About
Coverage.py is a tool for measuring code coverage of Python programs. It monitors your program, noting which parts of the code have been executed, then analyzes the source to identify code that could have been executed but was not. Coverage measurement is typically used to gauge the effectiveness of tests. It can show which parts of your code are being exercised by tests, and which are not. Use coverage run to run your test suite and gather data. However you normally run your test suite, and you can run your test runner under coverage. If your test runner command starts with “python”, just replace the initial “python” with “coverage run”. To limit coverage measurement to code in the current directory, and also find files that weren’t executed at all, add the source argument to your coverage command line. By default, it will measure line (statement) coverage. It can also measure branch coverage. It can tell you what tests ran which lines.
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About
The core of extensible programming is defining functions. Python allows mandatory and optional arguments, keyword arguments, and even arbitrary argument lists. Whether you're new to programming or an experienced developer, it's easy to learn and use Python. Python can be easy to pick up whether you're a first-time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way to writing programs with Python! The community hosts conferences and meetups to collaborate on code, and much more. Python's documentation will help you along the way, and the mailing lists will keep you in touch. The Python Package Index (PyPI) hosts thousands of third-party modules for Python. Both Python's standard library and the community-contributed modules allow for endless possibilities.
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About
Rivery’s SaaS ETL platform provides a fully-managed solution for data ingestion, transformation, orchestration, reverse ETL and more, with built-in support for your development and deployment lifecycles.
Key Features:
Data Workflow Templates: Extensive library of pre-built templates that enable teams to instantly create powerful data pipelines with the click of a button.
Fully managed: No-code, auto-scalable, and hassle-free platform. Rivery takes care of the back end, allowing teams to spend time on priorities rather than maintenance.
Multiple Environments: Construct and clone custom environments for specific teams or projects.
Reverse ETL: Automatically send data from cloud warehouses to business applications, marketing clouds, CPD’s, and more.
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About
dotCover is a .NET unit testing and code coverage tool that works right in Visual Studio and in JetBrains Rider, helps you know to what extent your code is covered with unit tests, provides great ways to visualize code coverage, and is Continuous Integration ready. dotCover calculates and reports statement-level code coverage in applications targeting .NET Framework, .NET Core, Mono for Unity, etc. dotCover is a plug-in to Visual Studio and JetBrains Rider, giving you the advantage of analyzing and visualizing code coverage without leaving the code editor. This includes running unit tests and analyzing coverage results right in the IDEs, as well as support for different color themes, new icons and menus. dotCover comes bundled with a unit test runner that it shares with another JetBrains tool for .NET developers, ReSharper. dotCover supports continuous testing, a modern unit testing workflow whereby dotCover figures out on-the-fly which unit tests are affected by your code changes.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Any user looking for a solution to measure line and branch coverage to produce test reports
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Audience
Developers interested in a beautiful but advanced programming language
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Audience
Marketing Analytics Teams, Data and Analytics Teams, BI Teams.
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Audience
Developers searching for a unit testing and code coverage solution to visualize code coverage
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Pricing
$0.75 Per Credit
Free Version
Free Trial
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Pricing
$399 per user per year
Free Version
Free Trial
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Reviews/
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Reviews/
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationCoverage.py
United States
coverage.readthedocs.io/en/7.0.0/
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Company InformationPython
Founded: 1991
www.python.org
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Company InformationRivery
Founded: 2017
United States
rivery.io
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Company InformationJetBrains
Founded: 2000
Czech Republic
www.jetbrains.com/dotcover/
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Alternatives |
Alternatives |
Alternatives |
Alternatives |
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Categories |
Categories |
Categories |
Categories |
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Data Extraction Features
Disparate Data Collection
Document Extraction
Email Address Extraction
Image Extraction
IP Address Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction
Data Management Features
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
Data Management Platforms (DMP) Features
Ad Network Integration
Analytics / ROI Tracking
Audience Targeting
Behavioral Analytics
Campaign Management
Competitive Analysis
CRM
Customer Journey Mapping
Data Capture / Transfer
Data Classification
Data Visualization
Data Preparation Features
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface
ETL Features
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control
Integration Features
Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services
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Integrations
Ai Intern
ApertureDB
Arachnophilia
Artelys Knitro
CodeFriends
Codey
Constructor Proctor
Encord
FeatureByte
HoundDog.ai
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Integrations
Ai Intern
ApertureDB
Arachnophilia
Artelys Knitro
CodeFriends
Codey
Constructor Proctor
Encord
FeatureByte
HoundDog.ai
|
Integrations
Ai Intern
ApertureDB
Arachnophilia
Artelys Knitro
CodeFriends
Codey
Constructor Proctor
Encord
FeatureByte
HoundDog.ai
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Integrations
Ai Intern
ApertureDB
Arachnophilia
Artelys Knitro
CodeFriends
Codey
Constructor Proctor
Encord
FeatureByte
HoundDog.ai
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