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Merge branch 'stable' of https://github.com/Dictionarry-Hub/database into stable
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"_id": "Architecture Overhaul",
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"_id": "Architecture Overhaul",
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"content": "Hey @everyone, here's a small update on what I've been working on lately:\n\nAs the project has grown bigger, it's gotten quite difficult to keep track of and manage a billion different custom formats, quality profiles, etc. To help improve development productivity, I've planned a complete overhaul of Dictionarry's architecture. This starts with separating things into modules - namely a separate database which powers the website and the profilarr tool.\n\nNext up is standardizing the actual entries inside the database. The biggest issue in development right now is making / editing / updating the same thing multiple times. If you have the same regex pattern for multiple CFs, it needs to be updated for each one of them. Quality profiles across different apps have miniscule differences in syntax (eg. web-dl in radarr vs web in sonarr), which means we need multiple files with tiny differences.\n\nWorking in this system is extremely error prone and time consuming. To fix this, I'm creating a standard unique to dictionarry based on a **single definition format**, i.e. Regex patterns, Custom Formats and Quality Profiles are defined once, and repeated in other places using foreign keys. I don't know exactly _how_ this will look, but the plan is simplicity above all. Outside of improving productivity, I hope this standard helps encourage people who feel less confident with custom formats / quality profiles make more intuitive changes to their own setups.\n\nNow, the problem with this new and improved standard is - the arrs won't be able to read the files anymore. Solution: A compiler! This is where the fun begins; we take our simple, easy-to-develop-for files and push them through the compiler. Out pops the required syntax, with those weird naming rules (web-dl for radarr, web for sonarr), without the developer needing to ever worry about it!\n\nHere's a canvas page I made in Obsidian which visualizes this architecture:\n\n\n\n# Profile Selector\n\nHere's an updated look at the new profile selector (WIP) in action. I'll leave explaining the selection algorithm for another day (because I'm still not quite happy with it), but I think it's still pretty cool to look at as is.\n\n",
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"content": "Hey @everyone, here's a small update on what I've been working on lately:\n\nAs the project has grown bigger, it's gotten quite difficult to keep track of and manage a billion different custom formats, quality profiles, etc. To help improve development productivity, I've planned a complete overhaul of Dictionarry's architecture. This starts with separating things into modules - namely a separate database which powers the website and the profilarr tool.\n\nNext up is standardizing the actual entries inside the database. The biggest issue in development right now is making / editing / updating the same thing multiple times. If you have the same regex pattern for multiple CFs, it needs to be updated for each one of them. Quality profiles across different apps have miniscule differences in syntax (eg. web-dl in radarr vs web in sonarr), which means we need multiple files with tiny differences.\n\nWorking in this system is extremely error prone and time consuming. To fix this, I'm creating a standard unique to dictionarry based on a **single definition format**, i.e. Regex patterns, Custom Formats and Quality Profiles are defined once, and repeated in other places using foreign keys. I don't know exactly _how_ this will look, but the plan is simplicity above all. Outside of improving productivity, I hope this standard helps encourage people who feel less confident with custom formats / quality profiles make more intuitive changes to their own setups.\n\nNow, the problem with this new and improved standard is - the arrs won't be able to read the files anymore. Solution: A compiler! This is where the fun begins; we take our simple, easy-to-develop-for files and push them through the compiler. Out pops the required syntax, with those weird naming rules (web-dl for radarr, web for sonarr), without the developer needing to ever worry about it!\n\nHere's a canvas page I made in Obsidian which visualizes this architecture:\n\n\n\n# Profile Selector\n\nHere's an updated look at the new profile selector (WIP) in action. I'll leave explaining the selection algorithm for another day (because I'm still not quite happy with it), but I think it's still pretty cool to look at as is.\n\n",
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"last_modified": "2025-03-01T10:02:33.288408+00:00",
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"last_modified": "2025-03-07T15:06:31.709032+00:00",
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"title": "Architecture Overhaul",
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"title": "Architecture Overhaul",
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"slug": "architecture_overhaul",
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"slug": "architecture_overhaul",
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"author": "santiagosayshey",
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"author": "santiagosayshey",
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@@ -15,7 +15,7 @@
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"_id": "Modular Choices",
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"_id": "Modular Choices",
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"content": "Hey @everyone, here's a small (but very important) post on the new update system!\n\n## Current Profilarr\n\nCurrently, there is 0 support for updates in Profilarr. This is obviously not ideal; it's a nightmare to keep up to date with changes and almost certainly breaks any custom changes you make.\n\n## Profilarr v1\n\nUsers will be able to view incoming and outgoing changes, as well as resolve any conflicts between the two. To achieve this, a user friendly GUI has been built on top of Git's merge functionality and allows fine control over what should be merged / ignored. More specifically, this functionality allows us to make custom changes and choose to retain them once a new update comes around.\n\n- As an example, let's say you've made the Dolby Vision custom formats negative because your TV doesn't support it. A new update has come out which shuffles around HDR scores, and this leads to a merge conflict between the two custom format scores.\n- In the settings page, you can choose to accept the incoming change or retain your local changes. Profilarr will 'remember' your choice and stop prompting you to update this custom format until a new update comes out, in which case, the situation repeats. Keep local or accept incoming.\n\n### Settings Page\n\nProfilarr now includes a dedicated page for 'Sync Settings'. It allows you to link / unlink a database repository, view and change branches as well as deal with incoming / outgoing changes and their conflicts. This page has been planned for developers too; you can add an authenticated github dev token to your environment and you have the ability to make changes directly to Profilarr's database (not to stable, obviously).\n\n# Beta Release\n\n- Still not quite ready yet, but I'm working hard to get it out! Stay tuned :hearts:\n\nHere's a screenshot of this new Conflict Resolver in action (Ignore the date modified row, it will be removed for actual use)\n\n",
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"content": "Hey @everyone, here's a small (but very important) post on the new update system!\n\n## Current Profilarr\n\nCurrently, there is 0 support for updates in Profilarr. This is obviously not ideal; it's a nightmare to keep up to date with changes and almost certainly breaks any custom changes you make.\n\n## Profilarr v1\n\nUsers will be able to view incoming and outgoing changes, as well as resolve any conflicts between the two. To achieve this, a user friendly GUI has been built on top of Git's merge functionality and allows fine control over what should be merged / ignored. More specifically, this functionality allows us to make custom changes and choose to retain them once a new update comes around.\n\n- As an example, let's say you've made the Dolby Vision custom formats negative because your TV doesn't support it. A new update has come out which shuffles around HDR scores, and this leads to a merge conflict between the two custom format scores.\n- In the settings page, you can choose to accept the incoming change or retain your local changes. Profilarr will 'remember' your choice and stop prompting you to update this custom format until a new update comes out, in which case, the situation repeats. Keep local or accept incoming.\n\n### Settings Page\n\nProfilarr now includes a dedicated page for 'Sync Settings'. It allows you to link / unlink a database repository, view and change branches as well as deal with incoming / outgoing changes and their conflicts. This page has been planned for developers too; you can add an authenticated github dev token to your environment and you have the ability to make changes directly to Profilarr's database (not to stable, obviously).\n\n# Beta Release\n\n- Still not quite ready yet, but I'm working hard to get it out! Stay tuned :hearts:\n\nHere's a screenshot of this new Conflict Resolver in action (Ignore the date modified row, it will be removed for actual use)\n\n",
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"last_modified": "2025-03-01T10:02:33.288408+00:00",
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"last_modified": "2025-03-07T15:06:31.709032+00:00",
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"title": "Modular Choices",
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"title": "Modular Choices",
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"slug": "modular_choices",
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"slug": "modular_choices",
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"author": "santiagosayshey",
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"author": "santiagosayshey",
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"_id": "Profile Selector v3",
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"_id": "Profile Selector v3",
