persons to whom the Software is# furnished to do so, subject to the following conditions:## The above copyright notice and this permission notice shall be included in all# copies or substantial portions of the Software.## THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE# SOFTWARE.print("Hello World")Configuration FileInstead of always using the CLI flags, you can define them in a JSON file. CLI
flags will have higher priority than the configuration file. None of the fields
are required (exceptlicensewhich must be defined with in the configuration
file or using the CLI flag,--license).The default configuration file name is.add-license-header.jsonin the working
directory. A custom path can be specified with the--config-fileCLI flag.Here is the schema of the configuration:{"author_name":"name of author or organization","end_year":"end year (number or string)","license":"path to license file","start_year":"start year (number or string)"} |
add-list-AK-311 | No description available on PyPI. |
addlogo | Add logo to the imageLogo is added to the bottom right of the image.Installpip install -U add_logoUseimage_with_logo = add_logo(image, logo, factor)whereimageandlogoare numpy arrays andfactoris the targetlogo_height/image_height. |
addlyrics | Adds lyrics (via getlyrics) to mp3 fileUsageusage: addlyrics [-h] [-i INDEX] [--lang LANG] [--desc DESC] filename term
positional arguments:
filename Filename of mp3 file to add lyrics
term Search term, passed to getlyrics
optional arguments:
-h, --help show this help message and exit
-i INDEX, --index INDEX
Song index, passed to getlyrics
--lang LANG Three letter code from ISO 639-2. Defaults to 'eng'
--desc DESC Description of lyrics. Defaults to 'Lyrics from
azlyrics.com'InstallationViapip:pip3 install addlyricsAlternatively:Clone the repository,cd addlyricsRunpython3 setup.py installorpip3 install-e |
add-methods-and-properties-to-existing-object | Add methods and properties to an existing object$pipinstalladd-methods-and-properties-to-existing-objectfromadd_methods_and_properties_to_existing_objectimportAddMethodsAndPropertiesclassNewClass(AddMethodsAndProperties):#inherit from AddMethodsAndProperties to add the method add_methodsdef__init__(self):self.bubu=5def_delete_files(self,file):#some random methodsprint(f"File will be deleted:{file}")defdelete_files(self,file):self._delete_files(file)def_copy_files(self,file,dst):print(f"File will be copied:{file}Dest:{dst}")defcopy_files(self,file,dst):self._copy_files(file,dst)def_create_files(self,file,folder):print(f"File will be created:{file}{folder}")defcreate_files(self,file,folder):self._create_files(file,folder)defmethod_with_more_kwargs(self,file,folder,one_more):print(file,folder,one_more)returnselfnc=NewClass()dict_all_files={r"C:\Windows\notepad.exe_delete":{"function":"delete_files","args":(),"kwargs":{"file":r"C:\Windows\notepad.exe"},"this_args_first":True,},r"C:\Windows\notepad.exe_argsfirst":{"function":"delete_files","args":(),"kwargs":{"file":r"C:\Windows\notepad.exe"},"this_args_first":True,},r"C:\Windows\notepad.exe_copy":{"function":"copy_files","args":(),"kwargs":{"file":r"C:\Windows\notepad.exe","dst":r"C:\Windows\notepad555.exe",},"this_args_first":True,},r"C:\Windows\notepad.exe_create":{"function":"create_files","args":(),"kwargs":{"file":r"C:\Windows\notepad.exe","folder":"c:\\windows95"},"this_args_first":True,},r"C:\Windows\notepad.exe_upper":{"function":str.upper,"args":(r"C:\Windows\notepad.exe",),"kwargs":{},"this_args_first":True,},r"C:\Windows\notepad.exe_method_with_more_kwargs":{"function":"method_with_more_kwargs","args":(),"kwargs":{"file":r"C:\Windows\notepad.exe","folder":"c:\\windows95"},"this_args_first":True,},r"C:\Windows\notepad.exe_method_with_more_kwargs_as_args_first":{"function":"method_with_more_kwargs","args":(r"C:\Windows\notepad.exe","c:\\windows95"),"kwargs":{},"this_args_first":True,},r"C:\Windows\notepad.exe_method_with_more_kwargs_as_args_last":{"function":"method_with_more_kwargs","args":(r"C:\Windows\notepad.exe","c:\\windows95"),"kwargs":{},"this_args_first":False,},"this_is_a_list":[55,3,3,1,4,43],}nc.add_methods(dict_all_files)print(nc.C_Windows_notepad_exe_delete)print(nc.C_Windows_notepad_exe_delete(),end="\n\n")print(nc.C_Windows_notepad_exe_argsfirst)print(nc.C_Windows_notepad_exe_argsfirst(),end="\n\n")print(nc.C_Windows_notepad_exe_copy)print(nc.C_Windows_notepad_exe_copy(),end="\n\n")print(nc.C_Windows_notepad_exe_create)print(nc.C_Windows_notepad_exe_create(),end="\n\n")print(nc.C_Windows_notepad_exe_upper)print(nc.C_Windows_notepad_exe_upper(),end="\n\n")print(nc.C_Windows_notepad_exe_method_with_more_kwargs)print(nc.C_Windows_notepad_exe_method_with_more_kwargs(one_more="f:\\blaaaaaaaaaaaaaaaaaaaaaaaa").C_Windows_notepad_exe_method_with_more_kwargs(one_more="f:\\ASJVASDFASÇDFJASÇDJFÇASWFJASÇ").C_Windows_notepad_exe_method_with_more_kwargs(one_more="f:\\XXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"),end="\n\n",)print(nc.C_Windows_notepad_exe_method_with_more_kwargs_as_args_first)print(nc.C_Windows_notepad_exe_method_with_more_kwargs_as_args_first("f:\\blaaaaaaaaaaaaaaaaaaaaaaaa"),end="\n\n",)print(nc.C_Windows_notepad_exe_method_with_more_kwargs_as_args_first("f:\\blaaaaaaaaaaaaaaaaaaaaaaaa").C_Windows_notepad_exe_method_with_more_kwargs_as_args_first("f:\\ASJVASDFASÇDFJASÇDJFÇASWFJASÇ").C_Windows_notepad_exe_method_with_more_kwargs_as_args_first("f:\\XXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"),end="\n\n",)print(nc.C_Windows_notepad_exe_method_with_more_kwargs_as_args_last)print(nc.C_Windows_notepad_exe_method_with_more_kwargs_as_args_last("f:\\blaaaaaaaaaaaaaaaaaaaaaaaa").C_Windows_notepad_exe_method_with_more_kwargs_as_args_last("f:\\ASJVASDFASÇDFJASÇDJFÇASWFJASÇ").C_Windows_notepad_exe_method_with_more_kwargs_as_args_last("f:\\XXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"),end="\n\n",)print(nc.C_Windows_notepad_exe_method_with_more_kwargs_as_args_last("f:\\blaaaaaaaaaaaaaaaaaaaaaaaa").C_Windows_notepad_exe_method_with_more_kwargs_as_args_last("f:\\ASJVASDFASÇDFJASÇDJFÇASWFJASÇ").C_Windows_notepad_exe_method_with_more_kwargs_as_args_last("f:\\XXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"),end="\n\n",)print(nc.this_is_a_list)checkit=(nc.C_Windows_notepad_exe_method_with_more_kwargs_as_args_last("f:\\blaaaaaaaaaaaaaaaaaaaaaaaa").C_Windows_notepad_exe_method_with_more_kwargs_as_args_last("f:\\ASJVASDFASÇDFJASÇDJFÇASWFJASÇ").C_Windows_notepad_exe_method_with_more_kwargs_as_args_last("f:\\XXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"))print(f'nc is checkit? ->{ncischeckit}')#output:NewClass.delete_files(self,file='C:\\Windows\\notepad.exe')Filewillbedeleted:C:\Windows\notepad.exeNoneNewClass.delete_files(self,file='C:\\Windows\\notepad.exe')Filewillbedeleted:C:\Windows\notepad.exeNoneNewClass.copy_files(self,file='C:\\Windows\\notepad.exe',dst='C:\\Windows\\notepad555.exe')Filewillbecopied:C:\Windows\notepad.exeDest:C:\Windows\notepad555.exeNoneNewClass.create_files(self,file='C:\\Windows\\notepad.exe',folder='c:\\windows95')Filewillbecreated:C:\Windows\notepad.exec:\windows95NoneNewClass.upper(self,'C:\\Windows\\notepad.exe')C:\WINDOWS\NOTEPAD.EXENewClass.method_with_more_kwargs(self,file='C:\\Windows\\notepad.exe',folder='c:\\windows95')C:\Windows\notepad.exec:\windows95f:\blaaaaaaaaaaaaaaaaaaaaaaaaC:\Windows\notepad.exec:\windows95f:\ASJVASDFASÇDFJASÇDJFÇASWFJASÇC:\Windows\notepad.exec:\windows95f:\XXXXXXXXXXXXXXXXXXXXXXXXXXXXXX<__main__.NewClassobjectat0x0000000005F199A0>NewClass.method_with_more_kwargs(self,'C:\\Windows\\notepad.exe','c:\\windows95')C:\Windows\notepad.exec:\windows95f:\blaaaaaaaaaaaaaaaaaaaaaaaa<__main__.NewClassobjectat0x0000000005F199A0>C:\Windows\notepad.exec:\windows95f:\blaaaaaaaaaaaaaaaaaaaaaaaaC:\Windows\notepad.exec:\windows95f:\ASJVASDFASÇDFJASÇDJFÇASWFJASÇC:\Windows\notepad.exec:\windows95f:\XXXXXXXXXXXXXXXXXXXXXXXXXXXXXX<__main__.NewClassobjectat0x0000000005F199A0>NewClass.method_with_more_kwargs(self,'C:\\Windows\\notepad.exe','c:\\windows95')f:\blaaaaaaaaaaaaaaaaaaaaaaaaC:\Windows\notepad.exec:\windows95f:\ASJVASDFASÇDFJASÇDJFÇASWFJASÇC:\Windows\notepad.exec:\windows95f:\XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXC:\Windows\notepad.exec:\windows95<__main__.NewClassobjectat0x0000000005F199A0>f:\blaaaaaaaaaaaaaaaaaaaaaaaaC:\Windows\notepad.exec:\windows95f:\ASJVASDFASÇDFJASÇDJFÇASWFJASÇC:\Windows\notepad.exec:\windows95f:\XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXC:\Windows\notepad.exec:\windows95<__main__.NewClassobjectat0x0000000005F199A0>[55,3,3,1,4,43]f:\blaaaaaaaaaaaaaaaaaaaaaaaaC:\Windows\notepad.exec:\windows95f:\ASJVASDFASÇDFJASÇDJFÇASWFJASÇC:\Windows\notepad.exec:\windows95f:\XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXC:\Windows\notepad.exec:\windows95ncischeckit?->True |
add-module | No description available on PyPI. |
add_months | UNKNOWN |
addm-toolbox | This toolbox can be used to perform model fitting and to generate
simulations for the attentional drift-diffusion model (aDDM), as well as
for the classic version of the drift-diffusion model (DDM) without an
attentional component.PrerequisitesaDDM-Toolbox supports Python 2.7 (and Python 3.6 tentatively – please
report any bugs). The following libraries are required:deapfuturematplotlibnumpypandasscipyInstalling$ pip install addm_toolboxRunning testsTo make sure everything is working correctly after installation, try
(from a UNIX shell, not the Python interpreter):$ addm_toolbox_testsThis should take a while to finish, so maybe go get a cup of tea :)Getting startedTo get a feel for how the algorithm works, try:$ addm_demo --display-figuresYou can see all the arguments available for the demo using:$ addm_demo --helpHere is a list of useful scripts which can be similarly run from a UNIX
shell:addm_demoddm_pta_testaddm_pta_testaddm_pta_mleaddm_pta_mapaddm_simulate_true_distributionsaddm_basinhoppingaddm_genetic_algorithmddm_mlaaddm_mlaYou can also have a look directly at the code in the following modules:addm.py contains the aDDM implementation, with functions to generate
model simulations and obtain the likelihood for a given data trial.ddm.py is equivalent to addm.py but for the DDM.addm_pta_test.py generates an artificial data set for a given set
of aDDM parameters and attempts to recover these parameters through
maximum a posteriori estimation.ddm_pta_test.py is equivalent to addm_pta_test.py but for the
DDM.addm_pta_mle.py fits the aDDM to a data set by performing maximum
likelihood estimation.addm_pta_map.py performs model comparison for the aDDM by obtaining
a posterior distribution over a set of models.simulate_addm_true_distributions.py generates aDDM simulations
using empirical data for the fixations.Common issuesIf you get errors while using the toolbox under Python 3, try it with
Python 2.7.If you get a Python RuntimeError with the message “Python is not
installed as a framework.”, try creating the
file ~/.matplotlib/matplotlibrc and adding the following code:backend: TkAggAuthorsGabriela [email protected],goptavaresLicenseThis project is licensed under the GNU GENERAL PUBLIC LICENSE - see the
COPYING file for details.AcknowledgmentsThis toolbox was developed as part of a research project in theRangel
Neuroeconomics Labat the California
Institute of Technology. |
addmul | No description available on PyPI. |
add-mul-test | No description available on PyPI. |
addmultiple | No description available on PyPI. |
addn | No description available on PyPI. |
addnumber1 | long_description |
add_numbers | No description available on PyPI. |
add-numbers-test-lib | Failed to fetch description. HTTP Status Code: 404 |
add-numbers-yourself | No description available on PyPI. |
addnumcsy1234 | No description available on PyPI. |
addnumroohann | No description available on PyPI. |
addok | AddokSearch engine for address. Only address.Addok will index your address data and provide an HTTP API for full text search.It is extensible withplugins,
for example for geocoding CSV files.Used in production by France administration, with around 26 millions addresses.
