Saravanan666/pypi-org huggingface dataset:
Package: xalc
Xalc is a hexadecimal calculator for embedded systems programmers, implemented
as a pre-processor for Python expressions, with a console interface based on
IPython.Features:Mixed calculations with hex, decimal, binary and binary prefix literalsSupport for undecorated hex literals.  Ambiguous literals can be forced to hex by either prefixing or suffixing with ‘x’.Display in hex, decimal, binary (with bit position ruler) and binary prefixes (sizes)Simple bit mask constructionBit field extraction operatorFrom IPython: Support for arbitrary Python expressions (minus the ones that conflict with the pre-processed syntax), command history, access to previous results with _* variables, etc.The following “screenshot” demonstrates some of the features of Xalc.  The real
program displays the different bases in different colors, if your console
supports that:$ xalc
In [1]: deadbeef
0xdeadbeef
Out[1]:
3735928559    │  28─╮ 24─╮ 20─╮ 16─╮ 12─╮  8─╮  4─╮  0─╮
0xdeadbeef    │  1101 1110 1010 1101 1011 1110 1110 1111
3 Gi + 490 Mi + 879 Ki + 751

In [2]: deadbeef $ m5t13
0xdeadbeef >> 5 & ((0x3fe0) >> 5)
Out[2]:
 503           │  28─╮ 24─╮ 20─╮ 16─╮ 12─╮  8─╮  4─╮  0─╮
 0x000001f7    │  0000 0000 0000 0000 0000 0001 1111 0111

In [3]: _ ^ cafe
_ ^ 0xcafe
Out[3]:
 51977         │  28─╮ 24─╮ 20─╮ 16─╮ 12─╮  8─╮  4─╮  0─╮
 0x0000cb09    │  0000 0000 0000 0000 1100 1011 0000 1001
 50 Ki + 777

In [4]: 7f000000 - 35000000x
0x7f000000 - 0x35000000
Out[4]:
 1241513984    │  28─╮ 24─╮ 20─╮ 16─╮ 12─╮  8─╮  4─╮  0─╮
 0x4a000000    │  0100 1010 0000 0000 0000 0000 0000 0000
 1 Gi + 160 Mi

In [5]: m2p0_5_8t9_29_31t31
(0x3|0x20|0x300|0x20000000|0x80000000)
Out[5]:
 2684355363    │  28─╮ 24─╮ 20─╮ 16─╮ 12─╮  8─╮  4─╮  0─╮
 0xa0000323    │  1010 0000 0000 0000 0000 0011 0010 0011
 2 Gi + 512 Mi + 803

In [6]: 2g | m12
0x80000000 | (0x1000)
Out[6]:
 2147487744    │  28─╮ 24─╮ 20─╮ 16─╮ 12─╮  8─╮  4─╮  0─╮
 0x80001000    │  1000 0000 0000 0000 0001 0000 0000 0000
 2 Gi + 4 Ki