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"content": "hey @everyone , thought I'd make a channel to share some development logs.\n\nI've been feeling pretty inspired code wise the past few days, so I've actually made some progress despite saying I would take a break...\n\nAnyways, after designing Profile Selector v3 in Figma for the past couple months, I started work on actually implementing it. Let me tell you that drawing shapes is much, much easier than coding them. After a couple days of regretting not paying attention in high school trigonometry, I have the basic functionality in place! We have three data points which represent each of the requirements - quality, efficiency, compatibility. The user can select points on each of the axes, and each combination is used to recommend a profile. It's not hooked up to the database yet, so random strings are being used as a placeholder.\n\nThe good thing about this design is that it's really modular. Once I finish the 'beginner' version of it, I'll be able to add an advanced mode which can be used to select any kind of requirement. Resolution, HDR, Audio, etc.\n\nHere's how it looks right now (obvious disclaimer that final version will look much much better):\n\n\n\nHere's a funny tidbit from development:\n\nI tried writing some animation styling to make the inner polygon look like its stretching (as opposed to instant, static movement). It didn't quite work..\n\nBehold: Frankenstein's Triangle.\n\n",
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"content": "hey @everyone , thought I'd make a channel to share some development logs.\n\nI've been feeling pretty inspired code wise the past few days, so I've actually made some progress despite saying I would take a break...\n\nAnyways, after designing Profile Selector v3 in Figma for the past couple months, I started work on actually implementing it. Let me tell you that drawing shapes is much, much easier than coding them. After a couple days of regretting not paying attention in high school trigonometry, I have the basic functionality in place! We have three data points which represent each of the requirements - quality, efficiency, compatibility. The user can select points on each of the axes, and each combination is used to recommend a profile. It's not hooked up to the database yet, so random strings are being used as a placeholder.\n\nThe good thing about this design is that it's really modular. Once I finish the 'beginner' version of it, I'll be able to add an advanced mode which can be used to select any kind of requirement. Resolution, HDR, Audio, etc.\n\nHere's how it looks right now (obvious disclaimer that final version will look much much better):\n\n\n\nHere's a funny tidbit from development:\n\nI tried writing some animation styling to make the inner polygon look like its stretching (as opposed to instant, static movement). It didn't quite work..\n\nBehold: Frankenstein's Triangle.\n\n",
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"last_modified": "2025-03-01T10:02:33.288408+00:00",
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"last_modified": "2025-03-07T15:06:31.709032+00:00",
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"title": "Profile Selector v3",
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"title": "Profile Selector v3",
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"slug": "profile_selector_v3",
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"slug": "profile_selector_v3",
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"author": "santiagosayshey",
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"author": "santiagosayshey",
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"_id": "Profile Tweaks",
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"_id": "Profile Tweaks",
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"content": "Hey @everyone, I've been hard at work on the next Profilarr version over the past few weeks and have new stuff to show off!\n\nThe profiles we make are meant to be (really good) starting points, not a strict standard on what you _should_ be grabbing. Up until now, profiles existed as singular entities that don't respect custom changes. Merge conflict resolution was a big step in the right direction for this (read more in the last dev log), but it's a bit more hands on, and not something I expect most people to engage with.\n\nEnter 'Profile Tweaks'. These are simple check boxes you can enable / disable and are unique to YOUR profiles. They will ALWAYS be respected, regardless of what updates we make to the base profile. For now, these tweaks include:\n\n- Prefer Freeleech\n- Allow Prereleases (CAMS, Screeners, etc)\n- Language Strictness\n- Allow Lossless audio\n- Allow Dolby Vision without Fallback\n- Allow bleeding edge codecs (AV-1, H266)\n\n(Some are only available for specific profiles, eg lossless audio for 1080p Encode profiles).\n\nIf anyone has any tweak ideas (even super specific ones), please let me know and I'll work on getting it integrated! Here's an image of the Tweaks Tab:\n\n## Profilarr Progress\n\n- Progress is steady, I've been working on it every day since my semester ended. It's taken way, way longer than I've expected (sorry!) but I'm happy with how it's starting to look.\n- Git integration is complete and working, but needs lots of testing.\n- Data modules (custom formats, regex patterns, quality profiles) are complete and fully implement the existing logic from Radarr / Sonarr.\n- I am currently in the progress of porting existing data to the new database (https://github.com/Dictionarry-Hub/database/tree/stable) in the new profilarr standard format. This is going to take a while, as I have to write descriptions, add tags, test cases, etc.\n- Finally, I am starting to work on the compilation engine (https://discord.com/channels/1202375791556431892/1246504849265266738/1272756617041154049) and the import module. Once these things are complete, and I'm confident we won't run into massive bugs, I'll release a beta docker image. ETA? I really don't know, but I'm working as hard as I can.\n\nIf anyone has any tweak ideas (even super specific ones), please let me know and I'll work on getting it integrated! Here's an image of the Tweaks Tab:\n\n",
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"content": "Hey @everyone, I've been hard at work on the next Profilarr version over the past few weeks and have new stuff to show off!\n\nThe profiles we make are meant to be (really good) starting points, not a strict standard on what you _should_ be grabbing. Up until now, profiles existed as singular entities that don't respect custom changes. Merge conflict resolution was a big step in the right direction for this (read more in the last dev log), but it's a bit more hands on, and not something I expect most people to engage with.\n\nEnter 'Profile Tweaks'. These are simple check boxes you can enable / disable and are unique to YOUR profiles. They will ALWAYS be respected, regardless of what updates we make to the base profile. For now, these tweaks include:\n\n- Prefer Freeleech\n- Allow Prereleases (CAMS, Screeners, etc)\n- Language Strictness\n- Allow Lossless audio\n- Allow Dolby Vision without Fallback\n- Allow bleeding edge codecs (AV-1, H266)\n\n(Some are only available for specific profiles, eg lossless audio for 1080p Encode profiles).\n\nIf anyone has any tweak ideas (even super specific ones), please let me know and I'll work on getting it integrated! Here's an image of the Tweaks Tab:\n\n## Profilarr Progress\n\n- Progress is steady, I've been working on it every day since my semester ended. It's taken way, way longer than I've expected (sorry!) but I'm happy with how it's starting to look.\n- Git integration is complete and working, but needs lots of testing.\n- Data modules (custom formats, regex patterns, quality profiles) are complete and fully implement the existing logic from Radarr / Sonarr.\n- I am currently in the progress of porting existing data to the new database (https://github.com/Dictionarry-Hub/database/tree/stable) in the new profilarr standard format. This is going to take a while, as I have to write descriptions, add tags, test cases, etc.\n- Finally, I am starting to work on the compilation engine (https://discord.com/channels/1202375791556431892/1246504849265266738/1272756617041154049) and the import module. Once these things are complete, and I'm confident we won't run into massive bugs, I'll release a beta docker image. ETA? I really don't know, but I'm working as hard as I can.\n\nIf anyone has any tweak ideas (even super specific ones), please let me know and I'll work on getting it integrated! Here's an image of the Tweaks Tab:\n\n",
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"last_modified": "2025-03-01T10:02:33.288408+00:00",
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"last_modified": "2025-03-07T15:06:31.709032+00:00",
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"title": "Profile Tweaks",
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"title": "Profile Tweaks",
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"slug": "profile_tweaks",
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"slug": "profile_tweaks",
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"author": "santiagosayshey",
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"_id": "Shiny New Stuff",
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"content": "hey @everyone, hope you guys are well. Here's another update!\n\n# Motivation\n\nI've been really struggling to work on this project for a few months now - I'll finally get some time at the end of the week but feel completely unmotivated to work on it for more than an hour. Well... after cracking the architecture problem last week and seeing all the support from you guys, I've felt especially motivated to dive back in.\n\n# Profilarr v2 (not really v2 but it sounded cool)\n\nProfilarr is getting some really nice upgrades. Here's an outline of the most important ones:\n\n## It's now a full stack application.\n\nThis means we have a frontend: a site that users can visit to adjust, import, and export regexes, custom formats, and quality profiles. It's built in a way that aims to 'remaster' how it's implemented in Radarr/Sonarr. All the existing functionality is there, but with some really nice quality of life features:\n\n- **Single definition format**: As outlined in the previous dev log, Profilarr's version of this system will use a single definition format. Notably, this allows you to set regex patterns ONCE, then add that regex as a condition inside a custom format.\n- **Sorting and Filtering**: You can now sort and filter items by title, date modified, etc.\n- **Exporting/Importing**: The standard format now allows _everyone_ to import/export regexes, custom formats, and quality profiles freely - no need to query APIs to do this anymore.\n- **Syncing**: Instead of clogging up everyone's arrs with unused custom formats, the sync functionality now only imports _used_ items.\n- **Mass selection**: You can mass select items to import/export/sync/delete.\n- **Tags**: Instead of manual selection, you can set tags on specific custom formats/quality profiles that should be synced. This works similar to how Prowlarr uses tags to selectively sync indexers. Since we are also using the same database for the website, tags can also be used for little tidbits of information too. Like where a release group is an internal at!