2023-04-04T02:26:03,546 Created temporary directory: /tmp/pip-ephem-wheel-cache-h01xx4w7
2023-04-04T02:26:03,552 Created temporary directory: /tmp/pip-build-tracker-bjwlcw98
2023-04-04T02:26:03,552 Initialized build tracking at /tmp/pip-build-tracker-bjwlcw98
2023-04-04T02:26:03,553 Created build tracker: /tmp/pip-build-tracker-bjwlcw98
2023-04-04T02:26:03,553 Entered build tracker: /tmp/pip-build-tracker-bjwlcw98
2023-04-04T02:26:03,554 Created temporary directory: /tmp/pip-wheel-k5owm84o
2023-04-04T02:26:03,565 DEPRECATION: --no-binary currently disables reading from the cache of locally built wheels. In the future --no-binary will not influence the wheel cache. pip 23.1 will enforce this behaviour change. A possible replacement is to use the --no-cache-dir option. You can use the flag --use-feature=no-binary-enable-wheel-cache to test the upcoming behaviour. Discussion can be found at https://github.com/pypa/pip/issues/11453
2023-04-04T02:26:03,571 Created temporary directory: /tmp/pip-ephem-wheel-cache-e113_bt4
2023-04-04T02:26:03,623 Looking in indexes: https://pypi.org/simple, https://www.piwheels.org/simple
2023-04-04T02:26:03,630 2 location(s) to search for versions of apache-iotdb:
2023-04-04T02:26:03,630 * https://pypi.org/simple/apache-iotdb/
2023-04-04T02:26:03,630 * https://www.piwheels.org/simple/apache-iotdb/
2023-04-04T02:26:03,632 Fetching project page and analyzing links: https://pypi.org/simple/apache-iotdb/
2023-04-04T02:26:03,633 Getting page https://pypi.org/simple/apache-iotdb/
2023-04-04T02:26:03,636 Found index url https://pypi.org/simple
2023-04-04T02:26:03,897 Fetched page https://pypi.org/simple/apache-iotdb/ as application/vnd.pypi.simple.v1+json
2023-04-04T02:26:03,926   Found link https://files.pythonhosted.org/packages/76/14/d01b6281df00530c69bc8eae2074b9970bbe865a5e971b5cd2019e8b8250/apache-iotdb-0.9.0.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.9.0
2023-04-04T02:26:03,927   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/84/aa/fa9401ccadb89ddce7c2b8a03baee9dbb9913c52b5936d0ec7968cabf056/apache_iotdb-0.9.0-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,928   Found link https://files.pythonhosted.org/packages/01/fa/e65db378e4d8e07322ec175f37568bceb55ebb3c8397fa7b48e9f087c451/apache-iotdb-0.9.2.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.9.2
2023-04-04T02:26:03,929   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/43/8d/72fa03325e9281b613a0eabae9cc7c606ce0e8952bee0c3ca855e4579a1d/apache_iotdb-0.9.2-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,930   Found link https://files.pythonhosted.org/packages/34/95/030c2da665358de8ba950099b3b0397dca437fcde60d5d1730d0c451d5e3/apache-iotdb-0.9.3.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.9.3
2023-04-04T02:26:03,931   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/5c/d4/2e329baab32ad93730ba4b79df9b91f1d55d0d37428a5dbbe2dd4c9f3a9d/apache_iotdb-0.9.3-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,932   Found link https://files.pythonhosted.org/packages/1d/dc/138e08717f8c2e0e238f35d39b34af6cfc1c7a1332b6aa4689750f4fda26/apache-iotdb-0.10.0.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.10.0
2023-04-04T02:26:03,933   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/c3/76/46884f04945b6f02bbec4e06d83fafc16f326ca0f9b35b8c0141018990c0/apache_iotdb-0.10.0-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,934   Found link https://files.pythonhosted.org/packages/f6/4d/b229b9f309431e8164c9cd893431009a57efcaa059f58c1091d222601da3/apache-iotdb-0.10.1.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.10.1
2023-04-04T02:26:03,935   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/d6/87/2e003dcf87ffa8e73f48a62a107b989967e906670d905a05ae1c1349f396/apache_iotdb-0.10.1-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,936   Found link https://files.pythonhosted.org/packages/16/8b/2ec65fa81d5961bd927c02d6a209490bf325b2a164506cd3b12e846d7061/apache-iotdb-0.11.0.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.11.0
2023-04-04T02:26:03,937   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/47/c8/047703f7e8125b15361c766b90c6f1cbdbf797f84803f38b1732c1a386cb/apache_iotdb-0.11.0-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,939   Found link https://files.pythonhosted.org/packages/55/a1/ef100f67e0f26fbc1d19b84115b21de942e7b7e01803706d19f841ac06c1/apache-iotdb-0.11.1.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.11.1
2023-04-04T02:26:03,939   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/9f/9f/dce2d782c8b64700539039ef5d66f5f7a781689538c0a176cf56099ec9d1/apache_iotdb-0.11.1-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,941   Found link https://files.pythonhosted.org/packages/69/d5/f1b9ff293fe02eb1f1cb3cba13b5d9a4b547415ab0045b2a8a3612249e12/apache-iotdb-0.11.2.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.11.2
2023-04-04T02:26:03,942   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/2b/96/a5f0c63659cc8477c53d8a8321c07ea5a0bb2430abaaab477a6185bb43a1/apache_iotdb-0.11.2-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,943   Found link https://files.pythonhosted.org/packages/7d/cf/0d672a828527f59cdc66c078b0b8e356ca0a3191224a4363ce2256337d1c/apache-iotdb-0.11.3.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.11.3
2023-04-04T02:26:03,944   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/d2/c7/6709b26341e59788d05a297182aa3f96c692e85421c169f657e92c3b4765/apache_iotdb-0.11.3-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,945   Found link https://files.pythonhosted.org/packages/00/a1/5b1b8a2754f4b25420d9a4461b5e2b8573bb89b43054f9303ea0558df0de/apache-iotdb-0.11.4.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.11.4
2023-04-04T02:26:03,946   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/48/f4/a21fd4495f93c428de788a477665f1815b257568469c38108666125fff4b/apache_iotdb-0.11.4-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,947   Found link https://files.pythonhosted.org/packages/9e/16/bb2ef45f62e9866f1be97f04e2c581247d3b145e5d8a01b7c143023c6c45/apache-iotdb-0.12.0.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.12.0
2023-04-04T02:26:03,948   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/93/32/e051c3ce387e54b1f036995e92ff352895cf01a51b170752e906a7d42364/apache_iotdb-0.12.0-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,949   Found link https://files.pythonhosted.org/packages/20/0c/b39e9f362fb0a1a43cb0a05a5b2d9163815f0048575e0c071bbaa50070b8/apache-iotdb-0.12.1.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.12.1
2023-04-04T02:26:03,950   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/55/cf/219a0c3cd17537cebf6e67deeaa77b57741c9b40bcddbb7f59ac9b828401/apache_iotdb-0.12.1-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,951   Found link https://files.pythonhosted.org/packages/fd/64/d83ceaaab941dd78df38cd8c35d27028a27724c2535f0e6f01a48472aa28/apache-iotdb-0.12.2.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.12.2
2023-04-04T02:26:03,952   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/0b/33/60af46cbc25d7ecf9722bf311295cb0acbf2841f6eb3e3af7433ac3e199d/apache_iotdb-0.12.2-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,953   Found link https://files.pythonhosted.org/packages/24/7c/81a9dcfd218d4654b03d9079578659d6201aa4f9e9ccba328c0742e8e9c1/apache-iotdb-0.12.3.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.12.3
2023-04-04T02:26:03,954   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/9f/ae/e79cef98fa20cf977ea22b065fcff8d7b976922dd281f4a74a02b1a72b41/apache_iotdb-0.12.3-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,955   Found link https://files.pythonhosted.org/packages/9e/11/0d12f9b906b3aac1446c09e297bcdf3a0cdfb016aae1ec77effa214999de/apache-iotdb-0.12.4.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.12.4
2023-04-04T02:26:03,956   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/2b/cb/34f5d9137086d912e4518d751eca1ac9a8b908706c4b3176ca32911fabd2/apache_iotdb-0.12.4-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,957   Found link https://files.pythonhosted.org/packages/8a/52/93503eac47c1561edc21431f7154b694afad9d461e2af0fea36966953c24/apache-iotdb-0.12.5.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.12.5
2023-04-04T02:26:03,958   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/7a/30/1cd9bca76c1f4f9b4cd48d11f23103ade9c5a35410bbf0a8f5997bab51b0/apache_iotdb-0.12.5-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,959   Found link https://files.pythonhosted.org/packages/00/d9/19746ff8906cc2ac3c9326fbcbd244d2424f4aad5d7201843956d27dcb0b/apache-iotdb-0.12.6.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.12.6
2023-04-04T02:26:03,960   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/cf/7b/ab3acb96fd057e900f9aca1b030f4fb42caf4104000ab742ce19a1029b6f/apache_iotdb-0.12.6-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,961   Found link https://files.pythonhosted.org/packages/a6/cd/33de301e51132f8d0d79adc346d38685a6b871251846bad95b35ebf74ac9/apache-iotdb-0.13.0.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.13.0
2023-04-04T02:26:03,962   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/71/c1/3684d3b6e6eddda5fbe994e123c6bc6569409994a44b5d3e4b130554802a/apache_iotdb-0.13.0-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,963   Found link https://files.pythonhosted.org/packages/7e/3e/40f0d900e04598036cc65ae437a2ee9f4aa149860d434a6f4b291460582c/apache-iotdb-0.13.0.post1.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.13.0.post1
2023-04-04T02:26:03,964   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/7c/f2/ef6f589910f1b850ad665d4958e2a26b5249bddc81d5f29a711e21a79dc1/apache_iotdb-0.13.0.post1-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,965   Found link https://files.pythonhosted.org/packages/e5/47/3efce218f936953f6ee5e338748981137a5d30579578038a67063b1c10d8/apache-iotdb-0.13.1.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.13.1
2023-04-04T02:26:03,966   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/b7/1d/3074d8ab58366c99783fe0ed853472a21d69dfd2b80ca001281d170833e2/apache_iotdb-0.13.1-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,967   Found link https://files.pythonhosted.org/packages/6f/55/1bcfde81cb204d77387e7cadbf8c3510ec04a2b02fa8b26d04b8f5037bca/apache-iotdb-0.13.2.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.13.2
2023-04-04T02:26:03,968   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/94/0c/3a7d8a238d7c8771453889f8f03f9ebcd418839306e64f4ddea8c0baee81/apache_iotdb-0.13.2-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,969   Found link https://files.pythonhosted.org/packages/30/a0/0153c56e1af8653bfdcf47423949dd6b23e53882c9009acc25e661a44dbe/apache-iotdb-0.13.3.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.13.3
2023-04-04T02:26:03,970   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/a0/51/7e8405405f7f0ef8eabab31b4860cb747a8acfa53e30f56939c115b53db9/apache_iotdb-0.13.3-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,971   Found link https://files.pythonhosted.org/packages/42/eb/3d7ac8d794238b75997ff3f55db6e02436bfa558a8df4ea21e58bf8db6fd/apache-iotdb-0.13.5.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.13.5
2023-04-04T02:26:03,972   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/51/a3/9117edfd3d72a1d338b7cff8060e672dd7b39dfeb2ca0d6c22db51bf9b90/apache_iotdb-0.13.5-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,973   Found link https://files.pythonhosted.org/packages/95/c9/5d7a22003e57fe3c1637928926a73d11815830ee63c62f2cefeaa8eed28f/apache-iotdb-0.13.5.1.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.13.5.1
2023-04-04T02:26:03,974   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/89/0a/816b8a85f6be9f8fe3534f79ea12341dad900b59ba0ac126835640a09db0/apache_iotdb-0.13.5.1-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,975   Found link https://files.pythonhosted.org/packages/bb/7d/24cefdcd57e96d496fd3492fc28b3d53da6ba0fc6ee69f99dddec1cf500c/apache-iotdb-0.14.0rc1.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 0.14.0rc1
2023-04-04T02:26:03,976   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/6d/37/0e5a292ed1a695927cefec20d4ad01d3c7af78e691d5250f1646f318d4ef/apache_iotdb-0.14.0rc1-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,977   Found link https://files.pythonhosted.org/packages/49/91/11702001bdc0af0266d5f4dd222b5f937684e8c08e5044735ade6748cd58/apache-iotdb-1.0.0.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 1.0.0
2023-04-04T02:26:03,978   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/3d/57/3019d5cf51e6198d5b7ee9e3c07a15efa7487e8b280b4b71cc521a6651e3/apache_iotdb-1.0.0-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,979   Found link https://files.pythonhosted.org/packages/0b/d7/475e11d05f2d4bc65f9b7d14691158489fbb7726a26cee5a016e94e6640a/apache-iotdb-1.0.1.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 1.0.1
2023-04-04T02:26:03,980   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/06/82/b658ff03f52072e1afde6bb9f1f1933427ef776a78e246965943fba552d8/apache_iotdb-1.0.1-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,981   Found link https://files.pythonhosted.org/packages/15/99/bf0d6eae0c005a4dcc88068be36ea3e5b4dcb26e50b6698b4bd814d052e9/apache-iotdb-1.1.0.tar.gz (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7), version: 1.1.0
2023-04-04T02:26:03,982   Skipping link: No binaries permitted for apache-iotdb: https://files.pythonhosted.org/packages/3b/cd/72bfb3f3f3684bfe0c054dfd8c34fdb8a85f7572a6ec27b7a6ff99127516/apache_iotdb-1.1.0-py3-none-any.whl (from https://pypi.org/simple/apache-iotdb/) (requires-python:>=3.7)
2023-04-04T02:26:03,983 Fetching project page and analyzing links: https://www.piwheels.org/simple/apache-iotdb/
2023-04-04T02:26:03,983 Getting page https://www.piwheels.org/simple/apache-iotdb/
2023-04-04T02:26:03,986 Found index url https://www.piwheels.org/simple
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2023-04-04T02:26:30,528   # Apache IoTDB

2023-04-04T02:26:30,529   [![Python Client](https://github.com/apache/iotdb/actions/workflows/client-python.yml/badge.svg?branch=master)](https://github.com/apache/iotdb/actions/workflows/client-python.yml)
2023-04-04T02:26:30,529   [![GitHub release](https://img.shields.io/github/release/apache/iotdb.svg)](https://github.com/apache/iotdb/releases)
2023-04-04T02:26:30,530   [![License](https://img.shields.io/badge/license-Apache%202-4EB1BA.svg)](https://www.apache.org/licenses/LICENSE-2.0.html)
2023-04-04T02:26:30,530   ![](https://github-size-badge.herokuapp.com/apache/iotdb.svg)
2023-04-04T02:26:30,530   ![](https://img.shields.io/github/downloads/apache/iotdb/total.svg)
2023-04-04T02:26:30,531   ![](https://img.shields.io/badge/platform-win%20%7C%20macos%20%7C%20linux-yellow.svg)
2023-04-04T02:26:30,531   [![IoTDB Website](https://img.shields.io/website-up-down-green-red/https/shields.io.svg?label=iotdb-website)](https://iotdb.apache.org/)


2023-04-04T02:26:30,532   Apache IoTDB (Database for Internet of Things) is an IoT native database with high performance for
2023-04-04T02:26:30,532   data management and analysis, deployable on the edge and the cloud. Due to its light-weight
2023-04-04T02:26:30,533   architecture, high performance and rich feature set together with its deep integration with
2023-04-04T02:26:30,533   Apache Hadoop, Spark and Flink, Apache IoTDB can meet the requirements of massive data storage,
2023-04-04T02:26:30,533   high-speed data ingestion and complex data analysis in the IoT industrial fields.

2023-04-04T02:26:30,534   ## Python Native API

2023-04-04T02:26:30,535   ### Requirements

2023-04-04T02:26:30,535   You have to install thrift (>=0.13) before using the package.



2023-04-04T02:26:30,537   ### How to use (Example)

2023-04-04T02:26:30,537   First, download the latest package: `pip3 install apache-iotdb`

2023-04-04T02:26:30,538   *Notice: If you are installing Python API v0.13.0, DO NOT install by `pip install apache-iotdb==0.13.0`, use `pip install apache-iotdb==0.13.0.post1` instead!*

2023-04-04T02:26:30,539   You can get an example of using the package to read and write data at here: [Example](https://github.com/apache/iotdb/blob/master/client-py/SessionExample.py)

2023-04-04T02:26:30,539   An example of aligned timeseries: [Aligned Timeseries Session Example](https://github.com/apache/iotdb/blob/master/client-py/SessionAlignedTimeseriesExample.py)

2023-04-04T02:26:30,540   (you need to add `import iotdb` in the head of the file)

2023-04-04T02:26:30,541   Or:

2023-04-04T02:26:30,541   ```python
2023-04-04T02:26:30,542   from iotdb.Session import Session

2023-04-04T02:26:30,542   ip = "127.0.0.1"
2023-04-04T02:26:30,543   port_ = "6667"
2023-04-04T02:26:30,543   username_ = "root"
2023-04-04T02:26:30,543   password_ = "root"
2023-04-04T02:26:30,544   session = Session(ip, port_, username_, password_)
2023-04-04T02:26:30,544   session.open(False)
2023-04-04T02:26:30,544   zone = session.get_time_zone()
2023-04-04T02:26:30,545   session.close()
2023-04-04T02:26:30,545   ```

2023-04-04T02:26:30,546   ### Initialization

2023-04-04T02:26:30,546   * Initialize a Session

2023-04-04T02:26:30,547   ```python
2023-04-04T02:26:30,547   session = Session(ip, port_, username_, password_, fetch_size=1024, zone_id="UTC+8")
2023-04-04T02:26:30,548   ```

2023-04-04T02:26:30,548   * Open a session, with a parameter to specify whether to enable RPC compression

2023-04-04T02:26:30,549   ```python
2023-04-04T02:26:30,549   session.open(enable_rpc_compression=False)
2023-04-04T02:26:30,550   ```

2023-04-04T02:26:30,550   Notice: this RPC compression status of client must comply with that of IoTDB server

2023-04-04T02:26:30,551   * Close a Session

2023-04-04T02:26:30,552   ```python
2023-04-04T02:26:30,552   session.close()
2023-04-04T02:26:30,552   ```

2023-04-04T02:26:30,553   ### Data Definition Interface (DDL Interface)

2023-04-04T02:26:30,554   #### DATABASE Management

2023-04-04T02:26:30,554   * CREATE DATABASE

2023-04-04T02:26:30,555   ```python
2023-04-04T02:26:30,555   session.set_storage_group(group_name)
2023-04-04T02:26:30,555   ```

2023-04-04T02:26:30,556   * Delete one or several databases

2023-04-04T02:26:30,557   ```python
2023-04-04T02:26:30,557   session.delete_storage_group(group_name)
2023-04-04T02:26:30,557   session.delete_storage_groups(group_name_lst)
2023-04-04T02:26:30,558   ```
2023-04-04T02:26:30,558   #### Timeseries Management

2023-04-04T02:26:30,559   * Create one or multiple timeseries

2023-04-04T02:26:30,559   ```python
2023-04-04T02:26:30,560   session.create_time_series(ts_path, data_type, encoding, compressor,
2023-04-04T02:26:30,560       props=None, tags=None, attributes=None, alias=None)

2023-04-04T02:26:30,561   session.create_multi_time_series(
2023-04-04T02:26:30,561       ts_path_lst, data_type_lst, encoding_lst, compressor_lst,
2023-04-04T02:26:30,561       props_lst=None, tags_lst=None, attributes_lst=None, alias_lst=None
2023-04-04T02:26:30,562   )
2023-04-04T02:26:30,562   ```

2023-04-04T02:26:30,563   * Create aligned timeseries

2023-04-04T02:26:30,563   ```python
2023-04-04T02:26:30,563   session.create_aligned_time_series(
2023-04-04T02:26:30,564       device_id, measurements_lst, data_type_lst, encoding_lst, compressor_lst
2023-04-04T02:26:30,564   )
2023-04-04T02:26:30,564   ```

2023-04-04T02:26:30,565   Attention: Alias of measurements are **not supported** currently.