In [7]: -45
-45
Out[7]:
 -45           │  28─╮ 24─╮ 20─╮ 16─╮ 12─╮  8─╮  4─╮  0─╮
 0xffffffd3    │  1111 1111 1111 1111 1111 1111 1101 0011Install with pip:pip install --upgrade xalcOr by cloning thegit repoand running:python setup.py installRunxalcafter installation.
Package: xalgorithm
My Implementation of Data Structure and Algorithms in PythonBuild and Update Packagemake upload version=a.b.cInstall This Packagepip install xalgorithmList of ImplementationsXalgorithm FunctionEffect@tag_meTag each function with a label and access the function using that label@print_mePrint the functon, its argument and result, helpful in debugging@ctrl_cAsk the user for confirmation to exit the program@record_itMeasure either the execution time or the execution count of a functionopathReturn the absolute path, expanding any user shortcutsojoinJoin multiple path components and optionally creates the path if it doesn't existosimplifyNormalize a pathxprintPrint text in styled format, please see my changelog for detailed usagesOut FunctonEffectmake_classificationGenerates a synthetic classification datasetdescribe_dfPerforms exploratory analysis on each featureprint_dfPrint a pandas DataFrame with rich APIBenchmarkThis class evaluates several well-known machine learning algorithms for a classification problem and provides multiple classification metrics for comparative analysis%py_versionPrint the current version of Python%%csvParses the cell into a DataFrame and then prints the DataFrame to the console in the specified format (rich-format, plain-format, markdown-format)%%timeDisplay the execution time of code within a cell in secondsOds FunctionEffectpower_analysisCalculate sample size for power analysis using effect size, significance, power, and population stdRFMSegment and Target customers for personalized marketing strategies using Recency, Frequency, Monetary analysisparse_vdsDownload Youtube subtitles, seexalgorithm --helpfor guidance. The Spacy English pipeline can be optionally loaded to segment sentences within subtitle scriptsArray AlgorithmDefinition:white_large_square: Sliding Window:white_check_mark: HuaRongDaoSolve a puzzle where the goal is to start from initial state and end in final stateAdvanced Algorithms and Data Structures (La Rocca, M., 2021)TopicNoteFinish DateChp 2: d-way heapsPriority Queue:white_large_square:Chp 2: huffman compressionxxxx:white_large_square:ChangeLogAll updates are tracked inthis file.CreditsTo better prepare myself for the challenges of algorithmic problems, I have included code fromOpen Data Structures. I will probably to rewrite some functions to make them compatible with my project as I continue to read this book. I owe huge gratitude for their work in jumping start my learning journey.
Package: xalpha
xalpha基金投资的全流程管理场外基金的信息与净值获取，精确到分的投资账户记录整合分析与丰富可视化，简单的策略回测以及根据预设策略的定时投资提醒。尤其适合资金反复进出的定投型和网格型投资的概览与管理分析。🎉 0.3 版本起支持通用日线和实时数据获取器，统一接口一行可以获得几乎任何市场上存在产品的价格数据，进行分析。🍭 0.9 版本起支持持仓基金组合的底层持仓配置和股票细节透视，掌握底层持仓和跟踪机构股票池与买卖特点，从未如此简单。一行拿到基金信息：nfyy=xa.fundinfo("501018")一行根据账单进行基金组合全模拟，和实盘完全相符:jiaoyidan=xa.record(path)# 额外一行先读入 path 处的 csv 账单shipan=xa.mul(status=jiaoyidan)# Let's rockshipan.summary()# 看所有基金总结效果shipan.get_stock_holdings()# 查看底层等效股票持仓一行获取各种金融产品的历史日线数据或实时数据xa.get_daily("SH518880")# 沪深市场历史数据xa.get_daily("USD/CNY")# 人民币中间价历史数据xa.get_rt("commodities/crude-oil")# 原油期货实时数据xa.get_rt("HK00700",double_check=True)# 双重验证高稳定性支持的实时数据一行拿到指数，行业，基金和个股的历史估值和即时估值分析（指数部分需要聚宽数据，本地试用申请或直接在聚宽云平台运行）xa.PEBHistory("SH000990").summary()xa.PEBHistory("F100032").v()一行定价可转债xa.CBCalculator("SH113577").analyse()一行估算基金净值 (QDII 基金需自己提供持仓字典)xa.QDIIPredict("SH501018",positions=True).get_t0_rate()xalpha 不止如此，更多特性，欢迎探索。不只是数据，更是工具！文档在线文档地址：https://xalpha.readthedocs.io/或者通过以下命令，在本地doc/build/html内阅读文档。$cddoc
$makehtml安装pipinstallxalpha目前仅支持 python 3 。若想要尝试最新版，$gitclonehttps://github.com/refraction-ray/xalpha.git
$cdxalpha&&python3setup.pyinstall用法本地使用由于丰富的可视化支持，建议配合 Jupyter Notebook 使用。可以参照这里给出的示例连接，快速掌握大部分功能。部分效果如下：在量化平台使用这里以聚宽为例，打开聚宽研究环境的 jupyter notebook，运行以下命令：>>> !pip3 install xalpha --user
>>> import sys
>>> sys.path.insert(0, "/home/jquser/.local/lib/python3.6/site-packages")
>>> import xalpha as xa即可在量化云平台正常使用 xalpha，并和云平台提供数据无缝结合。如果想在云平台研究环境尝试最新开发版 xalpha，所需配置如下。>>> !git clone https://github.com/refraction-ray/xalpha.git
>>> !cd xalpha && python3 setup.py develop --user
>>> import sys
>>> sys.path.insert(0, "/home/jquser/.local/lib/python3.6/site-packages")
>>> import xalpha as xa由于 xalpha 整合了部分聚宽数据源的 API，在云端直接xa.provider.set_jq_data(debug=True)即可激活聚宽数据源。致谢感谢集思录对本项目的支持和赞助，可以在这里查看基于 xalpha 引擎构建的 QDII 基金净值预测。博客xalpha 诞生记xalpha 设计哲学及其他
Package: xaml
an easier way for humans to write xml and htmlif a line starts with any xaml component ( ~ @ . # $ ) that line represents
an xml/http element:- an element continues until eol, or an unquoted :
- an element can be continued to the next line(s) using unquoted parensif a line starts with a “:” it is specifying how the following lines should
be interpreted:- :css -> cascading style sheets that are inserted with a <style> tag