\n- **Testing**: Developers can now permalink regexes to regex101. This makes it really easy to develop and test simultaneously.\n- **Descriptions**: You can now explain what specific items are for. No need to look it up on the website to see what it does.\n\n## Backend Improvements\n\nThe backend is essentially what Profilarr is right now - a tool to sync some JSON files to your arrs. However, this also has some major improvements:\n\n- **Git integration**: You can select a remote repository to connect to and:\n - Add, commit, and push files; branch off; merge into. This isn't that useful for end users, but I cannot stress enough how much time and suffering this has saved me. Being able to revert regex/custom format/quality profiles to the last commit is my favorite thing I've ever coded.\n - **Branching**: You can have different branches for different things. Of course, this is useful for development, but it also allows you to do things like: separate setups for Radarr/Sonarr/Lidarr. Most importantly, it allows us developers to set stable, dev, and feature branches.\n - **Pulling**: You can now pull in changes from specific branches from a remote repository. You can view differences and decide if you want to pull these changes in. You can set it to be automatic and only alert on merge conflicts (you change something, but an incoming change for that item exists as well). You can choose to get the most stable branch or the latest features merged into develop.\n - **External sources**: You can set your own repo of regexes, custom formats, and quality profiles and share it with whoever you want. As I mentioned in my last dev log, I'll be working on a compiler to convert our standard Profilarr format with the existing arr format. The really cool thing about this is it works both ways. This means the git integration + compiler will allow you to use Profilarr with the trash guides. It'll probably take some tweaking, but I know it's definitely possible now.\n\n## Containerisation\n\nProfilarr will FINALLY be dockerised.\n\n# Development\n\nWith these changes in place, it has massively improved and sped up development. Working in a proprietary tool now allows me the freedom to just implement a feature whenever I want to. Want to filter custom formats with the release tier tag? Boom, implemented. Want to auto-apply scores to custom formats in quality profiles based on tags? Boom, implemented.\n\n## Machine Learning\n\nThis part is mostly speculation and rambling - nothing concrete yet. I really want to incorporate some kind of AI help into Profilarr. A button you can press to auto-generate regex or a custom format. I've read countless Reddit posts of someone unfamiliar with regex/custom formats/profiles asking for help in trying to learn. \"How do I write a custom format that matches x265 releases under size x?\" It's so easily solved using AI.\n\nI want to implement this one day, I just Line truncated
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"content": "hey @everyone, hope you guys are well. Here's another update!\n\n# Motivation\n\nI've been really struggling to work on this project for a few months now - I'll finally get some time at the end of the week but feel completely unmotivated to work on it for more than an hour. Well... after cracking the architecture problem last week and seeing all the support from you guys, I've felt especially motivated to dive back in.\n\n# Profilarr v2 (not really v2 but it sounded cool)\n\nProfilarr is getting some really nice upgrades. Here's an outline of the most important ones:\n\n## It's now a full stack application.\n\nThis means we have a frontend: a site that users can visit to adjust, import, and export regexes, custom formats, and quality profiles. It's built in a way that aims to 'remaster' how it's implemented in Radarr/Sonarr. All the existing functionality is there, but with some really nice quality of life features:\n\n- **Single definition format**: As outlined in the previous dev log, Profilarr's version of this system will use a single definition format. Notably, this allows you to set regex patterns ONCE, then add that regex as a condition inside a custom format.\n- **Sorting and Filtering**: You can now sort and filter items by title, date modified, etc.\n- **Exporting/Importing**: The standard format now allows _everyone_ to import/export regexes, custom formats, and quality profiles freely - no need to query APIs to do this anymore.\n- **Syncing**: Instead of clogging up everyone's arrs with unused custom formats, the sync functionality now only imports _used_ items.\n- **Mass selection**: You can mass select items to import/export/sync/delete.\n- **Tags**: Instead of manual selection, you can set tags on specific custom formats/quality profiles that should be synced. This works similar to how Prowlarr uses tags to selectively sync indexers. Since we are also using the same database for the website, tags can also be used for little tidbits of information too. Like where a release group is an internal at!\n- **Testing**: Developers can now permalink regexes to regex101. This makes it really easy to develop and test simultaneously.\n- **Descriptions**: You can now explain what specific items are for. No need to look it up on the website to see what it does.\n\n## Backend Improvements\n\nThe backend is essentially what Profilarr is right now - a tool to sync some JSON files to your arrs. However, this also has some major improvements:\n\n- **Git integration**: You can select a remote repository to connect to and:\n - Add, commit, and push files; branch off; merge into. This isn't that useful for end users, but I cannot stress enough how much time and suffering this has saved me. Being able to revert regex/custom format/quality profiles to the last commit is my favorite thing I've ever coded.\n - **Branching**: You can have different branches for different things. Of course, this is useful for development, but it also allows you to do things like: separate setups for Radarr/Sonarr/Lidarr. Most importantly, it allows us developers to set stable, dev, and feature branches.\n - **Pulling**: You can now pull in changes from specific branches from a remote repository. You can view differences and decide if you want to pull these changes in. You can set it to be automatic and only alert on merge conflicts (you change something, but an incoming change for that item exists as well). You can choose to get the most stable branch or the latest features merged into develop.\n - **External sources**: You can set your own repo of regexes, custom formats, and quality profiles and share it with whoever you want. As I mentioned in my last dev log, I'll be working on a compiler to convert our standard Profilarr format with the existing arr format. The really cool thing about this is it works both ways. This means the git integration + compiler will allow you to use Profilarr with the trash guides. It'll probably take some tweaking, but I know it's definitely possible now.\n\n## Containerisation\n\nProfilarr will FINALLY be dockerised.\n\n# Development\n\nWith these changes in place, it has massively improved and sped up development. Working in a proprietary tool now allows me the freedom to just implement a feature whenever I want to. Want to filter custom formats with the release tier tag? Boom, implemented. Want to auto-apply scores to custom formats in quality profiles based on tags? Boom, implemented.\n\n## Machine Learning\n\nThis part is mostly speculation and rambling - nothing concrete yet. I really want to incorporate some kind of AI help into Profilarr. A button you can press to auto-generate regex or a custom format. I've read countless Reddit posts of someone unfamiliar with regex/custom formats/profiles asking for help in trying to learn. \"How do I write a custom format that matches x265 releases under size x?\" It's so easily solved using AI.\n\nI want to implement this one day, I just Line truncated
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"last_modified": "2025-03-01T10:02:33.288408+00:00",
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"last_modified": "2025-03-07T15:06:31.710032+00:00",
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"title": "Shiny New Stuff",
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"title": "Shiny New Stuff",
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"slug": "shiny_new_stuff",
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"author": "santiagosayshey",
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"_id": "Vision Almost Realised",
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"_id": "Vision Almost Realised",
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"content": "Hey @everyone, small log for today!\n\n```bash\n$ python profile_compile.py 'profiles/1080p Encode.yml' '1080p Encode (sonarr - master).json' -s\nConverted profile saved to: 1080p Encode (sonarr - master).json\n\n$ python importarr.py\nImporting Quality Profiles to sonarr : Master\nUpdating '1080p Encode' quality profile : SUCCESS\n```\n\nThese two commands are the culmination of the architecture overhaul I talked about in August: https://discord.com/channels/1202375791556431892/1246504849265266738/1272756617041154049. The Profilarr standard format _**works**_. A typical profile is now about 300 lines (down from 1000 each for radarr / sonarr), is able to be compiled from PSF to Radarr OR Sonarr (and back!). Regex patterns allow format resolution, so no more editing the same thing 5, 10... 20 times.\n\nI'm currently in the process of hooking up the database to the new website, and that's looking pretty cool too. I cannot even explain how good it feels to be able to edit a profile once inside Profilarr, push those changes directly from Profilarr, have those changes reflected as incoming changes for end users, and as updated information on the website all in one fell swoop.\n\nIt's taken a huge effort the past 4 months, and I still have to actually connect it to the backend, but I'm fairly happy with how it's turned out. The changes won't be all that evident right away for you guys, but it's going to save me (and anyone who wants to contribute) hours upon hours of development time for everything that I have planned.\n\n## Golden Popcorn Performance Index Changes\n\nThe current GPPi algorithm is strong, but fundamentally flawed. It does not take into consideration release groups who have no data. There are terrific new groups (ZoroSenpai for example) who should be tier ~2 at least, but aren't simply because they have no data. How do we fix this?\n\n### Popularity\n\nFor every encode at a specific resolution for a movie / tv show that is currently _popular_, a release group receives +1 score to their GPPi. At the end of every month, the score is reset, and the previous score is normalized (tbd on how) and added to their permanent GPPi score (up to a certain point and probably never past tier ~3)\n\nThis process will be completely automatic and will hopefully solve the problem of new good release groups.\n\n### Grouping\n\nThe previous 'tiers' for release groups was just natural intuitive grouping. Humans are surprisingly very, very good at pattern recognition so it was never really a problem. However, it was manual, and we dont like manual around here. Enter 'K Means Clustering'. Essentially it's just a fancy algorithm that finds natural break points between groups of numbers. Using K means, I've dropped the number of 1080p Tiers from 7 down to 5 which in turn has increased immutability. Small changes, but will be important in the long run.\n\n## Thank You!\n\nThat's all for today, I hope everyone's doing alright and enjoying the holidays :grinning:",
