Saravanan666/pypi-org huggingface dataset:
Package: nmap-query-tool
NMAP Query ToolPost-processor for nmap output that allows fast, simple filtering of data both interactively and inline (i.e. via a bash pipe).Usage:pythonnmap-query.py[-h][-pPORTS][-aIPS][-osOS][-dDEVICE_TYPE][-c][-iNMAP_SCAN_RESULTS_FILE][-oOUTPUT_FILENAME][-q]Note:thenmapscanresultscanbeprovidedeitherthroughaninputfileorfromSTDIN(throughapipe)Example:nmap-sV10.0.0.0/24|pythonnmap-query.py-q[-h|--help]:Willprintthehelp/usagemessage[-p|--ports]PORTS:specifyoneormore(open)portstofilteron.Thefollowinginputformatsareaccepted:Singleportnumber:-p22Setofportnumbers:-p22,80,443[-a|--ip-addrs]IPS:specifyoneormoreIPaddressesonwhichtofilter.Thefollowinginputformatsareaccepted:SingleIP:-a10.0.0.1SetofIPs:-a10.0.0.1,10.0.0.2,10.0.0.3SingleCIDRblock:-a10.0.0.0/24SetofCIDRblocks:-a10.0.0.0/24,10.0.1.0/24RangeofIPs:-a10.0.0.1-4[-os|--operating-system]OS:specifyoneormoreoperatingsystemsonwhichtofilter.Thefollowinginputformatsareaccepted:Singleoperatingsystem:-osWindwsSetofoperatingsystems:-osWindows,Linux[-d|--device-type]DEVICE_TYPE:specifyoneormoredevicetypesonwhichtofilter.Thefollowinginputformatsareaccepted:Singledevicetype:-drouterSetofdevicetypes:-drouter,switch[-c|--output-csv]:useCSVastheoutputformat[-i|--input-file]NMAP_SCAN_RESULTS_FILE:specifythenameoftheinputfile(i.e.thefilewhichcontainstheresultsoftheNmapscan)[-o|--output-file]OUTPUT_FILENAME:specifythenameoftheoutputfile[-q|--query-mode]:entertheinteractivequerymodeLocate script install locationpip3 show nmap-query-tool; will show the install directory of the packagecd <INSTALL DIRECTORY>/NmapQueryToolpython3 nmap_query_tool.pyYou can also setup an alias for running the script:alias nmap-query="python3 ${pwd}/nmap_query.py"
Package: nmapthon2
Nmapthon2The evolution ofNmapthon, an Nmap automation module for humans.What can I do with Nmapthon2?Perform Nmap scans: Easily customize your options, execute raw scans, parse an Nmap file or resume scans.Retrieve all theresultswith a few lines of code, including:Overall scan informationHosts, ports and services.Operating systems and OS matchesHost and port scriptsTraceroute informationAnd more!Extend the NSE(Nmap Scripting Engine) with your ownPython code.Performasynchronous scansand control your main thread.Viewscan status.Use several Nmap-basedutilitiesInstallationMake sure you have Python 3.5+ andNmapinstalled on your system. Then run:pip3 install nmapthon2