2023-04-04T02:26:30,566   * Delete one or several timeseries

2023-04-04T02:26:30,566   ```python
2023-04-04T02:26:30,566   session.delete_time_series(paths_list)
2023-04-04T02:26:30,567   ```

2023-04-04T02:26:30,567   * Check whether the specific timeseries exists

2023-04-04T02:26:30,568   ```python
2023-04-04T02:26:30,568   session.check_time_series_exists(path)
2023-04-04T02:26:30,569   ```

2023-04-04T02:26:30,569   ### Data Manipulation Interface (DML Interface)

2023-04-04T02:26:30,570   #### Insert

2023-04-04T02:26:30,571   It is recommended to use insertTablet to help improve write efficiency.

2023-04-04T02:26:30,571   * Insert a Tablet，which is multiple rows of a device, each row has the same measurements
2023-04-04T02:26:30,572       * **Better Write Performance**
2023-04-04T02:26:30,572       * **Support null values**: fill the null value with any value, and then mark the null value via BitMap (from v0.13)


2023-04-04T02:26:30,573   We have two implementations of Tablet in Python API.

2023-04-04T02:26:30,574   * Normal Tablet

2023-04-04T02:26:30,574   ```python
2023-04-04T02:26:30,574   values_ = [
2023-04-04T02:26:30,575       [False, 10, 11, 1.1, 10011.1, "test01"],
2023-04-04T02:26:30,575       [True, 100, 11111, 1.25, 101.0, "test02"],
2023-04-04T02:26:30,575       [False, 100, 1, 188.1, 688.25, "test03"],
2023-04-04T02:26:30,576       [True, 0, 0, 0, 6.25, "test04"],
2023-04-04T02:26:30,576   ]
2023-04-04T02:26:30,576   timestamps_ = [1, 2, 3, 4]
2023-04-04T02:26:30,577   tablet_ = Tablet(
2023-04-04T02:26:30,577       device_id, measurements_, data_types_, values_, timestamps_
2023-04-04T02:26:30,577   )
2023-04-04T02:26:30,578   session.insert_tablet(tablet_)

2023-04-04T02:26:30,578   values_ = [
2023-04-04T02:26:30,579       [None, 10, 11, 1.1, 10011.1, "test01"],
2023-04-04T02:26:30,579       [True, None, 11111, 1.25, 101.0, "test02"],
2023-04-04T02:26:30,579       [False, 100, None, 188.1, 688.25, "test03"],
2023-04-04T02:26:30,580       [True, 0, 0, 0, None, None],
2023-04-04T02:26:30,580   ]
2023-04-04T02:26:30,580   timestamps_ = [16, 17, 18, 19]
2023-04-04T02:26:30,580   tablet_ = Tablet(
2023-04-04T02:26:30,581       device_id, measurements_, data_types_, values_, timestamps_
2023-04-04T02:26:30,581   )
2023-04-04T02:26:30,581   session.insert_tablet(tablet_)
2023-04-04T02:26:30,582   ```
2023-04-04T02:26:30,582   * Numpy Tablet

2023-04-04T02:26:30,583   Comparing with Tablet, Numpy Tablet is using [numpy.ndarray](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html) to record data.
2023-04-04T02:26:30,583   With less memory footprint and time cost of serialization, the insert performance will be better.

2023-04-04T02:26:30,583   **Notice**
2023-04-04T02:26:30,584   1. time and value columns in Tablet are ndarray.
2023-04-04T02:26:30,584   2. recommended to use the specific dtypes to each ndarray, see the example below
2023-04-04T02:26:30,584   (if not, the default dtypes are also ok).

2023-04-04T02:26:30,585   ```python
2023-04-04T02:26:30,585   import numpy as np
2023-04-04T02:26:30,586   data_types_ = [
2023-04-04T02:26:30,586       TSDataType.BOOLEAN,
2023-04-04T02:26:30,586       TSDataType.INT32,
2023-04-04T02:26:30,587       TSDataType.INT64,
2023-04-04T02:26:30,587       TSDataType.FLOAT,
2023-04-04T02:26:30,587       TSDataType.DOUBLE,
2023-04-04T02:26:30,588       TSDataType.TEXT,
2023-04-04T02:26:30,588   ]
2023-04-04T02:26:30,588   np_values_ = [
2023-04-04T02:26:30,589       np.array([False, True, False, True], TSDataType.BOOLEAN.np_dtype()),
2023-04-04T02:26:30,589       np.array([10, 100, 100, 0], TSDataType.INT32.np_dtype()),
2023-04-04T02:26:30,589       np.array([11, 11111, 1, 0], TSDataType.INT64.np_dtype()),
2023-04-04T02:26:30,590       np.array([1.1, 1.25, 188.1, 0], TSDataType.FLOAT.np_dtype()),
2023-04-04T02:26:30,590       np.array([10011.1, 101.0, 688.25, 6.25], TSDataType.DOUBLE.np_dtype()),
2023-04-04T02:26:30,590       np.array(["test01", "test02", "test03", "test04"], TSDataType.TEXT.np_dtype()),
2023-04-04T02:26:30,591   ]
2023-04-04T02:26:30,591   np_timestamps_ = np.array([1, 2, 3, 4], TSDataType.INT64.np_dtype())
2023-04-04T02:26:30,591   np_tablet_ = NumpyTablet(
2023-04-04T02:26:30,592     device_id, measurements_, data_types_, np_values_, np_timestamps_
2023-04-04T02:26:30,592   )
2023-04-04T02:26:30,592   session.insert_tablet(np_tablet_)

2023-04-04T02:26:30,593   # insert one numpy tablet with none into the database.
2023-04-04T02:26:30,593   np_values_ = [
2023-04-04T02:26:30,593       np.array([False, True, False, True], TSDataType.BOOLEAN.np_dtype()),
2023-04-04T02:26:30,594       np.array([10, 100, 100, 0], TSDataType.INT32.np_dtype()),
2023-04-04T02:26:30,594       np.array([11, 11111, 1, 0], TSDataType.INT64.np_dtype()),
2023-04-04T02:26:30,594       np.array([1.1, 1.25, 188.1, 0], TSDataType.FLOAT.np_dtype()),
2023-04-04T02:26:30,595       np.array([10011.1, 101.0, 688.25, 6.25], TSDataType.DOUBLE.np_dtype()),
2023-04-04T02:26:30,595       np.array(["test01", "test02", "test03", "test04"], TSDataType.TEXT.np_dtype()),
2023-04-04T02:26:30,595   ]
2023-04-04T02:26:30,596   np_timestamps_ = np.array([98, 99, 100, 101], TSDataType.INT64.np_dtype())
2023-04-04T02:26:30,596   np_bitmaps_ = []
2023-04-04T02:26:30,596   for i in range(len(measurements_)):
2023-04-04T02:26:30,597       np_bitmaps_.append(BitMap(len(np_timestamps_)))
2023-04-04T02:26:30,597   np_bitmaps_[0].mark(0)
2023-04-04T02:26:30,597   np_bitmaps_[1].mark(1)
2023-04-04T02:26:30,598   np_bitmaps_[2].mark(2)
2023-04-04T02:26:30,598   np_bitmaps_[4].mark(3)
2023-04-04T02:26:30,598   np_bitmaps_[5].mark(3)
2023-04-04T02:26:30,599   np_tablet_with_none = NumpyTablet(
2023-04-04T02:26:30,599       device_id, measurements_, data_types_, np_values_, np_timestamps_, np_bitmaps_
2023-04-04T02:26:30,599   )
2023-04-04T02:26:30,600   session.insert_tablet(np_tablet_with_none)
2023-04-04T02:26:30,600   ```

2023-04-04T02:26:30,600   * Insert multiple Tablets

2023-04-04T02:26:30,601   ```python
2023-04-04T02:26:30,601   session.insert_tablets(tablet_lst)
2023-04-04T02:26:30,602   ```

2023-04-04T02:26:30,602   * Insert a Record

2023-04-04T02:26:30,603   ```python
2023-04-04T02:26:30,603   session.insert_record(device_id, timestamp, measurements_, data_types_, values_)
2023-04-04T02:26:30,603   ```

2023-04-04T02:26:30,604   * Insert multiple Records

2023-04-04T02:26:30,605   ```python
2023-04-04T02:26:30,605   session.insert_records(
2023-04-04T02:26:30,605       device_ids_, time_list_, measurements_list_, data_type_list_, values_list_
2023-04-04T02:26:30,606   )
2023-04-04T02:26:30,606   ```

2023-04-04T02:26:30,607   * Insert multiple Records that belong to the same device.
2023-04-04T02:26:30,607     With type info the server has no need to do type inference, which leads a better performance


2023-04-04T02:26:30,608   ```python
2023-04-04T02:26:30,608   session.insert_records_of_one_device(device_id, time_list, measurements_list, data_types_list, values_list)
2023-04-04T02:26:30,609   ```

2023-04-04T02:26:30,609   #### Insert with type inference

2023-04-04T02:26:30,610   When the data is of String type, we can use the following interface to perform type inference based on the value of the value itself. For example, if value is "true" , it can be automatically inferred to be a boolean type. If value is "3.2" , it can be automatically inferred as a flout type. Without type information, server has to do type inference, which may cost some time.

2023-04-04T02:26:30,611   * Insert a Record, which contains multiple measurement value of a device at a timestamp

2023-04-04T02:26:30,611   ```python
2023-04-04T02:26:30,612   session.insert_str_record(device_id, timestamp, measurements, string_values)
2023-04-04T02:26:30,612   ```

2023-04-04T02:26:30,613   #### Insert of Aligned Timeseries

2023-04-04T02:26:30,613   The Insert of aligned timeseries uses interfaces like insert_aligned_XXX, and others are similar to the above interfaces:

2023-04-04T02:26:30,614   * insert_aligned_record
2023-04-04T02:26:30,614   * insert_aligned_records
2023-04-04T02:26:30,614   * insert_aligned_records_of_one_device
2023-04-04T02:26:30,615   * insert_aligned_tablet
2023-04-04T02:26:30,615   * insert_aligned_tablets


2023-04-04T02:26:30,616   ### IoTDB-SQL Interface

2023-04-04T02:26:30,616   * Execute query statement

2023-04-04T02:26:30,617   ```python
2023-04-04T02:26:30,617   session.execute_query_statement(sql)
2023-04-04T02:26:30,618   ```

2023-04-04T02:26:30,618   * Execute non query statement

2023-04-04T02:26:30,619   ```python
2023-04-04T02:26:30,619   session.execute_non_query_statement(sql)
2023-04-04T02:26:30,620   ```

2023-04-04T02:26:30,620   * Execute statement

2023-04-04T02:26:30,621   ```python
2023-04-04T02:26:30,621   session.execute_statement(sql)
2023-04-04T02:26:30,622   ```

2023-04-04T02:26:30,622   ### Schema Template
2023-04-04T02:26:30,622   #### Create Schema Template
2023-04-04T02:26:30,623   The step for creating a metadata template is as follows
2023-04-04T02:26:30,623   1. Create the template class
2023-04-04T02:26:30,623   2. Adding child Node，InternalNode and MeasurementNode can be chose
2023-04-04T02:26:30,624   3. Execute create schema template function

2023-04-04T02:26:30,624   ```python
2023-04-04T02:26:30,625   template = Template(name=template_name, share_time=True)

2023-04-04T02:26:30,625   i_node_gps = InternalNode(name="GPS", share_time=False)
2023-04-04T02:26:30,626   i_node_v = InternalNode(name="vehicle", share_time=True)
2023-04-04T02:26:30,626   m_node_x = MeasurementNode("x", TSDataType.FLOAT, TSEncoding.RLE, Compressor.SNAPPY)

2023-04-04T02:26:30,627   i_node_gps.add_child(m_node_x)
2023-04-04T02:26:30,627   i_node_v.add_child(m_node_x)

2023-04-04T02:26:30,628   template.add_template(i_node_gps)
2023-04-04T02:26:30,629   template.add_template(i_node_v)
2023-04-04T02:26:30,629   template.add_template(m_node_x)

2023-04-04T02:26:30,630   session.create_schema_template(template)
2023-04-04T02:26:30,630   ```
2023-04-04T02:26:30,630   #### Modify Schema Template nodes
2023-04-04T02:26:30,631   Modify nodes in a template, the template must be already created. These are functions that add or delete some measurement nodes.
2023-04-04T02:26:30,631   * add node in template
2023-04-04T02:26:30,631   ```python
2023-04-04T02:26:30,631   session.add_measurements_in_template(template_name, measurements_path, data_types, encodings, compressors, is_aligned)
2023-04-04T02:26:30,632   ```

2023-04-04T02:26:30,632   * delete node in template
2023-04-04T02:26:30,633   ```python
2023-04-04T02:26:30,633   session.delete_node_in_template(template_name, path)
2023-04-04T02:26:30,633   ```

2023-04-04T02:26:30,634   #### Set Schema Template
2023-04-04T02:26:30,634   ```python
2023-04-04T02:26:30,634   session.set_schema_template(template_name, prefix_path)
2023-04-04T02:26:30,635   ```

2023-04-04T02:26:30,635   #### Uset Schema Template
2023-04-04T02:26:30,636   ```python
2023-04-04T02:26:30,636   session.unset_schema_template(template_name, prefix_path)
2023-04-04T02:26:30,636   ```

2023-04-04T02:26:30,637   #### Show Schema Template
2023-04-04T02:26:30,637   * Show all schema templates
2023-04-04T02:26:30,637   ```python
2023-04-04T02:26:30,638   session.show_all_templates()
2023-04-04T02:26:30,638   ```
2023-04-04T02:26:30,638   * Count all nodes in templates
2023-04-04T02:26:30,639   ```python
2023-04-04T02:26:30,639   session.count_measurements_in_template(template_name)
2023-04-04T02:26:30,639   ```

2023-04-04T02:26:30,640   * Judge whether the path is measurement or not in templates, This measurement must be in the template
2023-04-04T02:26:30,640   ```python
2023-04-04T02:26:30,640   session.count_measurements_in_template(template_name, path)
2023-04-04T02:26:30,641   ```

2023-04-04T02:26:30,641   * Judge whether the path is exist or not in templates, This path may not belong to the template
2023-04-04T02:26:30,642   ```python
2023-04-04T02:26:30,642   session.is_path_exist_in_template(template_name, path)
2023-04-04T02:26:30,642   ```

2023-04-04T02:26:30,643   * Show nodes under in schema template
2023-04-04T02:26:30,643   ```python
2023-04-04T02:26:30,643   session.show_measurements_in_template(template_name)
2023-04-04T02:26:30,644   ```

2023-04-04T02:26:30,644   * Show the path prefix where a schema template is set
2023-04-04T02:26:30,644   ```python
2023-04-04T02:26:30,645   session.show_paths_template_set_on(template_name)
2023-04-04T02:26:30,645   ```

2023-04-04T02:26:30,646   * Show the path prefix where a schema template is used (i.e. the time series has been created)
2023-04-04T02:26:30,646   ```python
2023-04-04T02:26:30,646   session.show_paths_template_using_on(template_name)
2023-04-04T02:26:30,647   ```

2023-04-04T02:26:30,647   #### Drop Schema Template
2023-04-04T02:26:30,647   Delete an existing metadata template，dropping an already set template is not supported
2023-04-04T02:26:30,648   ```python
2023-04-04T02:26:30,648   session.drop_schema_template("template_python")
2023-04-04T02:26:30,649   ```


2023-04-04T02:26:30,649   ### Pandas Support

2023-04-04T02:26:30,650   To easily transform a query result to a [Pandas Dataframe](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html)
2023-04-04T02:26:30,650   the SessionDataSet has a method `.todf()` which consumes the dataset and transforms it to a pandas dataframe.

2023-04-04T02:26:30,651   Example:

2023-04-04T02:26:30,651   ```python
2023-04-04T02:26:30,652   from iotdb.Session import Session

2023-04-04T02:26:30,652   ip = "127.0.0.1"
2023-04-04T02:26:30,653   port_ = "6667"
2023-04-04T02:26:30,653   username_ = "root"
2023-04-04T02:26:30,653   password_ = "root"
2023-04-04T02:26:30,654   session = Session(ip, port_, username_, password_)
2023-04-04T02:26:30,654   session.open(False)
2023-04-04T02:26:30,654   result = session.execute_query_statement("SELECT * FROM root.*")

2023-04-04T02:26:30,655   # Transform to Pandas Dataset
2023-04-04T02:26:30,655   df = result.todf()

2023-04-04T02:26:30,656   session.close()

2023-04-04T02:26:30,656   # Now you can work with the dataframe
2023-04-04T02:26:30,657   df = ...
2023-04-04T02:26:30,657   ```


2023-04-04T02:26:30,658   ### IoTDB Testcontainer

2023-04-04T02:26:30,659   The Test Support is based on the lib `testcontainers` (https://testcontainers-python.readthedocs.io/en/latest/index.html) which you need to install in your project if you want to use the feature.

2023-04-04T02:26:30,659   To start (and stop) an IoTDB Database in a Docker container simply do:
2023-04-04T02:26:30,660   ```python
2023-04-04T02:26:30,660   class MyTestCase(unittest.TestCase):

2023-04-04T02:26:30,660       def test_something(self):
2023-04-04T02:26:30,661           with IoTDBContainer() as c:
2023-04-04T02:26:30,661               session = Session("localhost", c.get_exposed_port(6667), "root", "root")
2023-04-04T02:26:30,661               session.open(False)
2023-04-04T02:26:30,662               result = session.execute_query_statement("SHOW TIMESERIES")
2023-04-04T02:26:30,662               print(result)
2023-04-04T02:26:30,662               session.close()
2023-04-04T02:26:30,663   ```

2023-04-04T02:26:30,663   by default it will load the image `apache/iotdb:latest`, if you want a specific version just pass it like e.g. `IoTDBContainer("apache/iotdb:0.12.0")` to get version `0.12.0` running.


2023-04-04T02:26:30,664   ### IoTDB DBAPI

2023-04-04T02:26:30,665   IoTDB DBAPI implements the Python DB API 2.0 specification (https://peps.python.org/pep-0249/), which defines a common
2023-04-04T02:26:30,665   interface for accessing databases in Python.

2023-04-04T02:26:30,666   #### Examples
2023-04-04T02:26:30,666   + Initialization

2023-04-04T02:26:30,667   The initialized parameters are consistent with the session part (except for the sqlalchemy_mode).
2023-04-04T02:26:30,667   ```python
2023-04-04T02:26:30,667   from iotdb.dbapi import connect

2023-04-04T02:26:30,668   ip = "127.0.0.1"
2023-04-04T02:26:30,668   port_ = "6667"
2023-04-04T02:26:30,668   username_ = "root"
2023-04-04T02:26:30,669   password_ = "root"
2023-04-04T02:26:30,669   conn = connect(ip, port_, username_, password_,fetch_size=1024,zone_id="UTC+8",sqlalchemy_mode=False)
2023-04-04T02:26:30,669   cursor = conn.cursor()
2023-04-04T02:26:30,670   ```
2023-04-04T02:26:30,670   + simple SQL statement execution
2023-04-04T02:26:30,670   ```python
2023-04-04T02:26:30,671   cursor.execute("SELECT * FROM root.*")
2023-04-04T02:26:30,671   for row in cursor.fetchall():
2023-04-04T02:26:30,671       print(row)
2023-04-04T02:26:30,672   ```

2023-04-04T02:26:30,672   + execute SQL with parameter

2023-04-04T02:26:30,673   IoTDB DBAPI supports pyformat style parameters
2023-04-04T02:26:30,673   ```python
2023-04-04T02:26:30,674   cursor.execute("SELECT * FROM root.* WHERE time < %(time)s",{"time":"2017-11-01T00:08:00.000"})
2023-04-04T02:26:30,674   for row in cursor.fetchall():
2023-04-04T02:26:30,674       print(row)
2023-04-04T02:26:30,675   ```

2023-04-04T02:26:30,675   + execute SQL with parameter sequences
2023-04-04T02:26:30,676   ```python
2023-04-04T02:26:30,676   seq_of_parameters = [
2023-04-04T02:26:30,676       {"timestamp": 1, "temperature": 1},
2023-04-04T02:26:30,677       {"timestamp": 2, "temperature": 2},
2023-04-04T02:26:30,677       {"timestamp": 3, "temperature": 3},
2023-04-04T02:26:30,677       {"timestamp": 4, "temperature": 4},
2023-04-04T02:26:30,677       {"timestamp": 5, "temperature": 5},
2023-04-04T02:26:30,678   ]
2023-04-04T02:26:30,678   sql = "insert into root.cursor(timestamp,temperature) values(%(timestamp)s,%(temperature)s)"
2023-04-04T02:26:30,678   cursor.executemany(sql,seq_of_parameters)
2023-04-04T02:26:30,679   ```

2023-04-04T02:26:30,679   + close the connection and cursor
2023-04-04T02:26:30,680   ```python
2023-04-04T02:26:30,680   cursor.close()
2023-04-04T02:26:30,680   conn.close()
2023-04-04T02:26:30,681   ```

2023-04-04T02:26:30,681   ### IoTDB SQLAlchemy Dialect (Experimental)
2023-04-04T02:26:30,682   The SQLAlchemy dialect of IoTDB is written to adapt to Apache Superset.
2023-04-04T02:26:30,682   This part is still being improved.
2023-04-04T02:26:30,682   Please do not use it in the production environment!
2023-04-04T02:26:30,683   #### Mapping of the metadata
2023-04-04T02:26:30,683   The data model used by SQLAlchemy is a relational data model, which describes the relationships between different entities through tables.
2023-04-04T02:26:30,683   While the data model of IoTDB is a hierarchical data model, which organizes the data through a tree structure.
2023-04-04T02:26:30,684   In order to adapt IoTDB to the dialect of SQLAlchemy, the original data model in IoTDB needs to be reorganized.
2023-04-04T02:26:30,684   Converting the data model of IoTDB into the data model of SQLAlchemy.