- :python -> python code inserted into a <script type="text/python"> tag
             (must have a python interpreter running in the browser; e.g.
             Brython (http://brython.info/index.html))

- :javascript -> javascript code inserted into a
                 <script type="text/javascript"> tagif a line starts with // it is a comment, and will be converted into an
xml/html commentif a line starts with a “-” (hyphen) it is a single line of Python code that
will be run to help generate the final outputotherwise the line represents the content of an elementxaml components:- ~ -> element name
- @ -> name attribute
- . -> class attribute
- # -> id attribute
- $ -> string attribute

  e.g. ~document .bold #doc_1 @AutoBiography $My_Biography ->

  <document class="bold" id="doc_1" name="AutoBiography" string="My Biography"/>Based on haml [1] but aimed at Python.Still in its early stages – send email to ethan at stoneleaf dot us if you
would like to get involved!Mercurial repository, wiki, and issue tracker at [2].[1]http://haml.info/[2]https://bitbucket.org/stoneleaf/xaml
Package: xanalyzer
xanalyzerEnglish简单分析文件和url，python3下运行。文件md5/sha256文件类型文件大小字符串扫描PE文件PE大小编译时间pdb路径版本信息证书验证节区名称DLL名称EXE导入表检查查壳资源段扫描ELF文件ELF大小查壳建议使用的工具url(website)域名解析ip获取robots.txt文件站内链接扫描(--deep)站内子域名扫描(--deep)安装使用pipx安装：# pipx: https://pypa.github.io/pipx/pipinstallpipxpipxensurepathpipxinstallxanalyzer# 还可以用来升级，但是不能检查新版本pipxupgradexanalyzer如果系统是 Debian/Ubuntu，需要安装依赖：sudoapt-getinstalllibmagic1使用帮助usage:xanalyzer[-h](-fFILE[FILE...]|-uURL|--version)[-s][--deep][--minstrlenMINSTRLEN]Processsomefilesandurls.optionalarguments:-h,--helpshowthishelpmessageandexit-fFILE[FILE...],--fileFILE[FILE...]analyzeoneormorefiles,canbeafolderpath-uURL,--urlURLanalyzetheurl--versionprintversioninfo-s,--savesaveloganddata--deepanalyzedeeply--minstrlenMINSTRLENminimumlengthofthestringtobeextracted,default4,notlessthan2使用示例xanalyzer-fhello.exexanalyzer-u"https://www.baidu.com/s?wd=hello"开发gitclonehttps://github.com/qux-bbb/xanalyzercdxanalyzervirtualenvvenv# windws使用虚拟环境: .\venv\Scripts\activate# linux使用虚拟环境: source venv/bin/activatepipinstall-rrequirements.txtpythonsetup.pydevelop# 退出虚拟环境: deactivate这样之后就可以用pycharm或vscode开发调试了打包发布该步骤仅本人使用打包前确保版本号和CHANGELOG.md已更新，清空dist文件夹安装依赖、通过测试项、打包：# windws使用虚拟环境: .\venv\Scripts\activate# linux使用虚拟环境: source venv/bin/activatepipinstall-rrequirements.txtpipinstall-rrequirements.my.txtpytestpython-mbuild# 退出虚拟环境: deactivate重新打开一个命令行，转到dist文件夹下本地安装，检查基本功能，举例：pipxuninstallxanalyzerpipxinstall./xanalyzer-0.2.3.tar.gzxanalyzer--versionxanalyzer-f./xanalyzer-0.2.3.tar.gz在github创建Release标题为xanalyzer <version>，如:xanalyzer v0.2.0内容基于CHANGELOG.md做一些修改将dist文件夹下所有文件传到Release页面然后发布即可将文件传到pypi(需要账号密码)python-mtwineupload--repositorypypidist/*其它这个项目的有些功能可能会用到:https://github.com/mitre/multiscanner参考链接:python打包:https://www.jianshu.com/p/692bab7f8e07setuptools官方文档:https://setuptools.readthedocs.io/en/latest/index.htmlPEiD查壳:https://github.com/erocarrera/pefile/blob/wiki/PEiDSignatures.md
Package: xanathar