# Or
pip install nmapthon2This library iscross-platform.DocumentationFull documentation inside ReadTheDocs, overhere.DisclaimerHope you all enjoy this module. Please, do not try its features without the consent of your targets. It is recommended to use your own virtual lab.
Package: nmap_vscan
nmap_vscancan finish Service and Application Version Detection without Nmap installation. It is not an official release from the Nmap Project.RequirementsPython 2.7Works on Linux, Windows, Mac OSX, BSDInstallThe quick way:pip install nmap_vscanUsagePlease downloadhttps://svn.nmap.org/nmap/nmap-service-probesat first.>>> from nmap_vscan import vscan
>>> nmap = vscan.ServiceScan('./nmap-service-probes')Let’s try to scan HTTP, MYSQL, SSH, REDIS and so on.>>> nmap.scan('www.apache.org', 80, "tcp")
{'match': {'pattern': '^HTTP/1\\.[01] \\d\\d\\d .*\\r\\nServer: Apache[/ ](\\d[-.\\w]+) ([^\\r\\n]+)',
  'versioninfo': {'cpename': ['apache:http_server:2.4.7'],
   'devicetype': [' v'],
   'hostname': [],
   'info': ['(Ubuntu)'],
   'operatingsystem': [],
   'vendorproductname': ['Apache httpd'],
   'version': ['2.4.7']}},
 'probe': {'probename': 'GetRequest',
  'probestring': 'GET / HTTP/1.0\\r\\n\\r\\n'}}>>> nmap.scan('192.168.1.245', 3306, 'tcp')
{'match': {'pattern': '^.\\0\\0\\0\\x0a(5\\.[-_~.+\\w]+)\\0',
  'versioninfo': {'cpename': ['mysql:mysql:5.5.28-log'],
   'hostname': [],
   'info': [],
   'operatingsystem': [],
   'vendorproductname': ['MySQL'],
   'version': ['5.5.28-log']}},
 'probe': {'probename': 'NULL', 'probestring': ''}}>>> nmap.scan('192.168.1.245', 6379, 'tcp')
{'match': {'pattern': '^\\$\\d+\\r\\n(?:#[^\\r\\n]*\\r\\n)*redis_version:([.\\d]+)\\r\\n',
  'versioninfo': {'cpename': [],
   'hostname': [],
   'info': [],
   'operatingsystem': [],
   'vendorproductname': ['Redis key-value store'],
   'version': ['2.6.12']}},
 'probe': {'probename': 'redis-server',
  'probestring': '*1\\r\\n$4\\r\\ninfo\\r\\n'}}Referenceshttps://nmap.org/https://nmap.org/book/vscan.htmlhttps://nmap.org/book/vscan-fileformat.htmlhttps://github.com/nmap/nmap/blob/master/service_scan.cchttps://svn.nmap.org/nmap/nmap-service-probes
Package: nmap-vscan-fix
nmap_vscancan finish Service and Application Version Detection without Nmap installation. It is not an official release from the Nmap Project.RequirementsWorks on Linux, Windows, Mac OSX, BSDInstallThe quick way:pip install nmap_vscan_fixUsagePlease downloadhttps://svn.nmap.org/nmap/nmap-service-probesat first.>>> from nmap_vscan import vscan
>>> nmap = vscan.ServiceScan('./nmap-service-probes')Let’s try to scan HTTP, MYSQL, SSH, REDIS and so on.>>> nmap.scan('www.apache.org', 80, "tcp")
{'match': {'pattern': '^HTTP/1\\.[01] \\d\\d\\d .*\\r\\nServer: Apache[/ ](\\d[-.\\w]+) ([^\\r\\n]+)',
  'versioninfo': {'cpename': ['apache:http_server:2.4.7'],
   'devicetype': [' v'],
   'hostname': [],
   'info': ['(Ubuntu)'],
   'operatingsystem': [],
   'vendorproductname': ['Apache httpd'],
   'version': ['2.4.7']}},
 'probe': {'probename': 'GetRequest',
  'probestring': 'GET / HTTP/1.0\\r\\n\\r\\n'}}>>> nmap.scan('192.168.1.245', 3306, 'tcp')
{'match': {'pattern': '^.\\0\\0\\0\\x0a(5\\.[-_~.+\\w]+)\\0',
  'versioninfo': {'cpename': ['mysql:mysql:5.5.28-log'],
   'hostname': [],