In those servers, full France data is imported in about 15 min and it scales
to around 2000 searches per second.Check thedocumentationand ademowith French data.For discussions, please use thediscourse Geocommun forum. Discussions are mostly French, but English is very welcome.Powered by Python and Redis. |
addok-csv | Addok plugin add CSV geocoding endpointsInstallpip install addok-csvAPIWarning: this plugin will not work when runningaddok serve, you need either
gunicorn or uWSGI (seefalcon-multipart issue).This plugin adds the following endpoints:/search/csv/Batch geocode a csv file.Parametersdata: the CSV file to be processedcolumns(multiple): the columns, ordered, to be used for geocoding; if no
column is given, all columns will be usedencoding(optional): encoding of the file (you can also specify acharsetin the
file mimetype), such as 'utf-8' or 'iso-8859-1' (default to 'utf-8-sig')delimiter(optional): CSV delimiter (,or;); if not given, we try to
guesswith_bom: if true, and if the encoding if utf-8, the returned CSV will contain
a BOM (for Excel users…)latandlonparameters (optionals), like filters, can be used to
define columns names that contain latitude and longitude
values, for adding a preference center in the geocoding of each rowExampleshttp -f POST http://localhost:7878/search/csv/ columns='voie' columns='ville' data@path/to/file.csv
http -f POST http://localhost:7878/search/csv/ columns='rue' postcode='code postal' data@path/to/file.csv/reverse/csv/Batch reverse geocode a csv file.Parametersdata: the CSV file to be processed; must contain columnslatitude(orlat) andlongitude(orlonorlng)encoding(optional): encoding of the file (you can also specify acharsetin the
file mimetype), such as 'utf-8' or 'iso-8859-1' (default to 'utf-8-sig')delimiter(optional): CSV delimiter (,or;); if not given, we try to
guessAny filter can be passed askey=valuequerystring, wherekeyis the filter
name andvalueis the column name containing the filter value for each row.
For example, if there is a column "code_insee" and we want to use it for
"citycode" filtering, we would passcitycode=code_inseeas query string
parameter.ConfigCSV_ENCODING: default encoding to open CSV files (default: 'utf-8-sig')CSV_EXTRA_FIELDS: list of field names to be added to the results rows
(default: names of the registeredFIELDS) |
addok-fr | # Addok plugin for French support## Installationpip install addok-fr## Configuration- Add `phonemicize` into PROCESSORS_PYPATHS:PROCESSORS_PYPATHS = […,'addok_fr.phonemicize'] |
addok-france | Addok plugin for France specificsInstallationpip install addok-franceConfigurationAdd QUERY_PROCESSORS_PYPATHSQUERY_PROCESSORS_PYPATHS = [
…,
"addok_france.extract_address",
"addok_france.clean_query",
]Add PROCESSORS_PYPATHSPROCESSORS_PYPATHS = [
…,
"addok_france.glue_ordinal",
"addok_france.fold_ordinal",
"addok_france.flag_housenumber",
…,
]Replace defaultmake_labelsby France dedicated one:SEARCH_RESULT_PROCESSORS_PYPATHS = [
'addok_france.make_labels',
…,
] |
addok-getbyid | Addok-getbyidGet anaddokobject by id.Installationpip install addok-getbyidAPIGET /id/:idThe response is the geojson encoded feature.LicenseMIT |
addok-sqlite-store | # Addok SQlite store pluginStore your documents into a SQlite database to save Redis RAM usage.## Installpip install addok-sqlite-store## ConfigurationThe plugin will register itself when installed, by setting the correctDOCUMENT_STORE_PYPATH.You want to define the path where the SQLite database will be created, by
settingSQLITE_DB_PATHinto your local
[configuration](http://addok.readthedocs.io/en/latest/config/). |
addok-trigrams | Addok-trigramsAlternative indexation pattern for Addok, based on trigrams.Installationpip install addok-trigramsConfigurationIn your local configuration file:remove unwanted RESULTS_COLLECTORS_PYPATHS:from addok.config.default import RESULTS_COLLECTORS_PYPATHS
RESULTS_COLLECTORS_PYPATHS.remove('addok.helpers.collectors.extend_results_reducing_tokens')
RESULTS_COLLECTORS_PYPATHS.remove('addok.autocomplete.only_commons_but_geohash_try_autocomplete_collector')
RESULTS_COLLECTORS_PYPATHS.remove('addok.autocomplete.no_meaningful_but_common_try_autocomplete_collector')
RESULTS_COLLECTORS_PYPATHS.remove('addok.autocomplete.only_commons_try_autocomplete_collector')
RESULTS_COLLECTORS_PYPATHS.remove('addok.autocomplete.autocomplete_meaningful_collector')
RESULTS_COLLECTORS_PYPATHS.remove('addok.fuzzy.fuzzy_collector')remove allautocompleteandfuzzyRESULTS_COLLECTORS_PYPATHS, add new ones:RESULTS_COLLECTORS_PYPATHS += [
'addok_trigrams.extend_results_removing_numbers',
'addok_trigrams.extend_results_removing_one_whole_word',
'addok_trigrams.extend_results_removing_successive_trigrams',
]addtrigramizeto PROCESSORS_PYPATHS:from addok.config.default import PROCESSORS_PYPATHS
PROCESSORS_PYPATHS += [
'addok_trigrams.trigramize',
]remove pairs and autocomplete indexers fromINDEXERS_PYPATHS:from addok.config.default import INDEXERS_PYPATHS
INDEXERS_PYPATHS.remove('addok.pairs.PairsIndexer')
INDEXERS_PYPATHS.remove('addok.autocomplete.EdgeNgramIndexer')By default, digit only words are not turned into trigrams. To prevent this,
setTRIGRAM_SKIP_DIGIT=False.UsageUseaddok batchjust like with genuine addok for importing documents, but no
need for runningaddok ngrams, given they are already part of the index
strategy. |
addon | Add all numbers |
addonalok1210 | PACKAGE FOR ADDITION |
add-on-class | Add-On Class PackageThis package provides you with a module that allows you to easily define classes stacked on top of each other and add features to each other, creating a whole new class. You can see an example of this application below.fromadd_on_classimportAOCclassParent:def__init__(self):self.parrent_property=1defparent_functionality(self):return10classChild(Parent):def__init__(self):super().__init__()self.child_property=2self.parrent_property=67defchild_functionality(self):return20classFirstAddOn(AOC):def__post_init__(self):self.first_added_property=3deffirst_added_functionality(self):return30defchild_functionality(self):returnself.__core.child_functionality(self)*2classSecondAddOn(AOC):def__pre_init__(self,pre):self.pre=predef__post_init__(self,post):self.post=postself.child_property=12defchild_functionality(self):returnself.__core.child_functionality(self)*3added=SecondAddOn(FirstAddOn(Child))(pre=4,post=8)print(added.parrent_property)# >>> 67print(added.child_property)# >>> 12print(added.first_added_property)# >>> 3print(added.parent_functionality())# >>> 10print(added.child_functionality())# >>> 120print(added.first_added_functionality())# >>> 30print(issubclass(type(added),Parent))# >>> Trueprint(added.pre)# >>> 4print(added.post)# >>> 8The output of the AOC constructor is a class itself, so you need to get an instance from it again.Based on order of calling add-on classes and according to__pre_init__and__post_init__functions, overrides occur. Use this logic to customize what you need.Useself.__coreto access the inner class directly. It's helpful to call a core class function overridden by the add-on one (See the example above).Another example is here. Note the type ofE(D(B)). It isBCoveredByDCoveredByEand is a subclass ofB:fromadd_on_classimportAOCclassA:def__init__(self):passdefmain(self):return"(A.main->"+self.function()+"->A.main.end)"deffunction(self):return"(A.function->A.function.end)"classB(A):defmain(self):return"(B.main->"+super().main()+"->B.main.end)"deffunction(self):return"(B.function->B.function.end)"classD(AOC):def__post_init__(self):self.new_attr=2deffunction(self):return"(D.function->"+self.__core.function(self)+"->D.function.end)"classE(AOC):def__pre_init__(self):self.new_attr=3deffunction(self):return"(E.function->"+self.__core.function(self)+"->E.function.end)"e=E(D(B))()print(e.main())# >>> (B.main->(A.main->(E.function->(D.function->(B.function->B.function.end)->D.function.end)->E.function.end)->A.main.end)->B.main.end)print(e.new_attr)# >>> 2print(issubclass(type(e),B))# >>> Trueprint(E(D(B)).__name__)# >>> BCoveredByDCoveredByENOTE: We can not add AOC to a class that receives "*args" or "**kwargs" as initialization input.A class decorator (covering_around) is also available to limit the core class type. See the example below:fromadd_on_classimportAOC,covering_aroundclassA:def__init__(self):passclassB(A):passclassC:def__init__(self):pass@covering_around([A])classD(AOC):def__pre_init__(self):self.new_attr=3deffunction(self):return"function"a=D(A)()print(a.new_attr)print(a.function())b=D(B)()print(b.new_attr)print(b.function())c=D(C)()Installationpip install add-on-class |
addone | No description available on PyPI. |
add-one | Example PackageThis is a simple example package with a flag. This time with the correct path. Now with init |
addoneaddmat | Same as regular description |
addoneexample | This is an example library for testing, which just adds 1 to any number.Change Log0.0.1 (4/28/2021)First Release |
addonenishka | Example PackageThis is a simple example package that adds one to input number. |
addOneSample-bharadwaj | Example PackageThis is a simple example package. You can useGithub-flavored Markdownto write your content. |
addonethousend | Example PackageThis is a simple add one thousend program. |
addonfactory-splunk-conf-parser-lib | addonfactory_splunk_conf_parser_libThis repository provides a one-file library to parse Splunk-specific.conffiles.Currently, it supports:Read/write .conf files with commentsAdditional comment prefix such as *Support multiline end with \DevelopmentThis project usespoetry 1.5.1. |
addongen | a minecraft bedrock addon framework for python |
addonlist | UNKNOWN |
add-only-dictionary | Add Only DictionaryFeaturesCreate dictionaries that let you continue adding key/value pairs, but never change existing values or remove existing keys. If a value is a dictionary, that will also be updated to have the same behavior. If the value is a list, items can only be added on to the list, but never removed from any position.InstallationYou can installAdd Only DictionaryviapipfromPyPI:$pipinstalladd-only-dictionaryUsagefromadd_only_dictionaryimportAODictregular_dict:Dict={"a":1}ao_dict:AODict=AODict(regular_dict)ao_dict["b"]=2# works!ao_dict["a"]=3# Nothing happens...ao_dict["a"]==1# True, since the key already existed.CreditsThis project was generated from@cjolowicz'sHypermodern Python Cookiecuttertemplate. |
addonpayments-sdk-python | AddonPayments SDK Python is a library that allows integration with the SDK’s of AddonPayments in a easy and fast way.
