# Frictionless Framework
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Frictionless is a framework to describe, extract, validate, and transform tabular data (DEVT Framework). It supports a great deal of data schemes and formats, as well as provides popular platforms integrations. The framework is powered by the lightweight yet comprehensive [Frictionless Data Specifications](https://specs.frictionlessdata.io/).
## Purpose
- **Describe your data**: You can infer, edit and save metadata of your data tables. It's a first step for ensuring data quality and usability. Frictionless metadata includes general information about your data like textual description, as well as, field types and other tabular data details.
- **Extract your data**: You can read your data using a unified tabular interface. Data quality and consistency are guaranteed by a schema. Frictionless supports various file schemes like HTTP, FTP, and S3 and data formats like CSV, XLS, JSON, SQL, and others.
- **Validate your data**: You can validate data tables, resources, and datasets. Frictionless generates a unified validation report, as well as supports a lot of options to customize the validation process.
- **Transform your data**: You can clean, reshape, and transfer your data tables and datasets. Frictionless provides a pipeline capability and a lower-level interface to work with the data.
## Features
- Open Source (MIT)
- Powerful Python framework
- Convenient command-line interface
- Low memory consumption for data of any size
- Reasonable performance on big data
- Support for compressed files
- Custom checks and formats
- Fully pluggable architecture
- The included API server
- More than 1000+ tests
## Example
```bash
$ frictionless validate data/invalid.csv
[invalid] data/invalid.csv
row field code message
----- ------- ---------------- --------------------------------------------
3 blank-header Header in field at position "3" is blank
4 duplicate-header Header "name" in field "4" is duplicated
2 3 missing-cell Row "2" has a missing cell in field "field3"
2 4 missing-cell Row "2" has a missing cell in field "name2"
3 3 missing-cell Row "3" has a missing cell in field "field3"
3 4 missing-cell Row "3" has a missing cell in field "name2"
4 blank-row Row "4" is completely blank
5 5 extra-cell Row "5" has an extra value in field "5"
```
## Documentation
Please visit our documentation portal:
- https://framework.frictionlessdata.io/docs/guides/quick-start
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PyPI 官网下载 | frictionless-4.17.5.tar.gz (166个子文件)
setup.cfg 67B
MANIFEST.in 125B
pytest.ini 222B
pylama.ini 152B
fiscal.json 222KB
tabular.json 104KB
tabular.json 82KB
general.json 62KB
general.json 22KB
topojson.json 10KB
general.json 10KB
general.json 8KB
report.json 6KB
pipeline.json 782B
status.json 635B
inquiry.json 587B
Makefile 1KB
README.md 3KB
AUTHORS.md 2KB
LICENSE.md 1KB
not-zip-safe 1B
PKG-INFO 5KB
PKG-INFO 5KB
resource.py 39KB
test_resource.py 36KB
package.py 22KB
excel.py 21KB
sql.py 19KB
table.py 16KB
bigquery.py 15KB
ckan.py 15KB
helpers.py 14KB
test_package.py 14KB
field.py 14KB
row.py 12KB
detector.py 11KB
system.py 11KB
layout.py 11KB
schema.py 10KB
metadata.py 10KB
loader.py 9KB
field.py 9KB
report.py 8KB
pandas.py 8KB
csv.py 8KB
validate.py 8KB
header.py 7KB
row.py 7KB
spss.py 7KB
json.py 6KB
cell.py 6KB
file.py 6KB
extract.py 6KB
resource.py 6KB
heuristic.py 6KB
test_resource.py 6KB
remote.py 5KB
describe.py 5KB
cell.py 5KB
regulation.py 5KB
status.py 5KB
inline.py 5KB
pipeline.py 5KB
s3.py 5KB
ods.py 5KB
test_package.py 4KB
common.py 4KB
multipart.py 4KB
parser.py 4KB
general.py 4KB
test_inquiry.py 4KB
inquiry.py 4KB
gsheets.py 4KB
html.py 4KB
resource.py 4KB
test_main.py 4KB
baseline.py 3KB
server.py 3KB
setup.py 3KB
package.py 3KB
plugin.py 3KB
stream.py 3KB
resource.py 3KB
settings.py 3KB
label.py 3KB
test_resource.py 3KB
test_pipeline.py 3KB
row.py 2KB
number.py 2KB
geopoint.py 2KB
buffer.py 2KB
check.py 2KB
local.py 2KB
test_main.py 2KB
test_package.py 2KB
transform.py 2KB
package.py 1KB
error.py 1KB
date.py 1KB
main.py 1KB
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