Skip to main content

Python library supplying a tool to record values during calculations

Project description

Python project mitschreiben

CodeShip Travis ci Read the Docs CodeFactor Grade Code Climate maintainability Codecov lgtm grade total lgtm alerts GitHub GitHub release PyPI Version PyPI - Python Version PyPI Downloads

mitschreiben (german for ‘to take notes’) helps recording values during calculations for later evaluation, e.g. check if the right objects or values were used or to present the results in structure of tables

It provides a class called Record which is basically used for everything. It grants access to record object, it is used for the recording and it is a context manager used to trigger whether to record or not.

Example Usage

In the first Record(key = value) or Record(dictionary) is placed where one wants to record a value. The decorator Prefix provided by this class is used to define a key extension under which the recorded value will be stored in the Record. The Prefixes get stacked, so when there is a successive function call to another function which is prefixed those Prefixes are concatenated.

from mitschreiben import Record

def magical_stuff_happens(baz, barz):
    return "That's", "great"

class Foo():

    @Record.Prefix()
    def bar(self, baz, barz)
        some_value1, some_value2 = self.do_something(baz, barz)

        Record(a_key=some_value1, another_key=some_value2)

        return some_value1, some_value2

    @Record.Prefix()
    def do_something(self, baz, barz):

        a_dict = {'again_a_key': baz, 'so_creative': barz}

        Record(a_dict)

        return magical_stuff_happens(baz, barz)

    def __repr__(self):
        return "Foo({})".format(id(self))

Now, since Record is a contextmanager, the recording will only happen in such a context. The with-statement activates the recording and returns the current scopes record object for convenient access. Another thing is, that record level is increased by this statement, leading to record objects that are only available in that scope. When leaving the with the outer scopes’s record will be extend by the inner one, by prepending the outer records current prefix stack to each key of the inner one.

with Record() as rec:
    foo = Foo()
    foo.do_something("baz", "barz")
    foo.bar("baz","barz")

    print rec.entries

The entries are a dict whose keys are tuples which are the stacked Prefixes. In this way it is possible to determine which method on which object was called, what then led to successive calls, where in the end a value is recorded. The example above has the following output.

{('Foo(42403656).do_something', 'again_a_key'): 'baz', ('Foo(42403656).bar', 'Foo(42403656).do_something', 'again_a_key'): 'baz', ('Foo(42403656).do_something', 'so_creative'): 'barz', ('Foo(42403656).bar', 'a_key'): "That's", ('Foo(42403656).bar', 'another_key'): 'great', ('Foo(42403656).bar', 'Foo(42403656).do_something', 'so_creative'): 'barz'}

Formatting the output

The Record can be represented in different formats. The base to this is a tree of dictionaries, implemented by the class DictTree in mitschreiben.formatting. For the two base outputs however, one does not need to actually instantiate a DictTree yourself. The respective methods are

Both of these methods produce tables of the output. The idea is that, that certain calculations are made with different objects, leading to the same keywords. So one obtains a table with row keys (object names) and column keys (the keywords used to record a value). As the name of the former methods suggests, it produces this tables and writes them as single .csv files into Path, whereas the latter construct a html document in which one can navigate through the tree structure and see the tables at those positions where they would be placed in the tree. Those tables would look similar to

<div class='panel-elem'><table>
<tr class='headrow'>
<th colspan='5'>table</th>
</tr>
<tr class='bodyrow'>
<th> </th>
<th>a_key</th>
<th>again_a_key</th>
<th>another_key</th>
<th>so_creative</th>
</tr>
<tr class='bodyrow'>
<th>Foo(42403656).bar</th>
<td>That's</td>
<td>None</td>
<td>great</td>
<td>None</td>
</tr><tr class='bodyrow'>
<th>Foo(42403656).do_something</th>
<td>None</td>
<td>baz</td>
<td>None</td>
<td>barz</td>
</tr></table></div>
<div class='panel'>
<div class='panel-elem'><table>
<tr class='headrow'>
<th colspan='2'>table</th>
</tr>
<tr class='bodyrow'>
<th> </th>
<th>Foo(42403656).do_something</th>
</tr>
<tr class='bodyrow'>
<th>again_a_key</th>
<td>baz</td>
</tr><tr class='bodyrow'>
<th>so_creative</th>
<td>barz</td>
</tr></table></div>

Another way would be to work with the DictTree directly.

from mitschreiben.formatting import DictTree

DT = DictTree(rec.entries)

tables = DT.make_tables()
for t in tables:
    print t.pretty_string()
    print

This results in the following output. The first table represents the top level of the record, whereas the other tabels are named by object.function.

                    Values |  a_key | again_a_key | another_key | so_creative
         Foo(42403656).bar | That's |        None |       great |        None
Foo(42403656).do_something |   None |         baz |        None |        barz

Foo(42403656).bar
                    Values | again_a_key | so_creative
Foo(42403656).do_something |         baz |        barz

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

mitschreiben-0.3.tar.gz (19.0 kB view hashes)

Uploaded Source

Built Distribution

mitschreiben-0.3-py3-none-any.whl (19.2 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page