There are two types of integration: HPP (Hosted Payment Page) and API.FeaturesHPPIntegrates in minutesMinimises the merchant’s PCI overheadsCustomisable, for a seamless checkout processAPIGives you full control of the payment processProvides access to a full suite of transaction management requestsSuitable for call centre integrationsQuick startFirst of all, you need to install AddonPayments SDK Python package:pip install addonpayments-sdk-pythonIn order to use the SDK it is necessary to have an account in Addon Payments, then it will be necessary to configure
the SDK with the values of your account. Create the settings.ini file in your project with the content that we provide
in the addonpayments/settings.ini.template file:; cp settings.ini.template your_project_folder/settings.ini
[settings]
DEBUG=True
MERCHANT_ID = yourmerchantid
SHARED_SECRET = yoursharedsecret
ADDONPAYMENTS_HPP_URL = https://hpp.sandbox.addonpayments.com/pay
ADDONPAYMENTS_API_URL = https://remote.sandbox.addonpayments.com/remoteUsageTake a look at the Django demo projectDocumentationVisit thedocumentationfor an in-depth look at AddonPayments SDK Python. |
addonpy | UNKNOWN |
addon.py | addon.pyAn API Wrapper for the addon.to API.Installationpip install addon.pyHow to useExamples can be found in the examples folder. The documentation can be foundhere |
addons-installer | No description available on PyPI. |
addon-tvg-karjakak | Add-On for Tree View Gui (TVG)Installationpip3 install -U addon-tvg-karjakak |
addonupdater | addonupdaterUpdate dependencies in Community add-ons.NB!: This package is intended only for maintainers of the community add-ons project.InstallRequire Python version 3.5.3+pipinstalladdonupdaterExampleaddonupdater--tokenAAAAAAAAAAAAAAAAAAAAA--addonsqlite-web--test
Startingupgradesequenceforsqlite-web
Checkingforapkuppdates
g++Allreadyhavethenewestversion6.4.0-r9
gccAllreadyhavethenewestversion6.4.0-r9
makeAllreadyhavethenewestversion4.2.1-r2
python3-devAllreadyhavethenewestversion3.6.6-r0
apache2-utilsAllreadyhavethenewestversion2.4.35-r0
nginxAllreadyhavethenewestversion1.14.2-r0
python3Allreadyhavethenewestversion3.6.6-r0
cythonAllreadyhavethenewestversion0.28.2-r0
Checkingforpipuppdates
flaskAllreadyhavethenewestversion1.0.2
sqlite-webAllreadyhavethenewestversion0.3.5
:arrow_up:Upgradespeeweetoversion3.8.0
Testwasenabled,skippingcommit
:arrow_up:Upgradesdatasettetoversion0.26
Testwasenabled,skippingcommitCLI optionsparamaliasdescription--token-TAn GitHub Access token withrepopermissions.--addon-AName of the add-on, this has to match the dir that contains theDockerfile.--repo-RName of the repo for the add-on, this is optional and defaults toaddon-ADDONNAME.--testNoneIf this flag is used commits will be omitted.--verboseNonePrint more stuff to the console.--apk_versionNoneTarget version of apk packages, like3.9.--skip_apkNoneSkip apk updates.--skip_customNoneSkip custom updates.--skip_pipNoneSkip pip updates.--skip_baseNoneSkip base image updates.--orgNoneSpecify GitHub org, defaults to 'hassio-addons'.-pull_request-PRCreate a PR instead of pushing directly to master. |
addorsub | No description available on PyPI. |
add-package | The codes have been tested on Python 3.6 + pytorch 1.1 + torchvision 0.3.0 (pytorch 1.3 seems also ok, but not test thoroughly)#Requirements:Center Computer:redis (ubuntu software, start using the command redis-server --protected-mode on)sshpass (python lib)Conter Computer & workers:multiprocess (python lib)redis (python lib)How to useStart the redis-server on the center computer (redis-server --protected-mode no)Start the init_compute.py script to start the compute platformStart the algorithm you would like to perform |
addpage | addpageis a package for adding page number to PDF file.$ addpage -h
usage: addpage [-h] [-o OUTFILE] [-n FONT_NAME] [-z FONT_SIZE] [-s START]
[-k SKIP] [-x MARGIN_X] [-y MARGIN_Y]
[-a {center,left,right}] [-f FORMAT]
infile
Add page number to PDF file.
positional arguments:
infile input PDF file
optional arguments:
-h, --help show this help message and exit
-o OUTFILE, --outfile OUTFILE
-n FONT_NAME, --font-name FONT_NAME
-z FONT_SIZE, --font-size FONT_SIZE
-s START, --start START
-k SKIP, --skip SKIP
-x MARGIN_X, --margin-x MARGIN_X
-y MARGIN_Y, --margin-y MARGIN_Y
-a {center,left,right}, --alignment {center,left,right}
-f FORMAT, --format FORMATRequirementsPython 3.6 laterFeaturesnothingSetup$ pip install addpageHistory0.0.1 (2018-9-23)first release |
add-parent-path | Usage# Just add path
add_parent_path(1)
# Append to syspath and delete when the exist of with statement.
with add_parent_path(1):
# Import modules in the parent path
passInstallationRequirementsCompatibilityLicenceAuthorsadd_parent_pathwas written byfx-kirin. |
add-pinyin-key | 说明安装pip install add_pinyin_keypythonsetup.pyinstall使用示例add_pinyin_keydemo.bibdemo_mod.bib% demo.bib
@article{_ct_2007,
author = {严汉民 and 黄岗},
date = {2007},
journaltitle = {医疗设备信息},
number = {12},
pages = {1-5},
title = {{{降低CT剂量的技术和方法探讨}}},
urldate = {2018-04-18},
volume = {22}
}%demo_mod.bib
@article{_ct_2007,
author = {严汉民 and 黄岗},
date = {2007},
journaltitle = {医疗设备信息},
key = {yan2han4min2 and huang2gang3},
number = {12},
pages = {1-5},
title = {{{降低CT剂量的技术和方法探讨}}},
urldate = {2018-04-18},
volume = {22}
}注意如果输入的bib文件有类似于month = jan的字符串，你需要使用--common-strings选项。add_pinyin_key--common-stringsdemo.bibdemo_mod.bib |
addpkg | No description available on PyPI. |
add-py | No description available on PyPI. |
add-pyproject | add-pyprojectTable of ContentsInstallationLicenseInstallationpip install add-pyprojectLicenseadd-pyprojectis distributed under the terms of theMITlicense. |
addr | Python Package Template📦 一个快速上传到PyPI的 Python Package 模版。上传到 PyPI 后可以使用pip install安装。1 使用方法点击本项目右上角的绿色按钮Use this template（使用此模板），输入名称和说明，完成创建；将项目克隆到本地，这里以本项目为例，实际操作时这里需要替换你自己的项目；gitclonehttps://github.com/Ailln/python-package-template.git--depth1修改配置，文件中有提示；cdyour_package_name# 1. 替换默认项目名称 package_name 为你的项目名称# Usage: bash scripts/set_package_name.sh os_name old_name new_name# os_name 支持的有 `mac` 和 `linux`# old_name 是 package_name# new_name 是你的项目名称bashscripts/set_package_name.shmacpackage_nameyour_package_name# 2. 将 `README.md` 修改为你的项目介绍，也就是你当前在读的这个文本。编写你的 Package 代码，并进行测试。# 在本地进行充分测试bashscripts/local_test.sh上传到 PyPi（需要注册），参考如何发布自己的包到 pypi；bashscripts/upload_pypi.sh更新到 Github。gitpush2 项目结构.
├── package_name # 项目名称
│ ├── shell # 在命令行中执行的代码
│ │ ├── __init__.py
│ │ └── usage.py
│ └── src # 静态资源
│ └── temp.txt
├── scripts
│ ├── set_package_name.sh # 批量替换默认的项目名称
│ ├── local_install.sh
│ ├── local_test.sh
│ └── upload_pypi.sh
├── README.md # 项目文档
├── requirements.txt # 包依赖
├── .gitignore # 忽略文件
├── MANIFEST.in # 要包含在 sdist 命令构建的分发中的文件列表。
├── LICENSE # 这里面的内容为本项目的 License，你需要手动替换它。
└── setup.py # 安装配置3 TODO增加 test 相关代码。4 许可5 参考Packaging Python Projects如何从模板创建仓库？如何发布自己的包到 pypi ？ |
addr2line | addr2lineinteract with addr2line commandInstallationpip install addr2lineTestpython -m unittest discover testsusagewith Addr2lineContext(Path("tests/source.out")) as c:
self.assertEqual(
c.get_function(0x1189),
"function3",
)
self.assertEqual(
c.get_function(0x11a8),
"main",
) |
addrcollector | A Python application for collecting email addresses from email messagesAboutaddrcollectorcollects email addresses from email messages. This is
similar to Thunderbird’s “Collected Addresses” feature and
corresponding functionality in other software. In the case of
addrcollector, however, email messages are read from standard input,
or manually on the command line, and the email address database can be
queried by keyword.It is possible for addrcollector to be integrated with a mail delivery
system like Procmail or Maildrop to collect addresses from all
messages, or with mail clients like Mutt or Alpine to collect
addresses selectively.Dates and display names are also collected. If an address is seen more
than once, then (1) the date is updated and (2) the display name is
updated if the new one is longer than the old one.For example, to add an address manually (the display name is optional):[email protected]"Jon Smith"[email protected] import addresses from a message passed on standard input:$addrcollectorimport<mymail.msgTo search for addresses using keywords (multiple keywords may be
given and are ORed):$addrcollectorsearchjonsven2020-07-03 [email protected] Jon Smith
2020-07-03 [email protected] from PyPIaddrcollector is published on PyPI and can be installed with pip.Install the addrcollector package.$pip3installaddrcollectorThis should provide a~/.local/bin/addrcollectorscript that you
can execute.If that path is included in yourPATHenvironment variable, you
can run theaddrcollectorcommand without typing the entire
path., To set up this, if it hasn’t been done already, add the
following code in your~/.bash_profile(it may be~/.profilefor a shell other than Bash):if[-d"$HOME/.local/bin"];thenPATH="$HOME/.local/bin:$PATH"fiRunning from repositoryIf you have cloned the repository, you can run addrcollector from it
directly.Install Poetry:$pip3installpoetryWith the addrcollector repository root as your current directory,
use Poetry to install the dependencies:$poetryinstallNow that the dependencies have been installed, use Poetry to run
addrcollector:$poetryrunaddrcollectorCopyright and LicenseCopyright 2020 Owen T. Heisler. Creative Commons Zero v1.0 Universal
(CC0 1.0).This program is distributed in the hope that it will be useful, but
WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.This source code may be used, modified, and/or redistributed according
to the terms of the Creative Commons Zero 1.0 Universal (CC0 1.0)
license. You should have received a copy of this license along with
this program (seeLICENSE). If not, see
<https://creativecommons.org/publicdomain/zero/1.0/>. |
addr-detector | Address Detector==============================How to detect if a user query might be an address and requires to launch a map answer.Project Modules------------The project implements 3 classifiers, using an a la scikit template.The first classifier is a simple scorer classifier, based on the parsing result of the address parser libpostal (https://github.com/openvenues/libpostal)According to how the parser manage to work, and which fields are parsed, we make a score and decide if an address or not.The second classifier is based on the FastText classifier trained on address data. The fasttext makes an embedding of the differents address it sees and therefore when a new address is submitted if it's in a close spaceto what have been learned.The classifier is pre-trained, and the Fasttext zip model is store within the package.The third classifier is a voting classifier combining the results of the two previous classifiers.Project Dependencies------------####Installation of Postal:Before you install `Postal` , make sure you have the following prerequisites:```sudo apt-get install curl autoconf automake libtool pkg-config```Then to install the C library:```git clone https://github.com/openvenues/libpostalcd libpostal./bootstrap.sh./configure --datadir=[...some dir with a few GB of space...]makesudo make install# On Linux it's probably a good idea to runsudo ldconfig```#### Installation of FastTextIn order to build `fastText`, use the following:```$ git clone https://github.com/facebookresearch/fastText.git$ cd fastText$ make```=======History=======0.1.0 (2017-10-25)------------------* First release on PyPI. |
add-registrant-zoom | zoom_registrant is a Python package that allows you to interact with the Zoom API.It provides functions for managing Zoom meetings and registrants.Project descriptionAdd Zoom RegistrantA simple package to add Zoom Registrant from csv also add email using api.How to installpip install add-registrant-zoomImportfrom myzoom.setting import configurefrom myzoom.AddZoomRegistrant import add_registrantsfrom myzoom.AddZoomRegistrant import add_registrant_apiInitialize the PackageWe can either setup via the environment or by passing the credentials directly to the plugin.client_id for the ClientIdclient_secret for the ClientSecretaccount_id for the AccountIdAnd then instantiate as shown belowsettings = configure(client_id, client_secret, account_id)And then Enter meeting Idmeeting_id = input("Enter meeting id: ")NOTEYou don't need to explicitely pass client_id, client_secret, account_id.API to add registrant into meetingjson_data = {"first_name": '', "last_name": '', "email": ''}add_registrant_api(settings,meeting_id,json_data)OREnter path of csv filecsv_path = input("Enter csv file path: ")add_registrants(configure, meeting_id, csv_path)zoom.csv format must as below.eg.Id FirstName LastName Email1 ABC PQR [email protected] |
addremoveoptions | UNKNOWN |
address | address is an address parsing library, taking the guesswork out of
using addresses in your applications. We use it as part of our apartment
search and apartment spider applications.Installationpip install addressExampleFirst, we create an AddressParser. AddressParser allows us to feed in
lists of cities, streets, and address suffixes. Then we call
parse_address on our address string, which returns an Address instance
with all the attributes filled out. From there, we can print parts of
the address, change them, validate them, create a database model to
store them, or anything else.from address import AddressParser, Address
ap = AddressParser()
address = ap.parse_address('123 West Mifflin Street, Madison, WI, 53703')
print "Address is: {0} {1} {2} {3}".format(address.house_number, address.street_prefix, address.street, address.street_suffix)
> Address is: 123 W. Mifflin St.AddressParserAddressParser(self, suffixes=None, cities=None, streets=None)suffixes, cities, and streets all accept lists as arguments. If you
leave them as none, they will read default files from the package,
namely suffixes.csv, cities.csv, and streets.csv. Streets is
intentionally blank.You can provide lists of acceptable suffixes, cities, and streets to
lower your false positives. If you know all the addresses you are
processing are in a small area, you can provide a list of the cities in
the area and should get more accurate results. If you are only doing one
city, you could provide that single city in a list, and a list of all
streets in that city.AddressAddresses get returned by AddressParser.parser_address(). They have the
following attributes:house_numberThe number on a house. This is required for all valid addresses. E.g.123W. Mifflin St.street_prefixThe direction before the street name. Always represented as one or two
letters followed by a period. Not required. E.g. 123W.Mifflin St.streetThe name of the street. Potentially multiple words. This is required for
a valid address. E.g. 123 W.MifflinSt.street_suffixThe ending of a street. This will always be the USPS abbreviation
followed by a period. Not required, but highly recommended. E.g. 123 W.