|
"content": "Hey @everyone, small log for today!\n\n```bash\n$ python profile_compile.py 'profiles/1080p Encode.yml' '1080p Encode (sonarr - master).json' -s\nConverted profile saved to: 1080p Encode (sonarr - master).json\n\n$ python importarr.py\nImporting Quality Profiles to sonarr : Master\nUpdating '1080p Encode' quality profile : SUCCESS\n```\n\nThese two commands are the culmination of the architecture overhaul I talked about in August: https://discord.com/channels/1202375791556431892/1246504849265266738/1272756617041154049. The Profilarr standard format _**works**_. A typical profile is now about 300 lines (down from 1000 each for radarr / sonarr), is able to be compiled from PSF to Radarr OR Sonarr (and back!). Regex patterns allow format resolution, so no more editing the same thing 5, 10... 20 times.\n\nI'm currently in the process of hooking up the database to the new website, and that's looking pretty cool too. I cannot even explain how good it feels to be able to edit a profile once inside Profilarr, push those changes directly from Profilarr, have those changes reflected as incoming changes for end users, and as updated information on the website all in one fell swoop.\n\nIt's taken a huge effort the past 4 months, and I still have to actually connect it to the backend, but I'm fairly happy with how it's turned out. The changes won't be all that evident right away for you guys, but it's going to save me (and anyone who wants to contribute) hours upon hours of development time for everything that I have planned.\n\n## Golden Popcorn Performance Index Changes\n\nThe current GPPi algorithm is strong, but fundamentally flawed. It does not take into consideration release groups who have no data. There are terrific new groups (ZoroSenpai for example) who should be tier ~2 at least, but aren't simply because they have no data. How do we fix this?\n\n### Popularity\n\nFor every encode at a specific resolution for a movie / tv show that is currently _popular_, a release group receives +1 score to their GPPi. At the end of every month, the score is reset, and the previous score is normalized (tbd on how) and added to their permanent GPPi score (up to a certain point and probably never past tier ~3)\n\nThis process will be completely automatic and will hopefully solve the problem of new good release groups.\n\n### Grouping\n\nThe previous 'tiers' for release groups was just natural intuitive grouping. Humans are surprisingly very, very good at pattern recognition so it was never really a problem. However, it was manual, and we dont like manual around here. Enter 'K Means Clustering'. Essentially it's just a fancy algorithm that finds natural break points between groups of numbers. Using K means, I've dropped the number of 1080p Tiers from 7 down to 5 which in turn has increased immutability. Small changes, but will be important in the long run.\n\n## Thank You!\n\nThat's all for today, I hope everyone's doing alright and enjoying the holidays :grinning:",
|
||||||
"last_modified": "2025-03-01T10:02:33.288408+00:00",
|
"last_modified": "2025-03-07T15:06:31.710032+00:00",
|
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"title": "Vision (Almost) Realised",
|
"title": "Vision (Almost) Realised",
|
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"slug": "vision_almost_realised",
|
"slug": "vision_almost_realised",
|
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"author": "santiagosayshey",
|
"author": "santiagosayshey",
|
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@@ -84,7 +84,7 @@
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{
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{
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"_id": "Website 2.0",
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"_id": "Website 2.0",
|
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"content": "Hey everyone, medium-ish update today.\n\n## Website 2.0\n\nI've wanted to transition away from the old site / mkdocs for a while now as its quite hard to maintain and keep everything up to date, so I built a new site using Next.js that uses ISR to rebuild its content using the dictionarry database. Basically this just means:\n\n- Database gets an update -> Website sees its data is stale -> Website rebuilds itself with new data -> Santiago smiles in not needing to do anything\n\nThis all ties into the whole \"write once\" philosophy that I instilled with Profilarr and has made development much easier. There are still quite a few layout issues and perhaps a devlog refactor I need to fit in somewhere, but I'm happy to share it with you guys as it is.\n\n[Website 2.0](https://dictionarry.dev/)\n\n\n\nThe old site will go down soon, sorry if I broke anyone's workflows D:\n\n### Profile Selector?\n\nThis idea has gone through many iterations since i started Dictionarry last year.\n\n1. A static flowchart with not nearly enough information / choice: https://github.com/santiagosayshey/website/blob/030f3631b4f6fffdb7fa9f4696e5d12defc84a46/docs/Profiles/flowchart.png\n2. The \"Profile Selector\" (terrible name): https://selectarr.pages.dev/\n3. Frankenstein's triangle: [Discord Link](https://discord.com/channels/1202375791556431892/1246504849265266738/1246536424925171925)\n\nFrankenstein's triangle was supposed to be what i shipped with the new website (and I actually finished it too!). It worked by calculating the area of the efficiency/quality/compatibility triangle using some formula named after some guy i forget, to guesstimate user choice based on their previous selection. It did this by normalizing the \"score\" of each profile on each of it's axes and finding the best fitting triangle that used the axis that was changed.\n\nResults were pretty good but I felt that it abstracted _too much_ of what made any user choice meaningful so I decided to scrap it.\n\n### Profile Builder!\n\nIn it's place is the \"Profile Builder\" (maybe also a terrible name). It still attempts to abstract audio/video down into more quantifiable groupings, but limits itself to explanations of certain things where more abstraction is detrimental. It's pretty self explanatory once you use it, but basically you choose through increasingly niche groupings -> resolution -> compression -> encode type -> codec -> HDR. At each step, a list of recommended profiles will be shown. I think this new system helps to fix the \"trying to get the profile I want\" issue as it starts pretty broad and gets increasingly more specific the more things you choose. It's up now, give it a playwith; let me know if its good / bad / needs changes: [Profile Buider](https://dictionarry.dev/builder)\n\n\n\n## Encode Efficiency Index\n\nHere we go, meat and potatoes. This is another release group metric just like the Golden Popcorn Performance Index. Heres's the play-by-play:\n\n- It evaluates release groups on their average compression ratio (how big their encode is compared to a source), to discern quality and/or efficiency.\n- It can discern transparency by targeting ratios at which a codec begins to \"saturate\"\n- It can discern efficiency by targeting ratios at which a codec reaches it's \"efficiency apex\"\n\nThis is a heavily watered down explanation of the metric, you can read about it (with examples), in very heavy detail [here](https://dictionarry.dev/wiki/EEi). Months of research and iteration has gone into this, and I really think this is Dictionarry's biggest asset so far. When AV1 profiles become a thing, this metric is ready for it.\n\n#### No More Parsing Codecs!!!!\n\nIf you parse the efficiency of a release group directly, then you know youre getting something at a file size you want. This means we don't have to use h265 / x265 as a ridiculous proxy baseline to find content we want anymore. We can just downrank all h264 instead which is much more reliable\n\n#### 2160p Quality (Encode) Profile + Release Group Tierlist!!!!!!!!\n\nUsing EEI, we target 4k release groups at 55% target ratio to discern transparency. No golden popcorns needed, no complex trump parsing crap. No \"popular\" vote. Whenever something isn't documented, we simply add that movie / tv show to the data source and groupings update automatically. It's almost like magic.\n\nThis metric has made the 2160p Quality profile possible and i dare say it's the most comprehensive one I've worked on thus far. Give the quality profile and tier lists a read here:\n\n- [216p Quality Profile](https://dictionarry.dev/profiles/2160p-quality)\n- [2160p Quality Release Group Tiers](https://dictionarry.dev/tiers/2160p/quality)\n\n#### Thanks\n\n- Thanks to @seraphys for helping out with the profile creation / giving constant feedback.\n- Thanks to @erphise for being a tester / the catalyst fLine truncated
|