XanatharName inspired byXanathar's Guide to Everything(© Wizards of the Coast)PipelineMade in draw.ioFeaturesCompiles directly to a binary (through LLVM IR)Fast (usesLarkandLLVMLite) for speedStrong typing (enforced by LLVM IR)Easy to learn syntaxWritten in Python, so no installation requiredSpecImplemented operationsKeep in mind, Xanathar is ahugeWIPVariables (statically allocated)Int / UInt1 Bit (Bool)8 Bit (Char)16 Bit32 Bit64 Bit128 Bit512 Bit1024 BitFloatsStrings (implemented as a statically allocated int8[])Printinglibcprintfcan be usedprint_s,print_i,print_x,print_cprint with theprintfformat string (%sforprint_s, etc.)Implemented as a libc call toprintfwith the corresponding format stringDeprecated in favour ofprintfCastingWorks!string >> intgives pointer to theint'th character instringuseful for (e.g.)printfLoopsWhile and ForWhile loops: more like a C-style do-whileFor loops: similar to a do-while style loopModulesstdioi8* get[i8*, i32]Implementsfgetsin C (source can be viewed instdlib/stdio.c)It's the best of both worlds: it keeps the amazing speed of low-level languages, but with the power and ease of high-level languages.
On a test of the Collatz conjecture, run for i = 1 to 10, and 77,031, (100 runs of the entire program) Python 3 ran in 1.9s, whereas Xanathar ran in 0.064s.
For 1000 runs of the program, Python 3 took 20.7s whereas Xanathar took 0.531s.
Package: xander
XanderXander is my first experience in developing MLOps tools. I developed this tool one piece at time since my first day in Bip spa.
This tool represents my personal and professional growth, it contains scripts on which every Data Science project is based. Repeating them every time was frustrating so why not create a tool that did it for me?Xander is a Greek name meaning "the one who saves".At the moment, two types of pipelines are provided with Xander:General Purpose Pipelines developed to support all process that takes one or more inputs, process them and returns an output.Machine Learning Pipelines developed to support Machine Learning and Deep Learning models development and deployment.Initialize XanderEngineGeneral Purpose PipelinesWhat's coming!
Package: xandr-statuspageio
StatusPage.oi  API V1 library client for Python. Based on the documentaion fromhttps://doers.statuspage.io/api/v1/Provides most of the funcitonality for thehttp://statuspage.ioapi’s via handy python code.InstallationStatuspageio package can be installed either via pip:$pipinstallgit+https://github.com/n8thegr8/python-statuspageioYou can install from the source code as well. First clone the repo and
then execute:$pythonsetup.pyinstallAfter installing, importstatuspageiopackage:importstatuspageioUsageimportstatuspageio# Then we instantiate a client (as shown below)Build a clientUsing this api without authentication gives an errorclient=statuspageio.Client(api_key='<YOUR_PERSONAL_API_KEY>',page_id='<YOUR_PERSONAL_PAGE_ID>')orclient=statuspageio.Client(api_key='<YOUR_PERSONAL_API_KEY>',page_id='<YOUR_PERSONAL_PAGE_ID>',organization_id='<YOUR_PERSONAL_ORGANIZATION_ID>')Client OptionsThe following options are available while instantiating a client:api_key: Personal API Keypage_id: Personal page idorganization_id: Personal organization id, used for managing users.base_url: Base url for the apiuser_agent: Default user-agent for all requeststimeout: Request timeoutverbose: Verbose/debug modeArchitectureThe library follows few architectural principles you should understand
before digging deeper. 1. Interactions with resources are done via
service objects. 2. Service objects are exposed as properties on client
instances. 3. Service objects expose resource-oriented actions. 4.
Actions return dictionaries that support attribute-style access, a la