MifflinSt.apartmentApartment number or unit style or any number of things signifying a
specific part of an address. Not required. E.g. 123 W. Mifflin St.Apt
10buidingSometimes addresses are grouped into buildings, or are more commonly
known as by building names. Not required, and often in parathenses. E.g.
123 W. Mifflin St. Apt 10(The Estates)cityThe city part of the address, preferably following a comma. E.g. 123 W.
Mifflin St.,Madison, WI 53703stateThe state of the address, preferably following the city and a comma.
Always two capitalized letters. E.g. 123 W. Mifflin St., Madison,WI53703zipThe 5 digit zip code of the address, preferably following the state. 9
digit zips not yet supported. E.g. 123 W. Mifflin St., Madison, WI53703full_address()Returns a human readable version of the address for display. Follows the
same style rules as the above attributes. Example return: (The Estates)
123 W. Mifflin St. Apt 10, Madison, WI 53703TodoAdd verification of an address through Google Maps API, given an API
key.Allow custom validation conditions in AddressParser for what counts
as a correct address or not.Add exceptions for incorrect addresses instead of silent failing and
letting user validate.GitHubFile support requests and obtain the source fromhttps://github.com/SwoopSearch/pyaddressAuthorsJosh GachnangRob JauquetLicense and CopyrightCopyright (c) 2013 Swoop Search LLC.This library is released under the New BSD License. |
address2img | # address2imgA python module to convert addresses to map images using open source map data sources and mapnik.## Installationaddress2img works on any system with mapnik 2.x or newer.Mapnik must be installed before proceeding with install.To test for mapnik, run```bashmapnik-config -v # Should return a version 2.x or newer```Use pip to install address2img```bashsudo python -m pip install address2img```## Basic UsageTo use address2img, the configuration file and mapnik xml file must be configured.The configuration file is [config.ini](config.ini) by default. To configure the mapnik xml file, see [here](https://github.com/mapnik/mapnik/wiki/XMLConfigReference).After the config and xml files are configured, usage is as simple as importing the module and calling the function.```python# importing map_maker file from address2imgfrom address2img import map_maker# defining addresses for which render maps, must be a listaddresses = ['Piazza del Duomo, 56126 Pisa PI, Italy','1600 Pennsylvania Ave NW, Washington, DC 20500',]# instantiating Map_Maker class with addressesworker = map_maker.Map_Maker(addresses)# calling make_map method of the Map_Maker instanceworker.make_map()``` |
addressable | addressableis a silly little utility that allows you to access
items inside of a list using one or more indices as keys. You pretty
much get to pretend pretend that a list is a souped-up dictionary.artists = [{
'id': '0488',
'name': 'Lambchop',
'members': ['Kurt Wagner'],
}, {
'id': '9924',
'name': 'Dire Straits',
'members': ['Mark Knopfler'],
}]
# keys are matched against one or more indices
artists = List(artists, indices=('id', 'name'))
print artists['0488'] == artists['Lambchop']
# fuzzy matching
artists = List(artists, indices=('id', 'title'), fuzzy=True)
print artists['strait']
# extract the value, not the metadata
artists = List(artists, indices=('id', 'title'), facet='title')
print artists['9924'] == 'Dire Straits'So why would you want to do any of this? You probably don’t.addressablecan be useful for certain DSL or library code where you
want to give the end users some freedom to code things their way, when
you need to be able to very easily refer to certain things that are
weirdly named or when there’s multiple common ways of referring to
something and you want the flexibility to mix-and-match. |
addressable-sql-queries | What is this library ?This library allows to make a SQL script (or possibly any script) addressable.
Once preprocessed or parsed, you can get any chunk of it (which could be a single query for instance) with its line number, key, or index of the chunk.Example & How to use:With a target SQL script : (toggle)raw_script.sql:CREATETEMPORARYVIEWfibonacci(a,index_)ASWITHRECURSIVEinner_fibo(b,c,index_)AS(SELECT0,1,0UNIONSELECTc,c+b,index_+1FROMinner_fibo)SELECTb,index_FROMinner_fibo;SELECT*FROMfibonacciLIMIT1OFFSET3;SELECT*FROMfibonacciLIMIT1OFFSET4;SELECT*FROMfibonacciLIMIT1OFFSET5;SELECT*FROMfibonacciLIMIT1OFFSET10;CREATETEMPORARYTABLEtest_table(ainteger)STRICT;We modify the above script by adding the following delimiter :-- % keywhere key is the string that will reference a particular chunk of the script that we want to separate and make addressable.
Note the prepended space. The delimiter is modifiable.
For instance :raw_script.sql:-- % fibonacci_view_creationCREATETEMPORARYVIEWfibonacci(a,index_)ASWITHRECURSIVEinner_fibo(b,c,index_)AS(SELECT0,1,0UNIONSELECTc,c+b,index_+1FROMinner_fibo)SELECTb,index_FROMinner_fibo;-- % contiguous_view_testsSELECT*FROMfibonacciLIMIT1OFFSET3;SELECT*FROMfibonacciLIMIT1OFFSET4;SELECT*FROMfibonacciLIMIT1OFFSET5;-- % testing_10nth_value_of_viewSELECT*FROMfibonacciLIMIT1OFFSET10;CREATETEMPORARYTABLEtest_table(ainteger)STRICT;Then we preprocess the script :importaddressable_sql_querieswith(open("raw_script.sql")asinput_file,open("preprocessed_script.py","w")asoutput_file):output_file.write(addressable_sql_queries.preprocess_to_str(input_file.read()))This step can also be done with :python-maddressable_sql_queriespath/to/raw_script.sql-opath/to/preprocessed_script.pyAs all keys in the example above are not only valid but usable python ids, you can then access chunks of this script like this :frompreprocessed_scriptimport*print(contiguous_view_tests)Which will outputs :-- % contiguous_view_tests
SELECT * FROM fibonacci LIMIT 1 OFFSET 3;
SELECT * FROM fibonacci LIMIT 1 OFFSET 4;
SELECT * FROM fibonacci LIMIT 1 OFFSET 5;Even when keys are invalid ids, you can access the chunks of the script by these means :frompreprocessed_scriptimportqueriesassql_queriesprint(sql_queries[0])# This will print the chunk before the first delimiter, which is nothing in this case : "\n".print(sql_queries[None])# Another way to do the same thing. None is always the first key.print(sql_queries["fibonacci_view_creation"])"""This will print :-- % fibonacci_view_creationCREATE TEMPORARY VIEW fibonacci (a, index_) ASWITH RECURSIVE inner_fibo(b, c, index_) AS (SELECT 0, 1, 0UNIONSELECT c, c + b, index_ + 1FROM inner_fibo)SELECT b, index_ FROM inner_fibo;"""print(sql_queries[1])# This will print the same thing as above (the second chunk).print(sql_queries.having_line(4))# This will print the chunk containing the line 4 (counting from 1), and thus does the same thing as above.Parser mode example :Alternatively, parser mode can be used :fromaddressable_sql_queriesimportQueryq=Query.fromFile("raw_script.sql")print(q[3])"""This will print :-- % testing_10nth_value_of_viewSELECT * FROM fibonacci LIMIT 1 OFFSET 10;CREATE TEMPORARY TABLE test_table (a integer) STRICT;"""Query object can also be built directly from a string.Note : in the case where the first line is a delimiter, thus making the first and second chunk shares the first line (starting at 1), the having_line function will return the second, non empty chunk. |
addressbook | WHY BUILD ANOTHER ADDRESS BOOK?Why build another address book?
I created this address book because I was frustrated with
current address book solutions which try to integrate
everything. The current software-industry ( or projects )
trend towards pushing users personal information into the
cloud; is alarming, not so-much about where the data is
stored but how badly data is leaked, hacked, and compelled
( by law enforcement ) for data access. Additionally,
cloud services have let me down by corrupting data, failing
to secure data, and worst of all; deleting data when
I needed it most.Perhaps, more simply-put, I wanted an address book that
no-one may control but me, is simple, and cloudless.After all clouds mean rain and I’ve had enough of it.
So, get this address book and take control of your
data.RELEASE NOTESAdded sorting to grids for main dashboard and relationships. Table headers sort by clicked column header.
Added postal code and status to address tab on dashboard to match address entry window.
Added settings for default window sizes so users can adjust, if needed, for their operating system. Change defaults by editing settings.py file.
Allow users to change the default search LIMIT on rows returned for search. Change defaults by editing settings.py file.INSTALL DIRECTIONS
Unfortunately I have not figured out how to get setup tools to cooperate with entry_pointsTherefore:
FIRST: Backup your database if you already installed a prior version.pip3.4 install addressbook
Then launch addressbook/main.py from the site-packages folder
Example: (Current directory) site-packages/addressbook python3.4 main.pyIf you have an existing database will not be overwritten, but again, just back it up first in case I made a mistake. |
addressbook-ccsss | 주소록 프로그램주소록 프로그램입니다. |
address-book-for-IVT2023 | No description available on PyPI. |
address_book_lansry | UNKNOWN |
addresscleaner | # Betwen the Bars address cleanerThis is a simple library to clean and normalize textual addresses. It is
biased toward the sorts of addresses people in prison are given.## Example usagefrom addresscleaner import parse_address, format_address>>> parsed = parse_address("""John Dough
... #1234567
... 7819 228th St.
