We have data on 29 companies that use Python Image Library (PIL/Pillow). The companies using Python Image Library (PIL/Pillow) are most often found in United States and in the Higher Education industry. Python Image Library (PIL/Pillow) is most often used by companies with >10000 employees and >1000M dollars in revenue. Our data for Python Image Library (PIL/Pillow) usage goes back as far as 3 years and 10 months.
|Company||Girls Who Code|
|Company||University of Alberta|
|Company||Rochester Institute of Technology|
|Girls Who Code||girlswhocode.com||United States||1M-10M||1000-5000|
|University of Alberta||ualberta.ca||Canada||>1000M||>10000|
|Rochester Institute of Technology||rit.edu||United States||200M-1000M||>10000|
We use the best indexing techniques combined with advanced data science to monitor the market share of over 15,000 technology products, including Software Frameworks. By scanning billions of public documents, we are able to collect deep insights on every company, with over 100 data fields per company at an average. In the Software Frameworks category, Python Image Library (PIL/Pillow) has a market share of about 0.1%. Other major and competing products in this category include:
Python Imaging Library (abbreviated as PIL) (in newer versions known as Pillow) is a free library for the Python programming language that adds support for opening, manipulating, and saving many different image file formats. It is available for Windows, Mac OS X and Linux. PIL is not compatible with Python 3.x whereas Pillow supports Python 3.x.
Looking at Python Image Library (PIL/Pillow) customers by industry, we find that Higher Education (19%) and Internet (9%) are the largest segments.
46% of Python Image Library (PIL/Pillow) customers are in United States, 19% are in Canada and 5% are in India.
Of all the customers that are using Python Image Library (PIL/Pillow), 6% are small (<50 employees), 20% are medium-sized and 47% are large (>1000 employees).
Of all the customers that are using Python Image Library (PIL/Pillow), 24% are small (<$50M), 10% are medium-sized and 37% are large (>$1000M).