Saravanan666/pypi-org huggingface dataset:
Package: cs.urlutils
URL related utility functions and classes.Cameron Simpsoncs@cskk.id.au26dec2011Latest release 20231129:Drop Python 2 support.No longer use cs.xml, which is going away.Make _URL type public as URL with a new promote() method, drop URL factory function, update URL constructors throughout.URL.init: make parameters keyword only.ClassNetrcHTTPPasswordMgr(urllib.request.HTTPPasswordMgrWithDefaultRealm, urllib.request.HTTPPasswordMgr)A subclass ofHTTPPasswordMgrWithDefaultRealmthat consults
the.netrcfile if no overriding credentials have been stored.Functionskip_errs(iterable)Iterate overiterableand yield its values.
If it raises URLError or HTTPError, report the error and skip the result.Functionstrip_whitespace(s)Strip whitespace characters from a string, per HTML 4.01 section 1.6 and appendix E.ClassURL(builtins.str, cs.deco.Promotable)Utility class to do simple stuff to URLs, subclassesstr.Release LogRelease 20231129:Drop Python 2 support.No longer use cs.xml, which is going away.Make _URL type public as URL with a new promote() method, drop URL factory function, update URL constructors throughout.URL.init: make parameters keyword only.Release 20191004:
Small updates for changes to other modules.Release 20160828:
Use "install_requires" instead of "requires" in DISTINFO.Release 20160827:Handle TimeoutError, reporting elapsed time.URL: present ._fetch as .GET.URL: add .resolve to resolve this URL against a base URL.URL: add .savepath and .unsavepath methods to generate nonconflicting save pathnames for URLs and the reverse.URL._fetch: record the post-redirection URL as final_url.New URLLimit class for specifying simple tests for URL acceptance.New walk(): method to walk website from starting URL, yielding URLs.URL.content_length property, returns int or None if header missing.New URL.normalised method to return URL with . and .. processed in the path.new URL.exists test function.Assorted bugfixes and improvements.Release 20150116:
Initial PyPI release.
Package: cs-util
cs_util packageUtility library for CosmoStatUsageDevelopmentReleaseAuthor:Martin KilbingerEmail:martin.kilbinger@cea.frYear: 2022ContentsLibraryGalaxy catalogue handlingWeak-lensing related cosmological quantities (e.g. surface mass density)VOS (Virtual Observatory Software)Command line loggingPlottingBasic statistic calculationsUNIONS/CFIS weak-lensing survey handling
Package: csv23
csv23provides the unicode-based API of the Python 3csvmodule for
Python 2 and 3. Code that should run under both versions of Python can use it
to hide thebytesvs.textdifference between 2 and 3 and stick to the
newer unicode-based interface.It usesutf-8as default encoding everywhere.Improvementscsv23works around for the following bugs in the stdlibcsvmodule:bpo-12178broken round-trip withescapecharif your data contains a literal escape
character (fixed in Python 3.10)bpo-31590broken round-trip withescapecharand embedded newlines under Python 2
(fixed in Python 3.4 but not backported): produce a warningLinksGitHub:https://github.com/xflr6/csv23PyPI:https://pypi.org/project/csv23/Documentation:https://csv23.readthedocs.ioChangelog:https://csv23.readthedocs.io/en/latest/changelog.htmlIssue Tracker:https://github.com/xflr6/csv23/issuesDownload:https://pypi.org/project/csv23/#filesExtrasThe package also provides some convenience functionality such as theopen_csv()context manager for opening a CSV file in the right mode and
returning acsv.readerorcsv.writer:>>>importcsv23>>>withcsv23.open_csv('spam.csv')asreader:# doctest: +SKIP...forrowinreader:...print(', '.join(row))Spam!,Spam!,Spam!'Spam!,LovelySpam!,LovelySpam!'Python 3 ExtrasTheread_csv()andwrite_csv()functions (available on Python 3 only)
are most useful if you want (or need to) open a file-like object in the calling
code, e.g. when reading or writing directly to a binary stream such as a ZIP
file controlled by the caller (emulated with aio.BytesIObelow):>>>importio>>>buf=io.BytesIO()>>>importzipfile>>>withzipfile.ZipFile(buf,'w')asz,z.open('spam.csv','w')asf:...csv23.write_csv(f,[[1,None]],header=['spam','eggs'])<zipfile...>>>>buf.seek(0)0>>>withzipfile.ZipFile(buf)asz,z.open('spam.csv')asf:...csv23.read_csv(f,as_list=True)[['spam','eggs'],['1','']]csv23internally wraps the byte stream in aio.TextIOWrapperwith the
given encoding andnewline=''(seecsvmoduledocs).Thewrite_csv()-function also supports updating objects with a.update(<bytes>)-method such ashashlib.new()instances, which allows
to calculate a checksum over the binary CSV file output produced from the given
rows without writing it to disk (note that the object is returned):>>>importhashlib>>>csv23.write_csv(hashlib.new('sha256'),[[1,None]],header=['spam','eggs']).hexdigest()'aed6871f9ca7c047eb55a569e8337af03fee508521b5ddfe7ad0ad1e1139980a'Both functions have an optionalautocompressargument: Set it toTrueto transparently compress (or decompress) if the file argument is a path that
ends in one of'.bz2','.gz', and'.xz'.InstallationThis package runs under Python 2.7, and 3.7+, usepipto install:$pipinstallcsv23See alsohttps://docs.python.org/2/library/csv.html#examples(UnicodeReader, UnicodeWriter)https://agate.readthedocs.io/en/latest/api/csv.htmlhttps://pypi.org/project/backports.csv/https://pypi.org/project/csv342/LicenseThis package is distributed under theMIT license.
Package: csv2arff
Usage$ csv2arff {input csv} {output arff}see help for other options:$ csv2arff -h