... Raiford, FL 32026-1120""")
>>> print parsed
{'name': 'John Dough', 'address1': '#1234567', 'address2': '7819 228th St.', 'city': 'Raiford', 'state': 'FL', 'zip': '32026-1120'}>>> format_address(parsed)
u'John Dough\n#1234567\n7819 228th St.\nRaiford, FL 32026-1120'An exception of typeaddresscleaner.AddressExceptionis raised if the
parser is unable to figure out something about the address. The exception’s
message tries to explain as much as possible where it went wrong. |
address-corrector | readme |
addresser | Addresser parses and normalizes street addresses and intersections. It is a port of the Node package,parse-address, which in turn is a port of the PERL package,Geo::StreetAddress::US.From theGeo::StreetAddress::USdescription:Geo::StreetAddress::US is a regex-based street address and street intersection parser for the United States. Its
basic goal is to be as forgiving as possible when parsing user-provided address strings. Geo::StreetAddress::US knows
about directional prefixes and suffixes, fractional building numbers, building units, grid-based addresses (such as
those used in parts of Utah), 5 and 9 digit ZIP codes, and all of the official USPS abbreviations for street types
and state names…InstallAddresser can be installed from pip:$ pip install addresserUsagefromaddresserimportparse_locationparse_location('1005 N Gravenstein Highway Sebastopol CA 95472')Result{'number':'1005','prefix':'N','street':'Gravenstein','type':'Hwy','city':'Sebastopol','state':'CA','zip':'95472'} |
address_extractor | A script to extract US-style street addresses from a text file$ address_extractor
1600 Pennsylvania Ave NW, Washington, DC 20500 ^D
1 lines in input
,1600 Pennsylvania Ave NW,Washington DC 20500
$ address_extractor -o output.csv input.csv
4361 lines in input
*snip*
11 lines unable to be parsed
$ ls
output.csvaddress_extractortakes text or a text file containing address-like data, one address per line, and parses it into a uniform format with theusaddresspackage.InstallationThis package is available from PyPi viapip:pip install address_extractorThis will install the module as well as the command-line script asaddress_extractor.Command-line Usageaddress_extractor [-h] [-o OUTPUT] [--remove-post-zip] [input]
positional arguments:
input the input file. Defaults to stdin.
optional arguments:
-h, --help show this help message and exit
-o OUTPUT, --output OUTPUT
the output file. Defaults to stdout.
--remove-post-zip, -r
when scanning the input lines, remove everything after
a sequence of 5 digits followed by a comma. The
parsing library used by this script chokes on
addresses containing this kind of information, often a
county name.Lines that could not be parsed will be printed toSTDERR. They can be saved to a file with standardbashredirection techniques:$ address_extractor -o good_addresses.csv has_some_bad_addresses.txt 2> bad_addresses.txtUsage as a Moduleaddress_extractorcan be used as a Python module:>>> import address_extractor
>>> address_extractor.main(input=input_file_object, output=output_file_object, remove_post_zip=a_bool)There are some small issues with this implementation:If usingsys.stdinorsys.stdoutfor input or output, respectively, the file objects will still be closed. This presents issues trying to use these in the future.Errored lines are still printed tosys.stderrwhich may not be expected.Versions and StabilityThis package is uploaded as a 0.1.0 release. There are no tests and little error checking–it originated as a quick-‘n-dirty script and I decided to release it as a package to gain familiarity with that process.Issues, comments, and pull requests are welcome at the GitHub page! |
addressformat | 地址解析模块 |
address-formatter | Python module to parse and render postal addresses respecting country standardRequirementsPackage requirements are handled using pip. To install them do` pip install-rrequirements.txt ` |
addressformatting | International Address formatterThis is a address formatter that can format addresses in multiple formats that are common
in different countries.For formatting the addresses theworldwide.ymlfromOpenCageData address-formatting repositoryis used to format the address according to customs in the country that is been encoded.API documentationThe complete project contains actually only one class:AddressFormatterPublicly accessible method prototypes are:def__init__(self,config=None):passdefformat(self,address,country=None):passdefone_line(self,address,country=None):pass__init__Initialize the address formatterconfig: (optional) override default config file to use for the address formatter, defaults to config file included in this packageformatFormat an address in the default layout used in the specified country. Return value may contain line breaks.address: Dictionary that contains the address parts, see below for recognized keyscountry: Country code of the formatting template to useRecognized keys inaddress:attentionhouseroadhouse_numberpostcodecitytownvillagecountystatecountrysuburbcity_districtstate_districtstate_codeneighbourhoodone_lineWorks the same asformatbut returns a single line of text. |
address-hammer | No description available on PyPI. |
addresshunt | DescriptionThe addresshunt package gives you painless access to the addresshunt API’s.
It performs requests against our API’s forAutocomplete addressMatching addressAddress validationSplit addressForward geocodingReverse geocodingTimezoneZone management (API only)For further details, please visit:homepageRequirementsaddresshunt-py is tested against Python 3.6, 3.7, 3.8 and 3.9, and PyPy3.6 and PyPy3.7.InstallationTo install from PyPI, simply use pip:pip install addresshuntUsageExamplesimportaddresshuntautocomplete_address="11 NICHOLSON STREET"match_address="NICHOLSON STREET"forward_geocode_address="MELBOURNE MUSEUM, 11 NICHOLSON STREET, CARLTON, VIC, 3053"reverse_geocode_address_latitude="-37.803165"reverse_geocode_address_longitude="144.971802"split_address="MELBOURNE MUSEUM, 11 NICHOLSON STREET, CARLTON, VIC, 3053"timezone_address="MELBOURNE MUSEUM, 11 NICHOLSON STREET, CARLTON, VIC, 3053"validate_address="MELBOURNE MUSEUM, 11 NICHOLSON STREET, CARLTON, VIC, 3053"client=addresshunt.Client(api_key='')# Specify your personal API keyautocomplete=client.autocomplete(autocomplete_address)print("autocomplete:\n"+str(autocomplete)+str('\n'))match=client.match(match_address)print("match:\n"+str(match)+str('\n'))forward_geocode=client.forward_geocode(forward_geocode_address)print("forward_geocode:\n"+str(forward_geocode)+str('\n'))reverse_geocode=client.reverse_geocode(reverse_geocode_address_latitude,reverse_geocode_address_longitude)print("reverse_geocode:\n"+str(reverse_geocode)+str('\n'))split=client.split(split_address)print("split:\n"+str(split)+str('\n'))timezone=client.timezone(timezone_address)print("timezone:\n"+str(timezone)+str('\n'))validate=client.validate(validate_address)print("validate:\n"+str(validate)+str('\n'))For convenience, all request performing module methods are wrapped inside theclientclass.Dry runAlthough errors in query creation should be handled quite decently, you can do a dry run to print the request and its parameters:importaddresshuntautocomplete_address="11 NICHOLSON STREET"client=addresshunt.Client(api_key='')# Specify your personal API keyaddress_list=client.autocomplete(autocomplete_address,dry_run='true')SupportFor issues/bugs/enhancement suggestions, please usehttps://github.com/AddressHunt/addresshunt-py/issues. |
addressify | Addressify Python Client========================.. image:: https://travis-ci.org/snowball-one/addressify.svg:target: https://travis-ci.org/snowball-one/addressifyThis is a simply Python client for the `addressify.com.au`_ API.*"Addressify is a cloud based web API that allows web site, web application anddesktop application developers to easily implement free address verification,validation, checking, parsing and autocomplete for Australia in theirapplications."*.. _addressify.com.au: http://www.addressify.com.auInstallation------------Since the Python addressify client has not yet been released to pypi, you willneed to install it from git. This can still be done using pip::pip install git+https://github.com/snowball-one/addressify.gitUsage Quickstart----------------The Addressify Python client currently covers all the available api calls of`addressify.com.au`_. e.g.:.. code-block:: Pythonfrom addressify import Clientclient = Client(your_api_key)results = client.auto_complete('109/175 Sturt Street, SOUTH')API Calls Available-------------------client.auto_complete++++++++++++++++++++Gets a list of addresses that begin with the given term.Arguments:term (Required)The start of an address.state (Optional)The state to search for addresses in. ('NSW', 'ACT', 'VIC', 'QLD', 'SA','WA', 'NT', 'TAS')postcode (Optional)The postcode to search for addresses in.max_results (Optional)The maximum number of results to return (minumum: 1, maximum: 20,default: 10).Example Response::["1 GEORGE ST, TAHMOOR NSW 2573","1 GEORGE ST, TELARAH NSW 2320","1 GEORGE ST, TEMORA NSW 2666","1 GEORGE ST, TENTERFIELD NSW 2372","1 GEORGE ST, THE ROCKS NSW 2000"]client.address_line_auto_complete+++++++++++++++++++++++++++++++++Gets a list of address lines that begin with the given term.Arguments:term (Required)The start of an address line.state (Optional)The state to search for addresses in. ('NSW', 'ACT', 'VIC', 'QLD', 'SA','WA', 'NT', 'TAS')postcode (Optional)The postcode to search for addresses in.max_results (Optional)The maximum number of results to return (minumum: 1, maximum: 20,default: 10).Example Response::["1 GEORDIE ST","1 GEORGANN ST","1 GEORGE AVE","1 GEORGE CL","1 GEORGE CRES"]client.suburb_auto_complete++++++++++++++++++++++++++++Gets a list of suburbs that begin with the given term.Arguments:term (Required)The start of a suburb namestate (Optional)The state to search for addresses in. ('NSW', 