What is csv file in linux

Содержание

csv (1) — Linux Manuals
Command line options
AUTHOR
THANKS
BUGS
COPYRIGHT (The MIT License)
SEE ALSO
Pages related to csv
Reading and Writing CSV in Bash
Reading CSV in Bash
Writing CSV in Bash
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Best Practices for Working with CSV in Bash
Conclusion

csv (1) — Linux Manuals

CSV (comma-separated value) files are the lowest common denominator of structured data interchange formats. For such a humble file format, it is pretty difficult to get right: embedded quote marks and linebreaks, slipshod delimiters, and no One True Validity Test make CSV data found in the wild hard to parse correctly. Text::CSV_XS provides flexible and performant access to CSV files from Perl, but is cumbersome to use in one-liners and the command line.

csv is intended to make commandline processing of CSV files as easy as plain text is meant to be on Unix. Internally, it holds two Text::CSV objects (for input and for output), which have reasonable defaults but which you can reconfigure to suit your needs. Then you can extract just the fields you want, change the delimiter, clean up the data etc.

In the simplest usage, csv filters stdio and takes a list of integers. These are 1-based column numbers to select from the input CSV stream. Negative numbers are counted from the line end. Without any column list, csv selects all columns (this is still useful to normalize quoting style etc.).

Command line options

The following options are passed to Text::CSV. When preceded by the prefix «output_», the destination is affected. Otherwise these options affect both input and output. —quote_char —escape_char —sep_char —eol —always_quote —binary —keep_meta_info —allow_loose_quotes —allow_loose_escapes —allow_whitespace —verbatim

NOTE : binary is set to 1 by default in csv. The other options have their Text::CSV defaults.

The following additional options are available: —input, -i —output, -o Filenames for input and output. «-» means stdio. Useful to trigger TSV mode ("--from_tsv" and "--to_tsv"). —columns, -c Column numbers may be specified using this option. —fields, -f When this option is specified, the first line of the input file is considered as a header line. This option takes a comma-separated list of column-names from the first line.

For convenience, this option also accepts a comma-separated list of column numbers as well. Multiple —fields options are allowed, and both column names and numbers can be mixed together.

—from_tsv, —from-tsv —to_tsv, —to-tsv Use tabs instead of commas as the delimiter. When csv has the input or output filenames available, this is inferred when they end with ".tsv". To disable this dwimmery, you may say "--to_tsv=0" and "--from_tsv=0".

AUTHOR

THANKS

BUGS

Please report any bugs or feature requests to "bug-app-csv at rt.cpan.org", or through the web interface at . I will be notified, and then you’ll automatically be notified of progress on your bug as I make changes.

You’re also invited to work on a patch. The source repo is at

COPYRIGHT (The MIT License)

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.

Reading and Writing CSV in Bash

Comma-Separated Values (CSV) is a widely used file format for storing data in tabular form, where each row represents a record and each column represents a field within that record. The values are separated by a comma, which is why the format is called CSV. CSV is a popular data format for exchanging information between different platforms, programs, and applications, and typially adopts the form of:

col1,col2,col3 val1,val2,val3 val1,val2,val3 val1,val2,val3

Working with CSV files is a common task for many people who work in fields such as data analysis, software development, and system administration. Knowing how to read and write CSV files in a Bash environment is essential for automating tasks and processing large amounts of data efficiently.

In this article, we will look at various ways to read and write CSV files in Bash. We’ll explore the different tools available and provide examples of how to use them. Whether you’re a beginner or an experienced Bash user, this article will provide you with the information you need to effectively work with CSV files in your shell scripts.

Reading CSV in Bash

Now, we’ll take a look at how to extract data from a CSV file using tools available in a Bash environment.

Here’s an example of how to use awk to read a CSV file and extract its data:

# Read the CSV file while IFS="," read -r col1 col2 col3 do # Do something with the columns echo "Column 1: $col1" echo "Column 2: $col2" echo "Column 3: $col3" done < input.csv

In this example, the while loop reads the CSV file line by line, with each line being separated into columns using the IFS variable, which is initially set to ",". The read command then reads the columns into the variables col1 , col2 , and col3 . Finally, we use echo to print out the values of each column.