2023-04-04T02:26:30,685   The metadata in the IoTDB are：

2023-04-04T02:26:30,685   1. Database
2023-04-04T02:26:30,685   2. Path
2023-04-04T02:26:30,686   3. Entity
2023-04-04T02:26:30,686   4. Measurement

2023-04-04T02:26:30,687   The metadata in the SQLAlchemy are：
2023-04-04T02:26:30,687   1. Schema
2023-04-04T02:26:30,687   2. Table
2023-04-04T02:26:30,688   3. Column

2023-04-04T02:26:30,688   The mapping relationship between them is：

2023-04-04T02:26:30,689   | The metadata in the SQLAlchemy | The metadata in the IoTDB                            |
2023-04-04T02:26:30,689   | -------------------- | ---------------------------------------------- |
2023-04-04T02:26:30,689   | Schema               |      Database                                  |
2023-04-04T02:26:30,690   | Table                | Path ( from database to entity ) + Entity |
2023-04-04T02:26:30,690   | Column               | Measurement                                    |

2023-04-04T02:26:30,691   The following figure shows the relationship between the two more intuitively:

2023-04-04T02:26:30,691   ![sqlalchemy-to-iotdb](https://github.com/apache/iotdb-bin-resources/blob/main/docs/UserGuide/API/IoTDB-SQLAlchemy/sqlalchemy-to-iotdb.png?raw=true)

2023-04-04T02:26:30,692   #### Data type mapping
2023-04-04T02:26:30,692   | data type in IoTDB | data type in SQLAlchemy |
2023-04-04T02:26:30,692   |--------------------|-------------------------|
2023-04-04T02:26:30,693   | BOOLEAN            | Boolean                 |
2023-04-04T02:26:30,693   | INT32              | Integer                 |
2023-04-04T02:26:30,693   | INT64              | BigInteger              |
2023-04-04T02:26:30,694   | FLOAT              | Float                   |
2023-04-04T02:26:30,694   | DOUBLE             | Float                   |
2023-04-04T02:26:30,694   | TEXT               | Text                    |
2023-04-04T02:26:30,694   | LONG               | BigInteger              |
2023-04-04T02:26:30,695   #### Example

2023-04-04T02:26:30,695   + execute statement

2023-04-04T02:26:30,696   ```python
2023-04-04T02:26:30,696   from sqlalchemy import create_engine

2023-04-04T02:26:30,697   engine = create_engine("iotdb://root:root@127.0.0.1:6667")
2023-04-04T02:26:30,697   connect = engine.connect()
2023-04-04T02:26:30,697   result = connect.execute("SELECT ** FROM root")
2023-04-04T02:26:30,698   for row in result.fetchall():
2023-04-04T02:26:30,698       print(row)
2023-04-04T02:26:30,698   ```

2023-04-04T02:26:30,699   + ORM (now only simple queries are supported)

2023-04-04T02:26:30,700   ```python
2023-04-04T02:26:30,700   from sqlalchemy import create_engine, Column, Float, BigInteger, MetaData
2023-04-04T02:26:30,700   from sqlalchemy.ext.declarative import declarative_base
2023-04-04T02:26:30,701   from sqlalchemy.orm import sessionmaker

2023-04-04T02:26:30,701   metadata = MetaData(
2023-04-04T02:26:30,702       schema='root.factory'
2023-04-04T02:26:30,702   )
2023-04-04T02:26:30,702   Base = declarative_base(metadata=metadata)


2023-04-04T02:26:30,703   class Device(Base):
2023-04-04T02:26:30,703       __tablename__ = "room2.device1"
2023-04-04T02:26:30,704       Time = Column(BigInteger, primary_key=True)
2023-04-04T02:26:30,704       temperature = Column(Float)
2023-04-04T02:26:30,704       status = Column(Float)


2023-04-04T02:26:30,705   engine = create_engine("iotdb://root:root@127.0.0.1:6667")

2023-04-04T02:26:30,706   DbSession = sessionmaker(bind=engine)
2023-04-04T02:26:30,706   session = DbSession()

2023-04-04T02:26:30,707   res = session.query(Device.status).filter(Device.temperature > 1)

2023-04-04T02:26:30,707   for row in res:
2023-04-04T02:26:30,708       print(row)
2023-04-04T02:26:30,708   ```


2023-04-04T02:26:30,709   ## Developers

2023-04-04T02:26:30,710   ### Introduction

2023-04-04T02:26:30,710   This is an example of how to connect to IoTDB with python, using the thrift rpc interfaces. Things are almost the same on Windows or Linux, but pay attention to the difference like path separator.



2023-04-04T02:26:30,711   ### Prerequisites

2023-04-04T02:26:30,712   Python3.7 or later is preferred.

2023-04-04T02:26:30,713   You have to install Thrift (0.11.0 or later) to compile our thrift file into python code. Below is the official tutorial of installation, eventually, you should have a thrift executable.

2023-04-04T02:26:30,713   ```
2023-04-04T02:26:30,714   http://thrift.apache.org/docs/install/
2023-04-04T02:26:30,714   ```

2023-04-04T02:26:30,715   Before starting you need to install `requirements_dev.txt` in your python environment, e.g. by calling
2023-04-04T02:26:30,715   ```shell
2023-04-04T02:26:30,715   pip install -r requirements_dev.txt
2023-04-04T02:26:30,716   ```



2023-04-04T02:26:30,717   ### Compile the thrift library and Debug

2023-04-04T02:26:30,718   In the root of IoTDB's source code folder,  run `mvn clean generate-sources -pl client-py -am`.

2023-04-04T02:26:30,718   This will automatically delete and repopulate the folder `iotdb/thrift` with the generated thrift files.
2023-04-04T02:26:30,718   This folder is ignored from git and should **never be pushed to git!**

2023-04-04T02:26:30,719   **Notice** Do not upload `iotdb/thrift` to the git repo.




2023-04-04T02:26:30,720   ### Session Client & Example

2023-04-04T02:26:30,721   We packed up the Thrift interface in `client-py/src/iotdb/Session.py` (similar with its Java counterpart), also provided an example file `client-py/src/SessionExample.py` of how to use the session module. please read it carefully.


2023-04-04T02:26:30,722   Or, another simple example:

2023-04-04T02:26:30,723   ```python
2023-04-04T02:26:30,723   from iotdb.Session import Session

2023-04-04T02:26:30,724   ip = "127.0.0.1"
2023-04-04T02:26:30,724   port_ = "6667"
2023-04-04T02:26:30,724   username_ = "root"
2023-04-04T02:26:30,725   password_ = "root"
2023-04-04T02:26:30,725   session = Session(ip, port_, username_, password_)
2023-04-04T02:26:30,725   session.open(False)
2023-04-04T02:26:30,725   zone = session.get_time_zone()
2023-04-04T02:26:30,726   session.close()
2023-04-04T02:26:30,726   ```



2023-04-04T02:26:30,727   ### Tests

2023-04-04T02:26:30,728   Please add your custom tests in `tests` folder.

2023-04-04T02:26:30,729   To run all defined tests just type `pytest .` in the root folder.

2023-04-04T02:26:30,729   **Notice** Some tests need docker to be started on your system as a test instance is started in a docker container using [testcontainers](https://testcontainers-python.readthedocs.io/en/latest/index.html).



2023-04-04T02:26:30,730   ### Futher Tools

2023-04-04T02:26:30,731   [black](https://pypi.org/project/black/) and [flake8](https://pypi.org/project/flake8/) are installed for autoformatting and linting.
2023-04-04T02:26:30,731   Both can be run by `black .` or `flake8 .` respectively.



2023-04-04T02:26:30,733   ## Releasing

2023-04-04T02:26:30,733   To do a release just ensure that you have the right set of generated thrift files.
2023-04-04T02:26:30,734   Then run linting and auto-formatting.
2023-04-04T02:26:30,734   Then, ensure that all tests work (via `pytest .`).
2023-04-04T02:26:30,734   Then you are good to go to do a release!



2023-04-04T02:26:30,736   ### Preparing your environment

2023-04-04T02:26:30,736   First, install all necessary dev dependencies via `pip install -r requirements_dev.txt`.



2023-04-04T02:26:30,737   ### Doing the Release

2023-04-04T02:26:30,738   There is a convenient script `release.sh` to do all steps for a release.
2023-04-04T02:26:30,738   Namely, these are

2023-04-04T02:26:30,739   * Remove all transient directories from last release (if exists)
2023-04-04T02:26:30,739   * (Re-)generate all generated sources via mvn
2023-04-04T02:26:30,740   * Run Linting (flake8)
2023-04-04T02:26:30,740   * Run Tests via pytest
2023-04-04T02:26:30,740   * Build
2023-04-04T02:26:30,741   * Release to pypi



2023-04-04T02:26:30,758   running egg_info
2023-04-04T02:26:30,769   writing apache_iotdb.egg-info/PKG-INFO
2023-04-04T02:26:30,775   writing dependency_links to apache_iotdb.egg-info/dependency_links.txt
2023-04-04T02:26:30,779   writing entry points to apache_iotdb.egg-info/entry_points.txt
2023-04-04T02:26:30,782   writing requirements to apache_iotdb.egg-info/requires.txt
2023-04-04T02:26:30,784   writing top-level names to apache_iotdb.egg-info/top_level.txt
2023-04-04T02:26:30,855   reading manifest file 'apache_iotdb.egg-info/SOURCES.txt'
2023-04-04T02:26:30,862   adding license file 'LICENSE'
2023-04-04T02:26:30,875   writing manifest file 'apache_iotdb.egg-info/SOURCES.txt'
2023-04-04T02:26:30,879   /tmp/pip-build-env-5ggwxfha/overlay/lib/python3.7/site-packages/setuptools/_distutils/dist.py:265: UserWarning: Unknown distribution option: 'website'
2023-04-04T02:26:30,880     warnings.warn(msg)
2023-04-04T02:26:30,992   Getting requirements to build wheel: finished with status 'done'
2023-04-04T02:26:31,012   Created temporary directory: /tmp/pip-modern-metadata-zsp_dymq
2023-04-04T02:26:31,018   Preparing metadata (pyproject.toml): started
2023-04-04T02:26:31,020   Running command Preparing metadata (pyproject.toml)
2023-04-04T02:26:32,112   <!--

2023-04-04T02:26:32,113       Licensed to the Apache Software Foundation (ASF) under one
2023-04-04T02:26:32,114       or more contributor license agreements.  See the NOTICE file
2023-04-04T02:26:32,114       distributed with this work for additional information
2023-04-04T02:26:32,114       regarding copyright ownership.  The ASF licenses this file
2023-04-04T02:26:32,115       to you under the Apache License, Version 2.0 (the
2023-04-04T02:26:32,115       "License"); you may not use this file except in compliance
2023-04-04T02:26:32,115       with the License.  You may obtain a copy of the License at

2023-04-04T02:26:32,116           http://www.apache.org/licenses/LICENSE-2.0

2023-04-04T02:26:32,117       Unless required by applicable law or agreed to in writing,
2023-04-04T02:26:32,117       software distributed under the License is distributed on an
2023-04-04T02:26:32,117       "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
2023-04-04T02:26:32,118       KIND, either express or implied.  See the License for the
2023-04-04T02:26:32,118       specific language governing permissions and limitations
2023-04-04T02:26:32,118       under the License.

2023-04-04T02:26:32,119   -->

2023-04-04T02:26:32,120   # Apache IoTDB

2023-04-04T02:26:32,120   [![Python Client](https://github.com/apache/iotdb/actions/workflows/client-python.yml/badge.svg?branch=master)](https://github.com/apache/iotdb/actions/workflows/client-python.yml)
2023-04-04T02:26:32,121   [![GitHub release](https://img.shields.io/github/release/apache/iotdb.svg)](https://github.com/apache/iotdb/releases)
2023-04-04T02:26:32,121   [![License](https://img.shields.io/badge/license-Apache%202-4EB1BA.svg)](https://www.apache.org/licenses/LICENSE-2.0.html)
2023-04-04T02:26:32,121   ![](https://github-size-badge.herokuapp.com/apache/iotdb.svg)
2023-04-04T02:26:32,122   ![](https://img.shields.io/github/downloads/apache/iotdb/total.svg)
2023-04-04T02:26:32,122   ![](https://img.shields.io/badge/platform-win%20%7C%20macos%20%7C%20linux-yellow.svg)
2023-04-04T02:26:32,122   [![IoTDB Website](https://img.shields.io/website-up-down-green-red/https/shields.io.svg?label=iotdb-website)](https://iotdb.apache.org/)


2023-04-04T02:26:32,123   Apache IoTDB (Database for Internet of Things) is an IoT native database with high performance for
2023-04-04T02:26:32,124   data management and analysis, deployable on the edge and the cloud. Due to its light-weight
2023-04-04T02:26:32,124   architecture, high performance and rich feature set together with its deep integration with
2023-04-04T02:26:32,124   Apache Hadoop, Spark and Flink, Apache IoTDB can meet the requirements of massive data storage,
2023-04-04T02:26:32,125   high-speed data ingestion and complex data analysis in the IoT industrial fields.

2023-04-04T02:26:32,125   ## Python Native API

2023-04-04T02:26:32,126   ### Requirements

2023-04-04T02:26:32,127   You have to install thrift (>=0.13) before using the package.



2023-04-04T02:26:32,128   ### How to use (Example)

2023-04-04T02:26:32,129   First, download the latest package: `pip3 install apache-iotdb`

2023-04-04T02:26:32,129   *Notice: If you are installing Python API v0.13.0, DO NOT install by `pip install apache-iotdb==0.13.0`, use `pip install apache-iotdb==0.13.0.post1` instead!*

2023-04-04T02:26:32,130   You can get an example of using the package to read and write data at here: [Example](https://github.com/apache/iotdb/blob/master/client-py/SessionExample.py)

2023-04-04T02:26:32,131   An example of aligned timeseries: [Aligned Timeseries Session Example](https://github.com/apache/iotdb/blob/master/client-py/SessionAlignedTimeseriesExample.py)

2023-04-04T02:26:32,131   (you need to add `import iotdb` in the head of the file)

2023-04-04T02:26:32,132   Or:

2023-04-04T02:26:32,132   ```python
2023-04-04T02:26:32,133   from iotdb.Session import Session

2023-04-04T02:26:32,133   ip = "127.0.0.1"
2023-04-04T02:26:32,134   port_ = "6667"
2023-04-04T02:26:32,134   username_ = "root"
2023-04-04T02:26:32,134   password_ = "root"
2023-04-04T02:26:32,135   session = Session(ip, port_, username_, password_)
2023-04-04T02:26:32,135   session.open(False)
2023-04-04T02:26:32,135   zone = session.get_time_zone()
2023-04-04T02:26:32,136   session.close()
2023-04-04T02:26:32,136   ```

2023-04-04T02:26:32,137   ### Initialization

2023-04-04T02:26:32,137   * Initialize a Session

2023-04-04T02:26:32,138   ```python
2023-04-04T02:26:32,138   session = Session(ip, port_, username_, password_, fetch_size=1024, zone_id="UTC+8")
2023-04-04T02:26:32,138   ```

2023-04-04T02:26:32,139   * Open a session, with a parameter to specify whether to enable RPC compression

2023-04-04T02:26:32,140   ```python
2023-04-04T02:26:32,140   session.open(enable_rpc_compression=False)
2023-04-04T02:26:32,140   ```

2023-04-04T02:26:32,141   Notice: this RPC compression status of client must comply with that of IoTDB server

2023-04-04T02:26:32,141   * Close a Session

2023-04-04T02:26:32,142   ```python
2023-04-04T02:26:32,142   session.close()
2023-04-04T02:26:32,143   ```

2023-04-04T02:26:32,143   ### Data Definition Interface (DDL Interface)

2023-04-04T02:26:32,144   #### DATABASE Management

2023-04-04T02:26:32,144   * CREATE DATABASE

2023-04-04T02:26:32,145   ```python
2023-04-04T02:26:32,145   session.set_storage_group(group_name)
2023-04-04T02:26:32,146   ```

2023-04-04T02:26:32,146   * Delete one or several databases

2023-04-04T02:26:32,147   ```python
2023-04-04T02:26:32,147   session.delete_storage_group(group_name)
2023-04-04T02:26:32,148   session.delete_storage_groups(group_name_lst)
2023-04-04T02:26:32,148   ```
2023-04-04T02:26:32,148   #### Timeseries Management

2023-04-04T02:26:32,149   * Create one or multiple timeseries

2023-04-04T02:26:32,150   ```python
2023-04-04T02:26:32,150   session.create_time_series(ts_path, data_type, encoding, compressor,
2023-04-04T02:26:32,150       props=None, tags=None, attributes=None, alias=None)

2023-04-04T02:26:32,151   session.create_multi_time_series(
2023-04-04T02:26:32,151       ts_path_lst, data_type_lst, encoding_lst, compressor_lst,
2023-04-04T02:26:32,151       props_lst=None, tags_lst=None, attributes_lst=None, alias_lst=None
2023-04-04T02:26:32,152   )
2023-04-04T02:26:32,152   ```

2023-04-04T02:26:32,152   * Create aligned timeseries

2023-04-04T02:26:32,153   ```python
2023-04-04T02:26:32,153   session.create_aligned_time_series(
2023-04-04T02:26:32,154       device_id, measurements_lst, data_type_lst, encoding_lst, compressor_lst
2023-04-04T02:26:32,154   )
2023-04-04T02:26:32,154   ```

2023-04-04T02:26:32,155   Attention: Alias of measurements are **not supported** currently.

2023-04-04T02:26:32,156   * Delete one or several timeseries

2023-04-04T02:26:32,156   ```python
2023-04-04T02:26:32,156   session.delete_time_series(paths_list)
2023-04-04T02:26:32,157   ```

2023-04-04T02:26:32,157   * Check whether the specific timeseries exists

2023-04-04T02:26:32,158   ```python
2023-04-04T02:26:32,158   session.check_time_series_exists(path)
2023-04-04T02:26:32,159   ```

2023-04-04T02:26:32,159   ### Data Manipulation Interface (DML Interface)

2023-04-04T02:26:32,160   #### Insert

2023-04-04T02:26:32,161   It is recommended to use insertTablet to help improve write efficiency.

2023-04-04T02:26:32,161   * Insert a Tablet，which is multiple rows of a device, each row has the same measurements
2023-04-04T02:26:32,162       * **Better Write Performance**
2023-04-04T02:26:32,162       * **Support null values**: fill the null value with any value, and then mark the null value via BitMap (from v0.13)


2023-04-04T02:26:32,163   We have two implementations of Tablet in Python API.