"content": "Hey everyone, medium-ish update today.\n\n## Website 2.0\n\nI've wanted to transition away from the old site / mkdocs for a while now as its quite hard to maintain and keep everything up to date, so I built a new site using Next.js that uses ISR to rebuild its content using the dictionarry database. Basically this just means:\n\n- Database gets an update -> Website sees its data is stale -> Website rebuilds itself with new data -> Santiago smiles in not needing to do anything\n\nThis all ties into the whole \"write once\" philosophy that I instilled with Profilarr and has made development much easier. There are still quite a few layout issues and perhaps a devlog refactor I need to fit in somewhere, but I'm happy to share it with you guys as it is.\n\n[Website 2.0](https://dictionarry.dev/)\n\n\n\nThe old site will go down soon, sorry if I broke anyone's workflows D:\n\n### Profile Selector?\n\nThis idea has gone through many iterations since i started Dictionarry last year.\n\n1. A static flowchart with not nearly enough information / choice: https://github.com/santiagosayshey/website/blob/030f3631b4f6fffdb7fa9f4696e5d12defc84a46/docs/Profiles/flowchart.png\n2. The \"Profile Selector\" (terrible name): https://selectarr.pages.dev/\n3. Frankenstein's triangle: [Discord Link](https://discord.com/channels/1202375791556431892/1246504849265266738/1246536424925171925)\n\nFrankenstein's triangle was supposed to be what i shipped with the new website (and I actually finished it too!). It worked by calculating the area of the efficiency/quality/compatibility triangle using some formula named after some guy i forget, to guesstimate user choice based on their previous selection. It did this by normalizing the \"score\" of each profile on each of it's axes and finding the best fitting triangle that used the axis that was changed.\n\nResults were pretty good but I felt that it abstracted _too much_ of what made any user choice meaningful so I decided to scrap it.\n\n### Profile Builder!\n\nIn it's place is the \"Profile Builder\" (maybe also a terrible name). It still attempts to abstract audio/video down into more quantifiable groupings, but limits itself to explanations of certain things where more abstraction is detrimental. It's pretty self explanatory once you use it, but basically you choose through increasingly niche groupings -> resolution -> compression -> encode type -> codec -> HDR. At each step, a list of recommended profiles will be shown. I think this new system helps to fix the \"trying to get the profile I want\" issue as it starts pretty broad and gets increasingly more specific the more things you choose. It's up now, give it a playwith; let me know if its good / bad / needs changes: [Profile Buider](https://dictionarry.dev/builder)\n\n\n\n## Encode Efficiency Index\n\nHere we go, meat and potatoes. This is another release group metric just like the Golden Popcorn Performance Index. Heres's the play-by-play:\n\n- It evaluates release groups on their average compression ratio (how big their encode is compared to a source), to discern quality and/or efficiency.\n- It can discern transparency by targeting ratios at which a codec begins to \"saturate\"\n- It can discern efficiency by targeting ratios at which a codec reaches it's \"efficiency apex\"\n\nThis is a heavily watered down explanation of the metric, you can read about it (with examples), in very heavy detail [here](https://dictionarry.dev/wiki/EEi). Months of research and iteration has gone into this, and I really think this is Dictionarry's biggest asset so far. When AV1 profiles become a thing, this metric is ready for it.\n\n#### No More Parsing Codecs!!!!\n\nIf you parse the efficiency of a release group directly, then you know youre getting something at a file size you want. This means we don't have to use h265 / x265 as a ridiculous proxy baseline to find content we want anymore. We can just downrank all h264 instead which is much more reliable\n\n#### 2160p Quality (Encode) Profile + Release Group Tierlist!!!!!!!!\n\nUsing EEI, we target 4k release groups at 55% target ratio to discern transparency. No golden popcorns needed, no complex trump parsing crap. No \"popular\" vote. Whenever something isn't documented, we simply add that movie / tv show to the data source and groupings update automatically. It's almost like magic.\n\nThis metric has made the 2160p Quality profile possible and i dare say it's the most comprehensive one I've worked on thus far. Give the quality profile and tier lists a read here:\n\n- [216p Quality Profile](https://dictionarry.dev/profiles/2160p-quality)\n- [2160p Quality Release Group Tiers](https://dictionarry.dev/tiers/2160p/quality)\n\n#### Thanks\n\n- Thanks to @seraphys for helping out with the profile creation / giving constant feedback.\n- Thanks to @erphise for being a tester / the catalyst fLine truncated
|
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"last_modified": "2025-03-01T10:02:33.288408+00:00",
|
"last_modified": "2025-03-07T15:06:31.710032+00:00",
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"title": "Website 2.0",
|
"title": "Website 2.0",
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"slug": "website2.0",
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"slug": "website2.0",
|
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"author": "santiagosayshey",
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"author": "santiagosayshey",
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@@ -651,7 +651,7 @@
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"Lossy Audio",
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"Lossy Audio",
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"Quality Focused"
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"Quality Focused"
|
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],
|
],
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"upgradesAllowed": false,
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"upgradesAllowed": true,
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"minCustomFormatScore": 0,
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"minCustomFormatScore": 0,
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"upgradeUntilScore": 320,
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"upgradeUntilScore": 320,
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"minScoreIncrement": 10,
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"minScoreIncrement": 10,
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@@ -1,5 +1,5 @@
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{
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{
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"updated_at": "2025-03-01T10:02:35.684434+00:00",
|
"updated_at": "2025-03-07T15:06:34.037680+00:00",
|
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"folders": [
|
"folders": [
|
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"custom_formats",
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"custom_formats",
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"profiles",
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"profiles",
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+7
-7
@@ -2,7 +2,7 @@
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{
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{
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"_id": "EEi",
|
"_id": "EEi",
|
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"content": "This metric is aimed at identifying and ranking release groups based on their propensity to release **encodes that meet certain compression ratios**, with particular focus on **HEVC** releases where optimal efficiency occurs in specific bitrate ranges. By ranking these groups, we effectively prioritize releases that maximize HEVC's compression capabilities while maintaining quality at minimal file sizes.\n\n## What is a Compression Ratio?\n\nA compression ratio is a (made up) metric that evaluates encodes against their sources. We express this as the **encoded file size as a percentage of its source size** (typically a **remux** or **WEB-DL**).\n\nFor example:\n\n| Movie | Source (Remux) | Encode | Compression Ratio |\n| ------- | -------------- | ------ | ----------------- |\n| Movie A | 40 GB | 10 GB | 25% |\n| Movie B | 30 GB | 6 GB | 20% |\n| Movie C | 50 GB | 15 GB | 30% |\n\n## Why Is This Important?\n\nUnderstanding compression ratios helps balance two competing needs: **maintaining high video quality while minimizing file size**. Modern codecs like **HEVC** have a **\"sweet spot\"** where they deliver excellent quality with significant size savings. Finding this optimal point is crucial because:\n\n- Storage and bandwidth are always **limited resources**\n- Going beyond certain bitrates provides **diminishing quality returns**\n- Different codecs have different **efficiency curves**\n- Release groups need clear standards for **quality vs. size trade-offs**\n\n## What Ratio is Best?\n\nThere's no one-size-fits-all answer when it comes to choosing the perfect compression ratio. The \"best\" ratio **depends entirely on your specific needs**. At 1080p:\n\n- Space-conscious users might prefer **smaller files (5-10% of source)** with quality trade-offs\n- Quality-focused users might push towards **higher quality (30-40% of source)** for transparency\n- Most users find a sweet spot in the middle\n\nHowever, there are technical limits - files larger than **40% for 1080p** and **60% for 2160p** provide no meaningful benefits.\n\n## Why Set Maximum Ratios of 40% and 60%?\n\nThe compression ratio ceilings are set based on different factors for 1080p and 2160p content:\n\n### 1080p (40% Maximum)\n\nThe 40% ceiling for 1080p exists because we can roughly measure where **HEVC stops being efficient compared to AVC**. We do this using two key video quality metrics:\n\n- **VMAF** - analyzes how humans perceive video quality and scores it from 0-100\n- **BD-Rate** - tells us how much smaller one encode is compared to another while maintaining the same quality level\n\nUsing these tools together shows us that:\n\n- HEVC achieves **20-40% smaller files** in the mid-bitrate range (~2-10 Mbps for 1080p)\n- These space savings are consistent across different quality levels\n- Beyond this point, both codecs achieve **near identical quality**\n- At ratios above 40%, **AVC becomes preferred** due to better tooling and quality control\n\n### 2160p (60% Maximum)\n\nThe 60% ceiling for 2160p content is based on different considerations:\n\n- This is approximately where **visual transparency** becomes achievable\n- Higher ratios provide **diminishing returns**\n- At this compression level, content achieves **VMAF scores above 95**\n- **Storage efficiency** becomes critical due to larger base file sizes\n- Quality improvements become **increasingly subtle** beyond this point\n\nRead these articles to better understand how VMAF and BD-Rate tell us how efficient a codec is[^1][^2]:\n\n## How Do We Apply This Index?\n\nThe ranking system works by calculating how close each Release Group / Streaming Service comes to achieving a user's desired compression ratio. This is done through a few key steps:\n\n1. **Delta Calculation**: We calculate the absolute difference (delta) between a group's average compression ratio and the target ratio. For example, if a group averages 25% compression and our target is 20%, their delta would be |25 - 20| = 5 percentage points.\n\n2. **K-means Clustering**: We use k-means clustering to automatically group release groups into tiers based on their deltas. K-means works by:\n - Starting with k random cluster centers\n - Assigning each group to its nearest center\n - Recalculating centers based on group assignments\n - Repeating until stable\n\n# Example Rankings\n\n## 1080p Examples\n\n### Example 1: Users prioritizing storage efficiency (10% target)\n\nUsers might choose this very aggressive compression target when:\n\n- Managing large libraries on limited storage\n- Collecting complete series where total size is a major concern\n- Primarily viewing on mobile devices or smaller screens\n- Dealing with bandwidth caps or slow internet connections\n\n| Tier | Group | Efficiency | Delta |\n| ---- | ----------------------- | ---------- | ----- |\n| 1 | iVy | 9.37% |Line truncated
