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Showing 10 open source projects for "compiler python linux"
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Gen AI apps are built with MongoDB AtlasMongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
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Photo and Video Editing APIs and SDKsUnlock Picsart's full editing suite by embedding our Editor SDK directly into your platform. Offer your users the power of a full design suite without leaving your site.
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Panda-Helper
Panda-Helper: Data profiling utility for Pandas DataFrames and Series
Panda-Helper is a simple data-profiling utility for Pandas DataFrames and Series. Assess data quality and usefulness with minimal effort. Quickly perform initial data exploration, so you can move on to more in-depth analysis. -
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Population Shift Monitoring
Monitor the stability of a Pandas or Spark dataframe
popmon is a package that allows one to check the stability of a dataset. popmon works with both pandas and spark datasets. popmon creates histograms of features binned in time-slices, and compares the stability of the profiles and distributions of those histograms using statistical tests, both over time and with respect to a reference. It works with numerical, ordinal, categorical features, and the histograms can be higher-dimensional, e.g. it can also track correlations between any two... -
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Metacrafter
Metadata and data identification tool and Python library
Python command line tool and Python engine to label table fields and fields in data files. It could help to find meaningful data in your tables and data files or to find Personal identifiable information (PII). Metacrafter is a rule-based tool that helps to label fields of the tables in databases. It scans table and finds person names, surnames, midnames, PII data, basic identifiers like UUID/GUID. These rules written as .yaml files and could be easily extended. -
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odd-collector
Open-source metadata collector based on ODD Specification
ODD Collector is a lightweight service that gathers metadata from all your data sources. Push-client is a provider which sends information directly to the central repository of the Platform. ODDRN (Open Data Discovery Resource Name) is a unique resource name that identifies entities such as data sources, data entities, dataset fields etc. It is used to build lineage and update metadata. -
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odd-collector-gcp
Open-source GCP metadata collector based on ODD Specification
ODD Collector GCP is a lightweight service which gathers metadata from all your Google Cloud Platform data sources. -
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Swiple
Swiple enables you to easily observe, understand, validate data
Swiple is an automated data monitoring platform that helps analytics and data engineering teams seamlessly monitor the quality of their data. With automated data analysis and profiling, scheduling and alerting, teams can resolve data quality issues before they impact mission critical resources. Experience hassle-free integration with Swiple's zero-infrastructure and zero-code setup. Seamlessly incorporate data quality checks into your existing workflows without any coding or infrastructure... -
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rimhistory
RimWorld game save data analyzer
RimWorld game save data analyzer. -
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Optimus
Agile Data Preparation Workflows made easy with Pandas
Easily write code to clean, transform, explore and visualize data using Python. Process using a simple API, making it easy to use for newcomers. More than 100 functions to handle strings, process dates, urls and emails. Easily plot data from any size. Out-of-box functions to explore and fix data quality. Use the same code to process your data in your laptop or in a remote cluster of GPUs. -
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NYCOpenData-Profiling-Analysis
Open Data Profiling, Quality and Analysis on NYC OpenData dataset
Open data often comes with little or no metadata. You will profile a large collection of open data sets and derive metadata that can be used for data discovery, querying, and identification of data quality problems. For each column, identify and summarize the semantic types present in the column. These can be generic types (e.g., city, state) or collection-specific types (NYU school names, NYC agency). For each semantic type T identified, enumerate all the values encountered for T in all... -
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Parse, analyze and -- most importantly -- use COBOL data definitions. This gives you access to COBOL data from Python programs. Write data analyzers, one-time data conversion utilities and Python programs that are part of COBOL systems. Really.
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