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Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

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Apache Airflow

PyPI version Airflow Coverage Status Documentation Status License PyPI - Python Version

Twitter Follow Slack Status

Apache Airflow (or simply Airflow) is a platform to programmatically author, schedule, and monitor workflows.

When workflows are defined as code, they become more maintainable, versionable, testable, and collaborative.

Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress, and troubleshoot issues when needed.

Table of contents

Requirements

Apache Airflow is tested with:

Master version (2.0.0dev)

  • Python versions: 3.6, 3.7, 3.8
  • Postgres DB: 9.6, 10
  • MySQL DB: 5.7
  • Sqlite - latest stable (it is used mainly for development purpose)
  • Kubernetes - 1.16.2, 1.17.0

Stable version (1.10.11)

  • Python versions: 2.7, 3.5, 3.6, 3.7
  • Postgres DB: 9.6, 10
  • MySQL DB: 5.6, 5.7
  • Sqlite - latest stable (it is used mainly for development purpose)
  • Kubernetes - 1.16.2, 1.17.0

Additional notes on Python version requirements

  • Stable version requires at least Python 3.5.3 when using Python 3
  • Stable version is currently incompatible with Python 3.8 due to a known compatibility issue with a dependent library

Getting started

Please visit the Airflow Platform documentation (latest stable release) for help with installing Airflow, getting a quick start, or a more complete tutorial.

Documentation of GitHub master (latest development branch): ReadTheDocs Documentation

For further information, please visit the Airflow Wiki.

Official container (Docker) images for Apache Airflow are described in IMAGES.rst.

Installing from PyPI

Airflow is published as apache-airflow package in PyPI. Installing it however might be sometimes tricky because Airflow is a bit of both a library and application. Libraries usually keep their dependencies open and applications usually pin them, but we should do neither and both at the same time. We decided to keep our dependencies as open as possible (in setup.py) so users can install different versions of libraries if needed. This means that from time to time plain pip install apache-airflow will not work or will produce unusable Airflow installation.

In order to have repeatable installation, however, starting from Airflow 1.10.10 we also keep a set of "known-to-be-working" requirement files in the requirements folder. Those "known-to-be-working" requirements are per major/minor python version (3.6/3.7/3.8). You can use them as constraint files when installing Airflow from PyPI. Note that you have to specify correct Airflow version and python versions in the URL.

  1. Installing just airflow:
pip install apache-airflow==1.10.10 \
 --constraint https://raw.githubusercontent.com/apache/airflow/1.10.10/requirements/requirements-python3.7.txt
  1. Installing with extras (for example postgres,gcp)
pip install apache-airflow[postgres,gcp]==1.10.10 \
 --constraint https://raw.githubusercontent.com/apache/airflow/1.10.10/requirements/requirements-python3.7.txt

Building customized production images

In order to use Airflow in Docker Compose or Kubernetes, you might need to use or build production images of Apache Airflow. The community provides two types of support for the production images:

  • We provide pre-build relesed version of production image in PyPI build from released sources of Apache Airflow - shortly after release. Those images are available in the DockerHub. You can pull those images via docker pull apache/airflow:<VERSION>-pythonX.Y - version is the version number (for example 1.10.11). Additionally docker pull apache/airflow will pull latest stable version of the image with default python version (currently 3.6)

  • In master branch of Airflow and in v1-10-stable branch we provide Dockerfiles and accompanying files that allow to build your own customized version of the Airflow Production image. The instructions on how to build your own image with additional dependencies (if needed) are provided in the IMAGES.rst if you want to build it using docker build command or in BREEZE.rst to use Breeze tool which easier interface, auto-complete, and accompanying screencast video. Note, that while it is possible to use master branch to build images for released Airflow versions, it might at times get broken so you should rather rely on building your own images from the v1-10-stable branch.

Beyond the Horizon

Airflow is not a data streaming solution. Tasks do not move data from one to the other (though tasks can exchange metadata!). Airflow is not in the Spark Streaming or Storm space, it is more comparable to Oozie or Azkaban.

Workflows are expected to be mostly static or slowly changing. You can think of the structure of the tasks in your workflow as slightly more dynamic than a database structure would be. Airflow workflows are expected to look similar from a run to the next, this allows for clarity around unit of work and continuity.

Principles

  • Dynamic: Airflow pipelines are configuration as code (Python), allowing for dynamic pipeline generation. This allows for writing code that instantiates pipelines dynamically.
  • Extensible: Easily define your own operators, executors and extend the library so that it fits the level of abstraction that suits your environment.
  • Elegant: Airflow pipelines are lean and explicit. Parameterizing your scripts is built into the core of Airflow using the powerful Jinja templating engine.
  • Scalable: Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers.