|
"content": "This metric is aimed at identifying and ranking release groups based on their propensity to release **encodes that meet certain compression ratios**, with particular focus on **HEVC** releases where optimal efficiency occurs in specific bitrate ranges. By ranking these groups, we effectively prioritize releases that maximize HEVC's compression capabilities while maintaining quality at minimal file sizes.\n\n## What is a Compression Ratio?\n\nA compression ratio is a (made up) metric that evaluates encodes against their sources. We express this as the **encoded file size as a percentage of its source size** (typically a **remux** or **WEB-DL**).\n\nFor example:\n\n| Movie | Source (Remux) | Encode | Compression Ratio |\n| ------- | -------------- | ------ | ----------------- |\n| Movie A | 40 GB | 10 GB | 25% |\n| Movie B | 30 GB | 6 GB | 20% |\n| Movie C | 50 GB | 15 GB | 30% |\n\n## Why Is This Important?\n\nUnderstanding compression ratios helps balance two competing needs: **maintaining high video quality while minimizing file size**. Modern codecs like **HEVC** have a **\"sweet spot\"** where they deliver excellent quality with significant size savings. Finding this optimal point is crucial because:\n\n- Storage and bandwidth are always **limited resources**\n- Going beyond certain bitrates provides **diminishing quality returns**\n- Different codecs have different **efficiency curves**\n- Release groups need clear standards for **quality vs. size trade-offs**\n\n## What Ratio is Best?\n\nThere's no one-size-fits-all answer when it comes to choosing the perfect compression ratio. The \"best\" ratio **depends entirely on your specific needs**. At 1080p:\n\n- Space-conscious users might prefer **smaller files (5-10% of source)** with quality trade-offs\n- Quality-focused users might push towards **higher quality (30-40% of source)** for transparency\n- Most users find a sweet spot in the middle\n\nHowever, there are technical limits - files larger than **40% for 1080p** and **60% for 2160p** provide no meaningful benefits.\n\n## Why Set Maximum Ratios of 40% and 60%?\n\nThe compression ratio ceilings are set based on different factors for 1080p and 2160p content:\n\n### 1080p (40% Maximum)\n\nThe 40% ceiling for 1080p exists because we can roughly measure where **HEVC stops being efficient compared to AVC**. We do this using two key video quality metrics:\n\n- **VMAF** - analyzes how humans perceive video quality and scores it from 0-100\n- **BD-Rate** - tells us how much smaller one encode is compared to another while maintaining the same quality level\n\nUsing these tools together shows us that:\n\n- HEVC achieves **20-40% smaller files** in the mid-bitrate range (~2-10 Mbps for 1080p)\n- These space savings are consistent across different quality levels\n- Beyond this point, both codecs achieve **near identical quality**\n- At ratios above 40%, **AVC becomes preferred** due to better tooling and quality control\n\n### 2160p (60% Maximum)\n\nThe 60% ceiling for 2160p content is based on different considerations:\n\n- This is approximately where **visual transparency** becomes achievable\n- Higher ratios provide **diminishing returns**\n- At this compression level, content achieves **VMAF scores above 95**\n- **Storage efficiency** becomes critical due to larger base file sizes\n- Quality improvements become **increasingly subtle** beyond this point\n\nRead these articles to better understand how VMAF and BD-Rate tell us how efficient a codec is[^1][^2]:\n\n## How Do We Apply This Index?\n\nThe ranking system works by calculating how close each Release Group / Streaming Service comes to achieving a user's desired compression ratio. This is done through a few key steps:\n\n1. **Delta Calculation**: We calculate the absolute difference (delta) between a group's average compression ratio and the target ratio. For example, if a group averages 25% compression and our target is 20%, their delta would be |25 - 20| = 5 percentage points.\n\n2. **K-means Clustering**: We use k-means clustering to automatically group release groups into tiers based on their deltas. K-means works by:\n - Starting with k random cluster centers\n - Assigning each group to its nearest center\n - Recalculating centers based on group assignments\n - Repeating until stable\n\n# Example Rankings\n\n## 1080p Examples\n\n### Example 1: Users prioritizing storage efficiency (10% target)\n\nUsers might choose this very aggressive compression target when:\n\n- Managing large libraries on limited storage\n- Collecting complete series where total size is a major concern\n- Primarily viewing on mobile devices or smaller screens\n- Dealing with bandwidth caps or slow internet connections\n\n| Tier | Group | Efficiency | Delta |\n| ---- | ----------------------- | ---------- | ----- |\n| 1 | iVy | 9.37% |Line truncated
|
||||||
"last_modified": "2025-03-01T10:02:33.298408+00:00",
|
"last_modified": "2025-03-07T15:06:31.720032+00:00",
|
||||||
"title": "Encode Efficiency Index",
|
"title": "Encode Efficiency Index",
|
||||||
"slug": "EEi",
|
"slug": "EEi",
|
||||||
"author": "santiagosayshey",
|
"author": "santiagosayshey",
|
||||||
@@ -17,7 +17,7 @@
|
|||||||
{
|
{
|
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"_id": "FAQ",
|
"_id": "FAQ",
|
||||||
"content": "This entry is dedicated to providing answers to the most frequently asked questions about Dictionarry / Profilarr.\n\n| Question | Answer |\n| ------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| Why isn't the highest scored release being grabbed? | You may have prefer propers and repacks on. This option forces releases with a proper / repack flag to be grabbed, even if it's Custom Format score is not the highest. To turn it off, navigate to Settings > Media Management > File Management and set Prefer Propers / Repacks to Do Not Prefer. |\n| What's the difference between h264, x264, AVC, h265, x265 and HEVC? | **H.264 (AVC)**: A video compression standard.<br>**x264**: An open source encoder that produces H.264 videos.<br>**H.265 (HEVC)**: A more advanced video compression standard than H.264, offering better compression and quality for 4K and higher resolutions.<br>**x265**: An open source encoder that produces H.265 videos.<br><br>**Key Points**:<br>- HEVC/AVC refers to the codec in general<br>- H.264/5 refers to a lossless rip (WEB-DL or remux)<br>- x264/5 refers to encoded content (WEBRip or Blu-ray encode)<br><br>_Note: Many HEVC files are mislabeled, making it challenging to distinguish between lossless and lossy releases based on release names alone._ Line truncated
|
"content": "This entry is dedicated to providing answers to the most frequently asked questions about Dictionarry / Profilarr.\n\n| Question | Answer |\n| ------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| Why isn't the highest scored release being grabbed? | You may have prefer propers and repacks on. This option forces releases with a proper / repack flag to be grabbed, even if it's Custom Format score is not the highest. To turn it off, navigate to Settings > Media Management > File Management and set Prefer Propers / Repacks to Do Not Prefer. |\n| What's the difference between h264, x264, AVC, h265, x265 and HEVC? | **H.264 (AVC)**: A video compression standard.<br>**x264**: An open source encoder that produces H.264 videos.<br>**H.265 (HEVC)**: A more advanced video compression standard than H.264, offering better compression and quality for 4K and higher resolutions.<br>**x265**: An open source encoder that produces H.265 videos.<br><br>**Key Points**:<br>- HEVC/AVC refers to the codec in general<br>- H.264/5 refers to a lossless rip (WEB-DL or remux)<br>- x264/5 refers to encoded content (WEBRip or Blu-ray encode)<br><br>_Note: Many HEVC files are mislabeled, making it challenging to distinguish between lossless and lossy releases based on release names alone._ Line truncated
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"last_modified": "2025-03-01T10:02:33.298408+00:00",
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"last_modified": "2025-03-07T15:06:31.720032+00:00",
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"title": "FAQ",
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"title": "FAQ",
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"slug": "faq",
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"slug": "faq",
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"author": "santiagosayshey",
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"author": "santiagosayshey",
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@@ -31,7 +31,7 @@
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{
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{
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"_id": "GPPi",
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"_id": "GPPi",
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"content": "## What are Golden Popcorns?\n\n**_Golden Popcorns_** are _very high quality encodes_, marked as such by one of the best private torrent trackers. These releases are manually reviewed by a dedicated, experienced team of _Golden Popcorn_ checkers. Golden Popcorns are the simplest way to quantify a subjective _best_ encode.\n\n## The Decision Engine\n\nThe Golden Popcorn Performance Index, or GPPI, is a calculated metric, pivotal to the [Transparent](../Profiles/1080p%20Transparent.md) profile's decision-making process. It's engineered to rank release groups based on their propensity to release a Golden Popcorn encode at any given resolution $r$.\n\n## Formula\n\nOn first glance, it seems the most obvious way to determine which release groups are most likely to release golden popcorns is to find their Golden Popcorn Ratio, i.e. The number of Golden Popcorns divided by the total number of encodes for any given resolution _r_.\n\nHowever, If we were to take Golden Popcorn ratio at face value, we might incorrectly prioritise a release group who has a high GP ratio, but a low number of encodes. On the opposite spectrum, if we take the raw number of Golden Popcorns for any group, we might incorrectly prioritise a group with a low GP ratio.\n\nSo instead, we multiply the number of Golden Popcorns at resolution $r$ for a given release group, by a factor of said release group's Golden Popcorn Ratio. This essentially limits both metrics as a factor of each other.\n\nFor any given resolution _r_, the GPPI is defined as:\n\n$$\n\\begin{aligned}\n\\text{GPPI}_r &= GPE_r \\cdot \\left( \\frac{GPE_r}{E_r} \\right) \\\\\n &= \\frac{GPE_r^2}{E_r}\n\\end{aligned}\n$$\n\nWhere:\n\n- $\\text{GPPI}_r$ is the Golden Popcorn Performance Index at resolution $r$\n- $GPE_r$ is the number of Golden Popcorns at resolution $r$\n- $E_r$ is the total number of encodes at resolution $r$",
|
