csvutil | command line tool for CSV | CSV Processing library
kandi X-RAY | csvutil Summary
kandi X-RAY | csvutil Summary
command line tool for CSV
Support
Quality
Security
License
Reuse
Top functions reviewed by kandi - BETA
- Name takes an io . Writer and writes it to w .
- Convert takes an io . Reader and writes it to w .
- Address is an alias for CSV .
- Collect collects CSV data from io . Reader .
- Combine is a convenience wrapper around CSV .
- Filter extracts CSV data from r and writes it to w .
- Sort reads data from r to w .
- Tail reads from r and writes to w .
- Build builds a CSV file from r .
- Email takes an io . Reader and writes the CSV to w .
csvutil Key Features
csvutil Examples and Code Snippets
Lines of Code : 16License : Permissive (MIT)
Copy$ csvutil generate --size 5 --count 10 --header 氏名:郵便番号:住所:建物:メール | \
csvutil name --name 氏名 | \
csvutil address --zip-code 郵便番号 --prefecture 住所 --city 住所 --town 住所 --block-number | \
csvutil building --column 建物 | \
csvutil email --column メー $ go get github.com/pinzolo/csvutil/cmd/csvutil
Community Discussions
Trending Discussions on csvutil
QUESTION
With the latest releases of Spring Boot 2.3.0, spring-graalvm-native 0.7.0.BUILD-SNAPSHOT, GraalVM 20.1.0.r11 and the corresponding blog posts
- https://spring.io/blog/2020/04/16/spring-tips-the-graalvm-native-image-builder-feature
- https://blog.codecentric.de/en/2020/05/spring-boot-graalvm
I also started to play around with one of my apps.
Luckily I was able to compile my app without any big hurdles. My compile.sh script looks as follows
ANSWER
Answered 2020-May-22 at 12:00Looks like adding following argument helps
-H:IncludeResources='.*/*.csv$'
QUESTION
I have a solution with a "Common" project. This "Common" project is used by other projects in the solution.
Within this "Common" project, I have a "Utilities" folder with several different utility classes, for example, "CsvUtilities.cs" and "JsonUtilities.cs". Assume that I could have many classes like this, and that all methods in these classes are pure functions. Based on this, it would make sense for these classes and methods to be static. Then from other projects I can import the common project and do things like:
...ANSWER
Answered 2020-Feb-26 at 21:46You can have Utilities.Json.StaticJsonMethod(); if you nest static class Json inside Utilities
QUESTION
ANSWER
Answered 2019-Sep-23 at 11:13I found this issue resolved. I've changed my code below and the title value is not junk for Japanese.
QUESTION
hello everyone i have created one Servlet file. it is downloading as a excel file but not containing any data in it while the code is made build for writing a data in excel file. Basically i have done this steps :- 1. access the data from the database 2.print that data to excel file. now up to this working as per the expectation but now at time of excel file gets downloaded. that time it is a blank excel file no data contains in that file. Why it is so Please Shed some light i have just started learning JAVA and SERVLET really new to this.
...ANSWER
Answered 2019-Jun-10 at 17:46Here is a version that writes to the response's outputstream. Note that I changed 'writer' to be an OutputStream instead of a FileWriter, as that is what you get from response.getOutputStream().
QUESTION
I'd like to infer a Spark.DataFrame schema from a directory of CSV files using a small subset of the rows (say limit(100)).
However, setting inferSchema to True means that the Input Size / Records for the FileScanRDD seems to always be equal to the number of rows in all the CSV files.
Is there a way to make the FileScan more selective, such that Spark looks at fewer rows when inferring a schema?
Note: setting the samplingRatio option to be < 1.0 does not have the desired behaviour, though it is clear that inferSchema uses only the sampled subset of rows.
ANSWER
Answered 2019-May-02 at 02:16You could read a subset of your input data into a dataSet of String. The CSV method allows you to pass this as a parameter.
Here is a simple example (I'll leave reading the sample of rows from the input file to you):
QUESTION
I was trying to integrate elasticsearch on my spring mvc project but i got error on this integration part error is org.springframework.beans.factory.BeanCreationException: Error creating bean with name 'elasticConfiguration'
...ANSWER
Answered 2019-Apr-29 at 08:31The latest version is 3.1.6, I believe. Maybe try updating it to that version.