JavaScript (thanks to Bunch and it’s form Munch).For example, to interact with components API you will usestatuspageio.ComponentsService, which you can get if you call:client=statuspageio.Client(api_key='<YOUR_PERSONAL_API_KEY>',page_id=<YOUR_PERSONAL_PAGE_ID')client.components# statuspageio.ComponentsServiceTo retrieve list of resources and use filtering you will call#listmethod:client=statuspageio.Client(api_key='<YOUR_PERSONAL_API_KEY>',page_id=<YOUR_PERSONAL_PAGE_ID')client.components.list()# list(dict|Munch)Resources and actionsDocumentation for every action can be found instatuspageio/services.pyfile.TestsSorry. These need to be written.ThanksThank you to the BaseCRM development team who created the majority of the code for this project.
We forked the code as the aritectural style worked really well for this project.
Please seehttps://github.com/basecrm/basecrm-pythonfor more detailsThank you so much!LicenseMITBug ReportsReporthere.
Package: xanespy
Xanespy is a library for analyzing X-ray absorbance spectroscopy data
for materials science, chemistry and similar fields. The major focus
is on X-ray microscopy frames collected at multiple energies and over
multiple timesteps. However, a design goal is for most (if not all) of
the calculation routines to be applicable to bulk XAS data as well.Motivation & FeaturesImporting and analysis of transmission X-ray microscopy framesetsAnalysis of X-ray spectroscopy data (K-edge XANES and L-edge)Efficient analysis of large operando datasetsInstallationXanespy can be installed from thepython package index (PyPI) using pip$pipinstallxanespyUsageEach beamline generally has its own importer in thexanespy.importersmodule, which will process the data and create an
HDF5 file ready for the rest of xanespy to useimportxanespy# Example for importing from SSRL 6-2cxanespy.import_ssrl_frameset('<data_dir>',hdf_filename='imported_data.h5')# Load a pre-defined XAS edge or create your own subclass xanespy.Edgeedge=xanespy.k_edges['Ni_NCA']# Now load the newly created HDF5 file and the X-ray absorbance edgefs=xanespy.XanesFrameset(filename='imported_data.h5',edge=edge)# Perform automatic frame alignmentfs.align_frames(passes=5)# Fit the absorbance spectra and extract the edge position (SLOW!)fs.fit_spectra()# Inspect the result with the built-in Qt5 GUIfs.qt_viewer()BeamlinesWe currently have importers for data from the following beamlines. If
you would like support a beamline that is not listed and are willing
to share some test data publicly, pleaseopen an
issue.32-ID-C - Advanced Photon Source8-BM-B - Advanced Photon Source6-2c - Stanford Synchrotron Radiation Lightsource5.3.2.1 - Advanced Light Source (ptychography)PtychographyXanespy has support for ptychography data from ALS beamline
5.3.2.1. Usexanespy.import_nanosurveyor_framesetto import the .cxi
files andxanespy.PtychoFramesetto load the data.LicenseThis project is released under theGNU General Public License version 3.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.  See the GNU
General Public License for more details.AcknowledgementThis work was supported as part of the NorthEast Center for Chemical
Energy Storage (NECCES), an Energy Frontier Research Center funded
by the U.S. Department of Energy, Office of Science, Basic Energy
Sciences under Award # DE-SC0012583.
Package: xango
XangoXangoAPIdbxql_to_aqlparse_xsqlparse_xgraphqlresolve_xgraphqlparse_dict_mutationsgen_xidCollectionCollectionItemCollectionActiveRecordMixinConnectionimport xango

