Table reader for simple reStructuredText tables
Project description
TableRead is a script designed to read reStructredText (reST) simple tables from a file and convert them into Python objects.
Quickstart
Say you have a simple table like this located in a ./example.rst:
++++++++++++ Damage Doers ++++++++++++ ====== === ============== Name Age Favorite Color ====== === ============== Mookie 26 Red Andrew 24 Red JD 31 Red Xander 26 Red ====== === ==============
Here are a few useful things you can do with that table:
>>> from tableread import SimpleRSTReader >>> >>> reader = SimpleRSTReader("./example.rst") >>> reader.tables ['Damage Doers'] >>> >>> table = reader["Damage Doers"] >>> table.fields ['name', 'age', 'favorite_color'] >>> >>> for row in table: ... print(row.favorite_color) ... Red Red Red Red >>> >>> for row in table.matches_all(age="26"): ... print(row.name) ... Mookie Xander >>> >>> for row in table.exclude_by(age="26"): ... print(row.name) ... Andrew JD
Usage
class tableread.SimpleRSTReader(file_path)
Parse a reStructredText file, file_path, and convert any simple tables into SimpleRSTTable objects. Individual tables can be accessed using the table name as the key (SimpleRSTReader['table_name'])
- data
An OrderedDict of the table(s) found in the reST file. The key is either the section header before the table name from the file, or Default for tables not under a header. For multiple tables in a section (or multiple Default tables), subsequent tables will have a incrementing number appended to the key: Default, Default_2, etc. The value is a SimpleRSTTable object.
- tables
A list of the table names; an alias for list(data.keys())
- first
A helper to get the first table found in the file; an alias for list(self.data.values())[0]
class tableread.SimpleRSTTable(header, rows, column_spans)
A representation of an individual table. In addition to the methods below, you may iterate over the table itself as a shortcut (for entry in table:), which will yield from table.data. len(table) will also return the number of entries in table.data.
- data
A list of namedtuples with fields as the names.
- fields
A tuple of the table fields, as used in the data namedtuple. Field names are adapted from table columns by lower-casing, and replacing spaces and periods with underscores.
- from_data(data)
A helper function to create an object with. Expects a prepared list of namedtuples.
- matches_all(**kwargs)
Given a set of key/value filters, returns a new TableRead object with only the filtered data, that can be iterated over. Values may be either a simple value (str, int) or a function that returns a boolean. See Quickstart for an example.
Note: When filtering both keys and values are not case sensitive.
- exclude_by(**kwargs)
Given a set of key/value filters, returns a new TableRead object without the matching data, that can be iterated over. Values may be either a simple value (str, int) or a function that returns a boolean. See Quickstart for an example.
Note: When filtering both keys and values are not case sensitive.
- get_fields(*fields)
Given a list of fields, return a list of only the values associated with those fields. A single field returns a list of values, multiple fields returns a list of value tuples.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for tableread-2.0.3-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 7d7e3afcde88528d7b2702bd4a89a38e636a97b84b8c50e3a044486842b4af07 |
|
MD5 | cf8bb5c4387228ca65d6302174bf24da |
|
BLAKE2b-256 | 46e9fa67282a23cf6156f33cfacd1a3bd323fd234f67a4cee9f0bc548a4e1270 |