'ACT', 'VIC', 'QLD', 'SA','WA', 'NT', 'TAS')postcode (Optional)The postcode to search for addresses in.max_results (Optional)The maximum number of results to return (minumum: 1, maximum: 20,default: 10).Example Response::["SUFFOLK PARK","SUGARLOAF","SUMMER HILL","SUMMER HILL CREEK","SUMMER ISLAND"]client.suburb_state_postcode_auto_complete++++++++++++++++++++++++++++++++++++++++++Gets a list of suburbs and postcodes where the suburb begins with the giventerm.Arguments:term (Required)The start of a suburb name.state (Optional)The state to search for addresses in. ('NSW', 'ACT', 'VIC', 'QLD', 'SA','WA', 'NT', 'TAS')postcode (Optional)The postcode to search for addresses in.max_results (Optional)The maximum number of results to return (minumum: 1, maximum: 20,default: 10).Example Response::["SUMMER HILL, NSW 2130","SUMMER HILL, NSW 2421","SUMMER HILL CREEK, NSW 2800","SUMMER ISLAND, NSW 2440","SUMMERHILL, TAS 7250"]client.suburbs_for_postcode+++++++++++++++++++++++++++Gets a list of suburbs for the given postcode.Arguments:postcode (Required)The postcode.Example Response::["BARANGAROO, NSW 2000","DAWES POINT, NSW 2000","HAYMARKET, NSW 2000","MILLERS POINT, NSW 2000","SYDNEY, NSW 2000","SYDNEY SOUTH, NSW 2000","THE ROCKS, NSW 2000"]client.state_for_postcode+++++++++++++++++++++++++Gets the state in which the given postcode is located.Arguments:postcode (Required)The postcode.Example Response::"NSW"client.parse_address++++++++++++++++++++Parses the given address into it's individual address fields.Arguments:address_line (Required)The address to parse.Example Response::addressify.client.Address(number="680",street="GEORGE",street_type="ST",suburb="SYDNEY",street_suffix=None,state="NSW",street_line="680 GEORGE ST",unit_type=Noneunit_number=None,postcode="2000")client.get_similar++++++++++++++++++Gets a list of valid addresses that are similar to the given term, can be usedto match invalid addresses to valid addresses.Arguments:address_line (Required)The address to find similar addresses formax_results (Optional)The maximum number of results to return (minumum: 1, maximum: 10,default: 10).Example Response::["1 GEORGE ST, SYDNEY NSW 2000"]client.validate+++++++++++++++Checks whether the given address is valid. Please note that validation is onlyperformed on the street, suburb, state and postcode. Street and unit numbersare not checked for validity.Argumentsaddress_line (Required)The address to validate.Example Response::trueclient.daily_call_count+++++++++++++++++++++++Gets the current daily API call count for your account. This counter will resetat midnight AEST. When this counter reaches the daily API call limit for youraccount type all other Addressify API calls will fail until the counter resets.Will return -1 if the api_key does not exist.Example Response::1000 |
addresslib3 | *******addresslib3*******This is a port of just address spec parsing/validating,for those of us who have made the jump to python3.In a form suitable for inclusion as a submodule. |
address-lookup | This package allows you to lookup partial addresses using various online services, returning the address in a standardized form.Supported servicesHERE API (API key required)Soon-to-be-supported servicesGoogle Maps APIObtaining an API keyHERE API keyCreate a HERE developer accounthere. Create a new project, and obtain a REST token. You can use this token with the Address Lookup library.UsageHERE API usagefromaddress_lookup.clientsimportAddressLookupHereClientAPI_KEY="YOUR_API_KEY"here_client=AddressLookupHereClient(API_KEY)result=here_client.lookup_address("White House, USA")print(result.asdict()) |
address-magic | # Table of Contents# Address magicAddress magic is a wraper around [postal](https://github.com/openvenues/pypostal).example:from address_magic import Address
address = Address(“The Book Club 100-106 Leonard St, Shoreditch, London, Greater London, EC2A 4RH, United Kingdom”)
print(address.road)
print(address.country)
print(address.postcode) |
address-name-system | Address Name System (ANS) for NarunoANS is a decentralized system that maps blockchain addresses to dynamic IPs, making it easy to access servers with changing IP addresses. With ANS, you can access your server by using your unique blockchain address instead of constantly searching for its changing IP address.FeaturesDecentralized systemSecure communication between nodesFast and easy to useMaps blockchain addresses to dynamic IPsUses encryption to protect sensitive informationInstallationYou can install ANS by pip3:pip3 install address_name_systemUsage*If you want to use address_name_system you must to use Naruno. For now please checkout theBaklava Testnet.Getting address of client and server:narunocli -pwServerFor accessing your dynamic IPs over blockchain you should create a address_name_system and giving trusted user addresses.fromaddress_name_systemimportansmy_ans_server=ans("MyNarunoPass")my_ans_server.set_encrypt_key("mystrongencrypt_key")my_ans_server.add_user("client_address")my_ans_server.run()also you can use in command line:ans --password MyNarunoPass --encrypt_key "mystrongencrypt_key" --trusted_users ["client_address"] runClientTo use ANS, you can call the ans.ip function with your blockchain address as the parameter:fromaddress_name_systemimportansmy_ans_client=ans("MyNarunoPass")ip_address=my_ans_client.ip("server_address","mystrongencrypt_key")print(ip_address)my_ans_client.close()also you can use in command line:ans --password "MyNarunoPass" ip "server_address" "mystrongencrypt_key"This will return the dynamic IP address associated with your blockchain address.ContributingContributions to ANS are welcome! If you have any suggestions or find a bug, please open an issue on the GitHub repository. If you want to contribute code, please fork the repository and create a pull request.LicenseANS is released under the MPL-2.0 License. |
address-ner | readme |
address-net | No description available on PyPI. |
address-parse | No description available on PyPI. |
addressparser | addressparser中文地址提取工具，支持中国三级区划地址（省、市、区）提取和级联映射，支持地址目的地热力图绘制。适配python2和python3。Feature地址提取["徐汇区虹漕路461号58号楼5楼", "福建泉州市洛江区万安塘西工业区"]
↓ 转换
|省 |市 |区 |地名 |
|上海市|上海市|徐汇区|虹漕路461号58号楼5楼 |
|福建省|泉州市|洛江区|万安塘西工业区 |注：“地名”列代表去除了省市区之后的具体地名数据集：中国行政区划地名数据源：爬取自国家统计局，中华人民共和国民政局全国行政区划查询平台数据文件存储在：addressparser/resources/pca.csv，数据为2021年统计用区划代码和城乡划分代码（截止时间：2021-10-31，发布时间：2021-12-30）Demohttp://42.193.145.218/product/address_extraction/Installpip install addressparserorgit clone https://github.com/shibing624/addressparser.git
cd addressparser
python3 setup.py installUsage省市区提取示例base_demo.pylocation_str=["徐汇区虹漕路461号58号楼5楼","泉州市洛江区万安塘西工业区","朝阳区北苑华贸城"]importaddressparserdf=addressparser.transform(location_str)print(df)output:省 市 区 地名
0 上海市 上海市 徐汇区 虹漕路461号58号楼5楼
1 福建省 泉州市 洛江区 万安塘西工业区
2 北京市 北京市 朝阳区 北苑华贸城程序的此处输入location_str可以是任意的可迭代类型，如list，tuple，set，pandas的Series类型等;输出的df是一个Pandas的DataFrame类型变量，DataFrame可以非常轻易地转化为csv或者excel文件，Pandas的官方文档：http://pandas.pydata.org/pandas-docs/version/0.20/dsintro.html#dataframe带位置索引的省市县提取示例pos_sensitive_demo.pylocation_str=["徐汇区虹漕路461号58号楼5楼","泉州市洛江区万安塘西工业区","朝阳区北苑华贸城"]importaddressparserdf=addressparser.transform(location_str,pos_sensitive=True)print(df)output:省 市 区 地名 省_pos 市_pos 区_pos
0 上海市 上海市 徐汇区 虹漕路461号58号楼5楼 -1 -1 0
1 福建省 泉州市 洛江区 万安塘西工业区 -1 0 3
2 北京市 北京市 朝阳区 北苑华贸城 -1 -1 0切词模式的省市区提取默认采用全文匹配模式，不进行分词，直接全文匹配，这样速度慢，准确率高。示例enable_cut_demo.pylocation_str=["浙江省杭州市下城区青云街40号3楼"]importaddressparserdf=addressparser.transform(location_str)print(df)output:省 市 区 地名
0 浙江省 杭州市 下城区 青云街40号3楼可以先通过jieba分词，之后做省市区提取及映射，所以我们引入了切词模式，速度很快，使用方法如下:location_str=["徐汇区虹漕路461号58号楼5楼","泉州市洛江区万安塘西工业区","朝阳区北苑华贸城"]importaddressparserdf=addressparser.transform(location_str,cut=True)print(df)output:省 市 区 地名
0 上海市 上海市 徐汇区 虹漕路461号58号楼5楼
1 福建省 泉州市 洛江区 万安塘西工业区
2 北京市 北京市 朝阳区 北苑华贸城但可能会出错，如下所示，这种错误的结果是因为jieba本身就将词给分错了：location_str=["浙江省杭州市下城区青云街40号3楼"]importaddressparserdf=addressparser.transform(location_str,cut=True)print(df)output:省 市 区 地名
0 浙江省 杭州市 城区 下城区青云街40号3楼默认情况下transform方法的cut参数为False，即采用全文匹配的方式，这种方式准确率高，但是速度可能会有慢一点；
如果追求速度而不追求准确率的话，建议将cut设为True，使用切词模式。地址经纬度、省市县级联关系查询示例find_place_demo.py## 查询经纬度信息fromaddressparserimportlatlnglatlng[('北京市','北京市','朝阳区')]#输出('39.95895316640668', '116.52169489108084')## 查询含有"鼓楼区"的全部地址fromaddressparserimportarea_maparea_map.get_relational_addrs('鼓楼区')#[('江苏省', '南京市', '鼓楼区'), ('江苏省', '徐州市', '鼓楼区'), ('福建省', '福州市', '鼓楼区'), ('河南省', '开封市', '鼓楼区')]#### 注: city_map可以用来查询含有某个市的全部地址, province_map可以用来查询含有某个省的全部地址## 查询含有"江苏省", "鼓楼区"的全部地址fromaddressparserimportprovince_area_mapprovince_area_map.get_relational_addrs(('江苏省','鼓楼区'))# [('江苏省', '南京市', '鼓楼区'), ('江苏省', '徐州市', '鼓楼区')]绘制echarts热力图使用echarts的热力图绘图函数之前需要先用如下命令安装它的依赖（为了减少本模块的体积，所以这些依赖不会被自动安装）：pip install pyecharts==0.5.11
pip install echarts-countries-pypkg
pip install pyecharts-snapshot使用本仓库提供的一万多条地址数据tests/addr.csv测试。示例draw_demo.py#读取数据importpandasaspdorigin=pd.read_csv("tests/addr.csv")#转换importaddressparseraddr_df=addressparser.transform(origin["原始地址"])#输出processed=pd.concat([origin,addr_df],axis=1)processed.to_csv("processed.csv",index=False,encoding="utf-8")fromaddressparserimportdrawerdrawer.echarts_draw(processed,"echarts.html")output:1) processed.csv：1万多地址的省市县提取结果
2）echarts.html：echarts热力图浏览器打开echarts.html后：绘制分类信息图样本分类绘制函数，通过额外传入一个样本的分类信息，能够在地图上以不同的颜色画出属于不同分类的样本散点图，以下代码以“省”作为类别信息绘制分类散点图（可以看到，属于不同省的样本被以不同的颜色标记了出来，这里以“省”作为分类标准只是举个例子，实际应用中可以选取更加有实际意义的分类指标）：示例draw_demo.py，接上面示例代码：fromaddressparserimportdrawerdrawer.echarts_cate_draw(processed,processed["省"],"echarts_cate.html")浏览器打开输出的echarts_cate.html后：Command line usage命令行模式支持批量提取地址的省市区信息：示例cmd_demo.pypython3 -m addressparser address_input.csv -o out.csv
usage: python3 -m addressparser [-h] -o OUTPUT [-c] input
@description:
positional arguments:
input the input file path, file encode need utf-8.
optional arguments:
-h, --help show this help message and exit
-o OUTPUT, --output OUTPUT
the output file path.