#--- connect
db = xango.db(hosts="http://host:8529", username="root", password:str)

#--- select collection
coll = db.select_collection('test')

#--- insert item
coll.insert({k:v, ...})

#--- insert item with custom _key
coll.insert({k:v,...}, _key='awesome')Query{
    "_modified_at:$datetime": "+2hh"
  }Format:YYYY: Year
MM: Month
DD: Date
HH: Hour
mm: Min
ss: seconds

ISODATE: YYYY-MM-DDTHH:mm:ss$AND and $ORfilters = {

  "$or": [
    { // query between dates
      "_created_at:$lt": "@@CURRDATE() -2days",
      "_created_at:$gt": "@@CURRDATE() +2days"
    }
  ]
}
Package: xangobolt-pulumi-aws
Example PackageThis is a simple example package. You can useGithub-flavored Markdownto write your content.code /Users/samson.adewale/OneDrive - Xangobolt Technologies/Development/SourceCode/AWS_IAC/xangobolt_pulumi_package/setup.cfg
Change package version
cd /Users/samson.adewale/OneDrive - Xangobolt Technologies/Development/SourceCode/AWS_IAC/xangobolt_pulumi_package
python3 -m build
python3 -m twine upload dist/xangobolt_pulumi_aws-1.0.1-py3-none-any.whlgit add -A && git commit -m "updated modules" && git push origin main
Package: xapian-bindings
xapian-bindingsNOTE: This package is not guaranteed to fully functional! Use at your own risk!xapian-bindings is a meta-package to simplify installation of thexapian-bindingsextension
for Python. It determines the version ofxapian-bindingsto use based on the version ofxapian-coreinstalled;
downloads and extracts the source code; then runs./configure,makeandmake install.This project is not affiliated with theXapianproject in any way.InstallationEnsure you have essential build & development tools installed on your system.Ensure you havexapian-coreinstalled via your system package manager or source tarball.Runpip install--no-cache-dirxapian-bindings.Verify installation by runningpython-c"import xapian; print(xapian.__version__)".TodosAdd.travis.yml.
Package: xapiand
Python Xapiand ClientOfficial low-level client for Xapiand. Its goal is to provide common
ground for all Xapiand-related code in Python; because of this it tries
to be opinion-free and very extendable.InstallationInstall thexapiandpackage withpip:pip install xapiandExample useSimple use-case:>>>fromdatetimeimportdatetime>>>fromxapiandimportXapiand# by default we connect to localhost:8880>>>client=Xapiand()# datetimes will be serialized>>>client.index(index="my-index",id=42,body={"any":"data","timestamp":datetime.now()}){'#docid':42,'#shard':2'_id':42,'_version':1,'any':'data','timestamp':'2019-07-18T09:04:54.182665'}# and deserialized>>>client.get(index="my-index",id=42){'#docid':42,'#shard':2'_id':42,'_version':1,'any':'data','timestamp':'2019-07-18T09:04:54.182665'}Full documentation.FeaturesThe client's features include:translating basic Python data types to and from msgpackconfigurable automatic discovery of cluster nodespersistent connectionsload balancing (with pluggable selection strategy) across all
available nodesfailed connection penalization (time based - failed connections
won't be retried until a timeout is reached)thread safetypluggable architectureLicenseCopyright 2018-2019 Dubalu LLC Copyright 2017 XapiandLicensed under the Apache License, Version 2.0 (the "License"); you