   'info': [],
   'operatingsystem': [],
   'vendorproductname': ['MySQL'],
   'version': ['5.5.28-log']}},
 'probe': {'probename': 'NULL', 'probestring': ''}}>>> nmap.scan('192.168.1.245', 6379, 'tcp')
{'match': {'pattern': '^\\$\\d+\\r\\n(?:#[^\\r\\n]*\\r\\n)*redis_version:([.\\d]+)\\r\\n',
  'versioninfo': {'cpename': [],
   'hostname': [],
   'info': [],
   'operatingsystem': [],
   'vendorproductname': ['Redis key-value store'],
   'version': ['2.6.12']}},
 'probe': {'probename': 'redis-server',
  'probestring': '*1\\r\\n$4\\r\\ninfo\\r\\n'}}Referenceshttps://nmap.org/https://nmap.org/book/vscan.htmlhttps://nmap.org/book/vscan-fileformat.htmlhttps://github.com/nmap/nmap/blob/master/service_scan.cchttps://svn.nmap.org/nmap/nmap-service-probes
Package: nmapvulners2csv
nmapvulners2csvTable of ContentsGetting StartedInstallRun without installingPrerequisitesEvidences DescriptionContributingCreditsLicenseGetting StartedRun nmap with enabled script Vulners and save xml output, for example:nmap -sV --script vulners -oX <nmap_output.xml>ExampleThe output of the tool is like the following:Install & RunTo install it you just need to run:pip install nmapvulners2csvRun without installingPrerequisitesInstall dependencies by using the following command:pip install -r requirements.txt
chmod +x nmapvulners2csv/nmapvulners2csv.pyUsage: nmapvulners2csv.py NMAP_XML_FILE <flags>
  optional flags:        --output | --descrTo run the converter:nmapvulners2csv.py <nmap_output.xml>the script will generate a file output.csv in output dir. If you want to set the output file:nmapvulners2csv.py <nmap_output.xml>  --output <output_csv_file> --dir <output_directory>For multiple data:for i in `ls -1 vulners*`; do python nmapvulners2csv.py $i ${i%%.xml}.csv ; doneEvidences Descriptionnmapvulners2csvdoes not generate descriptions for vulnerabilities. You can add--descrflag to add descriptions in CSV.  The script scrapes description information from Vulners site. The command is more time-expensive and send several HTTP requests against Vulners website. Not tested for IP ban and network 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 RequestCreditsnmapvulners2csvis proudly developed@SecSIby:Gaetano PerroneNdA994Angelo DelicatoLicenseDistributed under Apache 2 License. SeeLICENSEfor more information.
Package: nmapy
Notify My Android Module------------------------Implements the NMA API asan importable module orshell script.from nmapy import Nmanma = Nma()if nma.verify( "apikey" ):if not nma.notify( ["apikey1","apikey2"],"application text", "event text","description text", priority = 1, url = "http://notifymyandroid.com",content_html=True ):`handle error`or as a shell script./nmapy.py --help./nmapy.py --mode verify --apikey `key`./nmapy.py --mode notify --apikey ( `key`,`key`,etc ) or additional `--apikey` argumentsThis version requires a current release of python 2.7 series.A second module will be developed for python 3 users.
Package: nmaquifertool
NMAquiferToolExample usageUpload a Water Levels xlsx filenmatuploadwaterlevels--filewater_levels.xlsxby default the application will run in "dry-run" mode, i.e. data will not be added to database.