-c, --cut use cut mode.输入文件：address_input.csv；输出文件：out.csv，省市县地址以\t间隔，-c表示使用切词Todobug修复，吉林省、广西省部分地址和上海浦东新区等三级区划地址匹配错误增加定期从民政局官网，统计局官网爬取最新省市县镇村划分的功能，延后，原因是2018年后官网未更新解决路名被误识别为省市名的问题，eg"天津空港经济区环河北路80号空港商务园"添加省市区提取后的级联校验逻辑大批量地址数据，准召率效果评估补充香港、澳门、台湾三级区划地址信息ContactIssue(建议)：邮件我：xuming:[email protected]微信我：
加我微信号：xuming624, 备注：个人名称-公司-NLP进NLP交流群。Citation如果你在研究中使用了addressparser，请按如下格式引用：APA:Xu, M. Addressparser: Chinese address parser toolkit (Version 0.2.4) [Computer software]. https://github.com/shibing624/addressparserBibTeX:@software{Xu_Addressparser_Chinese_address,
author ={Xu, Ming},
title ={{Addressparser: Chinese address parser toolkit}},
url ={https://github.com/shibing624/addressparser},
version ={0.2.4}}License授权协议为The Apache License 2.0，可免费用做商业用途。请在产品说明中附加addressparser的链接和授权协议。Contribute项目代码还很粗糙，如果大家对代码有所改进，欢迎提交回本项目，在提交之前，注意以下两点：在tests添加相应的单元测试使用python pytest来运行所有单元测试，确保所有单测都是通过的之后即可提交PR。Referencechinese_province_city_area_mappersmartParsePro |
address-parser | Yet another python address parser for US postal addressesBasic usage:fromaddress_parserimportParserparser=Parser()adr=parser.parse(line)Theadrobject is a nested object with address parts as properties.returnTopBunch(number=Bunch(type='P',number=int(self.number)ifself.numberelse-1,tnumber=str(self.number),end_number=self.multinumber,fraction=self.fraction,suite=self.suite,is_block=self.is_block),road=Bunch(type='P',name=self.street_name,direction=self.street_directionifself.street_directionelse'',suffix=self.street_typeifself.street_typeelse''),locality=Bunch(type='P',city=self.city,state=self.state,zip=self.zip),hash=self.hash,text=str(self))Then, you can access properties on the object. The top level properties are:number: The house numbernumber.number. The number as an integer, or -1 if there is no house numbernumber.tnumber: The number as textnumber.end_number: The final number in a number ragenumber.fraction: The fractional part of the house numbernumber.suite: A suite or unit number.road: The streetroad.name: The bare street nameroad.direction. A cardinal direction, N, S, E, W, NE, NW, etc.road.suffix. The road type, sich as St, Ave, Pl.locality: City, state, ziplocality.citylocality.statelocality.ziptext: Holds the whole address as text.You can also access everything as dicts. From the top level,adr.dictwill return all parsed components as a dict, and each of the top level bunches can also be acess as dicts, such asadr.road.dict |
addressparser-x | addressparser本项目借鉴addressparser, 并做微调中文地址提取工具，支持中国三级区划地址（省、市、区）提取和级联映射，支持地址目的地热力图绘制。适配python2和python3。Feature地址提取["徐汇区虹漕路461号58号楼5楼", "福建泉州市洛江区万安塘西工业区"]
↓ 转换
|省 |市 |区 |地名 |
|上海市|上海市|徐汇区|虹漕路461号58号楼5楼 |
|福建省|泉州市|洛江区|万安塘西工业区 |注：“地名”列代表去除了省市区之后的具体地名数据集：中国行政区划地名数据源：爬取自国家统计局，中华人民共和国民政局全国行政区划查询平台数据文件存储在：addressparser/resources/pca.csv，数据为2021年统计用区划代码和城乡划分代码（截止时间：2021-10-31，发布时间：2021-12-30）Demohttp://42.193.145.218/product/address_extraction/Installpip install addressparserorgit clone https://github.com/shibing624/addressparser.git
cd addressparser
python3 setup.py installUsage省市区提取示例base_demo.pylocation_str=["徐汇区虹漕路461号58号楼5楼","泉州市洛江区万安塘西工业区","朝阳区北苑华贸城"]importaddressparserdf=addressparser.transform(location_str)print(df)output:省 市 区 地名
0 上海市 上海市 徐汇区 虹漕路461号58号楼5楼
1 福建省 泉州市 洛江区 万安塘西工业区
2 北京市 北京市 朝阳区 北苑华贸城程序的此处输入location_str可以是任意的可迭代类型，如list，tuple，set，pandas的Series类型等;输出的df是一个Pandas的DataFrame类型变量，DataFrame可以非常轻易地转化为csv或者excel文件，Pandas的官方文档：http://pandas.pydata.org/pandas-docs/version/0.20/dsintro.html#dataframe带位置索引的省市县提取示例pos_sensitive_demo.pylocation_str=["徐汇区虹漕路461号58号楼5楼","泉州市洛江区万安塘西工业区","朝阳区北苑华贸城"]importaddressparserdf=addressparser.transform(location_str,pos_sensitive=True)print(df)output:省 市 区 地名 省_pos 市_pos 区_pos
0 上海市 上海市 徐汇区 虹漕路461号58号楼5楼 -1 -1 0
1 福建省 泉州市 洛江区 万安塘西工业区 -1 0 3
2 北京市 北京市 朝阳区 北苑华贸城 -1 -1 0切词模式的省市区提取默认采用全文匹配模式，不进行分词，直接全文匹配，这样速度慢，准确率高。示例enable_cut_demo.pylocation_str=["浙江省杭州市下城区青云街40号3楼"]importaddressparserdf=addressparser.transform(location_str)print(df)output:省 市 区 地名
0 浙江省 杭州市 下城区 青云街40号3楼可以先通过jieba分词，之后做省市区提取及映射，所以我们引入了切词模式，速度很快，使用方法如下:location_str=["徐汇区虹漕路461号58号楼5楼","泉州市洛江区万安塘西工业区","朝阳区北苑华贸城"]importaddressparserdf=addressparser.transform(location_str,cut=True)print(df)output:省 市 区 地名
0 上海市 上海市 徐汇区 虹漕路461号58号楼5楼
1 福建省 泉州市 洛江区 万安塘西工业区
2 北京市 北京市 朝阳区 北苑华贸城但可能会出错，如下所示，这种错误的结果是因为jieba本身就将词给分错了：location_str=["浙江省杭州市下城区青云街40号3楼"]importaddressparserdf=addressparser.transform(location_str,cut=True)print(df)output:省 市 区 地名
0 浙江省 杭州市 城区 下城区青云街40号3楼默认情况下transform方法的cut参数为False，即采用全文匹配的方式，这种方式准确率高，但是速度可能会有慢一点；
如果追求速度而不追求准确率的话，建议将cut设为True，使用切词模式。地址经纬度、省市县级联关系查询示例find_place_demo.py## 查询经纬度信息fromaddressparserimportlatlnglatlng[('北京市','北京市','朝阳区')]#输出('39.95895316640668', '116.52169489108084')## 查询含有"鼓楼区"的全部地址fromaddressparserimportarea_maparea_map.get_relational_addrs('鼓楼区')#[('江苏省', '南京市', '鼓楼区'), ('江苏省', '徐州市', '鼓楼区'), ('福建省', '福州市', '鼓楼区'), ('河南省', '开封市', '鼓楼区')]#### 注: city_map可以用来查询含有某个市的全部地址, province_map可以用来查询含有某个省的全部地址## 查询含有"江苏省", "鼓楼区"的全部地址fromaddressparserimportprovince_area_mapprovince_area_map.get_relational_addrs(('江苏省','鼓楼区'))# [('江苏省', '南京市', '鼓楼区'), ('江苏省', '徐州市', '鼓楼区')]绘制echarts热力图使用echarts的热力图绘图函数之前需要先用如下命令安装它的依赖（为了减少本模块的体积，所以这些依赖不会被自动安装）：pip install pyecharts==0.5.11
pip install echarts-countries-pypkg
pip install pyecharts-snapshot使用本仓库提供的一万多条地址数据tests/addr.csv测试。示例draw_demo.py#读取数据importpandasaspdorigin=pd.read_csv("tests/addr.csv")#转换importaddressparseraddr_df=addressparser.transform(origin["原始地址"])#输出processed=pd.concat([origin,addr_df],axis=1)processed.to_csv("processed.csv",index=False,encoding="utf-8")fromaddressparserimportdrawerdrawer.echarts_draw(processed,"echarts.html")output:1) processed.csv：1万多地址的省市县提取结果
2）echarts.html：echarts热力图浏览器打开echarts.html后：绘制分类信息图样本分类绘制函数，通过额外传入一个样本的分类信息，能够在地图上以不同的颜色画出属于不同分类的样本散点图，以下代码以“省”作为类别信息绘制分类散点图（可以看到，属于不同省的样本被以不同的颜色标记了出来，这里以“省”作为分类标准只是举个例子，实际应用中可以选取更加有实际意义的分类指标）：示例draw_demo.py，接上面示例代码：fromaddressparserimportdrawerdrawer.echarts_cate_draw(processed,processed["省"],"echarts_cate.html")浏览器打开输出的echarts_cate.html后：Command line usage命令行模式支持批量提取地址的省市区信息：示例cmd_demo.pypython3 -m addressparser address_input.csv -o out.csv
usage: python3 -m addressparser [-h] -o OUTPUT [-c] input
@description:
positional arguments:
input the input file path, file encode need utf-8.
optional arguments:
-h, --help show this help message and exit
-o OUTPUT, --output OUTPUT
the output file path.
-c, --cut use cut mode.输入文件：address_input.csv；输出文件：out.csv，省市县地址以\t间隔，-c表示使用切词Todobug修复，吉林省、广西省部分地址和上海浦东新区等三级区划地址匹配错误增加定期从民政局官网，统计局官网爬取最新省市县镇村划分的功能，延后，原因是2018年后官网未更新解决路名被误识别为省市名的问题，eg"天津空港经济区环河北路80号空港商务园"添加省市区提取后的级联校验逻辑大批量地址数据，准召率效果评估补充香港、澳门、台湾三级区划地址信息ContactIssue(建议)：邮件我：xuming:[email protected]微信我：
加我微信号：xuming624, 备注：个人名称-公司-NLP进NLP交流群。Citation如果你在研究中使用了addressparser，请按如下格式引用：APA:Xu, M. Addressparser: Chinese address parser toolkit (Version 0.2.4) [Computer software]. https://github.com/shibing624/addressparserBibTeX:@software{Xu_Addressparser_Chinese_address,
author ={Xu, Ming},
title ={{Addressparser: Chinese address parser toolkit}},
url ={https://github.com/shibing624/addressparser},
version ={0.2.4}}License授权协议为The Apache License 2.0，可免费用做商业用途。请在产品说明中附加addressparser的链接和授权协议。Contribute项目代码还很粗糙，如果大家对代码有所改进，欢迎提交回本项目，在提交之前，注意以下两点：在tests添加相应的单元测试使用python -m pytest来运行所有单元测试，确保所有单测都是通过的之后即可提交PR。Referencechinese_province_city_area_mappersmartParsePro |
address-parsing-tool | readme |
address-ping-system | Address Ping System (APS) for NarunoAddress Ping System (APS) is a tool designed to check the online status of servers associated with blockchain addresses in Naruno. With APS, you can ensure that the servers you want to communicate with are online and reachable before sending any messages or making any transactions.FeaturesDecentralized systemSecure communication between nodesFast and easy to useChecks online status of servers associated with blockchain addressesInstallationYou can install APS by pip3:pip3 install address_ping_systemUsage*If you want to use address_ping_system you must to use Naruno. For now please checkout theBaklava Testnet.Getting address of client and server:narunocli -pwServerFor a server to be pinged by APS, it needs to have a corresponding APS entry with trusted user addresses set up.fromaddress_ping_systemimportapsmy_aps_server=aps("MyNarunoPass")my_aps_server.add_user("client_address")my_aps_server.run()also you can use in command line:aps --password MyNarunoPass --trusted_users ["client_address"] runClientTo use APS, you can call the aps.ping function with your blockchain address and the server's blockchain address as parameters:fromaddress_ping_systemimportapsmy_aps_client=aps("MyNarunoPass")result=my_aps_client.ping("server_address")print(result)my_aps_client.close()also you can use in command line:aps --password MyNarunoPass ping "server_address"This will return a boolean value indicating whether the server associated with the provided blockchain address is online and reachable.ContributingContributions to APS are welcome! If you have any suggestions or find a bug, please open an issue on the GitHub repository. If you want to contribute code, please fork the repository and create a pull request.LicenseAPS is released under the MPL-2.0 License. |
addressrec | 地址解析识别python版本👉JavaScript版本项目基于JioNLP 地址解析来进行地址识别地址库：2020年国家统计局行政区划基于结巴分词提供的分词以及语义化分析进行姓名识别基于Levenshtein字符串相似度算法来进行详细地址过滤依赖下载python支持版本：>=3.8pip3installaddressrec使用直接运行importaddressrec
print(addressrec.run('王志超029-68216000新疆维吾尔自治区乌鲁木齐市沙依巴克区西虹东路463号',True,False))# addressrec(text, town_village, town_village)# "text":"王志超029-68216000新疆维吾尔自治区乌鲁木齐市沙依巴克区西虹东路463号",# "town_village": True, //可不传默认True 指定参数town_village(bool)，可获取乡镇、村、社区两级详细地名# "change2new": False //可不传默认True 指定参数change2new(bool)可自动将旧地址转换为新地址返回结果：{"city":"乌鲁木齐市","county":"沙依巴克区","detail":"西虹东路463号","name":"王志超","phone":"029-68216000","province":"新疆维吾尔自治区","town":"","village":""}封装为接口调用：# pip3 install flaskfromflaskimportFlask,request,jsonifyapp=Flask(__name__)@app.route('/smart_address',methods=['POST'])defhandle_smart_address():data=request.get_json()text=data.get('text','')town_village=data.get('town_village',True)change2new=data.get('change2new',False)result=smart_address(text,town_village,change2new)ifresult:returnjsonify(result)else:returnjsonify({"error":"Failed to process the request"}),500if__name__=='__main__':app.run(host='0.0.0.0',port=3000)#URL: `http://127.0.0.1:3000/smart_address`#METHOD: 'POST'#BODY:#{# "text":"王志超029-68216000新疆维吾尔自治区乌鲁木齐市沙依巴克区西虹东路463号",# "town_village": true, //可不传默认true 指定参数town_village(bool)，可获取乡镇、村、社区两级详细地名# "change2new": false //可不传默认false 指定参数change2new(bool)可自动将旧地址转换为新地址#}识别结果测试广东省珠海市香洲区盘山路28号幸福茶庄,陈景勇，13593464918识别结果：{'city':'珠海市','county':'香洲区','detail':'盘山路28号幸福茶庄,，','name':'陈景勇','phone':'13593464918','province':'广东省','town':'','village':''}-----------------
马云，陕西省西安市雁塔区丈八沟街道高新四路高新大都荟13593464918识别结果：{'city':'西安市','county':'雁塔区','detail':'高新四路高新大都荟','name':'马云','phone':' 13593464918','province':'陕西省','town':'丈八沟街道','village':''}-----------------
陕西省西安市雁塔区丈八沟街道高新四路高新大都荟710061刘国良13593464918识别结果：{'city':'西安市','county':'雁塔区','detail':'高新四路高新大都荟710061','name':'刘国良','phone':' 13593464918','province':'陕西省','town':'丈八沟街道','village':''}-----------------
西安市雁塔区丈八沟街道高新四路高新大都荟710061刘国良13593464918识别结果：{'city':'西安市','county':'雁塔区','detail':'高新四路高新大都荟710061','name':'刘国良','phone':' 13593464918','province':'陕西省','town':'丈八沟街道','village':''}-----------------
雁塔区丈八沟街道高新四路高新大都荟710061刘国良13593464918识别结果：{'city':'西安市','county':'雁塔区','detail':'高新四路高新大都荟710061','name':'刘国良','phone':' 13593464918','province':'陕西省','town':'丈八沟街道','village':''}-----------------
