A utility library that provides a consistent interface for reading tabular data.
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)
[](https://gitter.im/frictionlessdata/chat)
A utility library that provides a consistent interface for reading tabular data.
## Getting Started
### Installation
To get started (under development):
```
$ pip install tabulator
```
### Quick Start
Fast access to the table with `topen` (stands for `table open`) function:
```python
from tabulator import topen, processors
with topen('path.csv', headers='row1') as table:
for row in table:
print(row) # will print row tuple
```
For the most use cases `topen` function is enough. It takes the
`source` argument:
```
<scheme>://path/to/file.<format>
```
and uses corresponding `Loader` and `Parser` to open and start to iterate
over the table. Also user can pass `scheme` and `format` explicitly
as function arguments. User can force Tabulator to use encoding of choice
to open the table passing `encoding` argument.
Function `topen` returns `Table` instance. We use context manager
to call `table.open()` on enter and `table.close()` when we exit:
- table can be iterated like file-like object returning row by row
- table can be used for manual iterating with `table.iter(keye/extended=False)`
- table can be read into memory using `read` function (return list or row tuples)
with `limit` of output rows as parameter.
- headers can be accessed via `headers` property
- rows sample can be accessed via `samle` property
- table pointer can be set to start via `reset` method.
### Advanced Usage
To get full control over the process you can use more parameters.
Below the more expanded example is presented:
```python
from tabulator import topen, loaders, parsers, processors
def skip_odd_rows(extended_rows):
for number, headers, row in extended_rows:
if number % 2:
yield (number, headers, row)
table = topen('path.csv', headers='row1', encoding='utf-8', sample_size=1000,
post_parse=[processors.skip_blank_rows, skip_odd_rows]
loader_options={'constructor': loaders.File},
parser_options={'constructor': parsers.CSV, delimeter': ',', quotechar: '|'})
print(table.samle) # will print sample
print(table.headers) # will print headers list
print(table.read(limit=10)) # will print 10 rows
table.reset()
for keyed_row in table.iter(keyed=True):
print keyed_row # will print row dict
for extended_row in table.iter(extended=True):
print extended_row # will print (number, headers, row) list
table.close()
```
## Read more
- [Documentation](https://github.com/frictionlessdata/tabulator-py/tree/master/tabulator)
- [Changelog](https://github.com/frictionlessdata/tabulator-py/releases)
- [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)
[](https://gitter.im/frictionlessdata/chat)
A utility library that provides a consistent interface for reading tabular data.
## Getting Started
### Installation
To get started (under development):
```
$ pip install tabulator
```
### Quick Start
Fast access to the table with `topen` (stands for `table open`) function:
```python
from tabulator import topen, processors
with topen('path.csv', headers='row1') as table:
for row in table:
print(row) # will print row tuple
```
For the most use cases `topen` function is enough. It takes the
`source` argument:
```
<scheme>://path/to/file.<format>
```
and uses corresponding `Loader` and `Parser` to open and start to iterate
over the table. Also user can pass `scheme` and `format` explicitly
as function arguments. User can force Tabulator to use encoding of choice
to open the table passing `encoding` argument.
Function `topen` returns `Table` instance. We use context manager
to call `table.open()` on enter and `table.close()` when we exit:
- table can be iterated like file-like object returning row by row
- table can be used for manual iterating with `table.iter(keye/extended=False)`
- table can be read into memory using `read` function (return list or row tuples)
with `limit` of output rows as parameter.
- headers can be accessed via `headers` property
- rows sample can be accessed via `samle` property
- table pointer can be set to start via `reset` method.
### Advanced Usage
To get full control over the process you can use more parameters.
Below the more expanded example is presented:
```python
from tabulator import topen, loaders, parsers, processors
def skip_odd_rows(extended_rows):
for number, headers, row in extended_rows:
if number % 2:
yield (number, headers, row)
table = topen('path.csv', headers='row1', encoding='utf-8', sample_size=1000,
post_parse=[processors.skip_blank_rows, skip_odd_rows]
loader_options={'constructor': loaders.File},
parser_options={'constructor': parsers.CSV, delimeter': ',', quotechar: '|'})
print(table.samle) # will print sample
print(table.headers) # will print headers list
print(table.read(limit=10)) # will print 10 rows
table.reset()
for keyed_row in table.iter(keyed=True):
print keyed_row # will print row dict
for extended_row in table.iter(extended=True):
print extended_row # will print (number, headers, row) list
table.close()
```
## Read more
- [Documentation](https://github.com/frictionlessdata/tabulator-py/tree/master/tabulator)
- [Changelog](https://github.com/frictionlessdata/tabulator-py/releases)
- [Contribute](CONTRIBUTING.md)
Thanks!
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
tabulator-0.5.0.tar.gz
(12.9 kB
view hashes)
Built Distribution
Close
Hashes for tabulator-0.5.0-py2.py3-none-any.whl
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | d66d7fcf016b06d9e0ebd14a310cd28180b27b9dd30adf9088d8fbfb28f862e9 |
|
| MD5 | 91fa34211385f4765e48d8efb8e07c8a |
|
| BLAKE2b-256 | a2488ca1e88538a42b4c845e12d323c8c4af1ba4d502ba18b35b181d8095b0a6 |
