oceano | Oceano project is an integrated environment | Configuration Management library
kandi X-RAY | oceano Summary
kandi X-RAY | oceano Summary
Oceano project is an integrated environment, focused on Software Configuration Management applied to projects under version control. Its design allows continuous addition of new modules, which enhance software evolution control. The services provided by the modules are accessible through a web interface, which allows projects to be registered and evaluated, called Oceano-web. Nowadays, the Oceano project is composed of the following modules: Peixe-Espada (beltfish in english): software automated refactoring Ostra (oyster in english): quality metrics monitoring and data mining Polvo (octopus in english): branch complexity measuring Ouriço (sea-urchin in english): protect repository from broken artifacts Peixe-dipnoico (lungfish in english): prediction of structural characteristics. This project was proposed by professor Leonardo Murta and implemented allong four dissertation projects from the Software Engineering postgraduate course at Universidade Federal Fluminense. A term project was also involved from the undergraduate Computer Science course at Universidade Federal Fluminense. This project is developed by the Software Maintenance and Evolution Group (GEMS), which has several others project and researches.
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Top functions reviewed by kandi - BETA
- Restore static fields .
- initialize metric metrics
- create a tree expression
- Gets loc .
- Insert configuration items and project .
- Adds the logical architecture for the given revision .
- Reckze the expression
- Gets the Visao for a project
- Extract metrics from all files in a project
- Initialize components .
oceano Key Features
oceano Examples and Code Snippets
Community Discussions
Trending Discussions on oceano
QUESTION
Let's say I have the following df
:
ANSWER
Answered 2022-Jan-28 at 07:49EDIT: Solution working if 2 duplicated values in columns names like in sample data:
QUESTION
If I have a df
like this one down below:
ANSWER
Answered 2022-Jan-27 at 15:40You can do that with the following
df[df.columns[-1]][0]
QUESTION
Let's suppose I have the following df
:
ANSWER
Answered 2022-Jan-27 at 14:14By slicing with double square brackets you get a (2D) DataFrame.
It looks like you're trying to loop in 1D. You should use Series.iteritems
:
QUESTION
The following program let the user define the order in which the key names (elements) from the_dictionary_list
will be inserted into Keys_input
:
ANSWER
Answered 2022-Jan-10 at 14:59Figured it out. After adding the penultimate element to the array, the program will use a for loop to iterate over the dictionary, and it will evaluate which key is not in the array, the one that is not there (as it will always be the last one) will be added automatically by the program. After this, the program breaks the while True
loop of the original code
QUESTION
Let's say I have the following df
:
ANSWER
Answered 2022-Jan-09 at 07:26Use sort_index
with axis=1
:
QUESTION
I got the following df
as the result of a previous process that made some Cartesian Products:
ANSWER
Answered 2022-Jan-09 at 07:13Use Series.str.split
and df.replace
with pd.concat
:
QUESTION
Let's say I have the following df
(it's a little sample from a bigger one), each row contains 3 cells:
ANSWER
Answered 2022-Jan-09 at 02:27You can extract the column names from the Permutations
column by splitting it with +
sign. Similarly, you can extract data from FilePermutations
column.
QUESTION
Let's say I have the following dictionary in a Python program:
...ANSWER
Answered 2022-Jan-02 at 05:22all(['None' in v for k, v in the_dictionary_list.items()])
This loops through the dictionary key value pairs and returns a True
or False
if 'None'
is in the value. And then all
checks if they are all true if one is false it will return False
if all are True
it returns true
QUESTION
I have the following dictionary:
...ANSWER
Answered 2021-Dec-29 at 08:35The following solution was built by @christian from stackoverflow en español, the translation of his answer is the following:
Pandas DataFrames have a method called iterrorws() that returns a generator and we can iterate through it, this returns the row itself as a tuple that contains two objects, the first one is the index of the row and the second one is a Pandas Series that contains the values of the next columns.
I would not recommend joining the names with a
+
, you can simply leave them in list format since later we will need them as lists again and you can save that conversion to a list by avoiding using'+'.join(x)
.
QUESTION
I have the following dictionary:
...ANSWER
Answered 2021-Dec-27 at 08:26IIUC, one way using pandas.Series.str.cat
:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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No vulnerabilities reported
Install oceano
You can use oceano like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the oceano component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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