"content": "## What are Golden Popcorns?\n\n**_Golden Popcorns_** are _very high quality encodes_, marked as such by one of the best private torrent trackers. These releases are manually reviewed by a dedicated, experienced team of _Golden Popcorn_ checkers. Golden Popcorns are the simplest way to quantify a subjective _best_ encode.\n\n## The Decision Engine\n\nThe Golden Popcorn Performance Index, or GPPI, is a calculated metric, pivotal to the [Transparent](../Profiles/1080p%20Transparent.md) profile's decision-making process. It's engineered to rank release groups based on their propensity to release a Golden Popcorn encode at any given resolution $r$.\n\n## Formula\n\nOn first glance, it seems the most obvious way to determine which release groups are most likely to release golden popcorns is to find their Golden Popcorn Ratio, i.e. The number of Golden Popcorns divided by the total number of encodes for any given resolution _r_.\n\nHowever, If we were to take Golden Popcorn ratio at face value, we might incorrectly prioritise a release group who has a high GP ratio, but a low number of encodes. On the opposite spectrum, if we take the raw number of Golden Popcorns for any group, we might incorrectly prioritise a group with a low GP ratio.\n\nSo instead, we multiply the number of Golden Popcorns at resolution $r$ for a given release group, by a factor of said release group's Golden Popcorn Ratio. This essentially limits both metrics as a factor of each other.\n\nFor any given resolution _r_, the GPPI is defined as:\n\n$$\n\\begin{aligned}\n\\text{GPPI}_r &= GPE_r \\cdot \\left( \\frac{GPE_r}{E_r} \\right) \\\\\n &= \\frac{GPE_r^2}{E_r}\n\\end{aligned}\n$$\n\nWhere:\n\n- $\\text{GPPI}_r$ is the Golden Popcorn Performance Index at resolution $r$\n- $GPE_r$ is the number of Golden Popcorns at resolution $r$\n- $E_r$ is the total number of encodes at resolution $r$",
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"last_modified": "2025-03-01T10:02:33.299408+00:00",
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"last_modified": "2025-03-07T15:06:31.720032+00:00",
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"title": "Golden Popcorn Performance Index",
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"title": "Golden Popcorn Performance Index",
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"slug": "GPPi",
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"slug": "GPPi",
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"author": "santiagosayshey",
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"author": "santiagosayshey",
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@@ -46,7 +46,7 @@
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{
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{
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"_id": "RGP",
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"_id": "RGP",
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"content": "## So, how does Dictionarry _actually simplify media automation?_\n\nWell, first we need to understand that we're trying to **automate the subjective analysis of how \"good\" a release is**. To do that, we need to first define **what \"good\" even means**. To some people, it could mean how well something looks on their screen, or sounds through speakers; we define this as _quality_. To others, it means how many releases they can download while still maintaining some kind of quality standard; we define this as _efficiency_.\n\nSo, that leads us to a new question - _how do we measure quality and efficiency_? You might think we'd want to parse releases and find their technical properties; resolution, bitrate, video / audio codecs, hdr, etc.\n\n```\nRelease 1 (25.2 GiB): Blockbuster Movie A 2022 Hybrid 1080p WEBRip DDPA5.1 x264-group A\n\nRelease 2 (27.3 GiB): Blockbuster Movie A.1080p.WEBRip.DD+7.1.x264-group B\n```\n\nLooking at these two releases, you'll notice that they both have the EXACT same technical specification and would rank equally. But they're different sizes... so which is better? Using audio / video properties to measure quality / efficiency can be effective, but is largely **limited by the information that they convey**. You can't adequately answer which is better just by looking at these releases in isolation. So how do we not look at these releases in isolation? Or rather, how do we _extrapolate information that isn't already there?_\n\n### Group Tags\n\nOur answer lies in the little bit of information at the end of every release - it's **group tag**. Dictionarry tracks historic release group data in order to **rank groups based on their propensity to reach quantifiable levels of quality and efficiency**. We do this using two metrics:\n\n1. Golden Popcorn Performance Index (GPPi): How many golden popcorns a release group has, as a ratio of their total number of releases\n2. Encode Efficiency Index (EEi): The average size of a release group's encode compared to it's likely source.\n\nThese metrics are **evidence based, data driven and objective**.\n\n### TL;DR\n\nTL;DR: Dictionarry **simplifies media automation by prioritizing release groups that achieve quantifiable levels of quality and efficiency through objective measurement**. These release group rankings are built and maintained as custom formats to be scored in their respective quality profiles. You can review these group rankings below.",
|
"content": "## So, how does Dictionarry _actually simplify media automation?_\n\nWell, first we need to understand that we're trying to **automate the subjective analysis of how \"good\" a release is**. To do that, we need to first define **what \"good\" even means**. To some people, it could mean how well something looks on their screen, or sounds through speakers; we define this as _quality_. To others, it means how many releases they can download while still maintaining some kind of quality standard; we define this as _efficiency_.\n\nSo, that leads us to a new question - _how do we measure quality and efficiency_? You might think we'd want to parse releases and find their technical properties; resolution, bitrate, video / audio codecs, hdr, etc.\n\n```\nRelease 1 (25.2 GiB): Blockbuster Movie A 2022 Hybrid 1080p WEBRip DDPA5.1 x264-group A\n\nRelease 2 (27.3 GiB): Blockbuster Movie A.1080p.WEBRip.DD+7.1.x264-group B\n```\n\nLooking at these two releases, you'll notice that they both have the EXACT same technical specification and would rank equally. But they're different sizes... so which is better? Using audio / video properties to measure quality / efficiency can be effective, but is largely **limited by the information that they convey**. You can't adequately answer which is better just by looking at these releases in isolation. So how do we not look at these releases in isolation? Or rather, how do we _extrapolate information that isn't already there?_\n\n### Group Tags\n\nOur answer lies in the little bit of information at the end of every release - it's **group tag**. Dictionarry tracks historic release group data in order to **rank groups based on their propensity to reach quantifiable levels of quality and efficiency**. We do this using two metrics:\n\n1. Golden Popcorn Performance Index (GPPi): How many golden popcorns a release group has, as a ratio of their total number of releases\n2. Encode Efficiency Index (EEi): The average size of a release group's encode compared to it's likely source.\n\nThese metrics are **evidence based, data driven and objective**.\n\n### TL;DR\n\nTL;DR: Dictionarry **simplifies media automation by prioritizing release groups that achieve quantifiable levels of quality and efficiency through objective measurement**. These release group rankings are built and maintained as custom formats to be scored in their respective quality profiles. You can review these group rankings below.",
|
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"last_modified": "2025-03-01T10:02:33.299408+00:00",
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"last_modified": "2025-03-07T15:06:31.720032+00:00",
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"title": "Release Group Philosophy",
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"title": "Release Group Philosophy",
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"slug": "RGP",
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"slug": "RGP",
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"author": "santiagosayshey",
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"author": "santiagosayshey",
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@@ -62,7 +62,7 @@
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{
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{
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"_id": "edition",
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"_id": "edition",
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"content": "By default, Dictionarry's profiles prefer the ['Special' Edition](https://dictionarry.dev/formats/special-edition) of each movie. This is because these editions are often considered the more 'definitive' version of the movie because they contain the director's complete creative vision without studio interference or runtime constraints, and are often recommended over their theatrical counterparts.\n\n| Movie | Preferred Version | Reasons |\n| ----------------------------------------- | ---------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| Aliens (1986) | Special | James Cameron's Special Edition enhances the film with crucial character development, particularly the scenes about Ripley's daughter which add emotional depth to her relationship with Newt. While the theatrical cut has tighter pacing, the added content like the sentry gun sequences adds valuable world-building and tension. The colony scenes provide important context that enriches rather than spoils the story. |\n| Blade Runner (1982) | Final Cut | The Final Cut (2007) is considered the definitive version over theatrical, workprint, and Director's Cut releases. It removes the theatrical's controversial voice-over narration and \"happy ending\" that were studio-mandated and disliked by cast and crew. It preserves the original's ambiguous ending about Deckard's nature while fixing numerous continuity errors and technical issues. Key improvements include: cleaned up wire removal in spinner scenes, fixed lip sync in Zhora's death scene, digital correction of the obvious stunt double's face, properly matching the number of replicants mentioned to those shown, correction of the dove release scene's obvious day-for-night shooting, improved color timing that better matches Jordan Cronenweth's original cinematography, and restoration of the full unicorn dream sequence that better supports the film's central mysteries. While some defend elements of other versions (particularly the 1992 Director's Cut), the Final Cut represents Ridley Scott's complete creative vision withLine truncated
|
