Python Reviews & Product Details

In our office case, we have linked Python and Smartsheet to perform various tasks. Our team has written the codes in Python to interact with Smartsheet and G-Drive. There are multiple use cases where we use Python in background as well in the form of an user interface for ease of use. It is easy to follow and understand the Python codes that I find it easy and comfortable to make minor changes within the codes to adapt to the new process changes or additions. We use this integrated approach of Python and Smartsheet quite extensively and frequently. Multiple features of Python are being used to perform various tasks like:

1) Clicking photographs - In an UI based python code we enter a date of receipt, upon which the Python code refers a particular Smartsheet, pull the data and number of rows, creates respective folders and starts saving the images in the respective folders while renaming them as per our requirement as we keep clicking the photos is the assets through a camera. This is an integration of Python, Smartsheet and a physical external Camera

2) Batching - In this UI based Python code, we enter a batch number, upon which it reads the data from the respective Smartsheet, creates multiple folders and downloads assets from G-drive and save it in the respective newly made folders. This is an integration of Python, Smartsheet and G-drive

3) Asset update - In this UI based Python script, the assets are compared with Smartsheet data and the processed assets saved in batches in Git folder, upon which new .xml and .json files are written and Smartsheets are updated accordingly. This is an integration of Python, Smartsheet and Git

4) Validation - In this Python script, the processed batches are validated for existence and accuracy of the processed assets within the batch folders. This is an integration of Python, Smartsheet, .xml and .json files

5) Uploading - In this script based Python (no UI), upon completion of the process and validations, the assets are uploaded on a cloud storage. This is an integration of Python, Smartsheet and a cloud storage

Considering the widely available feature and ease of implementation, we were able to automate most of our activities using the integration of Python and Smartsheet. Review collected by and hosted on G2.com.

While, our activities are not time bound or use up extensive processing, the widely know issues like slowness, memory allocation or design restriction, they do not bother us as such. Our work gets done, so for now we don't see any issue to be disliked. Review collected by and hosted on G2.com.

It's my daily work to use Python and develop applications, this is my job, and everything it provides is best, mostly it's ease of learning and simple syntax Review collected by and hosted on G2.com.

Nothing as such. It is solving all my problems right now and nothing to be disliked about it yet. Review collected by and hosted on G2.com.

I like it's massive library ecosystem, which allows me to solve complex problems in just few lines of code. Review collected by and hosted on G2.com.

I Don't like it's slow execution speed. Review collected by and hosted on G2.com.

Python is very easy to learn. There are so many libraries available that we can use for test automation. Review collected by and hosted on G2.com.

There is no issue with Python until now. Visual Studio Code is a great IDE and I can easily debug errors. Review collected by and hosted on G2.com.

• Python stands out as a high-level, general-purpose programming language with a design philosophy focused on code readability and simplicity. The syntax is clean and uncluttered, relying on indentation rather than braces or semicolons to define code blocks, which not only makes the code visually appealing but also reduces the likelihood of syntactic errors. This approach aligns with the Zen of Python principles, emphasizing that “readability counts” and “simple is better than complex,” which are deeply ingrained in the language’s evolution.

• Python supports multiple programming paradigms, including object-oriented, procedural, and functional programming. This multi-paradigm nature allows developers to choose the most suitable approach for the problem at hand, whether it involves building modular, reusable components using classes, or leveraging functional constructs like map, filter, and reduce for data processing. The language also features advanced constructs such as list comprehensions, generators, and decorators, enabling concise expression of complex logic.

• A major strength of Python is its dynamic typing system, where variable types are determined at runtime. This feature enables rapid prototyping and flexibility in code, as developers are not required to declare variable types explicitly. Python’s interpreted nature means code is executed line by line, facilitating interactive development, immediate feedback, and easier debugging. The interactive shell and bundled development environments like IDLE further enhance this experience, making it straightforward to test ideas and troubleshoot issues.