User Interface

  • DAGs: Overview of all DAGs in your environment.

  • Tree View: Tree representation of a DAG that spans across time.

  • Graph View: Visualization of a DAG's dependencies and their current status for a specific run.

  • Task Duration: Total time spent on different tasks over time.

  • Gantt View: Duration and overlap of a DAG.

  • Code View: Quick way to view source code of a DAG.

Backport packages

Context: Airflow 2.0 operators, hooks, and secrets

Currently, stable Apache Airflow versions are from the 1.10.* series. We are working on the future, major version of Airflow from the 2.0.* series. It is going to be released in 2020. However, the exact time of release depends on many factors and is not yet confirmed.

We have already a lot of changes in the operators, transfers, hooks, sensors, secrets for many external systems, but they are not used nor tested widely because they are part of the master/2.0 release.

In the Airflow 2.0 - following AIP-21 "change in import paths" all the non-core interfaces to external systems of Apache Airflow have been moved to the "airflow.providers" package.

Thanks to that and automated backport effort we took, the operators from Airflow 2.0 can be used in Airflow 1.10 as separately installable packages, with the constraint that those packages can only be used in python3.6+ environment.

Installing Airflow 2.0 operators in Airflow 1.10

We released backport packages that can be installed for older Airflow versions. Those backport packages are going to be released more frequently that main Airflow 1.10.& releases.

You will not have to upgrade your Airflow version to use those packages. You can find those packages in the PyPI and install them separately for each provider.

Those packages are available now and can be used in the latest Airflow 1.10* version. Most of those packages are also installable and usable in most Airflow 1.10.* releases but there is no extensive testing done beyond the latest released version, so you might expect more problems in earlier Airflow versions.

An easier migration path to 2.0

With backported providers package users can migrate their DAGs to the new providers package incrementally and once they convert to the new operators/sensors/hooks they can seamlessly migrate their environments to Airflow 2.0. The nice thing about providers backport packages is that you can use both old and new classes at the same time - even in the same DAG. So your migration can be gradual and smooth. Note that in Airflow 2.0 old classes raise deprecation warning and redirect to the new classes wherever it is possible. In some rare cases the new operators will not be fully backwards compatible - you will find information about those cases in UPDATING.md where we explained all such cases. Switching early to the Airflow 2.0 operators while still running Airflow 1.10 will make your migration much easier.

More information about the status and releases of the back-ported packages are available at Backported providers package page

Installing backport packages

Note that the backport packages might require extra dependencies. Pip installs the required dependencies automatically when it installs the backport package, but there are sometimes cross-dependencies between the backport packages. For example google package has cross-dependency with amazon package to allow transfers between those two cloud providers. You might need to install those packages in case you use cross-dependent packages. The easiest way to install them is to use "extras" when installing the package, for example the below will install both google and amazon backport packages:

pip install apache-airflow-backport-providers-google[amazon]

This is all documented in the PyPI description of the packages as well as in the README.md file available for each provider package. For example for google package you can find the readme in README.md. You will also find there the summary of both - new classes and moved classes as well as requirement information.

Troubleshooting installing backport packages

Backport providers only work when they are installed in the same namespace as the 'apache-airflow' 1.10 package. This is majority of cases when you simply run pip install - it installs all packages in the same folder (usually in /usr/local/lib/pythonX.Y/site-packages). But when you install the apache-airflow and apache-airflow-backport-package-* using different methods (for example using pip install -e . or pip install --user they might be installed in different namespaces. If that's the case, the provider packages will not be importable (the error in such case is ModuleNotFoundError: No module named 'airflow.providers').

If you experience the problem, you can easily fix it by creating symbolic link in your installed "airflow" folder to the "providers" folder where you installed your backport packages. If you installed it with -e, this link should be created in your airflow sources, if you installed it with the --user flag it should be from the ~/.local/lib/pythonX.Y/site-packages/airflow/ folder,

Contributing

Want to help build Apache Airflow? Check out our contributing documentation.

Who uses Apache Airflow?

As the Apache Airflow community grows, we'd like to keep track of who is using the platform. Please send a PR with your company name and @githubhandle if you may.