To add data to database, use the--commitflag:nmatuploadwaterlevels--commit--filewater_levels.xlsxYou can add verbose output with the--verboseflag:nmatuploadwaterlevels--commit--verbose--filewater_levels.xlsx
Package: nmath
♆ NEPTUNENEPTUNEis a set of decoupledPython librariesintended to facilitate Python development:nfin,ngui,nlearn,nmath andnutil.The librarynmathcontains mathematical utility functions; among them:wrappers around common statistical distributions (including normal, binomial and poisson).NEPTUNE is based on popular libraries like numpy, pandas, plotly and scipy.InstallLaunch the following commands in a shell:gitclonehttps://github.com/b-io/io.barras.gitcdio.barras/python/neptune/
mvncleaninstallLicenseFeel free to download, try and share your suggestions about the libraries,
while respectingthis MIT License (MIT).
Package: nmb_eeg
Power spectra of pure EEG from two temporarily paralysed subjects.Data from (Fig 1, B-traces):Scalp electrical recording during paralysis: Quantitative evidence that
EEG frequencies above 20 Hz are contaminated by EMG
Emma M. Whitham, Kenneth J. Pope, Sean P. Fitzgibbon, Trent Lewis,
C. Richard Clark, Stephen Loveless, Marita Broberg, Angus Wallace,
Dylan DeLosAngeles, Peter Lillie, Andrew Hardy, Rik.
Clinical Neurophysiology Volume 118, Issue 8, August 2007,
Pages 1877-1888.Please cite as “Data from …” as outlined above. This has been advised by Elsevier’s Copyrights Coordinator.UsageTo obtain the average PSD over all experiments just use
the default constructor:p = NMB_EEG_From_WhithamEtAl()If you want to extract the PSD of dataset one do:p = NMB_EEG_From_WhithamEtAl(1)Obtain the power spectral density in V^2/Hz use:psd = p.EEGVariance(f)wherefcan be either a single frequency or a numpy array.
The lowest permitted frequency isf_signal_minand the highestf_signal_max.The total power of the entire frequency range fromf_signal_mintof_signal_maxis:totalEEGPower = p.totalEEGPower()BecauseEEGVariance(f)accepts a numpy array plotting the spectrum is simply:f = np.linspace(p.f_signal_min,p.f_signal_max,100)
plt.plot(f,p.EEGVariance(f))Usage exampleRun:plot_paralysed_EEG_PSD.pyfrom the github page:https://github.com/berndporr/nmb_eegCreditBernd Porr <bernd.porr@glasgow.ac.uk>
Package: nmc-met-base
气象应用开发基本程序库提供一些关于气象科学计算的基础功能函数，包括数组处理、数学函数、物理常数、时间处理、客观分析等模块;以及气象诊断分析程序，包括动力, 热力, 水汽和天气特征分析等。Only Python 3 is supported.
建议安装Anaconda数据科学工具库,
已包括scipy, numpy, matplotlib等大多数常用科学程序库.InstallUsing the fellowing command to install packages:使用pypi安装源安装(https://pypi.org/project/nmc-met-base/)pip install nmc-met-base若要安装Github上的开发版(请先安装Git软件):pip install git+git://github.com/nmcdev/nmc_met_base.git或者下载软件包进行安装:git clone --recursive https://github.com/nmcdev/nmc_met_base.git
  cd nmc_met_base
  python setup.py install可选支持库:pyinterp,conda install pyinterp -c conda-forge
Package: nmc-met-graphics
气象数据绘图功能提供气象绘图功能函数, 包括颜色表处理, 屏蔽区域, 添加地图边界, 绘制天气分析图等.Only Python 3 is supported.建议安装Anaconda数据科学工具库,已包括scipy, numpy, matplotlib等大多数常用科学程序库.InstallUsing the fellowing command to install packages:预安装程序库conda install -c conda-forge cartopy使用pypi安装源安装(https://pypi.org/project/nmc-met-graphics/)pip install nmc-met-graphics若要安装Github上的开发版(请先安装Git软件):pip install git+git://github.com/nmcdev/nmc_met_graphics.git或者下载软件包进行安装:git clone --recursive https://github.com/nmcdev/nmc_met_graphics.git