may not use this file except in compliance with the License. You may
obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Package: xapian-haystack
Xapian-haystack is a backend ofDjango-Haystackfor theXapiansearch engine.
Thanks for checking it out.You can find more information about Xapianhere.FeaturesXapian-Haystack provides all the standard features of Haystack:WeightingFaceted search (date, query, etc.)SortingSpelling suggestionsEdgeNGram and Ngram (for autocomplete)LimitationsTheendswithsearch operation is not supported by Xapian-Haystack.RequirementsPython 3+Django 2.2+Django-Haystack 2.8.0Xapian 1.4+InstallationFirst, install Xapian in your machine e.g. with the script provided,install_xapian.sh. Call it after activating the virtual environment to install:source <path>/bin/activate
./install_xapian.sh <version><version>must be >=1.4.0. This takes around 10 minutes.Finally, install Xapian-Haystack by running:pip install xapian-haystackConfigurationXapian is configured as other backends of Haystack.
You have to define the connection to the database,
which is done to a path to a directory, e.g:HAYSTACK_CONNECTIONS = {
    'default': {
        'ENGINE': 'xapian_backend.XapianEngine',
        'PATH': os.path.join(os.path.dirname(__file__), 'xapian_index')
    },
}The backend has the following optional settings:HAYSTACK_XAPIAN_LANGUAGE: the stemming language; the default isenglishand the list of available languages
can be foundhere.HAYSTACK_XAPIAN_WEIGHTING_SCHEME: a tuple with parameters to be passed to the weighting schemeBM25.
By default, it uses the same parameters as Xapian recommends; this setting allows you to change them.HAYSTACK_XAPIAN_FLAGS: the options used to parseAutoQueries;
the default isFLAG_PHRASE | FLAG_BOOLEAN | FLAG_LOVEHATE | FLAG_WILDCARD | FLAG_PURE_NOTSeeherefor more information
on what they mean.HAYSTACK_XAPIAN_STEMMING_STRATEGY: This option lets you chose the stemming strategy used by Xapian. Possible
values areSTEM_NONE,STEM_SOME,STEM_ALL,STEM_ALL_Z, whereSTEM_SOMEis the default.
Seeherefor
more information about the different strategies.XAPIAN_NGRAM_MIN_LENGTH,XAPIAN_NGRAM_MAX_LENGTH: options for custom configuration of ngrams (phrases) length.HAYSTACK_XAPIAN_USE_LOCKFILE: Use a lockfile to prevent database locking errors when running management commands with multiple workers.
Defaults toTrue.TestingXapian-Haystack has a test suite in continuous deployment with GitHub Actions. The file.github/workflows/test.ymlcontains the steps required to run the test suite.SourceThe source code can be found ingithub.CreditsXapian-Haystack is maintained byJorge C. Leitão;David Sauvewas the main contributor of Xapian-Haystack and
Xapian-Haystack was originally funded byTrapeze.Claude Parozis a frequent contributor.ANtlordimplemented support for EdgeNgram and Ngram.LicenseXapian-haystack is free software licenced under GNU General Public Licence v2 and
Copyright (c) 2009, 2010, 2011, 2012 David Sauve, 2009, 2010 Trapeze, 2014 Jorge C. Leitão.
It may be redistributed under the terms specified in the LICENSE file.Questions, Comments, Concerns:Feel free to open an issuehereor pull request your work.You can ask questions on the django-haystackmailing list:
or in the irc#haystack.