Consistent interface for stream reading and writing tabular data (csv/xls/json/etc)
Project description
# tabulator-py
[](https://travis-ci.org/frictionlessdata/tabulator-py)
[](https://coveralls.io/r/frictionlessdata/tabulator-py?branch=master)
[](https://pypi-hypernode.com/pypi/tabulator)
[](http://semver.org/)
[](https://gitter.im/frictionlessdata/chat)
Consistent interface for stream reading and writing tabular data (csv/xls/json/etc).
> Release `v0.10` contains changes in `exceptions` module introduced in NOT backward-compatibility manner.
## Features
- supports various formats: csv/tsv/xls/xlsx/json/ndjson/ods/gsheet/native/etc
- reads data from variables, filesystem or Internet
- streams data instead of using a lot of memory
- processes data via simple user processors
- saves data using the same interface
## Getting Started
### Installation
To get started:
```
$ pip install tabulator
```
### Example
Open tabular stream from csv source:
```python
from tabulator import Stream
with Stream('path.csv', headers=1) as stream:
print(stream.headers) # will print headers from 1 row
for row in stream:
print(row) # will print row values list
```
### Stream
`Stream` takes the `source` argument:
```
<scheme>://path/to/file.<format>
```
and uses corresponding `Loader` and `Parser` to open and start to iterate over the tabular stream. Also user can pass `scheme` and `format` explicitly as constructor arguments. User can force Tabulator to use encoding of choice to open the table passing `encoding` argument.
In this example we use context manager to call `stream.open()` on enter and `stream.close()` when we exit:
- stream can be iterated like file-like object returning row by row
- stream can be used for manual iterating with `iter(keyed/extended)` function
- stream can be read into memory using `read(keyed/extended)` function with row count `limit`
- headers can be accessed via `headers` property
- rows sample can be accessed via `sample` property
- stream pointer can be set to start via `reset` method
- stream could be saved to filesystem using `save` method
Below the more expanded example is presented:
```python
from tabulator import Stream
def skip_even_rows(extended_rows):
for number, headers, row in extended_rows:
if number % 2:
yield (number, headers, row)
stream = Stream('http://example.com/source.xls',
headers=1, encoding='utf-8', sample_size=1000,
post_parse=[skip_even_rows], sheet=1)
stream.open()
print(stream.sample) # will print sample
print(stream.headers) # will print headers list
print(stream.read(limit=10)) # will print 10 rows
stream.reset()
for keyed_row in stream.iter(keyed=True):
print keyed_row # will print row dict
for extended_row in stream.iter(extended=True):
print extended_row # will print (number, headers, row)
stream.reset()
stream.save('target.csv')
stream.close()
```
For the full list of options see - https://github.com/frictionlessdata/tabulator-py/blob/master/tabulator/stream.py#L17
### CLI
> It's a provisional API excluded from SemVer. If you use it as a part of other program please pin concrete `goodtables` version to your requirements file.
The library ships with a simple CLI to read tabular data:
```bash
$ tabulator
Usage: cli.py [OPTIONS] SOURCE
Options:
--headers INTEGER
--scheme TEXT
--format TEXT
--encoding TEXT
--limit INTEGER
--help Show this message and exit.
```
Shell usage example:
```bash
$ tabulator data/table.csv
id, name
1, english
2, 中国人
```
## API Reference
### Snapshot
```
Stream(source,
headers=None,
scheme=None,
format=None,
encoding=None,
sample_size=None,
post_parse=None,
**options)
closed/open/close/reset
headers -> list
sample -> rows
iter(keyed/extended=False) -> (generator) (keyed/extended)row[]
read(keyed/extended=False, limit=None) -> (keyed/extended)row[]
save(target, format=None, encoding=None, **options)
exceptions
~cli
```
### Detailed
- [Docstrings](https://github.com/frictionlessdata/tabulator-py/tree/master/tabulator)
- [Changelog](https://github.com/frictionlessdata/tabulator-py/commits/master)
## Contributing
Please read the contribution guideline:
[How to Contribute](CONTRIBUTING.md)
Thanks!