2023-04-04T02:26:32,163   * Normal Tablet

2023-04-04T02:26:32,164   ```python
2023-04-04T02:26:32,164   values_ = [
2023-04-04T02:26:32,164       [False, 10, 11, 1.1, 10011.1, "test01"],
2023-04-04T02:26:32,165       [True, 100, 11111, 1.25, 101.0, "test02"],
2023-04-04T02:26:32,165       [False, 100, 1, 188.1, 688.25, "test03"],
2023-04-04T02:26:32,165       [True, 0, 0, 0, 6.25, "test04"],
2023-04-04T02:26:32,166   ]
2023-04-04T02:26:32,166   timestamps_ = [1, 2, 3, 4]
2023-04-04T02:26:32,166   tablet_ = Tablet(
2023-04-04T02:26:32,167       device_id, measurements_, data_types_, values_, timestamps_
2023-04-04T02:26:32,167   )
2023-04-04T02:26:32,167   session.insert_tablet(tablet_)

2023-04-04T02:26:32,168   values_ = [
2023-04-04T02:26:32,168       [None, 10, 11, 1.1, 10011.1, "test01"],
2023-04-04T02:26:32,169       [True, None, 11111, 1.25, 101.0, "test02"],
2023-04-04T02:26:32,169       [False, 100, None, 188.1, 688.25, "test03"],
2023-04-04T02:26:32,169       [True, 0, 0, 0, None, None],
2023-04-04T02:26:32,169   ]
2023-04-04T02:26:32,170   timestamps_ = [16, 17, 18, 19]
2023-04-04T02:26:32,170   tablet_ = Tablet(
2023-04-04T02:26:32,170       device_id, measurements_, data_types_, values_, timestamps_
2023-04-04T02:26:32,171   )
2023-04-04T02:26:32,171   session.insert_tablet(tablet_)
2023-04-04T02:26:32,171   ```
2023-04-04T02:26:32,171   * Numpy Tablet

2023-04-04T02:26:32,172   Comparing with Tablet, Numpy Tablet is using [numpy.ndarray](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html) to record data.
2023-04-04T02:26:32,172   With less memory footprint and time cost of serialization, the insert performance will be better.

2023-04-04T02:26:32,173   **Notice**
2023-04-04T02:26:32,173   1. time and value columns in Tablet are ndarray.
2023-04-04T02:26:32,174   2. recommended to use the specific dtypes to each ndarray, see the example below
2023-04-04T02:26:32,174   (if not, the default dtypes are also ok).

2023-04-04T02:26:32,174   ```python
2023-04-04T02:26:32,175   import numpy as np
2023-04-04T02:26:32,175   data_types_ = [
2023-04-04T02:26:32,175       TSDataType.BOOLEAN,
2023-04-04T02:26:32,176       TSDataType.INT32,
2023-04-04T02:26:32,176       TSDataType.INT64,
2023-04-04T02:26:32,176       TSDataType.FLOAT,
2023-04-04T02:26:32,177       TSDataType.DOUBLE,
2023-04-04T02:26:32,177       TSDataType.TEXT,
2023-04-04T02:26:32,177   ]
2023-04-04T02:26:32,177   np_values_ = [
2023-04-04T02:26:32,178       np.array([False, True, False, True], TSDataType.BOOLEAN.np_dtype()),
2023-04-04T02:26:32,178       np.array([10, 100, 100, 0], TSDataType.INT32.np_dtype()),
2023-04-04T02:26:32,178       np.array([11, 11111, 1, 0], TSDataType.INT64.np_dtype()),
2023-04-04T02:26:32,179       np.array([1.1, 1.25, 188.1, 0], TSDataType.FLOAT.np_dtype()),
2023-04-04T02:26:32,179       np.array([10011.1, 101.0, 688.25, 6.25], TSDataType.DOUBLE.np_dtype()),
2023-04-04T02:26:32,179       np.array(["test01", "test02", "test03", "test04"], TSDataType.TEXT.np_dtype()),
2023-04-04T02:26:32,180   ]
2023-04-04T02:26:32,180   np_timestamps_ = np.array([1, 2, 3, 4], TSDataType.INT64.np_dtype())
2023-04-04T02:26:32,180   np_tablet_ = NumpyTablet(
2023-04-04T02:26:32,181     device_id, measurements_, data_types_, np_values_, np_timestamps_
2023-04-04T02:26:32,181   )
2023-04-04T02:26:32,181   session.insert_tablet(np_tablet_)

2023-04-04T02:26:32,182   # insert one numpy tablet with none into the database.
2023-04-04T02:26:32,182   np_values_ = [
2023-04-04T02:26:32,182       np.array([False, True, False, True], TSDataType.BOOLEAN.np_dtype()),
2023-04-04T02:26:32,183       np.array([10, 100, 100, 0], TSDataType.INT32.np_dtype()),
2023-04-04T02:26:32,183       np.array([11, 11111, 1, 0], TSDataType.INT64.np_dtype()),
2023-04-04T02:26:32,183       np.array([1.1, 1.25, 188.1, 0], TSDataType.FLOAT.np_dtype()),
2023-04-04T02:26:32,184       np.array([10011.1, 101.0, 688.25, 6.25], TSDataType.DOUBLE.np_dtype()),
2023-04-04T02:26:32,184       np.array(["test01", "test02", "test03", "test04"], TSDataType.TEXT.np_dtype()),
2023-04-04T02:26:32,184   ]
2023-04-04T02:26:32,184   np_timestamps_ = np.array([98, 99, 100, 101], TSDataType.INT64.np_dtype())
2023-04-04T02:26:32,185   np_bitmaps_ = []
2023-04-04T02:26:32,185   for i in range(len(measurements_)):
2023-04-04T02:26:32,185       np_bitmaps_.append(BitMap(len(np_timestamps_)))
2023-04-04T02:26:32,186   np_bitmaps_[0].mark(0)
2023-04-04T02:26:32,186   np_bitmaps_[1].mark(1)
2023-04-04T02:26:32,186   np_bitmaps_[2].mark(2)
2023-04-04T02:26:32,186   np_bitmaps_[4].mark(3)
2023-04-04T02:26:32,187   np_bitmaps_[5].mark(3)
2023-04-04T02:26:32,187   np_tablet_with_none = NumpyTablet(
2023-04-04T02:26:32,187       device_id, measurements_, data_types_, np_values_, np_timestamps_, np_bitmaps_
2023-04-04T02:26:32,188   )
2023-04-04T02:26:32,188   session.insert_tablet(np_tablet_with_none)
2023-04-04T02:26:32,188   ```

2023-04-04T02:26:32,189   * Insert multiple Tablets

2023-04-04T02:26:32,190   ```python
2023-04-04T02:26:32,190   session.insert_tablets(tablet_lst)
2023-04-04T02:26:32,190   ```

2023-04-04T02:26:32,191   * Insert a Record

2023-04-04T02:26:32,192   ```python
2023-04-04T02:26:32,192   session.insert_record(device_id, timestamp, measurements_, data_types_, values_)
2023-04-04T02:26:32,192   ```

2023-04-04T02:26:32,193   * Insert multiple Records

2023-04-04T02:26:32,193   ```python
2023-04-04T02:26:32,194   session.insert_records(
2023-04-04T02:26:32,194       device_ids_, time_list_, measurements_list_, data_type_list_, values_list_
2023-04-04T02:26:32,194   )
2023-04-04T02:26:32,195   ```

2023-04-04T02:26:32,195   * Insert multiple Records that belong to the same device.
2023-04-04T02:26:32,196     With type info the server has no need to do type inference, which leads a better performance


2023-04-04T02:26:32,197   ```python
2023-04-04T02:26:32,197   session.insert_records_of_one_device(device_id, time_list, measurements_list, data_types_list, values_list)
2023-04-04T02:26:32,197   ```

2023-04-04T02:26:32,198   #### Insert with type inference

2023-04-04T02:26:32,199   When the data is of String type, we can use the following interface to perform type inference based on the value of the value itself. For example, if value is "true" , it can be automatically inferred to be a boolean type. If value is "3.2" , it can be automatically inferred as a flout type. Without type information, server has to do type inference, which may cost some time.

2023-04-04T02:26:32,199   * Insert a Record, which contains multiple measurement value of a device at a timestamp

2023-04-04T02:26:32,200   ```python
2023-04-04T02:26:32,200   session.insert_str_record(device_id, timestamp, measurements, string_values)
2023-04-04T02:26:32,200   ```

2023-04-04T02:26:32,201   #### Insert of Aligned Timeseries

2023-04-04T02:26:32,202   The Insert of aligned timeseries uses interfaces like insert_aligned_XXX, and others are similar to the above interfaces:

2023-04-04T02:26:32,202   * insert_aligned_record
2023-04-04T02:26:32,202   * insert_aligned_records
2023-04-04T02:26:32,203   * insert_aligned_records_of_one_device
2023-04-04T02:26:32,203   * insert_aligned_tablet
2023-04-04T02:26:32,203   * insert_aligned_tablets


2023-04-04T02:26:32,204   ### IoTDB-SQL Interface

2023-04-04T02:26:32,205   * Execute query statement

2023-04-04T02:26:32,206   ```python
2023-04-04T02:26:32,206   session.execute_query_statement(sql)
2023-04-04T02:26:32,206   ```

2023-04-04T02:26:32,207   * Execute non query statement

2023-04-04T02:26:32,207   ```python
2023-04-04T02:26:32,208   session.execute_non_query_statement(sql)
2023-04-04T02:26:32,208   ```

2023-04-04T02:26:32,209   * Execute statement

2023-04-04T02:26:32,209   ```python
2023-04-04T02:26:32,210   session.execute_statement(sql)
2023-04-04T02:26:32,210   ```

2023-04-04T02:26:32,211   ### Schema Template
2023-04-04T02:26:32,211   #### Create Schema Template
2023-04-04T02:26:32,211   The step for creating a metadata template is as follows
2023-04-04T02:26:32,212   1. Create the template class
2023-04-04T02:26:32,212   2. Adding child Node，InternalNode and MeasurementNode can be chose
2023-04-04T02:26:32,213   3. Execute create schema template function

2023-04-04T02:26:32,213   ```python
2023-04-04T02:26:32,214   template = Template(name=template_name, share_time=True)

2023-04-04T02:26:32,215   i_node_gps = InternalNode(name="GPS", share_time=False)
2023-04-04T02:26:32,215   i_node_v = InternalNode(name="vehicle", share_time=True)
2023-04-04T02:26:32,215   m_node_x = MeasurementNode("x", TSDataType.FLOAT, TSEncoding.RLE, Compressor.SNAPPY)

2023-04-04T02:26:32,216   i_node_gps.add_child(m_node_x)
2023-04-04T02:26:32,216   i_node_v.add_child(m_node_x)

2023-04-04T02:26:32,217   template.add_template(i_node_gps)
2023-04-04T02:26:32,217   template.add_template(i_node_v)
2023-04-04T02:26:32,218   template.add_template(m_node_x)

2023-04-04T02:26:32,218   session.create_schema_template(template)
2023-04-04T02:26:32,219   ```
2023-04-04T02:26:32,219   #### Modify Schema Template nodes
2023-04-04T02:26:32,219   Modify nodes in a template, the template must be already created. These are functions that add or delete some measurement nodes.
2023-04-04T02:26:32,220   * add node in template
2023-04-04T02:26:32,220   ```python
2023-04-04T02:26:32,220   session.add_measurements_in_template(template_name, measurements_path, data_types, encodings, compressors, is_aligned)
2023-04-04T02:26:32,220   ```

2023-04-04T02:26:32,221   * delete node in template
2023-04-04T02:26:32,221   ```python
2023-04-04T02:26:32,222   session.delete_node_in_template(template_name, path)
2023-04-04T02:26:32,222   ```

2023-04-04T02:26:32,222   #### Set Schema Template
2023-04-04T02:26:32,223   ```python
2023-04-04T02:26:32,223   session.set_schema_template(template_name, prefix_path)
2023-04-04T02:26:32,223   ```

2023-04-04T02:26:32,224   #### Uset Schema Template
2023-04-04T02:26:32,224   ```python
2023-04-04T02:26:32,224   session.unset_schema_template(template_name, prefix_path)
2023-04-04T02:26:32,225   ```

2023-04-04T02:26:32,225   #### Show Schema Template
2023-04-04T02:26:32,226   * Show all schema templates
2023-04-04T02:26:32,226   ```python
2023-04-04T02:26:32,226   session.show_all_templates()
2023-04-04T02:26:32,226   ```
2023-04-04T02:26:32,227   * Count all nodes in templates
2023-04-04T02:26:32,227   ```python
2023-04-04T02:26:32,227   session.count_measurements_in_template(template_name)
2023-04-04T02:26:32,228   ```

2023-04-04T02:26:32,228   * Judge whether the path is measurement or not in templates, This measurement must be in the template
2023-04-04T02:26:32,228   ```python
2023-04-04T02:26:32,229   session.count_measurements_in_template(template_name, path)
2023-04-04T02:26:32,229   ```

2023-04-04T02:26:32,230   * Judge whether the path is exist or not in templates, This path may not belong to the template
2023-04-04T02:26:32,230   ```python
2023-04-04T02:26:32,230   session.is_path_exist_in_template(template_name, path)
2023-04-04T02:26:32,231   ```

2023-04-04T02:26:32,231   * Show nodes under in schema template
2023-04-04T02:26:32,231   ```python
2023-04-04T02:26:32,232   session.show_measurements_in_template(template_name)
2023-04-04T02:26:32,232   ```

2023-04-04T02:26:32,233   * Show the path prefix where a schema template is set
2023-04-04T02:26:32,233   ```python
2023-04-04T02:26:32,233   session.show_paths_template_set_on(template_name)
2023-04-04T02:26:32,233   ```

2023-04-04T02:26:32,234   * Show the path prefix where a schema template is used (i.e. the time series has been created)
2023-04-04T02:26:32,234   ```python
2023-04-04T02:26:32,235   session.show_paths_template_using_on(template_name)
2023-04-04T02:26:32,235   ```

2023-04-04T02:26:32,236   #### Drop Schema Template
2023-04-04T02:26:32,236   Delete an existing metadata template，dropping an already set template is not supported
2023-04-04T02:26:32,236   ```python
2023-04-04T02:26:32,237   session.drop_schema_template("template_python")
2023-04-04T02:26:32,237   ```


2023-04-04T02:26:32,238   ### Pandas Support

2023-04-04T02:26:32,238   To easily transform a query result to a [Pandas Dataframe](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html)
2023-04-04T02:26:32,239   the SessionDataSet has a method `.todf()` which consumes the dataset and transforms it to a pandas dataframe.

2023-04-04T02:26:32,239   Example:

2023-04-04T02:26:32,240   ```python
2023-04-04T02:26:32,240   from iotdb.Session import Session

2023-04-04T02:26:32,241   ip = "127.0.0.1"
2023-04-04T02:26:32,241   port_ = "6667"
2023-04-04T02:26:32,241   username_ = "root"
2023-04-04T02:26:32,242   password_ = "root"
2023-04-04T02:26:32,242   session = Session(ip, port_, username_, password_)
2023-04-04T02:26:32,242   session.open(False)
2023-04-04T02:26:32,243   result = session.execute_query_statement("SELECT * FROM root.*")

2023-04-04T02:26:32,243   # Transform to Pandas Dataset
2023-04-04T02:26:32,243   df = result.todf()

2023-04-04T02:26:32,244   session.close()

2023-04-04T02:26:32,245   # Now you can work with the dataframe
2023-04-04T02:26:32,245   df = ...
2023-04-04T02:26:32,245   ```


2023-04-04T02:26:32,246   ### IoTDB Testcontainer

2023-04-04T02:26:32,247   The Test Support is based on the lib `testcontainers` (https://testcontainers-python.readthedocs.io/en/latest/index.html) which you need to install in your project if you want to use the feature.

2023-04-04T02:26:32,248   To start (and stop) an IoTDB Database in a Docker container simply do:
2023-04-04T02:26:32,248   ```python
2023-04-04T02:26:32,248   class MyTestCase(unittest.TestCase):

2023-04-04T02:26:32,249       def test_something(self):
2023-04-04T02:26:32,249           with IoTDBContainer() as c:
2023-04-04T02:26:32,249               session = Session("localhost", c.get_exposed_port(6667), "root", "root")
2023-04-04T02:26:32,250               session.open(False)
2023-04-04T02:26:32,250               result = session.execute_query_statement("SHOW TIMESERIES")
2023-04-04T02:26:32,250               print(result)
2023-04-04T02:26:32,251               session.close()
2023-04-04T02:26:32,251   ```

2023-04-04T02:26:32,252   by default it will load the image `apache/iotdb:latest`, if you want a specific version just pass it like e.g. `IoTDBContainer("apache/iotdb:0.12.0")` to get version `0.12.0` running.


2023-04-04T02:26:32,253   ### IoTDB DBAPI

2023-04-04T02:26:32,253   IoTDB DBAPI implements the Python DB API 2.0 specification (https://peps.python.org/pep-0249/), which defines a common
2023-04-04T02:26:32,253   interface for accessing databases in Python.

2023-04-04T02:26:32,254   #### Examples
2023-04-04T02:26:32,254   + Initialization

2023-04-04T02:26:32,255   The initialized parameters are consistent with the session part (except for the sqlalchemy_mode).
2023-04-04T02:26:32,255   ```python
2023-04-04T02:26:32,256   from iotdb.dbapi import connect

2023-04-04T02:26:32,256   ip = "127.0.0.1"
2023-04-04T02:26:32,257   port_ = "6667"
2023-04-04T02:26:32,257   username_ = "root"
2023-04-04T02:26:32,257   password_ = "root"
2023-04-04T02:26:32,258   conn = connect(ip, port_, username_, password_,fetch_size=1024,zone_id="UTC+8",sqlalchemy_mode=False)
2023-04-04T02:26:32,258   cursor = conn.cursor()
2023-04-04T02:26:32,258   ```
2023-04-04T02:26:32,259   + simple SQL statement execution
2023-04-04T02:26:32,259   ```python
2023-04-04T02:26:32,259   cursor.execute("SELECT * FROM root.*")
2023-04-04T02:26:32,259   for row in cursor.fetchall():
2023-04-04T02:26:32,260       print(row)
2023-04-04T02:26:32,260   ```

2023-04-04T02:26:32,261   + execute SQL with parameter

2023-04-04T02:26:32,261   IoTDB DBAPI supports pyformat style parameters
2023-04-04T02:26:32,262   ```python
2023-04-04T02:26:32,262   cursor.execute("SELECT * FROM root.* WHERE time < %(time)s",{"time":"2017-11-01T00:08:00.000"})
2023-04-04T02:26:32,262   for row in cursor.fetchall():
2023-04-04T02:26:32,263       print(row)
2023-04-04T02:26:32,263   ```

2023-04-04T02:26:32,264   + execute SQL with parameter sequences
2023-04-04T02:26:32,264   ```python
2023-04-04T02:26:32,264   seq_of_parameters = [
2023-04-04T02:26:32,264       {"timestamp": 1, "temperature": 1},
2023-04-04T02:26:32,265       {"timestamp": 2, "temperature": 2},
2023-04-04T02:26:32,265       {"timestamp": 3, "temperature": 3},
2023-04-04T02:26:32,265       {"timestamp": 4, "temperature": 4},
2023-04-04T02:26:32,266       {"timestamp": 5, "temperature": 5},
2023-04-04T02:26:32,266   ]
2023-04-04T02:26:32,266   sql = "insert into root.cursor(timestamp,temperature) values(%(timestamp)s,%(temperature)s)"
2023-04-04T02:26:32,267   cursor.executemany(sql,seq_of_parameters)
2023-04-04T02:26:32,267   ```

2023-04-04T02:26:32,268   + close the connection and cursor
2023-04-04T02:26:32,268   ```python
2023-04-04T02:26:32,268   cursor.close()
2023-04-04T02:26:32,269   conn.close()
2023-04-04T02:26:32,269   ```

2023-04-04T02:26:32,270   ### IoTDB SQLAlchemy Dialect (Experimental)
2023-04-04T02:26:32,270   The SQLAlchemy dialect of IoTDB is written to adapt to Apache Superset.
2023-04-04T02:26:32,270   This part is still being improved.
2023-04-04T02:26:32,271   Please do not use it in the production environment!
2023-04-04T02:26:32,271   #### Mapping of the metadata
2023-04-04T02:26:32,271   The data model used by SQLAlchemy is a relational data model, which describes the relationships between different entities through tables.
2023-04-04T02:26:32,271   While the data model of IoTDB is a hierarchical data model, which organizes the data through a tree structure.
2023-04-04T02:26:32,272   In order to adapt IoTDB to the dialect of SQLAlchemy, the original data model in IoTDB needs to be reorganized.
2023-04-04T02:26:32,272   Converting the data model of IoTDB into the data model of SQLAlchemy.

