{
  "channels": [
    "defaults"
  ],
  "conda_build_version": "3.20.5",
  "conda_private": false,
  "conda_version": "4.9.2",
  "description": "Use airflow to author workflows as directed acyclic graphs (DAGs)\nof tasks. The airflow scheduler executes your tasks on an array of\nworkers while following the specified dependencies. Rich command\nline utilities make performing complex surgeries on DAGs a snap.\nThe rich user interface makes it easy to visualize pipelines\nrunning in production, monitor progress, and troubleshoot issues\nwhen needed.\n\nWhen workflows are defined as code, they become more maintainable,\nversionable, testable, and collaborative.\n",
  "dev_url": "https://github.com/apache/airflow",
  "doc_url": "http://pythonhosted.org/airflow/profiling.html",
  "env_vars": {
    "CIO_TEST": "<not set>"
  },
  "extra": {
    "copy_test_source_files": true,
    "final": true,
    "parent_recipe": {
      "name": "airflow-split",
      "path": "/tmp/build/80754af9/rsync-recipes/airflow-split-1.10.12-on-linux_64",
      "version": "1.10.12"
    },
    "recipe-maintainers": [
      "sodre",
      "halldc",
      "xylar"
    ]
  },
  "home": "http://airflow.apache.org",
  "identifiers": [],
  "keywords": [],
  "license": "Apache 2.0",
  "license_file": "LICENSE",
  "root_pkgs": [
    "_libgcc_mutex 0.1 main",
    "anaconda-client 1.7.2 py37_0",
    "binutils_impl_linux-64 2.31.1 h6176602_1",
    "binutils_linux-64 2.31.1 h6176602_8",
    "bzip2 1.0.8 h7b6447c_0",
    "clyent 1.2.2 py37_1",
    "curl 7.65.3 hbc83047_0",
    "filelock 3.0.12 py_0",
    "gcc_impl_linux-64 7.3.0 habb00fd_1",
    "gcc_linux-64 7.3.0 h553295d_8",
    "git 2.20.1 pl526hacde149_0",
    "glob2 0.7 py_0",
    "gxx_impl_linux-64 7.3.0 hdf63c60_1",
    "gxx_linux-64 7.3.0 h553295d_8",
    "ipython_genutils 0.2.0 py37_0",
    "libcurl 7.65.3 h20c2e04_0",
    "libgcc-ng 9.1.0 hdf63c60_0",
    "libstdcxx-ng 9.1.0 hdf63c60_0",
    "perl 5.26.2 h14c3975_0",
    "pip 19.2.2 py37_0",
    "zlib 1.2.11 h7b6447c_3",
    "ca-certificates 2020.10.14 0",
    "ld_impl_linux-64 2.33.1 h53a641e_7",
    "ripgrep 12.1.1 0",
    "expat 2.2.10 he6710b0_2",
    "icu 58.2 he6710b0_3",
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    "libssh2 1.9.0 h1ba5d50_1",
    "libxml2 2.9.10 hb55368b_3",
    "readline 8.0 h7b6447c_0",
    "tk 8.6.10 hbc83047_0",
    "zstd 1.4.5 h9ceee32_0",
    "krb5 1.16.4 h173b8e3_0",
    "libarchive 3.4.2 h62408e4_0",
    "sqlite 3.33.0 h62c20be_0",
    "python 3.7.9 h7579374_0",
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    "py-lief 0.10.1 py37h403a769_0",
    "pycosat 0.6.3 py37h27cfd23_0",
    "pycparser 2.20 py_2",
    "pyrsistent 0.17.3 py37h7b6447c_0",
    "pysocks 1.7.1 py37_1",
    "python-libarchive-c 2.9 py_0",
    "pytz 2020.1 py_0",
    "pyyaml 5.3.1 py37h7b6447c_1",
    "ruamel_yaml 0.15.87 py37h7b6447c_1",
    "six 1.15.0 py37h06a4308_0",
    "soupsieve 2.0.1 py_0",
    "tqdm 4.51.0 pyhd3eb1b0_0",
    "wheel 0.35.1 pyhd3eb1b0_0",
    "zipp 3.4.0 pyhd3eb1b0_0",
    "beautifulsoup4 4.9.3 pyhb0f4dca_0",
    "cffi 1.14.3 py37h261ae71_2",
    "conda-package-handling 1.7.2 py37h03888b9_0",
    "importlib-metadata 2.0.0 py_1",
    "python-dateutil 2.8.1 py_0",
    "setuptools 50.3.1 py37h06a4308_1",
    "traitlets 5.0.5 py_0",
    "brotlipy 0.7.0 py37h27cfd23_1003",
    "cryptography 3.2.1 py37h3c74f83_1",
    "importlib_metadata 2.0.0 1",
    "jinja2 2.11.2 py_0",
    "jupyter_core 4.6.3 py37_0",
    "jsonschema 3.2.0 py_2",
    "pyopenssl 19.1.0 pyhd3eb1b0_1",
    "nbformat 5.0.8 py_0",
    "urllib3 1.25.11 py_0",
    "requests 2.24.0 py_0",
    "conda 4.9.2 py37h06a4308_0",
    "conda-build 3.20.5 py37_1"
  ],
  "summary": "Airflow is a platform to programmatically author, schedule and monitor\nworkflows\n",
  "tags": []
}