  cd nmc_met_graphics

  python setup.py install可选支持库:Magics,conda install -c conda-forge magicsChange log:
Package: nmc-met-io
气象数据读写及访问程序库提供对MICAPS文件, 卫星云图, 天气雷达等数据的读写程序, 并访问CMADaaS, CIMISS和MICAPS CASSANDRA数据库文件等.相应的Jupyter例子文件请见Examples若有问题或需求, 请在登录留言程序库更新, 请见更新日志Only Python 3 is supported.
建议安装Anaconda数据科学工具库,
已包括scipy, numpy, matplotlib等大多数常用科学程序库.InstallUsing the fellowing command to install packages:使用pypi安装源安装(https://pypi.org/project/nmc-met-io/)pip install nmc-met-io若要安装Github上的开发版(请先安装Git软件):pip install git+git://github.com/nmcdev/nmc_met_io.git或者下载软件包进行安装:git clone --recursive https://github.com/nmcdev/nmc_met_io.git
  cd nmc_met_io
  python setup.py install可选支持库:若需要实现对grib格式数据的读取, 请用conda安装:eccodes,conda install -c conda-forge eccodes(ECMWF的grib工具库, 支持Windows和Linux)cfgrib,conda install -c conda-forge cfgrib若需要使用将标准雷达格式转化为pyart格式程序standard_data_to_pyart, 请安装:arm_pyart,conda install -c conda-forge arm_pyart若需要对Cassandra集群数据库进行访问, 请安装:cassandra-driver, 'pip install cassandra-driver'设置配置文件若要访问CMADaaS(大数据云), MICAPS服务器等, 需在配置文件中设置地址和用户信息(若不需要, 则相应项无需配置).在系统用户目录下("C:\Users\用户名"(windows)或"/home/用户名/"(Linux)), 建立文件夹".nmcdev"(若Windows下无法直接创建, 在命令窗口中输入mkdir .nmcdev创建)在".nmcdev"中创建文本文件"config.ini", 内容模板为:# 用于nmc_met_io读取大数据云, MICAPS服务器等的配置文件.
# 若用不到某个服务器, 则不设置或删除改段落即可.
# 注意设置IP地址时, 不要加http等前缀信息.