usage: csv2arff [-h] [-n NAME] [-d DELIMITER] [-v] input output

positional arguments:
  input                 input CSV file name
  output                output ARFF file name

optional arguments:
  -h, --help            show this help message and exit
  -n NAME, --name NAME  ARFF relation name
  -d DELIMITER, --delimiter DELIMITER
                        CSV delimiter
  -v, --verbose         verbose outputInstallation$ [sudo] pip install csv2arffCompatibilitySupported Python versions:2.73.33.43.5Testspip install -r requirements-dev.txt
make testContributions@deric
Package: csv2athena_schema
A Python Script to build a athena create table from csv fileFeaturesTODOInstall & Setup$gitclonehttps://github.com/yuokada/csv2athena_schema.git$pip3install-rrequirements.txtExecute script$python3scripts/csv2athena_schema.py\--table-propertiesskip.header.line.count=1has_encrypted_data=false\--schemayour_schema\--location's3://your_bucket/path_to_csv'/path/to/your.csvRequirementsPython >= 3.5LicenseMIT licensed. See the bundledLICENSEfile for more details.Linksloria/cookiecutter-docopt: A Python command-line script template that uses docopt for arguments parsingokfn/messytables: Tools for parsing messy tabular data. This is now superseded by https://github.com/frictionlessdata/tabulator-pypallets/jinja: The Jinja2 template engineFlake8: Your Tool For Style Guide Enforcement — flake8 3.7.2 documentationAthenaCREATE TABLE - Amazon AthenaSerDe Reference - Amazon AthenaCompression Formats - Amazon Athena
Package: csv2bq
csv2bqpython package for uploading local csv files to google bigqueryInstallation$pipinstallcsv2bqPrerequisitesPlace your service account key file in~/.config/gcloud/application_default_credentials.jsonUsage$csv2bqsample.csv--project_id=sample--dataset_id=sample--table_id=sampleOptionsParameterDescriptionproject_idproject id (required)dataset_iddataset id (required)table_idtable id (required)modeappend or overwrite (default: append)auto_create_tableauto create table (default: True)
Package: csv2bufr
csv2bufrThe csv2bufr Python module contains both a command line interface and an API to convert data stored in a CSV file to the WMO BUFR data format.
More information on the BUFR format can be found in theWMO Manual on Codes, Volume I.2.InstallationRequirementsPython 3 and aboveecCodesDependenciesDependencies are listed inrequirements.txt. Dependencies are automatically installed during csv2bufr installation.dockerpullwmoim/csv2bufrRunningTransform data from file<my-csv-file.csv>for station<wigos_station_identifier>to BUFR using template
specified in file<csv-to-bufr-mapping.json>and with station metadata file the file<metadata-file.csv>.
Write output to<output-directory-path>.csv2bufrdatatransform<my-csv-file.csv>\<wigos_station_identifier>\--station-metadata<metadata-file.csv>\--bufr-template<csv-to-bufr-mapping.json>\--output<output-directory-path>Releasing# create release (x.y.z is the release version)vicsv2bufr/__init__.py# update __version__gitcommit-am'update release version vx.y.z'gitpushoriginmain
gittag-avx.y.z-m'tagging release version vx.y.z'gitpush--tags# upload to PyPIrm-frbuilddist*.egg-info
pythonsetup.pysdistbdist_wheel--universal
twineuploaddist/*# publish release on GitHub (https://github.com/wmo-im/csv2bufr/releases/new)# bump version back to devvicsv2bufr/__init__.py# update __version__gitcommit-am'back to dev'gitpushoriginmainDocumentationThe full documentation for csv2bufr can be found athttps://csv2bufr.readthedocs.io, including sample files.Code ConventionsPEP8Bugs and IssuesAll bugs, enhancements and issues are managed onGitHub.ContactDavid Berry
Package: csv2dictionary
timeconMTA conversion from csv file to dictionary by Malphrus TechUsageimportfromcsv2dictionary.csvproimportCsvBrainusedatacase1=CsvBrain('test.csv')case1.data#returns a list of dictionaries#the first line in the csv are the keys in the dictionariesheaderscase1=CsvBrain('test.csv')case1.header_labels#returns a list of Header labelsSearchcase1=CsvBrain('test.csv')case1.search('dog')#returns a list of dict's that contain "dog" as a value under any keycastIntcase1=CsvBrain('test.csv')case1.castInt('age')#loops thru the list of dictionaries and changes cast all values under an 'age' key to integerscastIntcase1=CsvBrain('test.csv')case1.castFloat('age')#loops thru the list of dictionaries and changes cast all values under an 'age' key to Floats
Package: csv2geojson
csv2geojsonConvert csv to geojsonInstallationpipinstallcsv2geojsonDevelopmentgitclonehttps://github.com/YuChunTsao/csv2geojson.gitcdcsv2geojson