[](https://travis-ci.org/frictionlessdata/tabulator-py)
[](https://coveralls.io/r/frictionlessdata/tabulator-py?branch=master)
[](https://pypi-hypernode.com/pypi/tabulator)
[](http://semver.org/)
[](https://gitter.im/frictionlessdata/chat)
Consistent interface for stream reading and writing tabular data (csv/xls/json/etc).
> Release `v0.10` contains changes in `exceptions` module introduced in NOT backward-compatibility manner.
## Features
- supports various formats: csv/tsv/xls/xlsx/json/ndjson/ods/gsheet/native/etc
- reads data from variables, filesystem or Internet
- streams data instead of using a lot of memory
- processes data via simple user processors
- saves data using the same interface
## Getting Started
### Installation
To get started:
```
$ pip install tabulator
```
### Example
Open tabular stream from csv source:
```python
from tabulator import Stream
with Stream('path.csv', headers=1) as stream:
print(stream.headers) # will print headers from 1 row
for row in stream:
print(row) # will print row values list
```
### Stream
`Stream` takes the `source` argument:
```
<scheme>://path/to/file.<format>
```
and uses corresponding `Loader` and `Parser` to open and start to iterate over the tabular stream. Also user can pass `scheme` and `format` explicitly as constructor arguments. User can force Tabulator to use encoding of choice to open the table passing `encoding` argument.
In this example we use context manager to call `stream.open()` on enter and `stream.close()` when we exit:
- stream can be iterated like file-like object returning row by row
- stream can be used for manual iterating with `iter(keyed/extended)` function
- stream can be read into memory using `read(keyed/extended)` function with row count `limit`
- headers can be accessed via `headers` property
- rows sample can be accessed via `sample` property
- stream pointer can be set to start via `reset` method
- stream could be saved to filesystem using `save` method
Below the more expanded example is presented:
```python
from tabulator import Stream
def skip_even_rows(extended_rows):
for number, headers, row in extended_rows:
if number % 2:
yield (number, headers, row)
stream = Stream('http://example.com/source.xls',
headers=1, encoding='utf-8', sample_size=1000,
post_parse=[skip_even_rows], sheet=1)
stream.open()
print(stream.sample) # will print sample
print(stream.headers) # will print headers list
print(stream.read(limit=10)) # will print 10 rows
stream.reset()
for keyed_row in stream.iter(keyed=True):
print keyed_row # will print row dict
for extended_row in stream.iter(extended=True):
print extended_row # will print (number, headers, row)
stream.reset()
stream.save('target.csv')
stream.close()
```
For the full list of options see - https://github.com/frictionlessdata/tabulator-py/blob/master/tabulator/stream.py#L17
### CLI
> It's a provisional API excluded from SemVer. If you use it as a part of other program please pin concrete `goodtables` version to your requirements file.
The library ships with a simple CLI to read tabular data:
```bash
$ tabulator
Usage: cli.py [OPTIONS] SOURCE
Options:
--headers INTEGER
--scheme TEXT
--format TEXT
--encoding TEXT
--limit INTEGER
--help Show this message and exit.
```
Shell usage example:
```bash
$ tabulator data/table.csv
id, name
1, english
2, 中国人
```
## API Reference
### Snapshot
```
Stream(source,
headers=None,
scheme=None,
format=None,
encoding=None,
sample_size=None,
post_parse=None,
**options)
closed/open/close/reset
headers -> list
sample -> rows
iter(keyed/extended=False) -> (generator) (keyed/extended)row[]
read(keyed/extended=False, limit=None) -> (keyed/extended)row[]
save(target, format=None, encoding=None, **options)
exceptions
~cli
```
### Detailed
- [Docstrings](https://github.com/frictionlessdata/tabulator-py/tree/master/tabulator)
- [Changelog](https://github.com/frictionlessdata/tabulator-py/commits/master)
## Contributing
Please read the contribution guideline:
[How to Contribute](CONTRIBUTING.md)
Thanks!
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