2023-04-04T02:26:32,273   The metadata in the IoTDB are：

2023-04-04T02:26:32,273   1. Database
2023-04-04T02:26:32,274   2. Path
2023-04-04T02:26:32,274   3. Entity
2023-04-04T02:26:32,274   4. Measurement

2023-04-04T02:26:32,275   The metadata in the SQLAlchemy are：
2023-04-04T02:26:32,275   1. Schema
2023-04-04T02:26:32,275   2. Table
2023-04-04T02:26:32,276   3. Column

2023-04-04T02:26:32,276   The mapping relationship between them is：

2023-04-04T02:26:32,277   | The metadata in the SQLAlchemy | The metadata in the IoTDB                            |
2023-04-04T02:26:32,277   | -------------------- | ---------------------------------------------- |
2023-04-04T02:26:32,278   | Schema               |      Database                                  |
2023-04-04T02:26:32,278   | Table                | Path ( from database to entity ) + Entity |
2023-04-04T02:26:32,278   | Column               | Measurement                                    |

2023-04-04T02:26:32,279   The following figure shows the relationship between the two more intuitively:

2023-04-04T02:26:32,280   ![sqlalchemy-to-iotdb](https://github.com/apache/iotdb-bin-resources/blob/main/docs/UserGuide/API/IoTDB-SQLAlchemy/sqlalchemy-to-iotdb.png?raw=true)

2023-04-04T02:26:32,280   #### Data type mapping
2023-04-04T02:26:32,281   | data type in IoTDB | data type in SQLAlchemy |
2023-04-04T02:26:32,281   |--------------------|-------------------------|
2023-04-04T02:26:32,281   | BOOLEAN            | Boolean                 |
2023-04-04T02:26:32,282   | INT32              | Integer                 |
2023-04-04T02:26:32,282   | INT64              | BigInteger              |
2023-04-04T02:26:32,282   | FLOAT              | Float                   |
2023-04-04T02:26:32,283   | DOUBLE             | Float                   |
2023-04-04T02:26:32,283   | TEXT               | Text                    |
2023-04-04T02:26:32,283   | LONG               | BigInteger              |
2023-04-04T02:26:32,284   #### Example

2023-04-04T02:26:32,284   + execute statement

2023-04-04T02:26:32,285   ```python
2023-04-04T02:26:32,285   from sqlalchemy import create_engine

2023-04-04T02:26:32,286   engine = create_engine("iotdb://root:root@127.0.0.1:6667")
2023-04-04T02:26:32,286   connect = engine.connect()
2023-04-04T02:26:32,286   result = connect.execute("SELECT ** FROM root")
2023-04-04T02:26:32,287   for row in result.fetchall():
2023-04-04T02:26:32,287       print(row)
2023-04-04T02:26:32,287   ```

2023-04-04T02:26:32,288   + ORM (now only simple queries are supported)

2023-04-04T02:26:32,289   ```python
2023-04-04T02:26:32,289   from sqlalchemy import create_engine, Column, Float, BigInteger, MetaData
2023-04-04T02:26:32,289   from sqlalchemy.ext.declarative import declarative_base
2023-04-04T02:26:32,290   from sqlalchemy.orm import sessionmaker

2023-04-04T02:26:32,290   metadata = MetaData(
2023-04-04T02:26:32,291       schema='root.factory'
2023-04-04T02:26:32,291   )
2023-04-04T02:26:32,291   Base = declarative_base(metadata=metadata)


2023-04-04T02:26:32,292   class Device(Base):
2023-04-04T02:26:32,292       __tablename__ = "room2.device1"
2023-04-04T02:26:32,293       Time = Column(BigInteger, primary_key=True)
2023-04-04T02:26:32,293       temperature = Column(Float)
2023-04-04T02:26:32,293       status = Column(Float)


2023-04-04T02:26:32,294   engine = create_engine("iotdb://root:root@127.0.0.1:6667")

2023-04-04T02:26:32,295   DbSession = sessionmaker(bind=engine)
2023-04-04T02:26:32,295   session = DbSession()

2023-04-04T02:26:32,296   res = session.query(Device.status).filter(Device.temperature > 1)

2023-04-04T02:26:32,296   for row in res:
2023-04-04T02:26:32,297       print(row)
2023-04-04T02:26:32,297   ```


2023-04-04T02:26:32,298   ## Developers

2023-04-04T02:26:32,299   ### Introduction

2023-04-04T02:26:32,299   This is an example of how to connect to IoTDB with python, using the thrift rpc interfaces. Things are almost the same on Windows or Linux, but pay attention to the difference like path separator.



2023-04-04T02:26:32,301   ### Prerequisites

2023-04-04T02:26:32,301   Python3.7 or later is preferred.

2023-04-04T02:26:32,302   You have to install Thrift (0.11.0 or later) to compile our thrift file into python code. Below is the official tutorial of installation, eventually, you should have a thrift executable.

2023-04-04T02:26:32,303   ```
2023-04-04T02:26:32,303   http://thrift.apache.org/docs/install/
2023-04-04T02:26:32,303   ```

2023-04-04T02:26:32,304   Before starting you need to install `requirements_dev.txt` in your python environment, e.g. by calling
2023-04-04T02:26:32,304   ```shell
2023-04-04T02:26:32,304   pip install -r requirements_dev.txt
2023-04-04T02:26:32,305   ```



2023-04-04T02:26:32,306   ### Compile the thrift library and Debug

2023-04-04T02:26:32,306   In the root of IoTDB's source code folder,  run `mvn clean generate-sources -pl client-py -am`.

2023-04-04T02:26:32,307   This will automatically delete and repopulate the folder `iotdb/thrift` with the generated thrift files.
2023-04-04T02:26:32,307   This folder is ignored from git and should **never be pushed to git!**

2023-04-04T02:26:32,308   **Notice** Do not upload `iotdb/thrift` to the git repo.




2023-04-04T02:26:32,310   ### Session Client & Example

2023-04-04T02:26:32,310   We packed up the Thrift interface in `client-py/src/iotdb/Session.py` (similar with its Java counterpart), also provided an example file `client-py/src/SessionExample.py` of how to use the session module. please read it carefully.


2023-04-04T02:26:32,311   Or, another simple example:

2023-04-04T02:26:32,312   ```python
2023-04-04T02:26:32,312   from iotdb.Session import Session

2023-04-04T02:26:32,313   ip = "127.0.0.1"
2023-04-04T02:26:32,313   port_ = "6667"
2023-04-04T02:26:32,314   username_ = "root"
2023-04-04T02:26:32,314   password_ = "root"
2023-04-04T02:26:32,314   session = Session(ip, port_, username_, password_)
2023-04-04T02:26:32,315   session.open(False)
2023-04-04T02:26:32,315   zone = session.get_time_zone()
2023-04-04T02:26:32,315   session.close()
2023-04-04T02:26:32,316   ```



2023-04-04T02:26:32,317   ### Tests

2023-04-04T02:26:32,317   Please add your custom tests in `tests` folder.

2023-04-04T02:26:32,318   To run all defined tests just type `pytest .` in the root folder.

2023-04-04T02:26:32,319   **Notice** Some tests need docker to be started on your system as a test instance is started in a docker container using [testcontainers](https://testcontainers-python.readthedocs.io/en/latest/index.html).



2023-04-04T02:26:32,320   ### Futher Tools

2023-04-04T02:26:32,320   [black](https://pypi.org/project/black/) and [flake8](https://pypi.org/project/flake8/) are installed for autoformatting and linting.
2023-04-04T02:26:32,321   Both can be run by `black .` or `flake8 .` respectively.



2023-04-04T02:26:32,322   ## Releasing

2023-04-04T02:26:32,323   To do a release just ensure that you have the right set of generated thrift files.
2023-04-04T02:26:32,323   Then run linting and auto-formatting.
2023-04-04T02:26:32,323   Then, ensure that all tests work (via `pytest .`).
2023-04-04T02:26:32,324   Then you are good to go to do a release!



2023-04-04T02:26:32,325   ### Preparing your environment

2023-04-04T02:26:32,326   First, install all necessary dev dependencies via `pip install -r requirements_dev.txt`.



2023-04-04T02:26:32,327   ### Doing the Release

2023-04-04T02:26:32,327   There is a convenient script `release.sh` to do all steps for a release.
2023-04-04T02:26:32,328   Namely, these are

2023-04-04T02:26:32,328   * Remove all transient directories from last release (if exists)
2023-04-04T02:26:32,329   * (Re-)generate all generated sources via mvn
2023-04-04T02:26:32,329   * Run Linting (flake8)
2023-04-04T02:26:32,329   * Run Tests via pytest
2023-04-04T02:26:32,330   * Build
2023-04-04T02:26:32,330   * Release to pypi



2023-04-04T02:26:32,331   running dist_info
2023-04-04T02:26:32,332   creating /tmp/pip-modern-metadata-zsp_dymq/apache_iotdb.egg-info
2023-04-04T02:26:32,332   writing /tmp/pip-modern-metadata-zsp_dymq/apache_iotdb.egg-info/PKG-INFO
2023-04-04T02:26:32,332   writing dependency_links to /tmp/pip-modern-metadata-zsp_dymq/apache_iotdb.egg-info/dependency_links.txt
2023-04-04T02:26:32,333   writing entry points to /tmp/pip-modern-metadata-zsp_dymq/apache_iotdb.egg-info/entry_points.txt
2023-04-04T02:26:32,333   writing requirements to /tmp/pip-modern-metadata-zsp_dymq/apache_iotdb.egg-info/requires.txt
2023-04-04T02:26:32,335   writing top-level names to /tmp/pip-modern-metadata-zsp_dymq/apache_iotdb.egg-info/top_level.txt
2023-04-04T02:26:32,338   writing manifest file '/tmp/pip-modern-metadata-zsp_dymq/apache_iotdb.egg-info/SOURCES.txt'
2023-04-04T02:26:32,403   reading manifest file '/tmp/pip-modern-metadata-zsp_dymq/apache_iotdb.egg-info/SOURCES.txt'
2023-04-04T02:26:32,408   adding license file 'LICENSE'
2023-04-04T02:26:32,418   writing manifest file '/tmp/pip-modern-metadata-zsp_dymq/apache_iotdb.egg-info/SOURCES.txt'
2023-04-04T02:26:32,420   creating '/tmp/pip-modern-metadata-zsp_dymq/apache_iotdb-1.1.0.dist-info'
2023-04-04T02:26:32,626   /tmp/pip-build-env-5ggwxfha/overlay/lib/python3.7/site-packages/setuptools/_distutils/dist.py:265: UserWarning: Unknown distribution option: 'website'
2023-04-04T02:26:32,626     warnings.warn(msg)
2023-04-04T02:26:32,751   Preparing metadata (pyproject.toml): finished with status 'done'
2023-04-04T02:26:32,771   Source in /tmp/pip-wheel-k5owm84o/apache-iotdb_dab6e5f0016a471398506ca1f859d472 has version 1.1.0, which satisfies requirement apache-iotdb==1.1.0 from https://files.pythonhosted.org/packages/15/99/bf0d6eae0c005a4dcc88068be36ea3e5b4dcb26e50b6698b4bd814d052e9/apache-iotdb-1.1.0.tar.gz
2023-04-04T02:26:32,773   Removed apache-iotdb==1.1.0 from https://files.pythonhosted.org/packages/15/99/bf0d6eae0c005a4dcc88068be36ea3e5b4dcb26e50b6698b4bd814d052e9/apache-iotdb-1.1.0.tar.gz from build tracker '/tmp/pip-build-tracker-bjwlcw98'
2023-04-04T02:26:32,792 Created temporary directory: /tmp/pip-unpack-2pdjqwhi
2023-04-04T02:26:32,793 Building wheels for collected packages: apache-iotdb
2023-04-04T02:26:32,803   Created temporary directory: /tmp/pip-wheel-8vdqb6w0
2023-04-04T02:26:32,803   Destination directory: /tmp/pip-wheel-8vdqb6w0
2023-04-04T02:26:32,808   Building wheel for apache-iotdb (pyproject.toml): started
2023-04-04T02:26:32,810   Running command Building wheel for apache-iotdb (pyproject.toml)
2023-04-04T02:26:33,868   <!--

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2023-04-04T02:26:33,870       or more contributor license agreements.  See the NOTICE file
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2023-04-04T02:26:33,871       regarding copyright ownership.  The ASF licenses this file
2023-04-04T02:26:33,871       to you under the Apache License, Version 2.0 (the
2023-04-04T02:26:33,871       "License"); you may not use this file except in compliance
2023-04-04T02:26:33,872       with the License.  You may obtain a copy of the License at

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2023-04-04T02:26:33,873       Unless required by applicable law or agreed to in writing,
2023-04-04T02:26:33,873       software distributed under the License is distributed on an
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2023-04-04T02:26:33,876   # Apache IoTDB

2023-04-04T02:26:33,877   [![Python Client](https://github.com/apache/iotdb/actions/workflows/client-python.yml/badge.svg?branch=master)](https://github.com/apache/iotdb/actions/workflows/client-python.yml)
2023-04-04T02:26:33,877   [![GitHub release](https://img.shields.io/github/release/apache/iotdb.svg)](https://github.com/apache/iotdb/releases)
2023-04-04T02:26:33,877   [![License](https://img.shields.io/badge/license-Apache%202-4EB1BA.svg)](https://www.apache.org/licenses/LICENSE-2.0.html)
2023-04-04T02:26:33,878   ![](https://github-size-badge.herokuapp.com/apache/iotdb.svg)
2023-04-04T02:26:33,878   ![](https://img.shields.io/github/downloads/apache/iotdb/total.svg)
2023-04-04T02:26:33,878   ![](https://img.shields.io/badge/platform-win%20%7C%20macos%20%7C%20linux-yellow.svg)
2023-04-04T02:26:33,879   [![IoTDB Website](https://img.shields.io/website-up-down-green-red/https/shields.io.svg?label=iotdb-website)](https://iotdb.apache.org/)


2023-04-04T02:26:33,880   Apache IoTDB (Database for Internet of Things) is an IoT native database with high performance for
2023-04-04T02:26:33,880   data management and analysis, deployable on the edge and the cloud. Due to its light-weight
2023-04-04T02:26:33,880   architecture, high performance and rich feature set together with its deep integration with
2023-04-04T02:26:33,881   Apache Hadoop, Spark and Flink, Apache IoTDB can meet the requirements of massive data storage,
2023-04-04T02:26:33,881   high-speed data ingestion and complex data analysis in the IoT industrial fields.

2023-04-04T02:26:33,882   ## Python Native API

2023-04-04T02:26:33,882   ### Requirements

2023-04-04T02:26:33,883   You have to install thrift (>=0.13) before using the package.



2023-04-04T02:26:33,884   ### How to use (Example)

2023-04-04T02:26:33,885   First, download the latest package: `pip3 install apache-iotdb`

2023-04-04T02:26:33,885   *Notice: If you are installing Python API v0.13.0, DO NOT install by `pip install apache-iotdb==0.13.0`, use `pip install apache-iotdb==0.13.0.post1` instead!*

2023-04-04T02:26:33,886   You can get an example of using the package to read and write data at here: [Example](https://github.com/apache/iotdb/blob/master/client-py/SessionExample.py)

2023-04-04T02:26:33,887   An example of aligned timeseries: [Aligned Timeseries Session Example](https://github.com/apache/iotdb/blob/master/client-py/SessionAlignedTimeseriesExample.py)

2023-04-04T02:26:33,887   (you need to add `import iotdb` in the head of the file)

2023-04-04T02:26:33,888   Or:

2023-04-04T02:26:33,889   ```python
2023-04-04T02:26:33,889   from iotdb.Session import Session

2023-04-04T02:26:33,890   ip = "127.0.0.1"
2023-04-04T02:26:33,890   port_ = "6667"
2023-04-04T02:26:33,890   username_ = "root"
2023-04-04T02:26:33,891   password_ = "root"
2023-04-04T02:26:33,891   session = Session(ip, port_, username_, password_)
2023-04-04T02:26:33,891   session.open(False)
2023-04-04T02:26:33,892   zone = session.get_time_zone()
2023-04-04T02:26:33,892   session.close()
2023-04-04T02:26:33,892   ```

2023-04-04T02:26:33,893   ### Initialization

2023-04-04T02:26:33,894   * Initialize a Session

2023-04-04T02:26:33,894   ```python
2023-04-04T02:26:33,895   session = Session(ip, port_, username_, password_, fetch_size=1024, zone_id="UTC+8")
2023-04-04T02:26:33,895   ```

2023-04-04T02:26:33,896   * Open a session, with a parameter to specify whether to enable RPC compression

2023-04-04T02:26:33,896   ```python
2023-04-04T02:26:33,896   session.open(enable_rpc_compression=False)
2023-04-04T02:26:33,897   ```

2023-04-04T02:26:33,897   Notice: this RPC compression status of client must comply with that of IoTDB server

2023-04-04T02:26:33,898   * Close a Session

2023-04-04T02:26:33,899   ```python
2023-04-04T02:26:33,899   session.close()
2023-04-04T02:26:33,899   ```

2023-04-04T02:26:33,900   ### Data Definition Interface (DDL Interface)

2023-04-04T02:26:33,901   #### DATABASE Management

2023-04-04T02:26:33,901   * CREATE DATABASE

2023-04-04T02:26:33,902   ```python
2023-04-04T02:26:33,902   session.set_storage_group(group_name)
2023-04-04T02:26:33,902   ```

2023-04-04T02:26:33,903   * Delete one or several databases

2023-04-04T02:26:33,904   ```python
2023-04-04T02:26:33,904   session.delete_storage_group(group_name)
2023-04-04T02:26:33,904   session.delete_storage_groups(group_name_lst)
2023-04-04T02:26:33,905   ```
2023-04-04T02:26:33,905   #### Timeseries Management

2023-04-04T02:26:33,906   * Create one or multiple timeseries

2023-04-04T02:26:33,906   ```python
2023-04-04T02:26:33,907   session.create_time_series(ts_path, data_type, encoding, compressor,
2023-04-04T02:26:33,907       props=None, tags=None, attributes=None, alias=None)

2023-04-04T02:26:33,908   session.create_multi_time_series(
2023-04-04T02:26:33,908       ts_path_lst, data_type_lst, encoding_lst, compressor_lst,
2023-04-04T02:26:33,908       props_lst=None, tags_lst=None, attributes_lst=None, alias_lst=None
2023-04-04T02:26:33,909   )
2023-04-04T02:26:33,909   ```

2023-04-04T02:26:33,909   * Create aligned timeseries

2023-04-04T02:26:33,910   ```python
2023-04-04T02:26:33,910   session.create_aligned_time_series(
2023-04-04T02:26:33,911       device_id, measurements_lst, data_type_lst, encoding_lst, compressor_lst
2023-04-04T02:26:33,911   )
2023-04-04T02:26:33,911   ```

2023-04-04T02:26:33,912   Attention: Alias of measurements are **not supported** currently.

2023-04-04T02:26:33,912   * Delete one or several timeseries

2023-04-04T02:26:33,913   ```python
2023-04-04T02:26:33,913   session.delete_time_series(paths_list)
2023-04-04T02:26:33,914   ```

2023-04-04T02:26:33,914   * Check whether the specific timeseries exists

2023-04-04T02:26:33,915   ```python
2023-04-04T02:26:33,915   session.check_time_series_exists(path)
2023-04-04T02:26:33,916   ```

2023-04-04T02:26:33,916   ### Data Manipulation Interface (DML Interface)

2023-04-04T02:26:33,917   #### Insert

2023-04-04T02:26:33,918   It is recommended to use insertTablet to help improve write efficiency.