Currently officially using Airflow:

  1. 4G Capital [@posei]
  2. 6play [@lemourA, @achaussende, @d-nguyen, @julien-gm]
  3. 8fit [@nicor88, @frnzska]
  4. 90 Seconds [@aaronmak]
  5. 99 [@fbenevides, @gustavoamigo & @mmmaia]
  6. AdBOOST [AdBOOST]
  7. Adobe [@mishikaSingh, @ramandumcs, @vardancse]
  8. Agari [@r39132]
  9. Agoda [@akki]
  10. Airbnb [@mistercrunch, @artwr]
  11. AirDNA
  12. Airfinity [@sibowyer]
  13. Airtel [@harishbisht]
  14. Akamas [@GiovanniPaoloGibilisco, @lucacavazzana]
  15. Alan [@charles-go]
  16. allegro.pl [@kretes]
  17. AloPeyk [@blcksrx, @AloPeyk]
  18. AltX [@pedromduarte]
  19. AMPATH[@AMPATH, @fatmali]
  20. Apigee [@btallman]
  21. ARGO Labs [@California Data Collaborative]
  22. ARMEDANGELS [@swiffer]
  23. Arquivei [@arquivei]
  24. Arrive
  25. Asana [@chang, @dima-asana, @jdavidheiser, @ricardoandresrojas]
  26. Astronomer [@schnie, @ashb, @kaxil, @dimberman, @andriisoldatenko, @ryw, @andrewhharmon]
  27. Auth0 [@sicarul]
  28. Automattic [@anandnalya, @bperson, @khrol, @xyu]
  29. Away [@trunsky]
  30. Azri Solutions [@userimack]
  31. Bagelcode
  32. BalanceHero [@swalloow]
  33. Banco de Formaturas [@guiligan]
  34. BandwidthX [@dineshdsharma]
  35. Basetis
  36. BBM
  37. Beamly [@christopheralcock]
  38. Beeswax
  39. Bellhops
  40. BelugaDB [@fabio-nukui & @joao-sallaberry & @lucianoviola & @tmatuki]
  41. Betterment [@betterment]
  42. Bexs Bank [@felipefb & @ilarsen]
  43. BigQuant [@bigquant]
  44. Birdz by Veolia [@benjamingrenier]
  45. BlaBlaCar [@puckel & @wmorin]
  46. Blacklane [@serkef]
  47. Bloc [@dpaola2]
  48. Bloomberg [@dimberman]
  49. Blue Yonder [@blue-yonder]
  50. BlueApron [@jasonjho & @matthewdavidhauser]
  51. Bluecore [@JLDLaughlin]
  52. Bluekiri [@Bluekiri]
  53. Boda Telecom Suite - CE [@erssebaggala, @bodastage]
  54. Bodastage Solutions [@erssebaggala, @bodastage]
  55. Bombora Inc [@jeffkpayne, @pakelley, @dNavalta, @austynh, @TheOriginalAlex]
  56. Bonial International GmbH
  57. Bonnier Broadcasting [@wileeam]
  58. BounceX [@JoshFerge, @hudsonrio, @ronniekritou]
  59. Braintree [@coopergillan, @curiousjazz77, @raymondberg]
  60. Branch [@sdebarshi, @dmitrig01]
  61. Caesars Entertainment
  62. California Data Collaborative powered by ARGO Labs
  63. Capital One [@anoopengineer]
  64. Carbonite [@ajbosco]
  65. CarLabs [@sganz & @odannyc]
  66. CAVA [@minh5 & @patchus]
  67. Celect [@superdosh & @chadcelect]
  68. Censys [@zakird, @dadrian, & @andrewsardone]
  69. Change.org [@change, @vijaykramesh]
  70. Chartboost [@cgelman & @dclubb]
  71. Checkr [@tongboh]
  72. Children's Hospital of Philadelphia Division of Genomic Diagnostics [@genomics-geek]
  73. Cinimex DataLab [@kdubovikov]
  74. City of San Diego [@MrMaksimize, @andrell81 & @arnaudvedy]
  75. City of Toronto [@CityofToronto, @radumas]
  76. ciValue [@chencivalue, @YoavGaudin, @saleem-boshnak]
  77. Civey [@WesleyBatista]
  78. Clairvoyant [@shekharv]
  79. Classmethod, Inc. [@shoito]
  80. Cleartax [@anks & @codebuff]
  81. Clover Health [@gwax & @vansivallab]
  82. Colgate-Palmolive [@fhoda]
  83. Collectivehealth Inc. [@retornam]
  84. Compass [@wdhorton]
  85. ConnectWise [@jacobeturpin]
  86. ContaAzul [@bern4rdelli, @renanleme & @sabino]