pipinstall-e'.[test]'CLI usageusage: csv2geojson [-h] [-v] [-lat lat] [-long long] [-exclude_columns [column_name ...] | -include_columns [column_name ...]]
                   input output

Convert csv to geojson

positional arguments:
  input                 Input csv file path
  output                Output geojson file path

options:
  -h, --help            show this help message and exit
  -v, --version         show program's version number and exit
  -lat lat              Specify the latitude column in csv (default: latitude)
  -long long            Specify the longitude column in csv (default: longitude)
  -exclude_columns [column_name ...]
                        Exclude columns from geojson properties (default: None)
  -include_columns [column_name ...]
                        Include only these columns in the geojson properties (default: None)
Package: csv2googlesheets
csv2googlesheetsПрограмма предназначена для извлечения данных из csv-файла и записи этих данных в Google Sheets.УстановкаЧтобы использовать эту программу, сначала нужно перейти по следующей ссылке:https://developers.google.com/sheets/api/quickstart/pythonИ выполнить требования в разделеPrerequisitesи в разделеStep 1: Turn on the Google Sheets APIПосле этого в командной строке:$ mkdir YOUR_NEW_DIR_NAME
$ cd YOU_NEW_DIR_NAME
$ python -m venv .venv
$ source .venv/bin/activate
(.venv) $ pip install csv2googlesheetsИспользование$ csv2g test_data/alpha_data.csv credentials.json