2023-04-04T02:26:33,918   * Insert a Tablet，which is multiple rows of a device, each row has the same measurements
2023-04-04T02:26:33,919       * **Better Write Performance**
2023-04-04T02:26:33,919       * **Support null values**: fill the null value with any value, and then mark the null value via BitMap (from v0.13)


2023-04-04T02:26:33,920   We have two implementations of Tablet in Python API.

2023-04-04T02:26:33,920   * Normal Tablet

2023-04-04T02:26:33,921   ```python
2023-04-04T02:26:33,921   values_ = [
2023-04-04T02:26:33,922       [False, 10, 11, 1.1, 10011.1, "test01"],
2023-04-04T02:26:33,922       [True, 100, 11111, 1.25, 101.0, "test02"],
2023-04-04T02:26:33,922       [False, 100, 1, 188.1, 688.25, "test03"],
2023-04-04T02:26:33,922       [True, 0, 0, 0, 6.25, "test04"],
2023-04-04T02:26:33,923   ]
2023-04-04T02:26:33,923   timestamps_ = [1, 2, 3, 4]
2023-04-04T02:26:33,923   tablet_ = Tablet(
2023-04-04T02:26:33,924       device_id, measurements_, data_types_, values_, timestamps_
2023-04-04T02:26:33,924   )
2023-04-04T02:26:33,924   session.insert_tablet(tablet_)

2023-04-04T02:26:33,925   values_ = [
2023-04-04T02:26:33,925       [None, 10, 11, 1.1, 10011.1, "test01"],
2023-04-04T02:26:33,926       [True, None, 11111, 1.25, 101.0, "test02"],
2023-04-04T02:26:33,926       [False, 100, None, 188.1, 688.25, "test03"],
2023-04-04T02:26:33,926       [True, 0, 0, 0, None, None],
2023-04-04T02:26:33,926   ]
2023-04-04T02:26:33,927   timestamps_ = [16, 17, 18, 19]
2023-04-04T02:26:33,927   tablet_ = Tablet(
2023-04-04T02:26:33,927       device_id, measurements_, data_types_, values_, timestamps_
2023-04-04T02:26:33,928   )
2023-04-04T02:26:33,928   session.insert_tablet(tablet_)
2023-04-04T02:26:33,928   ```
2023-04-04T02:26:33,929   * Numpy Tablet

2023-04-04T02:26:33,929   Comparing with Tablet, Numpy Tablet is using [numpy.ndarray](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html) to record data.
2023-04-04T02:26:33,930   With less memory footprint and time cost of serialization, the insert performance will be better.

2023-04-04T02:26:33,930   **Notice**
2023-04-04T02:26:33,931   1. time and value columns in Tablet are ndarray.
2023-04-04T02:26:33,931   2. recommended to use the specific dtypes to each ndarray, see the example below
2023-04-04T02:26:33,931   (if not, the default dtypes are also ok).

2023-04-04T02:26:33,932   ```python
2023-04-04T02:26:33,932   import numpy as np
2023-04-04T02:26:33,932   data_types_ = [
2023-04-04T02:26:33,933       TSDataType.BOOLEAN,
2023-04-04T02:26:33,933       TSDataType.INT32,
2023-04-04T02:26:33,933       TSDataType.INT64,
2023-04-04T02:26:33,933       TSDataType.FLOAT,
2023-04-04T02:26:33,934       TSDataType.DOUBLE,
2023-04-04T02:26:33,934       TSDataType.TEXT,
2023-04-04T02:26:33,934   ]
2023-04-04T02:26:33,935   np_values_ = [
2023-04-04T02:26:33,935       np.array([False, True, False, True], TSDataType.BOOLEAN.np_dtype()),
2023-04-04T02:26:33,935       np.array([10, 100, 100, 0], TSDataType.INT32.np_dtype()),
2023-04-04T02:26:33,936       np.array([11, 11111, 1, 0], TSDataType.INT64.np_dtype()),
2023-04-04T02:26:33,936       np.array([1.1, 1.25, 188.1, 0], TSDataType.FLOAT.np_dtype()),
2023-04-04T02:26:33,936       np.array([10011.1, 101.0, 688.25, 6.25], TSDataType.DOUBLE.np_dtype()),
2023-04-04T02:26:33,936       np.array(["test01", "test02", "test03", "test04"], TSDataType.TEXT.np_dtype()),
2023-04-04T02:26:33,937   ]
2023-04-04T02:26:33,937   np_timestamps_ = np.array([1, 2, 3, 4], TSDataType.INT64.np_dtype())
2023-04-04T02:26:33,937   np_tablet_ = NumpyTablet(
2023-04-04T02:26:33,938     device_id, measurements_, data_types_, np_values_, np_timestamps_
2023-04-04T02:26:33,938   )
2023-04-04T02:26:33,938   session.insert_tablet(np_tablet_)

2023-04-04T02:26:33,939   # insert one numpy tablet with none into the database.
2023-04-04T02:26:33,939   np_values_ = [
2023-04-04T02:26:33,940       np.array([False, True, False, True], TSDataType.BOOLEAN.np_dtype()),
2023-04-04T02:26:33,940       np.array([10, 100, 100, 0], TSDataType.INT32.np_dtype()),
2023-04-04T02:26:33,940       np.array([11, 11111, 1, 0], TSDataType.INT64.np_dtype()),
2023-04-04T02:26:33,941       np.array([1.1, 1.25, 188.1, 0], TSDataType.FLOAT.np_dtype()),
2023-04-04T02:26:33,941       np.array([10011.1, 101.0, 688.25, 6.25], TSDataType.DOUBLE.np_dtype()),
2023-04-04T02:26:33,941       np.array(["test01", "test02", "test03", "test04"], TSDataType.TEXT.np_dtype()),
2023-04-04T02:26:33,941   ]
2023-04-04T02:26:33,942   np_timestamps_ = np.array([98, 99, 100, 101], TSDataType.INT64.np_dtype())
2023-04-04T02:26:33,942   np_bitmaps_ = []
2023-04-04T02:26:33,942   for i in range(len(measurements_)):
2023-04-04T02:26:33,943       np_bitmaps_.append(BitMap(len(np_timestamps_)))
2023-04-04T02:26:33,943   np_bitmaps_[0].mark(0)
2023-04-04T02:26:33,943   np_bitmaps_[1].mark(1)
2023-04-04T02:26:33,943   np_bitmaps_[2].mark(2)
2023-04-04T02:26:33,944   np_bitmaps_[4].mark(3)
2023-04-04T02:26:33,944   np_bitmaps_[5].mark(3)
2023-04-04T02:26:33,944   np_tablet_with_none = NumpyTablet(
2023-04-04T02:26:33,945       device_id, measurements_, data_types_, np_values_, np_timestamps_, np_bitmaps_
2023-04-04T02:26:33,945   )
2023-04-04T02:26:33,945   session.insert_tablet(np_tablet_with_none)
2023-04-04T02:26:33,946   ```

2023-04-04T02:26:33,946   * Insert multiple Tablets

2023-04-04T02:26:33,947   ```python
2023-04-04T02:26:33,947   session.insert_tablets(tablet_lst)
2023-04-04T02:26:33,947   ```

2023-04-04T02:26:33,948   * Insert a Record

2023-04-04T02:26:33,949   ```python
2023-04-04T02:26:33,949   session.insert_record(device_id, timestamp, measurements_, data_types_, values_)
2023-04-04T02:26:33,949   ```

2023-04-04T02:26:33,950   * Insert multiple Records

2023-04-04T02:26:33,951   ```python
2023-04-04T02:26:33,951   session.insert_records(
2023-04-04T02:26:33,952       device_ids_, time_list_, measurements_list_, data_type_list_, values_list_
2023-04-04T02:26:33,952   )
2023-04-04T02:26:33,952   ```

2023-04-04T02:26:33,953   * Insert multiple Records that belong to the same device.
2023-04-04T02:26:33,953     With type info the server has no need to do type inference, which leads a better performance


2023-04-04T02:26:33,954   ```python
2023-04-04T02:26:33,954   session.insert_records_of_one_device(device_id, time_list, measurements_list, data_types_list, values_list)
2023-04-04T02:26:33,955   ```

2023-04-04T02:26:33,955   #### Insert with type inference

2023-04-04T02:26:33,956   When the data is of String type, we can use the following interface to perform type inference based on the value of the value itself. For example, if value is "true" , it can be automatically inferred to be a boolean type. If value is "3.2" , it can be automatically inferred as a flout type. Without type information, server has to do type inference, which may cost some time.

2023-04-04T02:26:33,956   * Insert a Record, which contains multiple measurement value of a device at a timestamp

2023-04-04T02:26:33,957   ```python
2023-04-04T02:26:33,957   session.insert_str_record(device_id, timestamp, measurements, string_values)
2023-04-04T02:26:33,958   ```

2023-04-04T02:26:33,958   #### Insert of Aligned Timeseries

2023-04-04T02:26:33,959   The Insert of aligned timeseries uses interfaces like insert_aligned_XXX, and others are similar to the above interfaces:

2023-04-04T02:26:33,959   * insert_aligned_record
2023-04-04T02:26:33,960   * insert_aligned_records
2023-04-04T02:26:33,960   * insert_aligned_records_of_one_device
2023-04-04T02:26:33,960   * insert_aligned_tablet
2023-04-04T02:26:33,961   * insert_aligned_tablets


2023-04-04T02:26:33,962   ### IoTDB-SQL Interface

2023-04-04T02:26:33,962   * Execute query statement

2023-04-04T02:26:33,963   ```python
2023-04-04T02:26:33,963   session.execute_query_statement(sql)
2023-04-04T02:26:33,964   ```

2023-04-04T02:26:33,964   * Execute non query statement

2023-04-04T02:26:33,965   ```python
2023-04-04T02:26:33,965   session.execute_non_query_statement(sql)
2023-04-04T02:26:33,965   ```

2023-04-04T02:26:33,966   * Execute statement

2023-04-04T02:26:33,967   ```python
2023-04-04T02:26:33,967   session.execute_statement(sql)
2023-04-04T02:26:33,968   ```

2023-04-04T02:26:33,969   ### Schema Template
2023-04-04T02:26:33,969   #### Create Schema Template
2023-04-04T02:26:33,969   The step for creating a metadata template is as follows
2023-04-04T02:26:33,970   1. Create the template class
2023-04-04T02:26:33,970   2. Adding child Node，InternalNode and MeasurementNode can be chose
2023-04-04T02:26:33,971   3. Execute create schema template function

2023-04-04T02:26:33,971   ```python
2023-04-04T02:26:33,971   template = Template(name=template_name, share_time=True)

2023-04-04T02:26:33,972   i_node_gps = InternalNode(name="GPS", share_time=False)
2023-04-04T02:26:33,972   i_node_v = InternalNode(name="vehicle", share_time=True)
2023-04-04T02:26:33,973   m_node_x = MeasurementNode("x", TSDataType.FLOAT, TSEncoding.RLE, Compressor.SNAPPY)

2023-04-04T02:26:33,973   i_node_gps.add_child(m_node_x)
2023-04-04T02:26:33,974   i_node_v.add_child(m_node_x)

2023-04-04T02:26:33,974   template.add_template(i_node_gps)
2023-04-04T02:26:33,975   template.add_template(i_node_v)
2023-04-04T02:26:33,975   template.add_template(m_node_x)

2023-04-04T02:26:33,976   session.create_schema_template(template)
2023-04-04T02:26:33,976   ```
2023-04-04T02:26:33,976   #### Modify Schema Template nodes
2023-04-04T02:26:33,977   Modify nodes in a template, the template must be already created. These are functions that add or delete some measurement nodes.
2023-04-04T02:26:33,977   * add node in template
2023-04-04T02:26:33,977   ```python
2023-04-04T02:26:33,977   session.add_measurements_in_template(template_name, measurements_path, data_types, encodings, compressors, is_aligned)
2023-04-04T02:26:33,978   ```

2023-04-04T02:26:33,978   * delete node in template
2023-04-04T02:26:33,979   ```python
2023-04-04T02:26:33,979   session.delete_node_in_template(template_name, path)
2023-04-04T02:26:33,979   ```

2023-04-04T02:26:33,980   #### Set Schema Template
2023-04-04T02:26:33,980   ```python
2023-04-04T02:26:33,980   session.set_schema_template(template_name, prefix_path)
2023-04-04T02:26:33,981   ```

2023-04-04T02:26:33,981   #### Uset Schema Template
2023-04-04T02:26:33,982   ```python
2023-04-04T02:26:33,982   session.unset_schema_template(template_name, prefix_path)
2023-04-04T02:26:33,982   ```

2023-04-04T02:26:33,983   #### Show Schema Template
2023-04-04T02:26:33,983   * Show all schema templates
2023-04-04T02:26:33,983   ```python
2023-04-04T02:26:33,984   session.show_all_templates()
2023-04-04T02:26:33,984   ```
2023-04-04T02:26:33,984   * Count all nodes in templates
2023-04-04T02:26:33,984   ```python
2023-04-04T02:26:33,985   session.count_measurements_in_template(template_name)
2023-04-04T02:26:33,985   ```

2023-04-04T02:26:33,986   * Judge whether the path is measurement or not in templates, This measurement must be in the template
2023-04-04T02:26:33,986   ```python
2023-04-04T02:26:33,986   session.count_measurements_in_template(template_name, path)
2023-04-04T02:26:33,986   ```

2023-04-04T02:26:33,987   * Judge whether the path is exist or not in templates, This path may not belong to the template
2023-04-04T02:26:33,987   ```python
2023-04-04T02:26:33,988   session.is_path_exist_in_template(template_name, path)
2023-04-04T02:26:33,988   ```

2023-04-04T02:26:33,988   * Show nodes under in schema template
2023-04-04T02:26:33,989   ```python
2023-04-04T02:26:33,989   session.show_measurements_in_template(template_name)
2023-04-04T02:26:33,989   ```

2023-04-04T02:26:33,990   * Show the path prefix where a schema template is set
2023-04-04T02:26:33,990   ```python
2023-04-04T02:26:33,991   session.show_paths_template_set_on(template_name)
2023-04-04T02:26:33,991   ```

2023-04-04T02:26:33,991   * Show the path prefix where a schema template is used (i.e. the time series has been created)
2023-04-04T02:26:33,992   ```python
2023-04-04T02:26:33,992   session.show_paths_template_using_on(template_name)
2023-04-04T02:26:33,992   ```

2023-04-04T02:26:33,993   #### Drop Schema Template
2023-04-04T02:26:33,993   Delete an existing metadata template，dropping an already set template is not supported
2023-04-04T02:26:33,994   ```python
2023-04-04T02:26:33,994   session.drop_schema_template("template_python")
2023-04-04T02:26:33,994   ```


2023-04-04T02:26:33,995   ### Pandas Support

2023-04-04T02:26:33,996   To easily transform a query result to a [Pandas Dataframe](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html)
2023-04-04T02:26:33,996   the SessionDataSet has a method `.todf()` which consumes the dataset and transforms it to a pandas dataframe.

2023-04-04T02:26:33,997   Example:

2023-04-04T02:26:33,997   ```python
2023-04-04T02:26:33,998   from iotdb.Session import Session

2023-04-04T02:26:33,998   ip = "127.0.0.1"
2023-04-04T02:26:33,999   port_ = "6667"
2023-04-04T02:26:33,999   username_ = "root"
2023-04-04T02:26:33,999   password_ = "root"
2023-04-04T02:26:33,999   session = Session(ip, port_, username_, password_)
2023-04-04T02:26:34,000   session.open(False)
2023-04-04T02:26:34,000   result = session.execute_query_statement("SELECT * FROM root.*")

2023-04-04T02:26:34,001   # Transform to Pandas Dataset
2023-04-04T02:26:34,001   df = result.todf()

2023-04-04T02:26:34,002   session.close()

2023-04-04T02:26:34,002   # Now you can work with the dataframe
2023-04-04T02:26:34,002   df = ...
2023-04-04T02:26:34,003   ```


2023-04-04T02:26:34,004   ### IoTDB Testcontainer

2023-04-04T02:26:34,004   The Test Support is based on the lib `testcontainers` (https://testcontainers-python.readthedocs.io/en/latest/index.html) which you need to install in your project if you want to use the feature.

2023-04-04T02:26:34,005   To start (and stop) an IoTDB Database in a Docker container simply do:
2023-04-04T02:26:34,005   ```python
2023-04-04T02:26:34,006   class MyTestCase(unittest.TestCase):

2023-04-04T02:26:34,006       def test_something(self):
2023-04-04T02:26:34,007           with IoTDBContainer() as c:
2023-04-04T02:26:34,007               session = Session("localhost", c.get_exposed_port(6667), "root", "root")
2023-04-04T02:26:34,007               session.open(False)
2023-04-04T02:26:34,007               result = session.execute_query_statement("SHOW TIMESERIES")
2023-04-04T02:26:34,008               print(result)
2023-04-04T02:26:34,008               session.close()
2023-04-04T02:26:34,008   ```

2023-04-04T02:26:34,009   by default it will load the image `apache/iotdb:latest`, if you want a specific version just pass it like e.g. `IoTDBContainer("apache/iotdb:0.12.0")` to get version `0.12.0` running.


2023-04-04T02:26:34,010   ### IoTDB DBAPI

2023-04-04T02:26:34,011   IoTDB DBAPI implements the Python DB API 2.0 specification (https://peps.python.org/pep-0249/), which defines a common
2023-04-04T02:26:34,011   interface for accessing databases in Python.

2023-04-04T02:26:34,012   #### Examples
2023-04-04T02:26:34,012   + Initialization

2023-04-04T02:26:34,013   The initialized parameters are consistent with the session part (except for the sqlalchemy_mode).
2023-04-04T02:26:34,013   ```python
2023-04-04T02:26:34,013   from iotdb.dbapi import connect

2023-04-04T02:26:34,014   ip = "127.0.0.1"
2023-04-04T02:26:34,014   port_ = "6667"
2023-04-04T02:26:34,014   username_ = "root"
2023-04-04T02:26:34,015   password_ = "root"
2023-04-04T02:26:34,015   conn = connect(ip, port_, username_, password_,fetch_size=1024,zone_id="UTC+8",sqlalchemy_mode=False)
2023-04-04T02:26:34,015   cursor = conn.cursor()
2023-04-04T02:26:34,016   ```
2023-04-04T02:26:34,016   + simple SQL statement execution
2023-04-04T02:26:34,016   ```python
2023-04-04T02:26:34,017   cursor.execute("SELECT * FROM root.*")
2023-04-04T02:26:34,017   for row in cursor.fetchall():
2023-04-04T02:26:34,017       print(row)
2023-04-04T02:26:34,017   ```

2023-04-04T02:26:34,018   + execute SQL with parameter

2023-04-04T02:26:34,019   IoTDB DBAPI supports pyformat style parameters
2023-04-04T02:26:34,019   ```python
2023-04-04T02:26:34,019   cursor.execute("SELECT * FROM root.* WHERE time < %(time)s",{"time":"2017-11-01T00:08:00.000"})
2023-04-04T02:26:34,020   for row in cursor.fetchall():
2023-04-04T02:26:34,020       print(row)
2023-04-04T02:26:34,020   ```

2023-04-04T02:26:34,021   + execute SQL with parameter sequences
2023-04-04T02:26:34,021   ```python
2023-04-04T02:26:34,021   seq_of_parameters = [
2023-04-04T02:26:34,022       {"timestamp": 1, "temperature": 1},
2023-04-04T02:26:34,022       {"timestamp": 2, "temperature": 2},
2023-04-04T02:26:34,022       {"timestamp": 3, "temperature": 3},
2023-04-04T02:26:34,023       {"timestamp": 4, "temperature": 4},
2023-04-04T02:26:34,023       {"timestamp": 5, "temperature": 5},
2023-04-04T02:26:34,023   ]
2023-04-04T02:26:34,024   sql = "insert into root.cursor(timestamp,temperature) values(%(timestamp)s,%(temperature)s)"
2023-04-04T02:26:34,024   cursor.executemany(sql,seq_of_parameters)
2023-04-04T02:26:34,024   ```

2023-04-04T02:26:34,025   + close the connection and cursor
2023-04-04T02:26:34,025   ```python
2023-04-04T02:26:34,025   cursor.close()
2023-04-04T02:26:34,026   conn.close()
2023-04-04T02:26:34,026   ```

2023-04-04T02:26:34,027   ### IoTDB SQLAlchemy Dialect (Experimental)
2023-04-04T02:26:34,027   The SQLAlchemy dialect of IoTDB is written to adapt to Apache Superset.
2023-04-04T02:26:34,027   This part is still being improved.
2023-04-04T02:26:34,028   Please do not use it in the production environment!
2023-04-04T02:26:34,028   #### Mapping of the metadata
2023-04-04T02:26:34,028   The data model used by SQLAlchemy is a relational data model, which describes the relationships between different entities through tables.
2023-04-04T02:26:34,029   While the data model of IoTDB is a hierarchical data model, which organizes the data through a tree structure.
2023-04-04T02:26:34,029   In order to adapt IoTDB to the dialect of SQLAlchemy, the original data model in IoTDB needs to be reorganized.
2023-04-04T02:26:34,029   Converting the data model of IoTDB into the data model of SQLAlchemy.