  87. Cotap [@maraca & @richardchew]
  88. Craig@Work
  89. Crealytics
  90. Credit Karma [@preete-dixit-ck & @harish-gaggar-ck & @greg-finley-ck]
  91. Creditas [@dcassiano]
  92. CreditCards.com[@vmAggies & @jay-wallaby]
  93. Cryptalizer.com
  94. Custom Ink [@david-dalisay, @dmartin11 & @mpeteuil]
  95. Cyscale [@ocical]
  96. Dailymotion [@germaintanguy & @hc]
  97. Danamica [@testvinder]
  98. Data Reply [@kaxil]
  99. DataCamp [@dgrtwo]
  100. DataFox [@sudowork]
  101. Dentsu Inc. [@bryan831 & @loozhengyuan]
  102. Deseret Digital Media [@formigone
  103. Digital First Media [@duffn & @mschmo & @seanmuth]
  104. DigitalOcean [@ajbosco]
  105. Digitas Pixelpark [@feluelle]
  106. DoorDash
  107. Dotmodus [@dannylee12]
  108. Drivy [@AntoineAugusti]
  109. Easy Taxi [@caique-lima & @diraol]
  110. EllisDon [@d2kalra & @zbasama]
  111. Endesa [@drexpp]
  112. Enigma [@hydrosquall]
  113. Datamaran [@valexharo]
  114. Etsy [@mchalek]
  115. evo.company [@orhideous]
  116. Experity (formerly DocuTAP) [@cloneluke & @tobyjoliver]
  117. Fathom Health
  118. Firestone Inventing [@zihengCat]
  119. Flipp [@sethwilsonwishabi]
  120. Format [@format & @jasonicarter]
  121. FreeNow [@freenowtech]
  122. FreshBooks [@DinoCow]
  123. Freshworks [@shaikshakeel]
  124. FullContact
  125. Fuller, Inc. [@wutali & @sh-tech]
  126. Fundera [@andyxhadji]
  127. G Adventures [@chchtv11, @tgumbley, @tomwross]
  128. GameWisp [@tjbiii & @theryanwalls]
  129. Geekie [@wolney]
  130. GeneCards [@oferze]
  131. Gentner Lab [@neuromusic]
  132. Get Simpl [@rootcss]
  133. GitLab [@tayloramurphy & @m_walker]
  134. Glassdoor [@syvineckruyk & @sid88in]
  135. Global Fashion Group [@GFG]
  136. GoDataDriven [@BasPH, @danielvdende, @ffinfo, @Fokko, @gglanzani, @hgrif, @jrderuiter, @NielsZeilemaker]
  137. Gojek [@gojek]
  138. GovTech GDS [@chrissng & @datagovsg]
  139. Grab [@calvintran]
  140. Gradeup [@gradeup]
  141. Grand Rounds [@richddr, @timz1290, @wenever, & @runongirlrunon]
  142. Greytip [@greytip]
  143. Groupalia [@jesusfcr]
  144. Groupon [@stevencasey]
  145. Growbots[@exploy]
  146. GrowthSimple
  147. GSN Games
  148. Gusto [@frankhsu]
  149. Handshake [@mhickman]
  150. Handy [@marcintustin / @mtustin-handy]
  151. happn [@pcorbel]
  152. HAVAN [@botbiz]
  153. HBC Digital [@tmccartan & @dmateusp]
  154. HBO[@yiwang]
  155. Healthjump [@miscbits]
  156. HelloFresh [@tammymendt & @davidsbatista & @iuriinedostup]
  157. Hipages [@arihantsurana]
  158. Holimetrix [@thibault-ketterer]
  159. HomeToGo [@HomeToGo, @AurimasGr]
  160. Hootsuite
  161. Hostnfly [@CyrilLeMat & @pierrechopin & @alexisrosuel]
  162. HotelQuickly [@zinuzoid]
  163. Huq Industries [@huqindustries, @alepuccetti, @turbomerl]
  164. Iflix [@ChaturvediSulabh]
  165. IFTTT [@apurvajoshi]
  166. iHeartRadio[@yiwang]
  167. imgix [@dclubb]
  168. ING
  169. Instacart 🥕 [@arp1t & @code-sauce & @jasonlew & @j4p3 & @lubert & @mmontagna & @RyanAD &@zzadeh]
  170. Intercom [@fox & @paulvic]
  171. Interia
  172. Investorise [@svenvarkel]
  173. iS2.co [@iS2co]
  174. Jampp
  175. Jeitto [@BrennerPablo & @ds-mauri]
  176. Jetlore [@bderose]
  177. JobTeaser [@stefani75 & @knil-sama]
  178. JULO [@sepam & @tenapril & @verzqy]
  179. Kalibrr [@charlesverdad]