Also you have a duplicate dependency for elasticsearch. One where you have version 3.0.8 and at the bottom where you have version 1.3.2, maybe remove this one as well.
The stacktrace is saying something about:
type org.elasticsearch.search.suggest.SuggestBuilder$SuggestionBuilder.
I dont see anything about this in the dependencies or imports, not sure if this matters.
QUESTION
I am developing a Spark Structured Streaming application that streams csv files and joins them with a static data. I have done some aggregation after join.
While writing the query result to HDFS in CSV format, I am getting the following error:
...ANSWER
Answered 2019-Jan-10 at 22:05The line where you do aggregation .groupBy(window($"event_time", "10 seconds", "5 seconds"), $"section", $"timestamp") creates the struct data type that is not supported by the CSV data source.
Just df_agg_without_time.printSchema and you see the column.
A solution is simply to transform it to some other simpler type (possibly with select or withColumn) or just select it out (i.e. not include in the following dataframe).
The following is a sample batch (non-streaming) structured query that shows the schema that your streaming structured query uses (when you create df_agg_without_time).
QUESTION
I can not export my dataframe to csv. The message "CSV data source does not support array"
predictions.write.option("delimiter", "\t").csv("/mnt/classification2018/testpredic2")
I tried this command but concated, but not sucess
...ANSWER
Answered 2018-Dec-19 at 18:54Cast the column to string and write to csv
QUESTION
I have following JSON, which I would like to convert into CSV.
Elements of JSON are going to be constant, if value is not present, then it will be null. But attribute will still be available.
I want to convert it into CSV with 9 columns.
I have flow like this =>
...ANSWER
Answered 2018-Oct-07 at 18:35Use ConvertRecord processor with
JsonPathReader as Record Reader
CsvSetWriter as Record Writer
JsonPathReader Configs:
As you are having static elements in the json so add new properties matching with the json path for all keys of the json message
AvroSchemaRegistry Configs:
This schema needs to match with the properties that we have added in JsonPathReader controller service.
CsvSetWriter Configs:
Input:
QUESTION
I am getting a CSV file from a 3rd party. Schema for this file is dynamic, the only thing I can be certain of is,
- each column with data will also have header name.
- file will always have a header.
- header name will always be a string of alphabets with no spaces and dots. (so, kind of "clean").
- values should be treated as strings, as I am not sure what they will be sending.
Now to use this type of data in my system, I am thinking of using MongoDB as staging area. As no. of columns, or order of columns, or columns name are not constant from one load to another. I think MongoDB will serve a good staging area.
I read about ConvertRecord processor, which is ideal for CSV to JSON converter, but I don't have a schema. I just want each row to go as a document, with header name as a key and value as value.
How should I go about it? Also this file is going to be in some 25-30 GB range, so I do not want to bring down my system.
I thought of doing it by my own processor (in Java), and I was able to get what I am looking for, but it seems to be taking too much time, and it kind of doesn't look optimal.
Let me know, if this can be achieved via existing processor?
Thanks, Rakesh
Updated on : 09/05/2018