# 当读取CMADaas, MICAPS Cassandra等数据时, 采取了本地文件缓存机制, 以便加快
# 文件的读取速度和减少数据库访问次数(设置函数参数cache=False可以不用缓存机制).
# CACHE_DIR, 缓存目录, 若没有设置, 默认为 /user_home/.nmcdev/cache
# CACHE_DAYS, 缓存天数, 若没有设置, 默认为7, 即7天之前的缓存数据将被删除
[CACHE]
# CACHE_DIR = ~
CACHE_DAYS = 7

# CMADaaS大数据云平台配置:
#     DNS为IP地址, PORT为端口
#     USER_ID和PASSWORD分别为用户名和密码
#     serviceNodeId为服务节点名称(一般为 NMIC_MUSIC_CMADAAS)
[CMADaaS]
DNS = xx.xx.xx.xx
PORT = xx
USER_ID = xxxxxxxx
PASSWORD = xxxxxxxx
serviceNodeId = NMIC_MUSIC_CMADAAS

# MICAPS Cassandra服务器配置(一般需要联系运维开通访问权限)
#     GDS_IP为IP地址, GDS_PORT为端口
#     可以人为设置本地数据缓存的地址CACHE_DIR, 默认为配置文件夹目录下的cache文件夹
[MICAPS]
GDS_IP = xx.xx.xx.xx
GDS_PORT = 8080

# CIMISS网址及用户ID和PASSWORD, 2021年年底CIMISS停止提供服务
#     DNS为IP地址, PORT为端口
#     USER_ID和PASSWORD分别为用户名和密码
[CIMISS]
DNS = xx.xx.xx.xx
USER_ID = xxxxxxxxx
PASSWORD = xxxxxxxx

# 彩云天气API的访问口令
[CAIY]
token = xxxxxxxxxxxxxx

# MAPBOX地图数据的访问口令(nmc_met_graphics绘图可以用)
# https://docs.mapbox.com/help/glossary/access-token 申请
[MAPBOX]
token = xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

# 天地地图数据的访问口令(nmc_met_graphics绘图可以用)
# http://lbs.tianditu.gov.cn/server/MapService.html 申请
[TIANDITU]
token = xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

# 配置Cassandra集群访问接口
[Cassandra]
ClusterIPAddresses=Cassandra集群IP地址以“,”分隔，可以参考MICAPS4的配置文件配置
ClusterPort=Cassandra集群服务端口
KeySpace=Cassandra上数据存储的主键名
Package: nmcog
<div><img src=”https://raw.githubusercontent.com/myHBPwork/NMCog/master/resources/images/nmcogLogo4.png” alt=”CerebUnit” height=”23%” width=”15%” align=”right”></div># nmcog
Library for simulating cognitive models in neuromorphic platforms.Current target platforms
- [SpiNNaker](http://spinnakermanchester.github.io/)[nmcog documentation](https://nmcog.readthedocs.io/en/latest/)<div><img src=”https://raw.githubusercontent.com/myHBPwork/NMCog/master/resources/images/eu_logo.jpg” alt=”EU Logo” height=”23%” width=”15%” align=”right”></div>### ACKNOWLEDGEMENTS
This open source software code was developed in part or in whole in the Human Brain Project, funded from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 785907 (Human Brain Project SGA2).
Package: nmdb
Access the Neutron Monitor database with pythonThis package provides python functions to access data from theNeutron Monitor database.InstallationYou can install directly from PyPI usingpip install nmdbUsagenmdb_realtimeis an example to access realtime data,
as presented in atutorialat theNMDB hybrid conference in 2022.nmdb_nest_singleandnmdb_nest_multiare examples to get data from theNESTinterface into a pandas dataframe.
These examples use the nest module from the nmdb package to generate html strings to query NEST.nmdb_conf2022is the script that creates the coverpage plot for the 2022 NMDB conference.
The plot shows GLE70 data as downloaded from NMDB
(with the data header manually edited so that the data can be read easily with pandas).
The plots are created using seaborn.
Package: nmdc
About pynmdcPyNMDC is a Python package to work with NMDC data.More about NMDC:https://microbiomedata.org/Install (for developers only):Clone the repositorygit clone git@github.com:microbiomedata/pynmdc.gitc.gitSetupPackage intall using pypipynmdc$pipinstallnmdcGo to the pynmdc package root dir and run the following command
to install the package in developer mode,pynmdc$pipinstall-e.Test Command line interfacepynmdc$ nmdc --help
Usage: nmdc [OPTIONS] COMMAND [ARGS]...