Alternatively, one of the most commonly used tools for reading CSV files in Bash is awk . awk is a powerful text-processing tool that can be used for a variety of tasks, including reading and processing CSV files. Here's an example command that prints the first two columns of a CSV file:

In this command, the -F ',' option specifies that the field separator is a comma, and tells awk to print out the first two columns of the file filename.csv . We can modify the command to print other columns or apply conditions on the fields.

If the CSV file has a different delimiter, we can modify the -F option to match it. For instance, if the CSV file uses tabs as a separator, we can use -F '\t' to split fields based on tabs. If the CSV file has a header row, we can skip it by using the NR>1 pattern before the statement.

In addition to awk , there are other tools available for reading CSV files in Bash, such as sed . sed is another text-processing tool that can be used to extract data from a CSV file.

While both awk and sed are powerful tools, they each have their own pros and cons. awk is often considered more flexible and easier to use, while sed is often considered faster and more efficient. The choice between these tools will depend on the specific requirements of your project.

Writing CSV in Bash

One of the simplest ways to write CSV files in Bash is to use the echo command and redirect its output to a file instead of the standard output pipe. For example:

#!/bin/bash # Write data to the CSV file echo "column1,column2,column3" > output.csv echo "data1,data2,data3" >> output.csv echo "data4,data5,data6" >> output.csv

In this example, we use the echo command to write the header row to the output.csv file. The > operator is used to create a new file or overwrite an existing file, while the >> operator is used to append data to an existing file. In this case, we use >> to add additional rows to the output.csv file.

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Another option for writing CSV files in Bash is to use printf . The printf command provides more control over the output format and is often used when writing to a file. For example:

#!/bin/bash # Write data to the CSV file using printf printf "column1,column2,column3\n" > output.csv printf "data1,data2,data3\n" >> output.csv printf "data4,data5,data6\n" >> output.csv

In this example, we use the printf command to write the header row and data rows to the output.csv file. The format string \n is used to add a newline character at the end of each row.

Best Practices for Working with CSV in Bash

When working with large or complex CSV files in Bash, we need to follow some best practices to avoid common pitfalls and improve performance. Here are some tips:

Use awk instead of sed or grep for complex CSV processing tasks: awk is optimized for handling large text files and can perform complex data transformations, filtering, and formatting. sed and grep are more suitable for simple text manipulation tasks and may be faster.
Avoid reading or writing to CSV files in a loop: Reading or writing CSV files in a loop can be slow and inefficient, especially for large files. Instead, try to use a single awk or echo command that handles all the rows at once.
Use a buffer when processing large CSV files: If the CSV file is too large to fit in memory, we can use a buffer to read or write the file in chunks. For example, we can use the head or tail command to read or write the first or last n lines of a file, or we can use a combination of awk and sed to read or write a specific chunk of rows.
Clean and format the data before processing: CSV files often contain missing or inconsistent data that can cause errors or unexpected results. Before processing a CSV file in Bash, we should clean and format the data using tools like tr , sed , or awk . For instance, we can remove extra spaces or newlines, convert data types, or remove special characters.
Test the commands on a small sample before applying them to the whole file: When processing a CSV file in Bash, it's important to test the commands on a small sample of the data to make sure they work as expected. We can use the head or tail command to extract a small subset of the CSV file and test our commands on it.

Conclusion

In conclusion, working with CSV files in Bash can be simple and efficient, as long as we follow some best practices and use the right tools.

By using awk and echo commands, we can read and write CSV files without relying on external tools or libraries. However, we need to be careful when processing large or complex CSV files and avoid common pitfalls, such as reading or writing to files in a loop or ignoring data cleaning and formatting.

With the tips and tricks we've covered in this article, we hope you'll be able to handle CSV files in Bash with ease and confidence.

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