• The standard library is extensive, covering everything from file I/O and regular expressions to networking and web services. This rich ecosystem reduces the need for third-party dependencies for common tasks and accelerates development by providing well-tested, ready-to-use modules. In addition, Python’s integration capabilities are robust: it can interface with C, C++, Java, and other languages, and is frequently used as a “glue language” to connect disparate systems.

• Python’s open-source status and cross-platform compatibility are significant advantages. The language runs natively on Windows, macOS, Linux, and Unix, and unofficial builds exist for mobile platforms. The vibrant, global community contributes to a wealth of documentation, tutorials, and third-party libraries, ensuring that support is readily available for both beginners and experienced developers. The ecosystem includes popular frameworks for web development (Django, Flask), data analysis (pandas, NumPy), machine learning (TensorFlow, scikit-learn), and more, making Python a versatile choice across domains.

• Python’s suitability for rapid development and prototyping is well recognized. Its concise syntax and high-level abstractions allow for quick translation of ideas into working code, which is particularly valuable in fast-paced environments or when developing minimum viable products. The language’s automatic memory management and built-in exception handling further streamline the development process, reducing boilerplate and minimizing the risk of memory leaks or unhandled errors.

• Python’s role in modern technology stacks is prominent. It is widely adopted in fields such as data science, artificial intelligence, web development, automation, and Internet of Things (IoT). The language’s flexibility allows it to be used for scripting, building complex applications, or as an embedded scripting language within larger systems. Its popularity is reflected in the job market and community activity, ensuring continued evolution and relevance. Review collected by and hosted on G2.com.

• Performance limitations: As an interpreted language, Python generally executes code slower than compiled languages like C++ or Java. This can be a bottleneck for compute-intensive or real-time applications.

• Memory consumption: Python’s dynamic typing and high-level abstractions can result in higher memory usage, especially when handling large datasets or complex data structures.

• Global Interpreter Lock (GIL): The GIL restricts true multi-threaded execution in CPython, limiting concurrency for CPU-bound tasks and affecting scalability in certain scenarios.

• Dependency management: The vast ecosystem of third-party packages can lead to version conflicts and intricate dependency trees, complicating project maintenance.

• Mobile development: Native support and tooling for mobile platforms are less mature compared to other languages, making Python less suitable for mobile-first projects.

• Dynamic typing pitfalls: While dynamic typing increases flexibility, it can also lead to runtime errors that are harder to detect during development, particularly in large codebases. Review collected by and hosted on G2.com.

Python is easy to use and helps with many libraries work in different machine learning models to build. Also easy to integrate with multiple softwares. And I use regularly and easy to implement the ideas. Review collected by and hosted on G2.com.

Frontend things like API still we have to depend on other programming languages. Review collected by and hosted on G2.com.

Python shines with its clean and readable syntax, which allows developers to write less code and accomplish more. It's extremely powerful enough for large scale applications. The rich ecosystem of libraries and frameworks, especially for web development, data science and automation, makes it a go to language across many domains. The active community and extensive documentation also make problem solving and learning much smoother. Review collected by and hosted on G2.com.

While Python's dynamic typing is convenient, its type system still feels limited compared to more better solutions like TypeScript. Even with the addition of type hints and tools like mypy, the enforcement is optional and lacks the strictness and tooling support that make TypeScript's typing so effective. This can lead to runtime issues that would be caught during compile time in statically typed languages. Review collected by and hosted on G2.com.

Python is a very useful language that can be combined with AI and generate new AI requests or things that are helpful Review collected by and hosted on G2.com.

Well that we use pyscript to run it on the computer Review collected by and hosted on G2.com.

Coding is simple to understand and write dynamic code Review collected by and hosted on G2.com.

Currently no dislikes with python codes. Review collected by and hosted on G2.com.

It's easy to learn and use. It is also having so many libraries for different tasks and also a great support forum. Review collected by and hosted on G2.com.

It's not that fast and lacks machine level programming. It's also not good with frontend. Review collected by and hosted on G2.com.