Created spreadsheet ID: 11potDwqU96ckscLNQeU1pm_GPwSuIx0NwlVl2K_uu0w
8 cells updated.
Package: csv2graph
csv2graph'csv2graph'is a Python class that can read a CSV file and create a NetworkX graph from its content.
DescriptionThe csv2graph class can read a CSV file and create a NetworkX graph from it, where the nodes and edges are defined by
the columns of the CSV file. The class provides methods to add nodes and edges to the graph, and allows to specify the
data to be stored in the nodes and edges. It also allows to define the mapping between the columns of the CSV file and
the attributes of the nodes and edges.
InstallationThe class can be installed via pip:pip install csv2graphExampleThis is an example of a CSV file that can be used to create a graph:id,id_person1,person1_firstname,person1_lastname,id_person2,person2_firstname,person2_lastname,relation_type,relation_mechanism,relation_date
1,1,Alice,Smith,2,Bob,Jones,Friend,Introduction,2022-02-18
2,3,Charlie,Chan,4,David,Lee,Colleague,Work,2021-11-05
3,2,Bob,Jones,3,Charlie,Chan,Friend,Shared Interest,2020-03-21
4,4,David,Lee,1,Alice,Smith,Enemy,Personal Conflict,2019-09-12For this example, I created two classes, Person and Relation, that represent the nodes and edges of the graph.# This is the class that represents the nodes of the graphclassPerson:fname=""lname=""# This is the class that represents the edges of the graphclassRelation:type=""mechanism=""date=""The following code creates a graph where each row of the CSV file represents a relation between two persons, and where
the attributes of the nodes are the first and last names of the persons.importcsv2graph# Create the csv2graph objectcsv2graph_obj=csv2graph('data.csv')# Add nodes to the graphcsv2graph_obj.add_node(Person,_id="identifier",_label="Person1",firstname='person1_firstname',lastname='person1_lastname')csv2graph_obj.add_node(Person,_id="identifier",_label="Person2",firstname='person2_firstname',lastname='person2_lastname')# Add edges to the graphcsv2graph_obj.add_edge(Relation,start_node="Person1",end_node="Person2",type="relation_type",mechanism="relation_mechanism",date="relation_date")# Create the graphgraph=csv2graph_obj.create_graph()# Print the nodes and edges of the graphprint(graph.nodes())print(graph.edges())TestsThe class comes with a test suite that can be run via pytest:pytest csv2graph.pyDependenciesThe class depends on the following Python packages:networkx
pandas
Package: csv2graphite
NAMEcsv2graphite - Send metrics in CSV CodaHale into a Graphite serverDESCRIPTIONOutput the graphite format to stdout.USAGEcsv2graphite [–version] [–prefix=PREFIX] CSV_DIRECTORYcsv2graphite -hEXAMPLEScsv2graphite /path/to/dir_that_contains_csv_file/ | localhost 2030LIMITATIONSINSTALLATIONSOURCE REPOSITORYcsv2graphite is currently hosted atgithub.ISSUES AND BUG REPORTSFeature requests and bug reports can be made here:https://github.com/bdelbosc/csv2graphite/issues
Package: csv2http
csv2httpCLI tool and library for making a series of JSON or form-encoded HTTP requests based on a CSV file input.Quick startInstallpip install csv2httpOr withpipx(recommended)pipx install csv2httpCheck CLI usage❯ csv2http --help
usage: csv2http [-h] [-c CONCURRENCY] [--method {POST,PATCH,PUT}] [-a AUTH] [-H [HEADER ...]] [-d] [-n] [-t TIMEOUT] file url

HTTP request for every row of a CSV file - v0.0.3a1

positional arguments:
  file                  payload csv file
  url                   URL destination - called with `http` if scheme is absent