收货人:李节霁手机号码:15180231234所在地区:浙江省金华市婺城区西关街道详细地址:金磐路上坞街识别结果：{'city':'金华市','county':'婺城区','detail':'详细地址: 金磐路上坞街','name':'李节','phone':' 15180231234','province':'浙江省','town':'西关街道','village':''}-----------------
收货人:马云手机号码:150-3569-6956详细地址:河北省石家庄市新华区中华北大街68号鹿城商务中心6号楼1413室识别结果：{'city':'石家庄市','county':'新华区','detail':'中华北大街68号鹿城商务中心6号楼1413室','name':'马云','phone':' 150-3569-6956','phone1':'150-3569-6956','province':'河北省','town':'','village':''}-----------------LICENSE：Apache LicenseIDE:致谢JetBrains为本项目提供免费license支持联系我，欢迎交流qq交流群 |
address-search-google | Search Google AddressUsageGoogle Search API with caching for repeated search.Example Codefromsearch_addrimportSearchAddressGoogleAPIsearch_lib=SearchAddressGoogleAPI(key="YOUR_GOOGLE_SERVER_KEY")search_lib.search_google("569KA/104 Shen Nagar, Alambagh, Lucknow, Uttar Pradesh, 226005") |
address-so | No description available on PyPI. |
address-templeter | address_templeterБиблиотека предназначена для поиска, смысловому разделению и чистки адресных строк.Пример использованияМетод parse возвращает массив с метками для каждого токена:<<< address_templeter.parse("г. Судак Солнечная 9 а")
>>> [('г', 'PlacePretext'), ('Судак', 'Place'), ('Солнечная', 'Street'), ('9', 'HouseNumber'), ('а', 'HouseNumber')]Метод clean возвращает строку без знаков препинания и лишних пробелов. Параметр prefix указывает возвращать ли значения не являющиеся наименованиями. Параметры: name_building указывает возвращать ли наименование объекта (если оно имеется):address:str - строка с адрессомhouse:bool - возвращать номер дома (например 21-Б), наименования объекта, и его префикс (магазин, парк, прочее)По умолчанию False;index:bool - возвращать почтовый индекс. По умолчанию False.place_pretext:bool возвразать тип места (город, село). По умолчанию False;region_pretext:bool возвразать тип региона (область, регион). Также, расшифровываться аббревиатуры и сокращения. По умолчанию False;address_pretext:bool возвразать тип улицы (проспект, бульвар). Также, расшифровываться аббревиатуры и сокращения. По умолчанию False;<<< address_templeter.clean("Ясниноватский район, возле белого магазина, Донецкая область, улица Садовая, 26а", prefix=False, house=True)
>>> Ясниноватский Садовая 26аУстановкаpip install address-templeterФормирования дата сета и обучениеПо умолчанию, библиотека уже содержит модель для использования необходимых методов.Для формирования своей уникальной модели, необходимо:Сформировать xml файл для обучения можно выполнив checked_to_xml.ipynb (необходим jupyter notebook).Выполнить следующие команды для создания файла модели:cd/path/to/Address_Templeter
pipinstallparserator
parseratortraintraining/dataset.xmladdress_templeter# По окончание обучения получится файл можели learned_settings.crfsuiteПереустановить библиотеку address_templeter |
address-to-line | address_to_lineTranslate return addresses into source locations using thereadelfandaddr2lineutilities from theGNU Binutilspackage.RequirementsThis package depends on thereadelfandaddr2lineutilities from theGNU Binutilspackage.UsageConverting return addresses captured from within some process requires a copy of that process'/proc/[pid]/mapsfile.Command line:python3 -m address_to_line <proc_map_file> <addresses>whereproc_map_fileis a copy of a process'/proc/[pid]/mapsfile andaddressesis a text file containing 1 (hexaecimal) return address per line.Code:fromaddress_to_lineimportresolve_source_locationsproc_map_file="memory_map.txt"# The relevant /proc/[pid]/maps fileaddresses_file="addresses.txt"# Contains 1 (hexadecimal) return address per linewithopen(addresses_file,"r")asf:addresses=[int(line,base=16)forlineinf.readlines()]# A list of named tuples of address, function, source file and linesource_locations=resolve_source_locations("memory_map.txt",addresses) |
addressValidator | addressValidatorValidate urban and rural addresses in ColombiaExplore the docs»Report Bug·Request FeatureTable of ContentsAbout The ProjectDocumentationGetting StartedInstallationUsagefunctionsaddress_validatoraddress_validator_dianaddress_validator_fileaddress_validator_file_dianRoadmapContributingLicenseAbout The Projectthe project was developed through the definition of Mealy machines, regular expressions, regular grammars, Automata, for the validation of all addresses currently valid in Colombia.the standardization ofurban addresses of the ministry of educationwas used as a guideline.DocumentationGetting StartedInstallationpipinstalladdressValidator
or
py-mpipinstalladdressValidatorlatest stable versionaddressValidator==1.2.1UsageExamplefromaddressValidatorimportaddress_validatoraddress="Calle 3BC #10-2 Barrio San Juan Apartamento 201"ifaddress_validator(address):print(address+" direccion valida")else:print(address+" direccion invalida")For more examples, please refer to theExamples packagesFunctionswe can use 4 functions to validate both urban and rural addressesaddress_validatoraddress_validator function receives as a parameter a mandatory string which will be evaluated and will return a boolean if valid or not.fromaddressValidatorimportaddress_validator# address_validator(str) -> booladdress=address_validator("Calle 13B #10-3")print(address)//#Trueif the address is not valid it will return FalsefromaddressValidatorimportaddress_validator# address_validator(str) -> booladdress=address_validator("Calle 13sur 13-121B")print(address)//#Falseaddress_validator_dianfucntion address_validator_dian returns the address validation according todian nomenclaturefromaddressValidatorimportaddress_validator_dian# address_validator_dian(str) -> booladdress=address_validator_dian("Cl 13 B 10 3")print(address)//#Trueif the address is not valid it will return FalsefromaddressValidatorimportaddress_validator_dian# address_validator_dian(str) -> booladdress=address_validator_dian("Cl 13 sur 13 121 B")print(address)//#Falseaddress_validator_fileaddress_validator_file function receives a text file, does not return any value, this function creates a text file with the respective validations.fromaddressValidatorimportaddress_validator_file# address_validator_file(file) -> Nonewithopen("address.txt")asfile_object:address_validator_file(file_object)# create output.txthere we can see that we read a file calledaddress.txtthat we find in the examples folder this function will return the validations of all the strings as we can see in theoutput.txtfile.All this for urban and rural addressesaddress_validator_file_dianThe function address_validator_file_dian receives a text file, creates a text file with the validations of the addresses with dian nomenclaturefromaddressValidatorimportaddress_validator_file_dian# address_validator_file_dian(file) -> Nonewithopen("addressDian.txt")asfile_object:address_validator_file_dian(file_object)# create output.txtWe read theaddressDianfile from the root path and send the document to the function and it returns the validations in anoutput.txtfile. Validations with file for dian nomenclature is in theoutput_dian.txtfileRoadmapSee theopen issuesfor a list of proposed features (and known issues).ContributingContributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make aregreatly appreciated.Fork the ProjectCreate your Feature Branch (git checkout -b feature/AmazingFeature)Commit your Changes (git commit -m 'Add some AmazingFeature')Push to the Branch (git push origin feature/AmazingFeature)Open a Pull RequestLicenseDistributed under the MIT License. SeeLICENSEfor more information. |
add-return-None-to-init | Automatic add 'None' return type to initThis moduel automatically addsNonereturn type to every init function, i.e.def__init__(...)->None:Usage``sh
usage: py-add-return-None-to-all-init [-h] [-d] PATHYou can run the module with
```sh
py-add-return-None-to-all-init MY_PYTHON_PROJ [--dry-run]With the--dry-runflag it will only be verbose on what it's gonna perform without writing to disk. It will performs the actual run it the dry run flag is not presence. |
addrext | No description available on PyPI. |
addr-match | readme |
addrmatcher | IntroductionAddrmatcher is an open-source Python software for matching input string addresses to the most similar street addresses and the geo coordinates inputs to the nearest street addresses. The result provides not only the matched addresses, but also the respective country’s different levels of regions for instance - in Australia, government administrative regions, statistical areas and suburb in which the address belongs to.The Addrmatcher library is built to work with rapidfuzz, scikit-learn, pandas, numpy and provides user-friendly output. It supports python version 3.6 and above. It runs on all popular operating systems, and quick to install and is free of charge.In this initial release, the scope of input data and matching capability are limited to Australian addresses only. The Addrmatcher library will see the opportunity to scale the matching beyond Australia in future.The package offers two matching capabilities -address-based matchingaccepts string address as argument.coordinate-based matchingtakes geo coordinate (latitude and longititude) as input.The development team achieved the optimal speed of matching less than one second for each address and each pair of coordinate input.The reference dataset is built upon GNAF(Geocoded National Address File) and ASGS(Australian Statistical Geography Standard) for the Australian addresses. The package users will require to download the optimised format of reference dataset into the working direcory once the package has been installed.Installationpip install addrmatcherData DownloadOnce the package has been installed, the reference dataset needs to be downloaded intothe local current project working directoryprior to implementation of the package's matching functions.In the command line interface,addrmatcher-data ausThe above console script will download the dataset which is currently hosted in Github into the user's directory. By default, the country isAustraliaand Australia physical addresses will be downloaded. After executing the command, the 37 parquet files will be stored in directories for example /data/Australia/*.parquet.Import the package and classes# Import the installed packagefromaddrmatcherimportAUS,GeoMatcher# Initialise the geo region as AUSmatcher=GeoMatcher(AUS)Example - Address-based Matchingmatched_address=matcher.get_region_by_address("9121, George Street, North Strathfield, NSW 2137")print(matched_address)>{'SA4_NAME_2016':['Sydney - Inner West'],'LGA_NAME_2016':['Canada Bay (A)'],'SA3_NAME_2016':['Canada Bay'],'RATIO':[100.0],'STATE':['NSW'],'FULL_ADDRESS':['9121 GEORGE STREET NORTH STRATHFIELD NSW 2137'],'SA2_NAME_2016':['Concord West - North Strathfield'],'SSC_NAME_2016':['North Strathfield'],'MB_CODE_2016':['11205258900'],'SA1_7DIGITCODE_2016':['1138404']}Example - Coordinate-based Matchingnearest_address=matcher.get_region_by_coordinates(-29.1789874,152.628291)print(nearest_address)>{'IDX':[129736],'FULL_ADDRESS':['3 7679 CLARENCE WAY MALABUGILMAH NSW 2460'],'LATITUDE':[-29.17898685],'LONGITUDE':[152.62829132],'LGA_NAME_2016':['Clarence Valley (A)'],'SSC_NAME_2016':['Baryulgil'],'SA4_NAME_2016':['Coffs Harbour - Grafton'],'SA3_NAME_2016':['Clarence Valley'],'SA2_NAME_2016':['Grafton Region'],'SA1_7DIGITCODE_2016':['1108103'],'MB_CODE_2016':['11205732700'],'STREET_NAME':['CLARENCE'],'STREET_TYPE_CODE':['WAY'],'LOCALITY_NAME':['MALABUGILMAH'],'STATE':['NSW'],'POSTCODE':['2460'],'ADDRESS_DETAIL_PID':['GANSW706638188'],'FILE_NAME':['NSW-10.parquet'],'DISTANCE':[6.859565028181215e-05]} |
addroni | Developed By Roni Das ,A complete packing for neo4j operations |