2023-04-04T02:26:34,030   The metadata in the IoTDB are：

2023-04-04T02:26:34,031   1. Database
2023-04-04T02:26:34,031   2. Path
2023-04-04T02:26:34,031   3. Entity
2023-04-04T02:26:34,031   4. Measurement

2023-04-04T02:26:34,032   The metadata in the SQLAlchemy are：
2023-04-04T02:26:34,032   1. Schema
2023-04-04T02:26:34,033   2. Table
2023-04-04T02:26:34,033   3. Column

2023-04-04T02:26:34,034   The mapping relationship between them is：

2023-04-04T02:26:34,034   | The metadata in the SQLAlchemy | The metadata in the IoTDB                            |
2023-04-04T02:26:34,035   | -------------------- | ---------------------------------------------- |
2023-04-04T02:26:34,035   | Schema               |      Database                                  |
2023-04-04T02:26:34,035   | Table                | Path ( from database to entity ) + Entity |
2023-04-04T02:26:34,035   | Column               | Measurement                                    |

2023-04-04T02:26:34,036   The following figure shows the relationship between the two more intuitively:

2023-04-04T02:26:34,037   ![sqlalchemy-to-iotdb](https://github.com/apache/iotdb-bin-resources/blob/main/docs/UserGuide/API/IoTDB-SQLAlchemy/sqlalchemy-to-iotdb.png?raw=true)

2023-04-04T02:26:34,038   #### Data type mapping
2023-04-04T02:26:34,038   | data type in IoTDB | data type in SQLAlchemy |
2023-04-04T02:26:34,038   |--------------------|-------------------------|
2023-04-04T02:26:34,038   | BOOLEAN            | Boolean                 |
2023-04-04T02:26:34,039   | INT32              | Integer                 |
2023-04-04T02:26:34,039   | INT64              | BigInteger              |
2023-04-04T02:26:34,040   | FLOAT              | Float                   |
2023-04-04T02:26:34,040   | DOUBLE             | Float                   |
2023-04-04T02:26:34,040   | TEXT               | Text                    |
2023-04-04T02:26:34,041   | LONG               | BigInteger              |
2023-04-04T02:26:34,041   #### Example

2023-04-04T02:26:34,041   + execute statement

2023-04-04T02:26:34,042   ```python
2023-04-04T02:26:34,042   from sqlalchemy import create_engine

2023-04-04T02:26:34,043   engine = create_engine("iotdb://root:root@127.0.0.1:6667")
2023-04-04T02:26:34,043   connect = engine.connect()
2023-04-04T02:26:34,044   result = connect.execute("SELECT ** FROM root")
2023-04-04T02:26:34,044   for row in result.fetchall():
2023-04-04T02:26:34,044       print(row)
2023-04-04T02:26:34,044   ```

2023-04-04T02:26:34,045   + ORM (now only simple queries are supported)

2023-04-04T02:26:34,046   ```python
2023-04-04T02:26:34,046   from sqlalchemy import create_engine, Column, Float, BigInteger, MetaData
2023-04-04T02:26:34,046   from sqlalchemy.ext.declarative import declarative_base
2023-04-04T02:26:34,047   from sqlalchemy.orm import sessionmaker

2023-04-04T02:26:34,047   metadata = MetaData(
2023-04-04T02:26:34,047       schema='root.factory'
2023-04-04T02:26:34,048   )
2023-04-04T02:26:34,048   Base = declarative_base(metadata=metadata)


2023-04-04T02:26:34,049   class Device(Base):
2023-04-04T02:26:34,049       __tablename__ = "room2.device1"
2023-04-04T02:26:34,050       Time = Column(BigInteger, primary_key=True)
2023-04-04T02:26:34,050       temperature = Column(Float)
2023-04-04T02:26:34,050       status = Column(Float)


2023-04-04T02:26:34,051   engine = create_engine("iotdb://root:root@127.0.0.1:6667")

2023-04-04T02:26:34,052   DbSession = sessionmaker(bind=engine)
2023-04-04T02:26:34,052   session = DbSession()

2023-04-04T02:26:34,053   res = session.query(Device.status).filter(Device.temperature > 1)

2023-04-04T02:26:34,054   for row in res:
2023-04-04T02:26:34,054       print(row)
2023-04-04T02:26:34,054   ```


2023-04-04T02:26:34,055   ## Developers

2023-04-04T02:26:34,056   ### Introduction

2023-04-04T02:26:34,056   This is an example of how to connect to IoTDB with python, using the thrift rpc interfaces. Things are almost the same on Windows or Linux, but pay attention to the difference like path separator.



2023-04-04T02:26:34,058   ### Prerequisites

2023-04-04T02:26:34,058   Python3.7 or later is preferred.

2023-04-04T02:26:34,059   You have to install Thrift (0.11.0 or later) to compile our thrift file into python code. Below is the official tutorial of installation, eventually, you should have a thrift executable.

2023-04-04T02:26:34,060   ```
2023-04-04T02:26:34,060   http://thrift.apache.org/docs/install/
2023-04-04T02:26:34,060   ```

2023-04-04T02:26:34,061   Before starting you need to install `requirements_dev.txt` in your python environment, e.g. by calling
2023-04-04T02:26:34,061   ```shell
2023-04-04T02:26:34,061   pip install -r requirements_dev.txt
2023-04-04T02:26:34,062   ```



2023-04-04T02:26:34,063   ### Compile the thrift library and Debug

2023-04-04T02:26:34,064   In the root of IoTDB's source code folder,  run `mvn clean generate-sources -pl client-py -am`.

2023-04-04T02:26:34,064   This will automatically delete and repopulate the folder `iotdb/thrift` with the generated thrift files.
2023-04-04T02:26:34,064   This folder is ignored from git and should **never be pushed to git!**

2023-04-04T02:26:34,065   **Notice** Do not upload `iotdb/thrift` to the git repo.




2023-04-04T02:26:34,067   ### Session Client & Example

2023-04-04T02:26:34,067   We packed up the Thrift interface in `client-py/src/iotdb/Session.py` (similar with its Java counterpart), also provided an example file `client-py/src/SessionExample.py` of how to use the session module. please read it carefully.


2023-04-04T02:26:34,068   Or, another simple example:

2023-04-04T02:26:34,069   ```python
2023-04-04T02:26:34,069   from iotdb.Session import Session

2023-04-04T02:26:34,070   ip = "127.0.0.1"
2023-04-04T02:26:34,070   port_ = "6667"
2023-04-04T02:26:34,071   username_ = "root"
2023-04-04T02:26:34,071   password_ = "root"
2023-04-04T02:26:34,071   session = Session(ip, port_, username_, password_)
2023-04-04T02:26:34,071   session.open(False)
2023-04-04T02:26:34,072   zone = session.get_time_zone()
2023-04-04T02:26:34,072   session.close()
2023-04-04T02:26:34,072   ```



2023-04-04T02:26:34,074   ### Tests

2023-04-04T02:26:34,074   Please add your custom tests in `tests` folder.

2023-04-04T02:26:34,075   To run all defined tests just type `pytest .` in the root folder.

2023-04-04T02:26:34,075   **Notice** Some tests need docker to be started on your system as a test instance is started in a docker container using [testcontainers](https://testcontainers-python.readthedocs.io/en/latest/index.html).



2023-04-04T02:26:34,077   ### Futher Tools

2023-04-04T02:26:34,077   [black](https://pypi.org/project/black/) and [flake8](https://pypi.org/project/flake8/) are installed for autoformatting and linting.
2023-04-04T02:26:34,078   Both can be run by `black .` or `flake8 .` respectively.



2023-04-04T02:26:34,079   ## Releasing

2023-04-04T02:26:34,079   To do a release just ensure that you have the right set of generated thrift files.
2023-04-04T02:26:34,080   Then run linting and auto-formatting.
2023-04-04T02:26:34,080   Then, ensure that all tests work (via `pytest .`).
2023-04-04T02:26:34,080   Then you are good to go to do a release!



2023-04-04T02:26:34,082   ### Preparing your environment

2023-04-04T02:26:34,082   First, install all necessary dev dependencies via `pip install -r requirements_dev.txt`.



2023-04-04T02:26:34,083   ### Doing the Release

2023-04-04T02:26:34,084   There is a convenient script `release.sh` to do all steps for a release.
2023-04-04T02:26:34,084   Namely, these are

2023-04-04T02:26:34,085   * Remove all transient directories from last release (if exists)
2023-04-04T02:26:34,085   * (Re-)generate all generated sources via mvn
2023-04-04T02:26:34,086   * Run Linting (flake8)
2023-04-04T02:26:34,086   * Run Tests via pytest
2023-04-04T02:26:34,086   * Build
2023-04-04T02:26:34,086   * Release to pypi