  180. Kargo [@chaithra-yenikapati, @akarsh3007 & @dineshanchan]
  181. Karmic [@hyw]
  182. King [@nathadfield]
  183. King Abdullah Petroleum Studies and Research Center(KAPSARC) [@saianupkumarp]
  184. Kiwi.com [@underyx]
  185. Kogan.com [@geeknam]
  186. Korbit [@jensenity]
  187. KPN B.V. [@biyanisuraj & @gmic]
  188. Kroton Educacional
  189. Lemann Foundation [@fernandosjp]
  190. LeMans Corporation [@alloydwhitlock] & [@tinyrye]
  191. LendUp [@lendup]
  192. LetsBonus [@jesusfcr & @OpringaoDoTurno]
  193. Liberty Global [@LibertyGlobal]
  194. liligo [@tromika]
  195. LingoChamp [@haitaoyao]
  196. Logitravel Group
  197. Los Angeles Times [@standyro]
  198. LokSuvidha [@saurabhwahile]
  199. Lucid [@jbrownlucid & @kkourtchikov]
  200. Lumos Labs [@rfroetscher & @zzztimbo]
  201. Lyft [@feng-tao, @milton0825, @astahlman, @youngyjd, @ArgentFalcon]
  202. M4U [@msantino]
  203. Madrone [@mbreining & @scotthb]
  204. Markovian [@al-xv, @skogsbaeck, @waltherg]
  205. Mercadoni [@demorenoc]
  206. Mercari [@yu-iskw]
  207. MFG Labs
  208. Ministry of Economy of Brazil [@nitaibezerra, @vitorbellini]
  209. MiNODES [@dice89, @diazcelsa]
  210. Modernizing Medicine[@kehv1n, @dalupus]
  211. Movember
  212. Multiply [@nrhvyc]
  213. National Bank of Canada [@brilhana]
  214. Neoway [@neowaylabs]
  215. Nerdwallet
  216. New Relic [@marcweil]
  217. Newzoo [@newzoo-nexus]
  218. NEXT Trucking [@earthmancash2, @kppullin]
  219. Nextdoor [@SivaPandeti, @zshapiro & @jthomas123]
  220. Nine [@TheZepto]
  221. OdysseyPrime [@davideberdin]
  222. OfferUp
  223. OneFineStay [@slangwald]
  224. Open Knowledge International @vitorbaptista
  225. Optum - UnitedHealthGroup [@fhoda, @ianstanton, @nilaybhatt,@hiteshrd]
  226. OrangeBank [@HamzaBoukraa]
  227. Outcome Health [@mikethoun, @rolandotribo]
  228. Overstock [@mhousley & @mct0006]
  229. OVH [@ncrocfer & @anthonyolea]
  230. Pagar.me [@pagarme]
  231. Palo Alto Networks [@PaloAltoNetworks]
  232. Pandora Media [@Acehaidrey & @wolfier]
  233. Paraná Banco [@lopesdiego12]
  234. PayFit [@pcorbel]
  235. PAYMILL [@paymill & @matthiashuschle]
  236. PayPal [@r39132 & @jhsenjaliya]
  237. Pecan [@ohadmata]
  238. Pernod-Ricard [@romain-nio]
  239. Plaid [@plaid, @AustinBGibbons & @jeeyoungk]
  240. Playbuzz [@clintonboys & @dbn]
  241. PMC [@andrewm4894]
  242. Polidea [@potiuk, @mschickensoup, @mik-laj, @turbaszek, @michalslowikowski00, @olchas], @debek
  243. Poshmark
  244. Postmates [@syeoryn]
  245. Premise [@jmccallum-premise]
  246. Promofarma [@JavierLopezT]
  247. Pronto Tools [@zkan & @mesodiar]
  248. proton.ai [@prmsolutions]
  249. PubNub [@jzucker2]
  250. PXYData [@patchus]
  251. Qplum [@manti]
  252. Quantopian [@eronarn]
  253. Qubole [@msumit]
  254. QuintoAndar [@quintoandar]
  255. Quizlet [@quizlet]
  256. Quora
  257. Qoala [@gnomeria, @qoala-engineering]
  258. Rakuten
  259. RaĂ­zen [@rudlac & @guifneves]
  260. Rapido [@ChethanUK]
  261. REA Group
  262. Reddit [@reddit]
  263. Reverb[@reverbdotcom]
  264. Revolut [@sztanko & @nautilus28]
  265. Robinhood [@vineet-rh]
  266. RushOwl [@songyanho]
  267. Scaleway [@kdeldycke]
  268. Seasoned [@joshuacano] & [@mmyers] & [@tjward]
  269. Secret Escapes [@secretescapes]
