Every day, observations and orbit solutions for Near-Earth Asteroids (NEAs) are received from the Minor Planet Center (MPC) in Cambridge, Massachusetts. Once classified as an NEA, the asteroid is thereafter given automatic orbit updates within our Sentry system. A new orbit solution for an NEA is computed whenever new optical or radar observations for that object become available. Some high-priority objects are observed daily, while other objects go unobserved for days or weeks, even though they may still be bright enough to be seen. Optical observations cease when an object recedes from the Earth (becoming too faint to be seen even with moderate-size telescopes), or when the object moves into the daytime sky. Similarly, radar observations are possible only when the object is near enough to the Earth for the echo of a radar bounce to be detected. Once all the observations for an object have been collected, an orbit determination process is used to find the orbit that best fits all the observations.

It is important to understand that an object’s orbit is never known perfectly. Although the nominal orbit solution fits the observations best, slightly different orbits may still fit the observations to within their expected accuracies. There is in fact a whole set of orbits around the nominal that will fit the observations acceptably well: these all lie within what we call the uncertainty region about the nominal orbit. The ‘true’ orbit is expected to lie somewhere within this region. As new observations of the object are made, the uncertainty region becomes more tightly constrained and the range of possible values for the orbital elements narrows. As a result, objects that have been observed for decades will have highly constrained, well-known orbits, while newly discovered objects tracked for only a few days or weeks, will have relatively poorly constrained, uncertain orbits.

Once the nominal orbit and its associated uncertainty region have been determined, the object’s motion is numerically propagated forward in time for at least 100 years in order to determine its close approaches to the Earth. These nominal orbit close approach predictions are tabulated in our Earth Close Approach Tables along with other uncertainty-related information such as the minimum possible close approach distance, and the impact probability. The uncertainty-related parameters in the close approach tables are computed by propagating the uncertainty region from the epoch to the respective close approach times via so-called linearized techniques. Since these techniques lose accuracy when the uncertainties become large, we include only reasonably certain predictions in our Close Approach Tables. As a result, close approaches may be tabulated decades into the future for objects with well-known orbits, but only a few months or years into the future for objects with poorly known orbits. On the other hand, Sentry assesses the long-term possibilities of an Earth impact for all objects whose orbits can bring them close to the Earth, even those with poorly known orbits. To perform this risk analysis Sentry uses more sophisticated nonlinear methods.

I don't know if there's an API or feeds or what, I haven't looked that closely into it yet.

lakeFS is an open-source tool that transforms your object storage into a Git-like repository. It enables you to manage your data lake the way you manage your code. With lakeFS you can build repeatable, atomic, and versioned data lake operations - from complex ETL jobs to data science and analytics. lakeFS supports AWS S3, Azure Blob Storage, and Google Cloud Storage as its underlying storage service. It is API compatible with S3 and works seamlessly with all modern data frameworks such as Spark, Hive, AWS Athena, DuckDB, and Presto.

Doesn't force you to use Docker.

pyspread is a non-traditional spreadsheet application that is based on and written in the programming language Python. The goal of pyspread is to be the most pythonic spreadsheet.

pyspread expects Python expressions in its grid cells and returns Python objects, which makes a spreadsheet specific language obsolete. Each cell returns a Python object that can be accessed from other cells. These objects can represent anything including lists or matrices. Has a built-in renderer that interfaces with matplotlib for showing visualizations and graphics. Other Python modules can be imported and referenced as cells. Import CSV, export CSV, PDF, and SVG.

The latest stable release v1.1.3 of pyspread runs on Python 2.7.x. A Python 3 compatible version that runs on Python 3.6+ is available as a beta.

Git repo: https://gitlab.com/pyspread/pyspread

minidb 2 makes it easy to store Python objects in a SQLite 3 database and work with the data in an easy way with concise syntax. Designed for embedded use (imported as a module) and not a stand-alone server. Supports SQL queries.

SeaweedFS is a simple and highly scalable distributed file system. There are two objectives: to store billions of relatively small files, and to serve those files fast. Implements an object store with O(1) disk seek and an optional filer with a POSIX interface. Metadata can be stored in one of several RDBMSes. Speaks HTTP(S). Supports multiple access APIs, including S3, HDFS, and WebDAV. Can automatically back itself up offsite. Supports multiple URI formats, with varying degrees of niceness. Large files are chunked transparently to the user.

Following the Terms of Service change at Thingiverse, archive.org downloaded the whole bloody thing and put it online. The tarball's 81 gigabytes in size, so I hope you've got some disk space...

A very well done description of decorators in python. Go in depth about how functions are first class objects, scope, self-modifying code, and how everything works. programming languages documentation tutorial

The homepage of the Open Graph protocol, a system of tags for turning web pages into smart objects in a social graph. Describes what kind of content it is (which implies how to treat it) and allows functionality to be imported from social media sites. Supplies much greater context for web pages. Includes multimedia content.