a2bd0551-0165-1000-7c6a-a32ca4db047ccsv_to_json_no_schema_v191bc4a66-704c-3a2f-0000-000000000000defb04c4-c15c-3a07-0000-0000000000001 GB10000defb04c4-c15c-3a07-0000-000000000000bb6c25ae-f2b6-386a-0000-000000000000PROCESSOR0 sec1successdefb04c4-c15c-3a07-0000-000000000000eb6cd54a-e1f1-3871-0000-000000000000PROCESSOR0ad804e3c-f233-3556-0000-000000000000defb04c4-c15c-3a07-0000-0000000000001 GB10000defb04c4-c15c-3a07-0000-00000000000064b15a56-8a5f-3297-0000-000000000000PROCESSOR0 sec1invaliddefb04c4-c15c-3a07-0000-000000000000bb6c25ae-f2b6-386a-0000-000000000000PROCESSOR0c30bd123-c436-36ce-0000-000000000000defb04c4-c15c-3a07-0000-0000000000001 GB10000defb04c4-c15c-3a07-0000-0000000000008a0e37da-acd2-3d72-0000-000000000000PROCESSOR0 sec1validdefb04c4-c15c-3a07-0000-000000000000bb6c25ae-f2b6-386a-0000-000000000000PROCESSOR0247d2139-26b7-31fe-0000-000000000000defb04c4-c15c-3a07-0000-0000000000001 GB10000defb04c4-c15c-3a07-0000-0000000000001297bea9-b30f-3f45-0000-000000000000PROCESSOR0 sec1failuredefb04c4-c15c-3a07-0000-0000000000008a0e37da-acd2-3d72-0000-000000000000PROCESSOR045e5403f-99f7-3ddf-0000-000000000000defb04c4-c15c-3a07-0000-0000000000001 GB10000defb04c4-c15c-3a07-0000-0000000000009f8f32f7-130c-35bd-0000-000000000000PROCESSOR0 sec1successdefb04c4-c15c-3a07-0000-0000000000008a0e37da-acd2-3d72-0000-000000000000PROCESSOR088b0195a-34b2-34f0-0000-000000000000defb04c4-c15c-3a07-0000-000000000000nifi-record-serialization-services-narorg.apache.nifi1.6.0Schema Write StrategySchema Write Strategyschema-access-strategyschema-access-strategyschema-registryorg.apache.nifi.schemaregistry.services.SchemaRegistryschema-registryschema-nameschema-nameschema-versionschema-versionschema-branchschema-branchschema-textschema-textDate FormatDate FormatTime FormatTime FormatTimestamp FormatTimestamp FormatPretty Print JSONPretty Print JSONsuppress-nullssuppress-nullsJsonRecordSetWriterfalseSchema Write Strategyno-schemaschema-access-strategyschema-registryschema-nameschema-versionschema-branchschema-textDate FormatTime FormatTimestamp FormatPretty Print JSONsuppress-nullsENABLEDorg.apache.nifi.json.JsonRecordSetWriterc3e80a29-498b-36d4-0000-000000000000defb04c4-c15c-3a07-0000-000000000000nifi-record-serialization-services-narorg.apache.nifi1.6.0schema-access-strategyschema-access-strategyschema-registryorg.apache.nifi.schemaregistry.services.SchemaRegistryschema-registryschema-nameschema-nameschema-versionschema-versionschema-branchschema-branchschema-textschema-textcsv-reader-csv-parsercsv-reader-csv-parserDate FormatDate FormatTime FormatTime FormatTimestamp FormatTimestamp FormatCSV FormatCSV FormatValue SeparatorValue SeparatorSkip Header LineSkip Header Lineignore-csv-headerignore-csv-headerQuote CharacterQuote CharacterEscape CharacterEscape CharacterComment MarkerComment MarkerNull StringNull StringTrim FieldsTrim Fieldscsvutils-character-setcsvutils-character-setCSVReaderfalseschema-access-strategyschema-registryschema-nameschema-versionschema-branchschema-textcsv-reader-csv-parserDate FormatTime FormatTimestamp FormatCSV FormatValue SeparatorSkip Header Linetrueignore-csv-headertrueQuote CharacterEscape CharacterComment MarkerNull StringTrim Fieldscsvutils-character-setENABLEDorg.apache.nifi.csv.CSVReader8a0e37da-acd2-3d72-0000-000000000000defb04c4-c15c-3a07-0000-0000000000000.0227.99996948242188nifi-standard-narorg.apache.nifi1.6.0WARN1record-readerorg.apache.nifi.serialization.RecordReaderFactoryrecord-readerrecord-writerorg.apache.nifi.serialization.RecordSetWriterFactoryrecord-writerALLfalse30 secrecord-readerc3e80a29-498b-36d4-0000-000000000000record-writer88b0195a-34b2-34f0-0000-00000000000000 secTIMER_DRIVEN1 secConvertRecordfalsefailurefalsesuccessSTOPPEDorg.apache.nifi.processors.standard.ConvertRecord9f8f32f7-130c-35bd-0000-000000000000defb04c4-c15c-3a07-0000-00000000000011.0483.0nifi-standard-narorg.apache.nifi1.6.0WARN1Log LevelLog LevelLog PayloadLog PayloadAttributes to LogAttributes to Logattributes-to-log-regexattributes-to-log-regexAttributes to IgnoreAttributes to Ignoreattributes-to-ignore-regexattributes-to-ignore-regexLog prefixLog prefixcharacter-setcharacter-setALLfalse30 secLog LevelinfoLog PayloadfalseAttributes to Logattributes-to-log-regex.