  NMDC Tools v0.2.

Options:
  --help  Show this message and exit.

Commands:
  gff2json  Convert GFF3 to NMDC JSON format.Test the packageThe test_data directory contains two example gff files and the corresponding JSON outputs. Note that the stringnmdc:4ce9a799923b238585fc952135e5a0f5is an example activity id.MetaG_annotation$nmdcgff2json-ofsimple_feature.json-oasimple_func.json-ainmdc:4ce9a799923b238585fc952135e5a0f5simple_example.gffThis command will generate two json files:simple_feature.jsonhas the genome feature andsimple_func.jsonhas the functional annotation.The content of thesrc/nmdc/test_data/MetaG_annotation/simple_example.gfffile is:Ga0185794_41	GeneMark.hmm-2 v1.05	CDS	48	1037	56.13	+	0	ID=Ga0185794_41_48_1037;translation_table=11;start_type=ATG;product=5-methylthioadenosine/S-adenosylhomocysteine deaminase;product_source=KO:K12960;cath_funfam=3.20.20.140;cog=COG0402;ko=KO:K12960;ec_number=EC:3.5.4.28,EC:3.5.4.31;pfam=PF01979;superfamily=51338,51556```simple_feature.jsonlooks like this:{"genome_feature_set":[{"seqid":"nmdc:Ga0185794_41","start":48,"end":1037,"strand":"+","type":"SO:0000316","encodes":"nmdc:Ga0185794_41_48_1037"}]}simple_func.jsonlooks like this:{"functional_annotation_set":[{"subject":"nmdc:Ga0185794_41_48_1037","has_function":"5-methylthioadenosine/S-adenosylhomocysteine deaminase","was_generated_by":"nmdc:4ce9a799923b238585fc952135e5a0f5"},{"subject":"nmdc:Ga0185794_41_48_1037","has_function":"CATH:3.20.20.140","was_generated_by":"nmdc:4ce9a799923b238585fc952135e5a0f5"},{"subject":"nmdc:Ga0185794_41_48_1037","has_function":"EGGNOG:COG0402","was_generated_by":"nmdc:4ce9a799923b238585fc952135e5a0f5"},{"subject":"nmdc:Ga0185794_41_48_1037","has_function":"KEGG.ORTHOLOGY:K12960","was_generated_by":"nmdc:4ce9a799923b238585fc952135e5a0f5"},{"subject":"nmdc:Ga0185794_41_48_1037","has_function":"EC:3.5.4.28","was_generated_by":"nmdc:4ce9a799923b238585fc952135e5a0f5"},{"subject":"nmdc:Ga0185794_41_48_1037","has_function":"PFAM:PF01979","was_generated_by":"nmdc:4ce9a799923b238585fc952135e5a0f5"},{"subject":"nmdc:Ga0185794_41_48_1037","has_function":"SUPFAM:51338","was_generated_by":"nmdc:4ce9a799923b238585fc952135e5a0f5"}]}
Package: nmdc-mongo-tools
Tools for validation and storage of JSON data using theNMDC Schema.Getting Startedpip install nmdc-mongo-toolsCreate a.envfile in your working directory and add the following lines to it:NMDC_JSON_SCHEMA_URL=https://raw.githubusercontent.com/microbiomedata/nmdc-metadata/master/schema/nmdc.schema.json
NMDC_MONGO_HOST=<host>
NMDC_MONGO_USERNAME=<username>
NMDC_MONGO_PWD=<password>, setting appropriate values for connecting to a MongoDB instance. As an alternative toNMDC_JSON_SCHEMA_URL, you may
setNMDC_JSON_SCHEMA_FILEto be the path to your local copy of the NMDC Schema JSON file. You may also set your
environment variables any other way -- the.env-file approach is supported but not required.Then, import from thenmdc_mongopackage, e.g.fromnmdc_mongoimportget_dbdb=get_db("dwinston_share")db.list_collection_names()# ['metagenome_assembly_set', 'omics_processing_set', 'metaproteomics_analysis_activity_set', 'mags_activity_set',# 'read_QC_analysis_activity_set', 'nom_analysis_activity_set', 'biosample_set', 'read_based_analysis_activity_set',# 'study_set', 'metabolomics_analysis_activity_set', 'metagenome_annotation_activity_set', 'data_object_set',# 'raw.functional_annotation_set']
Package: nmdc-schema
National Microbiome Data Collaborative SchemaThe NMDC is a multi-organizational effort to integrate microbiome data across diverse areas in medicine, agriculture,
bioenergy, and the environment. This integrated platform facilitates comprehensive discovery of and access to
multidisciplinary microbiome data in order to unlock new possibilities with microbiome data science.This repository mainly defines aLinkMLschema for managing metadata from
theNational Microbiome Data Collaborative (NMDC).Repository Contents OverviewSome products that are maintained, and tasks orchestrated within this repository are:Maintenance of LinkML YAML that specifies the NMDC Schemasrc/schema/nmdc.yamland various other YAML schemas imported by it,
likeprov.yaml,annotation.yaml, etc. all which you can find
in thesrc/schemafolderMakefile targets for converting the schema from it's native LinkML YAML format to other artifact
likeJSON SchemaBuild, deployment and distribution of the schema as a PyPI packageAutomatic publishing of refreshed documentation upon change to the schema,
accessiblehereBackgroundThe NMDCIntroduction to metadata and ontologiesprimer provides some the context for this project.Maintaining the SchemaSeeDEVELOPMENT.mdfor instructions on setting up a development environment.SeeMAINTAINERS.mdfor instructions on using that development environment to maintain the schema.MakefilesMakefiles are text files people can use to tellmake(a computer program) how it canmakethings (or—in general—dothings). In the world of Makefiles, thosethingsare calledtargets.This repo contains 2 Makefiles:Makefile, based on the generic Makefile from theLinkML cookiecutterproject.Makefile, which containstargetsthat are specific to this projectHere's an example of usingmakein this repo:# Deletes all files in `examples/output`.makeexamples-cleanTheexamples-cleantargetis defined in theproject.Makefile. In this repo, theMakefileincludes theproject.Makefile. As a result,makehas access to thetargetsdefined in both files.Data downloadsThe NMDC's metadata about biosamples, studies, bioinformatics workflows, etc. can be obtained from our nmdc-runtime API.
Try entering "biosample_set" or "study_set" into thecollection_namebox
athttps://api.microbiomedata.org/docs#/metadata/list_from_collection_nmdcschema__collection_name__getOr use the API programmatically! Note that some collections are large, so the responses are paged.You can learn about the other available collections athttps://microbiomedata.github.io/nmdc-schema/Database/
Package: nmdc-submission-schema
submission-schemaThe home of the NMDC submission schema.Notthe home of sheets_and_friends. In development: GH pages hosted NMDC DataHarmonizer interface.Note that the while this repo is namedsubmission-schema, the generated artifacts are namednmdc_submission_schemafor disambiguation purposes when publishing to PyPI.Websitehttps://microbiomedata.github.io/submission-schemaRepository Structureexamples/- example dataproject/- project files (do not edit these)src/- source files (edit these)nmdc_submission_schemaschema-- LinkML schema (edit this)datamodel-- Generated python datamodeltests- python testsDeveloper DocumentationUse the `make` command to generate project artefacts:make all: make everythingmake deploy: deploys siteCreditsthis project was made withlinkml-project-cookiecutter