options:
  -h, --help            show this help message and exit
  -c CONCURRENCY, --concurrency CONCURRENCY
                        Maximum number of concurrent requests (default: 25)
  --method {POST,PATCH,PUT}
                        HTTP method/verb (default: POST)
  -a AUTH, --auth AUTH  Basic Authentication enter <USERNAME>:<PASSWORD>. If password is blank you will be prompted for input
  -H [HEADER ...], --header [HEADER ...]
                        Header `key:value` pairs
  -d, --form-data       Send payload as form encoded data instead of JSON (default: false)
  -n, --no-save         Do not save results to log file (default: false)
  -t TIMEOUT, --timeout TIMEOUT
                        Connection timeout of the request in seconds (default: 5)Mockbin ExampleMake POST calls tohttp://mockbin.orgfrom a local csv file.First setup a newbin, usinghttpie, curl or theweb uiand get a bin id.❯ http POST mockbin.com/bin/create status:=201 statusText=Created httpVersion=HTTP/1.1 headers:='[]' cookies:='[]' 'content[mimeType]'=application/json --body
"9e95289e-d048-4515-9a61-07f2c74810f5"Create yourmy_file.csvand pass it tocsv2http.
Use the returned bin id from before.❯ csv2http my_file.csv mockbin.org/bin/9e95289e-d048-4515-9a61-07f2c74810f5 --concurrency 3
 POST http://mockbin.org/bin/mockbin.org/bin/9e95289e-d048-4515-9a61-07f2c74810f5
  status codes - {200: 3}
  status codes - {200: 3}
  status codes - {200: 3}
  status codes - {200: 1}Check the bin log from.https://mockbin.org/bin/9e95289e-d048-4515-9a61-07f2c74810f5/logSet Auth and HeadersHeader key, value pairs can be set with the-Hor-headerflag.Key value pairs should be separated with either a:or=.csv2http my_file.csv httpbin.org/post -H user-agent:csv2http-cli x-custom-header=foobarTo provide basic auth pass a username and password with-aor--auth.If the password is omitted you will be prompted to provide it.--auth my_username:my_password--auth my_usernameRoadmapAs Library - Alphaparse csv as dictionary/json - Alphaaccept mutator function - AlphaHTTP POST request with json from csv - Alphalimit concurrency - Alphanon-blocking file IO - ???hooks for response results - Betamkdoc docs - BetaAs CLI - Betaargparse - Alphawrite results to logfile - Betaprogress bar - ???use dedicated CLI library with pretty colors (typer, rich etc.) - BetaNested fields - V1Complete Docs - V1create_mockbin.csvandexample.csvto use in quickstart - Betaexamples for using as libraryGH Actions CI (lint, test, etc.)GH Actions CD (publish to pypi)
Package: csv2img
csv2imgThis is a project that save CSV file as PNG images.InstallationRun the following to install:pipinstallcsv2imgPre-requisiteTo use csv2img, make sure that you have installed the package of csv2pdf, fitz and PyMuPDF, since this package is a combination of csv2pdf and fitz.pipinstallcsv2pdfpipinstallfitz#please install fitz first, else it may crush with PyMuPDFpipinstallPyMuPDFUsagefromcsv2imgimportsaveassaveas(csv_file)Examplefromcsv2imgimportsaveassaveas("data.csv")Error HandlingIf the occured error is related to the packages of fitz and PyMuPDF, please uninstall these packages and install them again.pipuninstallfitzpipuninstallPyMuPDFpipinstallfitz#please install fitz first, else it may crush with PyMuPDFpipinstallPyMuPDF
Package: csv2json.py
csv2jsonA command-line utility that quickly and easily converts CSVs to JSON.UsageYou can install csv2json using PyPi and use it as follows:$pipinstallcsv2json.py
$cat<mycsv>|csv2json-p# See --help for more information.HelpAutilitytoconvertCSVstoJSONquicklyandeasily.

optionalarguments:-h,--helpshowthishelpmessageandexit-iINPUT,--inputINPUT-oOUTPUT,--outputOUTPUT-cINCLUDE_COLUMNS[INCLUDE_COLUMNS...],--include-columnsINCLUDE_COLUMNS[INCLUDE_COLUMNS...]-xEXCLUDE_COLUMNS[EXCLUDE_COLUMNS...],--exclude-columnsEXCLUDE_COLUMNS[EXCLUDE_COLUMNS...]-p,--pretty--indentINDENTContributingcsv2json.py welcomes contributions. Please submit PRs & issues as needed. Just don't be a dick.
Package: csv2md-tddschn
csv2mdCommand line tool for converting CSV files into Markdown tables.Installationcsv2md can be installed from source:# type in project directory
python setup.py installOr withpipfrom PyPI:pip install csv2mdRequirementsPython 3.6 or later. Seehttps://www.python.org/getit/UsageGenerate Markdown table from CSV file:csv2md table.csvGenerate Markdown table from TSV file:csv2md -d $'\t' table.tsvGenerate Markdown tables from list of CSV files:csv2md table1.csv table2.csv table3.csvGenerate Markdown table from standard input:csv2mdYou can also use it right inside your code, for example:fromcsv2md.tableimportTablewithopen("input.csv")asf:table=Table.parse_csv(f)print(table.markdown())ExamplesInput file:simple.csvyear,make,model,description,price
1997,Ford,E350,"ac, abs, moon",3000.00
1999,Chevy,"Venture «Extended Edition»","",4900.00
1996,Jeep,Grand Cherokee,"MUST SELL! air, moon roof, loaded",4799.00Output:csv2md simple.csv| year | make  | model                      | description                       | price   |
| ---- | ----- | -------------------------- | --------------------------------- | ------- |
| 1997 | Ford  | E350                       | ac, abs, moon                     | 3000.00 |
| 1999 | Chevy | Venture «Extended Edition» |                                   | 4900.00 |
| 1996 | Jeep  | Grand Cherokee             | MUST SELL! air, moon roof, loaded | 4799.00 |Markdown table:yearmakemodeldescriptionprice1997FordE350ac, abs, moon3000.001999ChevyVenture «Extended Edition»4900.001996JeepGrand CherokeeMUST SELL! air, moon roof, loaded4799.00You can also specify delimiter, quotation characters and alignment (seeHelp).HelpTo view help runcsv2md -h:usage: csv2md [-h] [-d DELIMITER] [-q QUOTECHAR] [-c [CENTER_ALIGNED_COLUMNS ...]] [-r [RIGHT_ALIGNED_COLUMNS ...]] [-H] [CSV_FILE ...]