2023-04-04T02:26:34,127   running bdist_wheel
2023-04-04T02:26:34,207   running build
2023-04-04T02:26:34,207   running build_py
2023-04-04T02:26:34,226   creating build
2023-04-04T02:26:34,226   creating build/lib
2023-04-04T02:26:34,228   creating build/lib/iotdb
2023-04-04T02:26:34,230   copying iotdb/IoTDBContainer.py -> build/lib/iotdb
2023-04-04T02:26:34,234   copying iotdb/Session.py -> build/lib/iotdb
2023-04-04T02:26:34,241   copying iotdb/__init__.py -> build/lib/iotdb
2023-04-04T02:26:34,247   creating build/lib/tests
2023-04-04T02:26:34,248   copying tests/test_one_device.py -> build/lib/tests
2023-04-04T02:26:34,252   copying tests/test_tablet.py -> build/lib/tests
2023-04-04T02:26:34,256   copying tests/test_template.py -> build/lib/tests
2023-04-04T02:26:34,260   copying tests/test_session.py -> build/lib/tests
2023-04-04T02:26:34,264   copying tests/test_aligned_timeseries.py -> build/lib/tests
2023-04-04T02:26:34,269   copying tests/test_todf.py -> build/lib/tests
2023-04-04T02:26:34,273   copying tests/test_dataframe.py -> build/lib/tests
2023-04-04T02:26:34,276   copying tests/tablet_performance_comparison.py -> build/lib/tests
2023-04-04T02:26:34,281   copying tests/__init__.py -> build/lib/tests
2023-04-04T02:26:34,284   copying tests/test_numpy_tablet.py -> build/lib/tests
2023-04-04T02:26:34,288   copying tests/test_delete_data.py -> build/lib/tests
2023-04-04T02:26:34,294   creating build/lib/iotdb/utils
2023-04-04T02:26:34,295   copying iotdb/utils/SessionDataSet.py -> build/lib/iotdb/utils
2023-04-04T02:26:34,300   copying iotdb/utils/Field.py -> build/lib/iotdb/utils
2023-04-04T02:26:34,303   copying iotdb/utils/RowRecord.py -> build/lib/iotdb/utils
2023-04-04T02:26:34,307   copying iotdb/utils/NumpyTablet.py -> build/lib/iotdb/utils
2023-04-04T02:26:34,311   copying iotdb/utils/IoTDBRpcDataSet.py -> build/lib/iotdb/utils
2023-04-04T02:26:34,316   copying iotdb/utils/__init__.py -> build/lib/iotdb/utils
2023-04-04T02:26:34,320   copying iotdb/utils/IoTDBConstants.py -> build/lib/iotdb/utils
2023-04-04T02:26:34,323   copying iotdb/utils/BitMap.py -> build/lib/iotdb/utils
2023-04-04T02:26:34,327   copying iotdb/utils/Tablet.py -> build/lib/iotdb/utils
2023-04-04T02:26:34,332   creating build/lib/iotdb/tsfile
2023-04-04T02:26:34,334   copying iotdb/tsfile/__init__.py -> build/lib/iotdb/tsfile
2023-04-04T02:26:34,339   creating build/lib/iotdb/thrift
2023-04-04T02:26:34,340   copying iotdb/thrift/__init__.py -> build/lib/iotdb/thrift
2023-04-04T02:26:34,345   creating build/lib/iotdb/dbapi
2023-04-04T02:26:34,347   copying iotdb/dbapi/Connection.py -> build/lib/iotdb/dbapi
2023-04-04T02:26:34,351   copying iotdb/dbapi/Exceptions.py -> build/lib/iotdb/dbapi
2023-04-04T02:26:34,354   copying iotdb/dbapi/Cursor.py -> build/lib/iotdb/dbapi
2023-04-04T02:26:34,359   copying iotdb/dbapi/__init__.py -> build/lib/iotdb/dbapi
2023-04-04T02:26:34,364   creating build/lib/iotdb/sqlalchemy
2023-04-04T02:26:34,365   copying iotdb/sqlalchemy/IoTDBSQLCompiler.py -> build/lib/iotdb/sqlalchemy
2023-04-04T02:26:34,370   copying iotdb/sqlalchemy/IoTDBDialect.py -> build/lib/iotdb/sqlalchemy
2023-04-04T02:26:34,374   copying iotdb/sqlalchemy/IoTDBTypeCompiler.py -> build/lib/iotdb/sqlalchemy
2023-04-04T02:26:34,378   copying iotdb/sqlalchemy/IoTDBIdentifierPreparer.py -> build/lib/iotdb/sqlalchemy
2023-04-04T02:26:34,382   copying iotdb/sqlalchemy/__init__.py -> build/lib/iotdb/sqlalchemy
2023-04-04T02:26:34,387   creating build/lib/iotdb/template
2023-04-04T02:26:34,388   copying iotdb/template/Template.py -> build/lib/iotdb/template
2023-04-04T02:26:34,392   copying iotdb/template/TemplateQueryType.py -> build/lib/iotdb/template
2023-04-04T02:26:34,396   copying iotdb/template/MeasurementNode.py -> build/lib/iotdb/template
2023-04-04T02:26:34,399   copying iotdb/template/InternalNode.py -> build/lib/iotdb/template
2023-04-04T02:26:34,403   copying iotdb/template/TemplateNode.py -> build/lib/iotdb/template
2023-04-04T02:26:34,406   copying iotdb/template/__init__.py -> build/lib/iotdb/template
2023-04-04T02:26:34,411   creating build/lib/iotdb/tsfile/utils
2023-04-04T02:26:34,413   copying iotdb/tsfile/utils/ReadWriteIOUtils.py -> build/lib/iotdb/tsfile/utils
2023-04-04T02:26:34,417   copying iotdb/tsfile/utils/Pair.py -> build/lib/iotdb/tsfile/utils
2023-04-04T02:26:34,420   copying iotdb/tsfile/utils/__init__.py -> build/lib/iotdb/tsfile/utils
2023-04-04T02:26:34,425   creating build/lib/iotdb/tsfile/common
2023-04-04T02:26:34,427   copying iotdb/tsfile/common/__init__.py -> build/lib/iotdb/tsfile/common
2023-04-04T02:26:34,432   creating build/lib/iotdb/tsfile/common/constant
2023-04-04T02:26:34,433   copying iotdb/tsfile/common/constant/TsFileConstant.py -> build/lib/iotdb/tsfile/common/constant
2023-04-04T02:26:34,437   copying iotdb/tsfile/common/constant/__init__.py -> build/lib/iotdb/tsfile/common/constant
2023-04-04T02:26:34,442   creating build/lib/iotdb/thrift/rpc
2023-04-04T02:26:34,444   copying iotdb/thrift/rpc/IClientRPCService.py -> build/lib/iotdb/thrift/rpc
2023-04-04T02:26:34,469   copying iotdb/thrift/rpc/constants.py -> build/lib/iotdb/thrift/rpc
2023-04-04T02:26:34,473   copying iotdb/thrift/rpc/ttypes.py -> build/lib/iotdb/thrift/rpc
2023-04-04T02:26:34,491   copying iotdb/thrift/rpc/__init__.py -> build/lib/iotdb/thrift/rpc
2023-04-04T02:26:34,496   creating build/lib/iotdb/thrift/common
2023-04-04T02:26:34,498   copying iotdb/thrift/common/constants.py -> build/lib/iotdb/thrift/common
2023-04-04T02:26:34,502   copying iotdb/thrift/common/ttypes.py -> build/lib/iotdb/thrift/common
2023-04-04T02:26:34,509   copying iotdb/thrift/common/__init__.py -> build/lib/iotdb/thrift/common
2023-04-04T02:26:34,514   creating build/lib/iotdb/thrift/datanode
2023-04-04T02:26:34,516   copying iotdb/thrift/datanode/IDataNodeRPCService.py -> build/lib/iotdb/thrift/datanode
2023-04-04T02:26:34,545   copying iotdb/thrift/datanode/constants.py -> build/lib/iotdb/thrift/datanode
2023-04-04T02:26:34,549   copying iotdb/thrift/datanode/ttypes.py -> build/lib/iotdb/thrift/datanode
2023-04-04T02:26:34,565   copying iotdb/thrift/datanode/__init__.py -> build/lib/iotdb/thrift/datanode
2023-04-04T02:26:34,568   copying iotdb/thrift/datanode/MPPDataExchangeService.py -> build/lib/iotdb/thrift/datanode
2023-04-04T02:26:34,575   creating build/lib/iotdb/dbapi/tests
2023-04-04T02:26:34,577   copying iotdb/dbapi/tests/test_cursor.py -> build/lib/iotdb/dbapi/tests
2023-04-04T02:26:34,581   copying iotdb/dbapi/tests/test_connection.py -> build/lib/iotdb/dbapi/tests
2023-04-04T02:26:34,584   copying iotdb/dbapi/tests/__init__.py -> build/lib/iotdb/dbapi/tests
2023-04-04T02:26:34,589   creating build/lib/iotdb/sqlalchemy/tests
2023-04-04T02:26:34,591   copying iotdb/sqlalchemy/tests/__init__.py -> build/lib/iotdb/sqlalchemy/tests
2023-04-04T02:26:34,594   copying iotdb/sqlalchemy/tests/test_dialect.py -> build/lib/iotdb/sqlalchemy/tests
2023-04-04T02:26:34,654   installing to build/bdist.linux-armv7l/wheel
2023-04-04T02:26:34,655   running install
2023-04-04T02:26:34,716   running install_lib
2023-04-04T02:26:34,734   creating build/bdist.linux-armv7l
2023-04-04T02:26:34,735   creating build/bdist.linux-armv7l/wheel
2023-04-04T02:26:34,738   creating build/bdist.linux-armv7l/wheel/iotdb
2023-04-04T02:26:34,742   creating build/bdist.linux-armv7l/wheel/iotdb/utils
2023-04-04T02:26:34,744   copying build/lib/iotdb/utils/SessionDataSet.py -> build/bdist.linux-armv7l/wheel/iotdb/utils
2023-04-04T02:26:34,749   copying build/lib/iotdb/utils/Field.py -> build/bdist.linux-armv7l/wheel/iotdb/utils
2023-04-04T02:26:34,753   copying build/lib/iotdb/utils/RowRecord.py -> build/bdist.linux-armv7l/wheel/iotdb/utils
2023-04-04T02:26:34,757   copying build/lib/iotdb/utils/NumpyTablet.py -> build/bdist.linux-armv7l/wheel/iotdb/utils
2023-04-04T02:26:34,762   copying build/lib/iotdb/utils/IoTDBRpcDataSet.py -> build/bdist.linux-armv7l/wheel/iotdb/utils
2023-04-04T02:26:34,767   copying build/lib/iotdb/utils/__init__.py -> build/bdist.linux-armv7l/wheel/iotdb/utils
2023-04-04T02:26:34,771   copying build/lib/iotdb/utils/IoTDBConstants.py -> build/bdist.linux-armv7l/wheel/iotdb/utils
2023-04-04T02:26:34,775   copying build/lib/iotdb/utils/BitMap.py -> build/bdist.linux-armv7l/wheel/iotdb/utils
2023-04-04T02:26:34,779   copying build/lib/iotdb/utils/Tablet.py -> build/bdist.linux-armv7l/wheel/iotdb/utils
2023-04-04T02:26:34,784   copying build/lib/iotdb/IoTDBContainer.py -> build/bdist.linux-armv7l/wheel/iotdb
2023-04-04T02:26:34,790   creating build/bdist.linux-armv7l/wheel/iotdb/tsfile
2023-04-04T02:26:34,793   creating build/bdist.linux-armv7l/wheel/iotdb/tsfile/utils
2023-04-04T02:26:34,795   copying build/lib/iotdb/tsfile/utils/ReadWriteIOUtils.py -> build/bdist.linux-armv7l/wheel/iotdb/tsfile/utils
2023-04-04T02:26:34,799   copying build/lib/iotdb/tsfile/utils/Pair.py -> build/bdist.linux-armv7l/wheel/iotdb/tsfile/utils
2023-04-04T02:26:34,803   copying build/lib/iotdb/tsfile/utils/__init__.py -> build/bdist.linux-armv7l/wheel/iotdb/tsfile/utils
2023-04-04T02:26:34,807   copying build/lib/iotdb/tsfile/__init__.py -> build/bdist.linux-armv7l/wheel/iotdb/tsfile
2023-04-04T02:26:34,812   creating build/bdist.linux-armv7l/wheel/iotdb/tsfile/common
2023-04-04T02:26:34,815   creating build/bdist.linux-armv7l/wheel/iotdb/tsfile/common/constant
2023-04-04T02:26:34,817   copying build/lib/iotdb/tsfile/common/constant/TsFileConstant.py -> build/bdist.linux-armv7l/wheel/iotdb/tsfile/common/constant
2023-04-04T02:26:34,822   copying build/lib/iotdb/tsfile/common/constant/__init__.py -> build/bdist.linux-armv7l/wheel/iotdb/tsfile/common/constant
2023-04-04T02:26:34,826   copying build/lib/iotdb/tsfile/common/__init__.py -> build/bdist.linux-armv7l/wheel/iotdb/tsfile/common
2023-04-04T02:26:34,830   copying build/lib/iotdb/Session.py -> build/bdist.linux-armv7l/wheel/iotdb
2023-04-04T02:26:34,837   copying build/lib/iotdb/__init__.py -> build/bdist.linux-armv7l/wheel/iotdb
2023-04-04T02:26:34,842   creating build/bdist.linux-armv7l/wheel/iotdb/thrift
2023-04-04T02:26:34,844   creating build/bdist.linux-armv7l/wheel/iotdb/thrift/rpc
2023-04-04T02:26:34,846   copying build/lib/iotdb/thrift/rpc/IClientRPCService.py -> build/bdist.linux-armv7l/wheel/iotdb/thrift/rpc
2023-04-04T02:26:34,869   copying build/lib/iotdb/thrift/rpc/constants.py -> build/bdist.linux-armv7l/wheel/iotdb/thrift/rpc
2023-04-04T02:26:34,873   copying build/lib/iotdb/thrift/rpc/ttypes.py -> build/bdist.linux-armv7l/wheel/iotdb/thrift/rpc
2023-04-04T02:26:34,893   copying build/lib/iotdb/thrift/rpc/__init__.py -> build/bdist.linux-armv7l/wheel/iotdb/thrift/rpc
2023-04-04T02:26:34,897   copying build/lib/iotdb/thrift/__init__.py -> build/bdist.linux-armv7l/wheel/iotdb/thrift
2023-04-04T02:26:34,902   creating build/bdist.linux-armv7l/wheel/iotdb/thrift/common
2023-04-04T02:26:34,904   copying build/lib/iotdb/thrift/common/constants.py -> build/bdist.linux-armv7l/wheel/iotdb/thrift/common
2023-04-04T02:26:34,908   copying build/lib/iotdb/thrift/common/ttypes.py -> build/bdist.linux-armv7l/wheel/iotdb/thrift/common
2023-04-04T02:26:34,916   copying build/lib/iotdb/thrift/common/__init__.py -> build/bdist.linux-armv7l/wheel/iotdb/thrift/common
2023-04-04T02:26:34,922   creating build/bdist.linux-armv7l/wheel/iotdb/thrift/datanode
2023-04-04T02:26:34,924   copying build/lib/iotdb/thrift/datanode/IDataNodeRPCService.py -> build/bdist.linux-armv7l/wheel/iotdb/thrift/datanode
2023-04-04T02:26:34,949   copying build/lib/iotdb/thrift/datanode/constants.py -> build/bdist.linux-armv7l/wheel/iotdb/thrift/datanode
2023-04-04T02:26:34,953   copying build/lib/iotdb/thrift/datanode/ttypes.py -> build/bdist.linux-armv7l/wheel/iotdb/thrift/datanode
2023-04-04T02:26:34,969   copying build/lib/iotdb/thrift/datanode/__init__.py -> build/bdist.linux-armv7l/wheel/iotdb/thrift/datanode
2023-04-04T02:26:34,973   copying build/lib/iotdb/thrift/datanode/MPPDataExchangeService.py -> build/bdist.linux-armv7l/wheel/iotdb/thrift/datanode
2023-04-04T02:26:34,979   creating build/bdist.linux-armv7l/wheel/iotdb/dbapi
2023-04-04T02:26:34,981   copying build/lib/iotdb/dbapi/Connection.py -> build/bdist.linux-armv7l/wheel/iotdb/dbapi
2023-04-04T02:26:34,985   copying build/lib/iotdb/dbapi/Exceptions.py -> build/bdist.linux-armv7l/wheel/iotdb/dbapi
2023-04-04T02:26:34,988   copying build/lib/iotdb/dbapi/Cursor.py -> build/bdist.linux-armv7l/wheel/iotdb/dbapi
2023-04-04T02:26:34,995   creating build/bdist.linux-armv7l/wheel/iotdb/dbapi/tests
2023-04-04T02:26:34,997   copying build/lib/iotdb/dbapi/tests/test_cursor.py -> build/bdist.linux-armv7l/wheel/iotdb/dbapi/tests
2023-04-04T02:26:35,002   copying build/lib/iotdb/dbapi/tests/test_connection.py -> build/bdist.linux-armv7l/wheel/iotdb/dbapi/tests
2023-04-04T02:26:35,006   copying build/lib/iotdb/dbapi/tests/__init__.py -> build/bdist.linux-armv7l/wheel/iotdb/dbapi/tests
2023-04-04T02:26:35,009   copying build/lib/iotdb/dbapi/__init__.py -> build/bdist.linux-armv7l/wheel/iotdb/dbapi
2023-04-04T02:26:35,014   creating build/bdist.linux-armv7l/wheel/iotdb/sqlalchemy
2023-04-04T02:26:35,016   copying build/lib/iotdb/sqlalchemy/IoTDBSQLCompiler.py -> build/bdist.linux-armv7l/wheel/iotdb/sqlalchemy
2023-04-04T02:26:35,021   copying build/lib/iotdb/sqlalchemy/IoTDBDialect.py -> build/bdist.linux-armv7l/wheel/iotdb/sqlalchemy
2023-04-04T02:26:35,025   copying build/lib/iotdb/sqlalchemy/IoTDBTypeCompiler.py -> build/bdist.linux-armv7l/wheel/iotdb/sqlalchemy
2023-04-04T02:26:35,029   copying build/lib/iotdb/sqlalchemy/IoTDBIdentifierPreparer.py -> build/bdist.linux-armv7l/wheel/iotdb/sqlalchemy
2023-04-04T02:26:35,034   creating build/bdist.linux-armv7l/wheel/iotdb/sqlalchemy/tests
2023-04-04T02:26:35,036   copying build/lib/iotdb/sqlalchemy/tests/__init__.py -> build/bdist.linux-armv7l/wheel/iotdb/sqlalchemy/tests
2023-04-04T02:26:35,040   copying build/lib/iotdb/sqlalchemy/tests/test_dialect.py -> build/bdist.linux-armv7l/wheel/iotdb/sqlalchemy/tests
2023-04-04T02:26:35,044   copying build/lib/iotdb/sqlalchemy/__init__.py -> build/bdist.linux-armv7l/wheel/iotdb/sqlalchemy
2023-04-04T02:26:35,049   creating build/bdist.linux-armv7l/wheel/iotdb/template
2023-04-04T02:26:35,050   copying build/lib/iotdb/template/Template.py -> build/bdist.linux-armv7l/wheel/iotdb/template
2023-04-04T02:26:35,055   copying build/lib/iotdb/template/TemplateQueryType.py -> build/bdist.linux-armv7l/wheel/iotdb/template
2023-04-04T02:26:35,058   copying build/lib/iotdb/template/MeasurementNode.py -> build/bdist.linux-armv7l/wheel/iotdb/template
2023-04-04T02:26:35,062   copying build/lib/iotdb/template/InternalNode.py -> build/bdist.linux-armv7l/wheel/iotdb/template
2023-04-04T02:26:35,066   copying build/lib/iotdb/template/TemplateNode.py -> build/bdist.linux-armv7l/wheel/iotdb/template
2023-04-04T02:26:35,069   copying build/lib/iotdb/template/__init__.py -> build/bdist.linux-armv7l/wheel/iotdb/template
2023-04-04T02:26:35,074   creating build/bdist.linux-armv7l/wheel/tests
2023-04-04T02:26:35,076   copying build/lib/tests/test_one_device.py -> build/bdist.linux-armv7l/wheel/tests
2023-04-04T02:26:35,080   copying build/lib/tests/test_tablet.py -> build/bdist.linux-armv7l/wheel/tests
2023-04-04T02:26:35,084   copying build/lib/tests/test_template.py -> build/bdist.linux-armv7l/wheel/tests
2023-04-04T02:26:35,088   copying build/lib/tests/test_session.py -> build/bdist.linux-armv7l/wheel/tests
2023-04-04T02:26:35,093   copying build/lib/tests/test_aligned_timeseries.py -> build/bdist.linux-armv7l/wheel/tests
2023-04-04T02:26:35,098   copying build/lib/tests/test_todf.py -> build/bdist.linux-armv7l/wheel/tests
2023-04-04T02:26:35,102   copying build/lib/tests/test_dataframe.py -> build/bdist.linux-armv7l/wheel/tests
2023-04-04T02:26:35,106   copying build/lib/tests/tablet_performance_comparison.py -> build/bdist.linux-armv7l/wheel/tests
2023-04-04T02:26:35,110   copying build/lib/tests/__init__.py -> build/bdist.linux-armv7l/wheel/tests
2023-04-04T02:26:35,114   copying build/lib/tests/test_numpy_tablet.py -> build/bdist.linux-armv7l/wheel/tests
2023-04-04T02:26:35,118   copying build/lib/tests/test_delete_data.py -> build/bdist.linux-armv7l/wheel/tests
2023-04-04T02:26:35,122   running install_egg_info
2023-04-04T02:26:35,182   running egg_info
2023-04-04T02:26:35,192   writing apache_iotdb.egg-info/PKG-INFO
2023-04-04T02:26:35,198   writing dependency_links to apache_iotdb.egg-info/dependency_links.txt
2023-04-04T02:26:35,202   writing entry points to apache_iotdb.egg-info/entry_points.txt
2023-04-04T02:26:35,205   writing requirements to apache_iotdb.egg-info/requires.txt
2023-04-04T02:26:35,207   writing top-level names to apache_iotdb.egg-info/top_level.txt
2023-04-04T02:26:35,247   reading manifest file 'apache_iotdb.egg-info/SOURCES.txt'
2023-04-04T02:26:35,255   adding license file 'LICENSE'
2023-04-04T02:26:35,269   writing manifest file 'apache_iotdb.egg-info/SOURCES.txt'
2023-04-04T02:26:35,272   Copying apache_iotdb.egg-info to build/bdist.linux-armv7l/wheel/apache_iotdb-1.1.0-py3.7.egg-info
2023-04-04T02:26:35,297   running install_scripts
2023-04-04T02:26:35,346   creating build/bdist.linux-armv7l/wheel/apache_iotdb-1.1.0.dist-info/WHEEL
2023-04-04T02:26:35,351   creating '/tmp/pip-wheel-8vdqb6w0/.tmp-ogs2xu8a/apache_iotdb-1.1.0-py3-none-any.whl' and adding 'build/bdist.linux-armv7l/wheel' to it
2023-04-04T02:26:35,359   adding 'iotdb/IoTDBContainer.py'
2023-04-04T02:26:35,372   adding 'iotdb/Session.py'
2023-04-04T02:26:35,375   adding 'iotdb/__init__.py'
2023-04-04T02:26:35,380   adding 'iotdb/dbapi/Connection.py'
2023-04-04T02:26:35,383   adding 'iotdb/dbapi/Cursor.py'
2023-04-04T02:26:35,386   adding 'iotdb/dbapi/Exceptions.py'
2023-04-04T02:26:35,389   adding 'iotdb/dbapi/__init__.py'
2023-04-04T02:26:35,392   adding 'iotdb/dbapi/tests/__init__.py'
2023-04-04T02:26:35,395   adding 'iotdb/dbapi/tests/test_connection.py'
2023-04-04T02:26:35,398   adding 'iotdb/dbapi/tests/test_cursor.py'
2023-04-04T02:26:35,402   adding 'iotdb/sqlalchemy/IoTDBDialect.py'
2023-04-04T02:26:35,405   adding 'iotdb/sqlalchemy/IoTDBIdentifierPreparer.py'
2023-04-04T02:26:35,409   adding 'iotdb/sqlalchemy/IoTDBSQLCompiler.py'
2023-04-04T02:26:35,412   adding 'iotdb/sqlalchemy/IoTDBTypeCompiler.py'
2023-04-04T02:26:35,414   adding 'iotdb/sqlalchemy/__init__.py'
2023-04-04T02:26:35,418   adding 'iotdb/sqlalchemy/tests/__init__.py'
2023-04-04T02:26:35,421   adding 'iotdb/sqlalchemy/tests/test_dialect.py'
2023-04-04T02:26:35,425   adding 'iotdb/template/InternalNode.py'
2023-04-04T02:26:35,427   adding 'iotdb/template/MeasurementNode.py'
2023-04-04T02:26:35,430   adding 'iotdb/template/Template.py'
2023-04-04T02:26:35,433   adding 'iotdb/template/TemplateNode.py'
2023-04-04T02:26:35,435   adding 'iotdb/template/TemplateQueryType.py'
2023-04-04T02:26:35,438   adding 'iotdb/template/__init__.py'
2023-04-04T02:26:35,441   adding 'iotdb/thrift/__init__.py'
2023-04-04T02:26:35,445   adding 'iotdb/thrift/common/__init__.py'
2023-04-04T02:26:35,447   adding 'iotdb/thrift/common/constants.py'
2023-04-04T02:26:35,455   adding 'iotdb/thrift/common/ttypes.py'
2023-04-04T02:26:35,490   adding 'iotdb/thrift/datanode/IDataNodeRPCService.py'
2023-04-04T02:26:35,503   adding 'iotdb/thrift/datanode/MPPDataExchangeService.py'
2023-04-04T02:26:35,506   adding 'iotdb/thrift/datanode/__init__.py'
2023-04-04T02:26:35,509   adding 'iotdb/thrift/datanode/constants.py'
2023-04-04T02:26:35,537   adding 'iotdb/thrift/datanode/ttypes.py'
2023-04-04T02:26:35,573   adding 'iotdb/thrift/rpc/IClientRPCService.py'
2023-04-04T02:26:35,583   adding 'iotdb/thrift/rpc/__init__.py'
2023-04-04T02:26:35,585   adding 'iotdb/thrift/rpc/constants.py'
2023-04-04T02:26:35,614   adding 'iotdb/thrift/rpc/ttypes.py'
2023-04-04T02:26:35,623   adding 'iotdb/tsfile/__init__.py'
2023-04-04T02:26:35,627   adding 'iotdb/tsfile/common/__init__.py'
2023-04-04T02:26:35,631   adding 'iotdb/tsfile/common/constant/TsFileConstant.py'
2023-04-04T02:26:35,633   adding 'iotdb/tsfile/common/constant/__init__.py'
2023-04-04T02:26:35,637   adding 'iotdb/tsfile/utils/Pair.py'
2023-04-04T02:26:35,640   adding 'iotdb/tsfile/utils/ReadWriteIOUtils.py'
2023-04-04T02:26:35,642   adding 'iotdb/tsfile/utils/__init__.py'
2023-04-04T02:26:35,646   adding 'iotdb/utils/BitMap.py'
2023-04-04T02:26:35,650   adding 'iotdb/utils/Field.py'
2023-04-04T02:26:35,652   adding 'iotdb/utils/IoTDBConstants.py'
2023-04-04T02:26:35,657   adding 'iotdb/utils/IoTDBRpcDataSet.py'
2023-04-04T02:26:35,661   adding 'iotdb/utils/NumpyTablet.py'
2023-04-04T02:26:35,664   adding 'iotdb/utils/RowRecord.py'
2023-04-04T02:26:35,667   adding 'iotdb/utils/SessionDataSet.py'
2023-04-04T02:26:35,670   adding 'iotdb/utils/Tablet.py'
2023-04-04T02:26:35,673   adding 'iotdb/utils/__init__.py'
2023-04-04T02:26:35,677   adding 'tests/__init__.py'
2023-04-04T02:26:35,681   adding 'tests/tablet_performance_comparison.py'
2023-04-04T02:26:35,685   adding 'tests/test_aligned_timeseries.py'
2023-04-04T02:26:35,688   adding 'tests/test_dataframe.py'
2023-04-04T02:26:35,691   adding 'tests/test_delete_data.py'
2023-04-04T02:26:35,694   adding 'tests/test_numpy_tablet.py'
2023-04-04T02:26:35,698   adding 'tests/test_one_device.py'
2023-04-04T02:26:35,702   adding 'tests/test_session.py'
2023-04-04T02:26:35,705   adding 'tests/test_tablet.py'
2023-04-04T02:26:35,708   adding 'tests/test_template.py'
2023-04-04T02:26:35,711   adding 'tests/test_todf.py'
2023-04-04T02:26:35,716   adding 'apache_iotdb-1.1.0.dist-info/LICENSE'
2023-04-04T02:26:35,723   adding 'apache_iotdb-1.1.0.dist-info/METADATA'
2023-04-04T02:26:35,726   adding 'apache_iotdb-1.1.0.dist-info/WHEEL'
2023-04-04T02:26:35,728   adding 'apache_iotdb-1.1.0.dist-info/entry_points.txt'
2023-04-04T02:26:35,729   adding 'apache_iotdb-1.1.0.dist-info/top_level.txt'
2023-04-04T02:26:35,733   adding 'apache_iotdb-1.1.0.dist-info/RECORD'
2023-04-04T02:26:35,743   removing build/bdist.linux-armv7l/wheel
2023-04-04T02:26:35,790   /tmp/pip-build-env-5ggwxfha/overlay/lib/python3.7/site-packages/setuptools/_distutils/dist.py:265: UserWarning: Unknown distribution option: 'website'
2023-04-04T02:26:35,791     warnings.warn(msg)
2023-04-04T02:26:35,923   Building wheel for apache-iotdb (pyproject.toml): finished with status 'done'
2023-04-04T02:26:35,948   Created wheel for apache-iotdb: filename=apache_iotdb-1.1.0-py3-none-any.whl size=154875 sha256=17b0261e5e0602df730baf1bdd055750c850a2fd0163d2ce09d0083dfcf169f4
2023-04-04T02:26:35,951   Stored in directory: /tmp/pip-ephem-wheel-cache-e113_bt4/wheels/c6/ec/12/a8bb808c94807147f44e15f2e87797f9f94b5b9b1906c04cf8
2023-04-04T02:26:35,989 Successfully built apache-iotdb
2023-04-04T02:26:36,010 Removed build tracker: '/tmp/pip-build-tracker-bjwlcw98'