https://github.com/antman261/csvputty
https://github.com/antman261/csvputty
Last synced: 4 days ago
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- Host: GitHub
- URL: https://github.com/antman261/csvputty
- Owner: Antman261
- License: mit
- Created: 2017-04-03T05:33:04.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2017-06-07T05:16:21.000Z (almost 8 years ago)
- Last Synced: 2025-04-21T01:56:11.182Z (7 days ago)
- Language: Python
- Size: 22.5 KB
- Stars: 2
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# csvputty
_Command-fu with csv files_
A set of command line interfaces and python modules for easily manipulating, transforming and dealing with csv files quickly and effectively.
## Installation
`$ pip install csvputty`
csvputty is now available in the commandline, try `$ csvputty --help` or `import csvputty` in a project!
## CLI Usage
All csvputty commands start with `csvputty`, optionally any input/output files you wish to use, and then the command you wish to perform.
If you do not supply i/o files then csvputty will use stdin/stdout instead.
`$ csvputty -i data.csv -o out.txt [COMMAND]`
### markup
This command will take the selected columns of a CSV file, process each row through a format string, and return the collective output.
```bash
$ csvputty -i data.csv markup 0 1 3 template.html
```
This parses each row of `data.csv` using the content of `template.html` as a format string, printing the results to stdout.
In the above example, `template.html` could be the following:
```html
{}
{}
{}
```
or if used with the `-h --header` flag the first row of the CSV is used to key the template.
```html
{coconuts}
{cheese}
{sausages}
```
However csvputty really becomes useful in the full context of the command line. Take the following example:
`$ cat data1.csv data2.csv | csvputty markup 0 1 template.html > rendered.html`
This passes `data1.csv` and `data2.csv` through the same template and renders them together in a single file.
`csvputty -i data.csv markup 0 1 -`
This opens stdin allowing you to enter the template via command line and prints the results to stdout.
### diff
Diff compares the input CSV against another CSV and outputs rows where selected columns fulfil the match condition.
`$ cat subtract1.csv subtract2.csv | csvputty -i source.csv -o out.csv diff -sc 18 -`
The above example returns rows from `source.csv` where column 18 is not found on column column 0 anywhere in `subtract1.csv` or `subtract2.csv`.
## Package Usage
Importing csvputty into your project allows you to use some features unavailable via the command line interface.
For example:
```python
import csvputty
def parse_row(row):
for idx, col in enumerate(row):
row[idx] = col.strip().replace("&", "&")
img_url = row[2].lower().replace(" ", "_").replace('&', 'and')
insta_url = row[4].replace("@", "")
return (img_url, row[1], insta_url, row[3], row[6])
input = open('data.csv', 'r')
out = open('rendered.html', 'w')
template = open('template.html', 'r')
csvputty.markup.generate(custom_row_parser=parse_row, csv_file=input
template_file=template, out_file=out)
```
The above example allows me to strip whitespace and replace ampersands with html entities on all columns, and perform further processing on other columns.