*Attributes to Ignoreattributes-to-ignore-regexLog prefixcharacter-setUTF-800 secTIMER_DRIVEN1 secLogAttributetruesuccessSTOPPEDorg.apache.nifi.processors.standard.LogAttributebb6c25ae-f2b6-386a-0000-000000000000defb04c4-c15c-3a07-0000-000000000000670.0225.0nifi-standard-narorg.apache.nifi1.6.0WARN1validate-csv-schemavalidate-csv-schemavalidate-csv-headervalidate-csv-headervalidate-csv-delimitervalidate-csv-delimitervalidate-csv-quotevalidate-csv-quotevalidate-csv-eolvalidate-csv-eolvalidate-csv-strategyvalidate-csv-strategyALLfalse30 secvalidate-csv-schemaNotNull,ParseInt(),Optional(ParseInt()),Nullvalidate-csv-headertruevalidate-csv-delimiter,validate-csv-quote"validate-csv-eol\nvalidate-csv-strategyLine by line validation00 secTIMER_DRIVEN1 secValidateCsvfalseinvalidfalsevalidSTOPPEDorg.apache.nifi.processors.standard.ValidateCsveb6cd54a-e1f1-3871-0000-000000000000defb04c4-c15c-3a07-0000-000000000000688.00.0nifi-standard-narorg.apache.nifi1.6.0WARN1File SizeFile SizeBatch SizeBatch SizeData FormatData FormatUnique FlowFilesUnique FlowFilesgenerate-ff-custom-textgenerate-ff-custom-textcharacter-setcharacter-setschema.nameschema.nameALLfalse30 secFile Size0BBatch Size1Data FormatTextUnique FlowFilesfalsegenerate-ff-custom-textname,age,int_val,address
Rakesh Prasad,0,99,"address 12 33333, 444441"
rakesh Prasad1,1,,"address 12 33333, 444442"
rakesh Prasad2,2,55,"address 12 33333, 444443"
rakesh Prasad3,,33,"address 12 33333, 444444"character-setUTF-8schema.nameempData01 dayTIMER_DRIVEN1 secGenerateFlowFilefalsesuccessSTOPPEDorg.apache.nifi.processors.standard.GenerateFlowFile1297bea9-b30f-3f45-0000-000000000000defb04c4-c15c-3a07-0000-000000000000450.0539.0nifi-standard-narorg.apache.nifi1.6.0WARN1Log LevelLog LevelLog PayloadLog PayloadAttributes to LogAttributes to Logattributes-to-log-regexattributes-to-log-regexAttributes to IgnoreAttributes to Ignoreattributes-to-ignore-regexattributes-to-ignore-regexLog prefixLog prefixcharacter-setcharacter-setALLfalse30 secLog LevelinfoLog PayloadfalseAttributes to Logattributes-to-log-regex.*Attributes to Ignoreattributes-to-ignore-regexLog prefixcharacter-setUTF-800 secTIMER_DRIVEN1 secLogAttributetruesuccessSTOPPEDorg.apache.nifi.processors.standard.LogAttribute64b15a56-8a5f-3297-0000-000000000000defb04c4-c15c-3a07-0000-000000000000837.0482.0000305175781nifi-standard-narorg.apache.nifi1.6.0WARN1Log LevelLog LevelLog PayloadLog PayloadAttributes to LogAttributes to Logattributes-to-log-regexattributes-to-log-regexAttributes to IgnoreAttributes to Ignoreattributes-to-ignore-regexattributes-to-ignore-regexLog prefixLog prefixcharacter-setcharacter-setALLfalse30 secLog LevelinfoLog PayloadfalseAttributes to Logattributes-to-log-regex.*Attributes to Ignoreattributes-to-ignore-regexLog prefixcharacter-setUTF-800 secTIMER_DRIVEN1 secLogAttributetruesuccessSTOPPEDorg.apache.nifi.processors.standard.LogAttribute09/05/2018 01:32:27 EDT
ANSWER
Answered 2018-Sep-04 at 13:04You can use ConvertRecord with a CSV Reader and in the CSV Reader choose "Use String Fields From Header" for the Schema Access Strategy. This will create a schema dynamically from the header.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install csvutil
Support
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page