Parse CSV files into Markdown tables.

positional arguments:
  CSV_FILE              One or more CSV files to parse

options:
  -h, --help            show this help message and exit
  -d DELIMITER, --delimiter DELIMITER
                        delimiter character. Default is ','
  -q QUOTECHAR, --quotechar QUOTECHAR
                        quotation character. Default is '"'
  -c [CENTER_ALIGNED_COLUMNS ...], --center-aligned-columns [CENTER_ALIGNED_COLUMNS ...]
                        column numbers with center alignment (from zero)
  -r [RIGHT_ALIGNED_COLUMNS ...], --right-aligned-columns [RIGHT_ALIGNED_COLUMNS ...]
                        column numbers with right alignment (from zero)
  -H, --no-header-row   specify that the input CSV file has no header row. Will create default headers in Excel format (a,b,c,...)Running TestsTo run the tests, enter:nosetestIssue trackerPlease report any bugs and enhancement ideas using the csv2md issue tracker:https://github.com/lzakharov/csv2md/issuesFeel free to also ask questions on the tracker.LicenseCopyright (c) 2023 Lev Zakharov. Licensed underthe MIT License.
Package: csv-2-mongo
csv-2-mongoImport a CSV to MongoDB using Python 🐍.Installation$pipinstallcsv-2-mongoUsageUsage: csv_2_mongo.py [OPTIONS] FILE

  Import a csv FILE to MongoDB

Options:
  -h, --help             Show this message and exit.
  -v, --version          Show the version and exit.
  -d, --database name    Database name.  [default: test]
  -c, --collection name  Collection name.  [default: test]
  -H, --host host        Host name.  [default: 0.0.0.0]
  -p, --port port        Port number.  [default: 27017]
  -t, --timeout sec      Connection timeout (seconds).  [default: 5]
  -f, --force            Overwrite collection if exists.
  -y, --yes              Automatic yes to prompts.Note: CSV headers arerequiredto correctly correlate MongoDBfieldsto CSVfields.ExamplesImportmammals.csvto amammalscollection in theanimalsdatabase:$csv-2-mongo-danimals-cmammals./mammals.csv....................................
Connecting to 0.0.0.0:27017
....................................

Import data.csv to database=animals collection=mammals [y/N]? y
Import complete!Importmammals.csvto amammalscollection in theanimalsdatabaseoverwriting the collection if it exists:Note: the-f, --forceflag will overwrite the collection without a prompt. If the flag is omitted,csv-2-mongowill prompt you before operations with potential data loss.$csv-2-mongo-f-danimals-cmammals./mammals.csv....................................
Connecting to 0.0.0.0:27017
....................................

Import data.csv to database=animals collection=mammals [y/N]? y
Import complete!Importmammals.csvto amammalscollection in theanimalsdatabase running onhostmongo.travismclarke.comatport27111:$csv-2-mongo-danimals-cmammals-Hmongo.travismclarke.com-p27111./mammals.csv....................................
Connecting to mongo.travismclarke.com:27111
....................................

Import data.csv to database=animals collection=mammals [y/N]? y
Import complete!To skip the prompt (e.g.Import data.csv to ...), such as running via a script, one can pass the-y,--yesflag to force ayesresponse to the confirmation prompt:Note: this will not suppress theoverwriteprompt which still requires the-f, --forceflag.$csv-2-mongo-y-danimals-cmammals./mammals.csv....................................
Connecting to 0.0.0.0:27017
....................................

Import complete!LicenseMIT ©Travis Clarke