「python」の検索結果

Azure Key Vault SDK for Python. Use for secrets, keys, and certificates management with secure storage.

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Azure Web PubSub Service SDK for Python. Use for real-time messaging, WebSocket connections, and pub/sub patterns.

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Azure Event Grid SDK for Python. Use for publishing events, handling CloudEvents, and event-driven architectures.

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Azure Fabric Management SDK for Python. Use for managing Microsoft Fabric capacities and resources.

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Azure Bot Service Management SDK for Python. Use for creating, managing, and configuring Azure Bot Service resources.

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Azure API Management SDK for Python. Use for managing APIM services, APIs, products, subscriptions, and policies.

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Azure API Center Management SDK for Python. Use for managing API inventory, metadata, and governance across your organization.

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Azure Container Registry SDK for Python. Use for managing container images, artifacts, and repositories.

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Azure Cosmos DB SDK for Python (NoSQL API). Use for document CRUD, queries, containers, and globally distributed data.

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Azure Identity SDK for Python authentication. Use for DefaultAzureCredential, managed identity, service principals, and token caching.

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Azure Event Hubs SDK for Python streaming. Use for high-throughput event ingestion, producers, consumers, and checkpointing.

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Azure Tables SDK for Python (Storage and Cosmos DB). Use for NoSQL key-value storage, entity CRUD, and batch operations.

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Azure Machine Learning SDK v2 for Python. Use for ML workspaces, jobs, models, datasets, compute, and pipelines.

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Azure AI Content Safety SDK for Python. Use for detecting harmful content in text and images with multi-severity classification.

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Azure App Configuration SDK for Python. Use for centralized configuration management, feature flags, and dynamic settings.

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Azure AI Content Understanding SDK for Python. Use for multimodal content extraction from documents, images, audio, and video.

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Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization.

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Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

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Build persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK.

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Loads, converts, and manipulates Hi-C contact matrices in cooler format (.cool/.mcool/.scool) and Juicer .hic, using cooler (Python + CLI), hic2cool, and hictk. Covers the single-resolution mcool URI (file.mcool::/resolutions/<bp>), the load-bearing divisive-vs-multiplicative weight-naming rule (KR/VC/VC_SQRT auto-divisive vs cooler's multiplicative weight), what survives .hic<->.cool conversion (FRAG matrices and norm vectors do not), raw-vs-balanced coarsening, the .pairs upper-triangle/chromsize-order contract, and chrom-naming/bin-table provenance. Use when loading a cooler, converting .hic to .mcool, selecting a resolution, building a cooler from pairs or a matrix, coarsening/zoomifying, importing Juicer norm vectors, or debugging all-NaN balanced matrices and chr1-vs-1 empty fetches.

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Reads, queries, and writes bigWig indexed binary signal tracks (coverage, fold-change, conservation, methylation-rate) with pyBigWig (Python) and the UCSC Kent tools (bedGraphToBigWig, bigWigToBedGraph, bigWigInfo, bigWigSummary, bigWigAverageOverBed) and deepTools (multiBigwigSummary, computeMatrix, bigwigCompare). Covers the central trap that a wide query returns a precomputed zoom-level summary (by default the mean, which annihilates narrow peaks) not per-base data, when exact=True/values() is mandatory, the NaN-not-zero gap-handling fork, choosing mean vs max vs sum vs coverage by biological question, and the sorted-bedGraph plus chrom.sizes build requirement. Use when extracting signal at regions, computing mean signal per gene/peak, building a browser track from bedGraph, comparing tracks, or building TSS/gene-body metaprofiles.

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Handles BED-format genomic intervals (BED3 through BED12, narrowPeak/broadPeak) and the coordinate-system substrate the whole interval category rests on, with bedtools (CLI) and pybedtools/pyranges/pandas (Python). Covers the 0-based half-open vs 1-based-closed convention boundary and the start-1/end-unchanged conversion, the silent failures (chrom-name mismatch, CRLF, lexicographic-vs-version sort under -sorted), genome/chrom.sizes generation, sorting contracts, BED12 block invariants, validation, makewindows, cross-assembly liftover (liftOver/CrossMap), and BED<->VCF/BAM/FASTA conversion. Use when reading, creating, validating, sorting, lifting between genome builds, or converting interval files, preparing inputs for bedtools/tabix/bigBed, or debugging an off-by-one or empty-overlap result.

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Performs set operations on genomic intervals - intersect (-wa/-wb/-wo/-wao/-loj/-c/-v/-u), subtract (-A), merge (-d, -c/-o), complement, cluster, multiinter, unionbedg, map, and groupby - with bedtools (CLI) and pybedtools/pyranges/bioframe (Python). Covers the sorted-input contract and the -sorted chromosome-order footgun, reciprocal/fractional overlap (-f/-F/-r/-e) and the A-vs-B asymmetry, -split for spliced/BED12/BAM features, and jaccard/fisher as mechanics only. Use when finding overlapping or unique regions between BED/peak/feature files, building consensus peaksets, removing blacklisted regions, transferring annotation values onto intervals, or computing interval-set similarity; route overlap-significance testing to overlap-significance.

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Reads, inspects, and writes Flow Cytometry Standard (FCS) files from conventional, spectral, and mass cytometry (CyTOF), and parses FlowJo/Cytobank/Diva workspaces. Covers FCS 2.0/3.0/3.1/3.2 internals ($PnE linear-vs-log, $DATATYPE, $SPILLOVER vs SPILL vs $COMP, $TIMESTEP), channel/parameter metadata, the silent linearize/truncate defaults, and R (flowCore, flowWorkspace, CytoML) plus Python (FlowKit, readfcs) readers. Use when loading flow or mass cytometry data, mapping detector channels to antibodies, extracting the event matrix, choosing a reader, or bridging FCS to the scanpy/AnnData ecosystem before preprocessing.

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