  270. Semantics3 [@abishekk92]
  271. Sense360 [@kamilmroczek]
  272. Sentry.io [@tiopi]
  273. ShopBack [@shopback]
  274. Shopkick [@shopkick]
  275. Sidecar [@getsidecar]
  276. SimilarWeb [@similarweb]
  277. Simply Business [@simplybusiness]
  278. Skyscanner [@skyscanner]
  279. SmartNews [@takus]
  280. SnapTravel
  281. SocialCops [@vinayak-mehta & @sharky93]
  282. Société générale [@medmrgh & @s83]
  283. Spotahome [@spotahome]
  284. SpotHero [@benjigoldberg]
  285. Spotify [@znichols]
  286. Square
  287. Stackspace
  288. StoneCo [@lgwacker]
  289. Strava [@strava, @dhuang & @liamstewart]
  290. Stripe [@jbalogh]
  291. Strongmind [@tomchapin & @wongstein]
  292. Surfline [@jawang35]
  293. T2 Systems [@unclaimedpants]
  294. Tails.com [@alanmcruickshank]
  295. TEK [@telac]
  296. Telefonica Innovation Alpha [@Alpha-Health]
  297. Telia Company
  298. Ternary Data [@mhousley, @JoeReis]
  299. Tesla [@thoralf-gutierrez]
  300. The Climate Corporation[@jmelching]
  301. The Home Depot[@apekshithr]
  302. THE ICONIC [@revathijay] [@ilikedata]
  303. Thinking Machines [@marksteve]
  304. Thinknear [@d3cay1, @ccson, & @ababian]
  305. ThoughtWorks [@sann3]
  306. Thumbtack [@kamalacharya, @dwjoss]
  307. Tictail
  308. Tile [@ranjanmanish]
  309. Tinder [@kbendick]
  310. Tink [@tink-ab]
  311. TokenAnalyst [@simonohanlon101, @ankitchiplunkar, @sidshekhar, @sp6pe]
  312. Tokopedia [@topedmaria]
  313. Trocafone [@idontdomath & @gseva & @ordonezf & @PalmaLeandro]
  314. TruFactor [@gholmes & @angadsingh]
  315. Twine Labs [@ivorpeles]
  316. Twitter [@aoen]
  317. Ubisoft [@Walkoss]
  318. Udacity [@dandikunited, @simon-uc]
  319. United Airlines [@ilopezfr]
  320. Upsight
  321. VeeR VR [@pishilong]
  322. Veikkaus [@hixus]
  323. Vente-Exclusive.com [@alexvanboxel]
  324. Vevo [@csetiawan & @jerrygillespie]
  325. Vidio
  326. Ville de Montréal@VilledeMontreal]
  327. Vnomics [@lpalum]
  328. Walmart Labs [@bharathpalaksha, @vipul007ravi]
  329. Waze [@waze]
  330. WePay [@criccomini & @mtagle]
  331. WeTransfer [@coredipper & @higee & @azclub]
  332. Whistle Labs [@ananya77041]
  333. Wildlifestudios
  334. WiseBanyan
  335. Wooga
  336. WorldRemit [@boittega]
  337. Wrike [@eliseealex & teoretic6]
  338. Xero [@yan9yu & adamantnz]
  339. Xoom
  340. Yahoo!
  341. Yieldr [@ggeorgiadis]
  342. Zapier [@drknexus & @statwonk]
  343. Zego [@ruimffl, @james-welly, @ken-payne]
  344. Zendesk
  345. Zenly [@cerisier & @jbdalido]
  346. Zerodha [@johnnybravo-xyz]
  347. Zymergen
  348. Zynga

Who Maintains Apache Airflow?

Airflow is the work of the community, but the core committers/maintainers are responsible for reviewing and merging PRs as well as steering conversation around new feature requests. If you would like to become a maintainer, please review the Apache Airflow committer requirements.

Can I use the Apache Airflow logo in my presentation?

Yes! Be sure to abide by the Apache Foundation trademark policies and the Apache Airflow Brandbook. The most up to date logos are found in this repo and on the Apache Software Foundation website.

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Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

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