"content": "By default, Dictionarry's profiles prefer the ['Special' Edition](https://dictionarry.dev/formats/special-edition) of each movie. This is because these editions are often considered the more 'definitive' version of the movie because they contain the director's complete creative vision without studio interference or runtime constraints, and are often recommended over their theatrical counterparts.\n\n| Movie | Preferred Version | Reasons |\n| ----------------------------------------- | ---------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| Aliens (1986) | Special | James Cameron's Special Edition enhances the film with crucial character development, particularly the scenes about Ripley's daughter which add emotional depth to her relationship with Newt. While the theatrical cut has tighter pacing, the added content like the sentry gun sequences adds valuable world-building and tension. The colony scenes provide important context that enriches rather than spoils the story. |\n| Blade Runner (1982) | Final Cut | The Final Cut (2007) is considered the definitive version over theatrical, workprint, and Director's Cut releases. It removes the theatrical's controversial voice-over narration and \"happy ending\" that were studio-mandated and disliked by cast and crew. It preserves the original's ambiguous ending about Deckard's nature while fixing numerous continuity errors and technical issues. Key improvements include: cleaned up wire removal in spinner scenes, fixed lip sync in Zhora's death scene, digital correction of the obvious stunt double's face, properly matching the number of replicants mentioned to those shown, correction of the dove release scene's obvious day-for-night shooting, improved color timing that better matches Jordan Cronenweth's original cinematography, and restoration of the full unicorn dream sequence that better supports the film's central mysteries. While some defend elements of other versions (particularly the 1992 Director's Cut), the Final Cut represents Ridley Scott's complete creative vision withLine truncated
|
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"last_modified": "2025-03-01T10:02:33.299408+00:00",
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"last_modified": "2025-03-07T15:06:31.721032+00:00",
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"title": "Edition Philosophy",
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"title": "Edition Philosophy",
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"slug": "edtion-philosophy",
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"slug": "edtion-philosophy",
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"author": "santiagosayshey",
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"author": "santiagosayshey",
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@@ -77,7 +77,7 @@
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{
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{
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"_id": "home",
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"_id": "home",
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"content": "# \ud83d\udc4b Hey!\n\nWelcome to Dictionarry! This project aims to wiki-fy and **simplify media automation** in Radarr / Sonarr through extensive, data driven documentation, custom formats and quality profiles.\n\n## \ud83d\udca1 Motivation\n\nNavigating the world of media automation and coming across quality terms like \"Remux\", or \"HEVC\" or \"Dolby Vision\" can be quite daunting when all you want to do is setup a media server to watch some content. It often **feels like you need a masters in audio / video just to grab the latest blockbuster.** Dictionarry aims not to explain these concepts in detail, but **abstract them into more approachable ideas** that don't require extensive knowledge or experience.\n\nDictionarry leverages two key features of Radarr and Sonarr to simplify media automation:\n\n1. Custom Formats - Think of these as smart filters that scan release titles for specific patterns. They help **identify important characteristics** of your media, such as:\n\n - Video quality (4K, HDR, Dolby Vision)\n - Audio formats (Atmos, DTS, TrueHD)\n - Source types (Remux, Web-DL, Blu-ray)\n - Potential issues (upscaled content, poor encodes)\n\n2. Quality Profiles - These act like a scoring system that **ranks releases** based on their Custom Format matches. You can:\n - Prioritize what matters most to you\n - Automatically upgrade to better versions\n - Avoid problematic releases\n\nThink of Dictionarry as your personal car-buying expert: Instead of researching every technical specification and test-driving dozens of vehicles, you get access to a curated showroom of pre-vetted options that match what you're looking for. Whether you want:\n\n- 2160p Remux - **Maximum Quality** 4K HDR remuxes with lossless audio and Dolby Vision\n- 2160p Quality - **Transparent 4K** HDR encodes selected using the Encode Efficiency Index\n- 1080p Quality - **Transparent 1080p** encodes optimized using the Golden Popcorn Performance Index\n- 1080p Efficient - **Efficient x265 1080p** Encodes optimized to save space using the Encode Efficiency Index\n\n\n\nDictionarry's database of tested profiles and formats handles the technical decisions for you.\n\n## \u2699\ufe0f Profilarr\n\nThe database by itself does nothing. Custom Formats and Quality Profiles **need to be imported** and configured in your individual arr installations. Rather than leaving you to manually create everything yourself based on our guides, we've created **Profilarr** to automate this process.\n\nProfilarr is a **configuration management tool** for Radarr and Sonarr that can interface with **ANY remote configuration database** (not just Dictionarry's!). It automatically:\n\n- **Pulls** new updates from your chosen database\n- **Compiles** the database format into specific arr formats\n- **Imports** them to your arr installations\n- Manages version control of your configurations\n\nBuilt on top of git, Profilarr treats your configurations like code, allowing you to:\n\n- Track changes over time\n- Maintain your own customizations while still receiving database updates\n- Resolve conflicts between local / remote changes when they arise\n\nThe architecture was specifically built like this to **put user choice first**. We believe that:\n\n- **Your media setup should reflect your needs, not our opinions**\n- Updates should enhance your configuration, not override it\n- Different users have different requirements (storage constraints, hardware capabilities, quality preferences)\n- The ability to customize should never be sacrificed for convenience\n\nProfilarr empowers you to use Dictionarry's database (or anyone elses!) as a foundation while maintaining the freedom to adapt it to your specific needs.\n\n## \ud83d\udd28 Development Notice\n\nCustom Formats / Quality profiles on this site reflect the contents of the [Dictionarry Database](https://github.com/Dictionarry-Hub/database) and what the upcoming Profilarr GUI will clone / import. The old profilarr scripts still use outdated profiles / custom formats! We're currently in a bit of an inbetween state at the moment, so please bare with us as we get the new Profilarr version out!",
|
"content": "# \ud83d\udc4b Hey!\n\nWelcome to Dictionarry! This project aims to wiki-fy and **simplify media automation** in Radarr / Sonarr through extensive, data driven documentation, custom formats and quality profiles.\n\n## \ud83d\udca1 Motivation\n\nNavigating the world of media automation and coming across quality terms like \"Remux\", or \"HEVC\" or \"Dolby Vision\" can be quite daunting when all you want to do is setup a media server to watch some content. It often **feels like you need a masters in audio / video just to grab the latest blockbuster.** Dictionarry aims not to explain these concepts in detail, but **abstract them into more approachable ideas** that don't require extensive knowledge or experience.\n\nDictionarry leverages two key features of Radarr and Sonarr to simplify media automation:\n\n1. Custom Formats - Think of these as smart filters that scan release titles for specific patterns. They help **identify important characteristics** of your media, such as:\n\n - Video quality (4K, HDR, Dolby Vision)\n - Audio formats (Atmos, DTS, TrueHD)\n - Source types (Remux, Web-DL, Blu-ray)\n - Potential issues (upscaled content, poor encodes)\n\n2. Quality Profiles - These act like a scoring system that **ranks releases** based on their Custom Format matches. You can:\n - Prioritize what matters most to you\n - Automatically upgrade to better versions\n - Avoid problematic releases\n\nThink of Dictionarry as your personal car-buying expert: Instead of researching every technical specification and test-driving dozens of vehicles, you get access to a curated showroom of pre-vetted options that match what you're looking for. Whether you want:\n\n- 2160p Remux - **Maximum Quality** 4K HDR remuxes with lossless audio and Dolby Vision\n- 2160p Quality - **Transparent 4K** HDR encodes selected using the Encode Efficiency Index\n- 1080p Quality - **Transparent 1080p** encodes optimized using the Golden Popcorn Performance Index\n- 1080p Efficient - **Efficient x265 1080p** Encodes optimized to save space using the Encode Efficiency Index\n\n\n\nDictionarry's database of tested profiles and formats handles the technical decisions for you.\n\n## \u2699\ufe0f Profilarr\n\nThe database by itself does nothing. Custom Formats and Quality Profiles **need to be imported** and configured in your individual arr installations. Rather than leaving you to manually create everything yourself based on our guides, we've created **Profilarr** to automate this process.\n\nProfilarr is a **configuration management tool** for Radarr and Sonarr that can interface with **ANY remote configuration database** (not just Dictionarry's!). It automatically:\n\n- **Pulls** new updates from your chosen database\n- **Compiles** the database format into specific arr formats\n- **Imports** them to your arr installations\n- Manages version control of your configurations\n\nBuilt on top of git, Profilarr treats your configurations like code, allowing you to:\n\n- Track changes over time\n- Maintain your own customizations while still receiving database updates\n- Resolve conflicts between local / remote changes when they arise\n\nThe architecture was specifically built like this to **put user choice first**. We believe that:\n\n- **Your media setup should reflect your needs, not our opinions**\n- Updates should enhance your configuration, not override it\n- Different users have different requirements (storage constraints, hardware capabilities, quality preferences)\n- The ability to customize should never be sacrificed for convenience\n\nProfilarr empowers you to use Dictionarry's database (or anyone elses!) as a foundation while maintaining the freedom to adapt it to your specific needs.\n\n## \ud83d\udd28 Development Notice\n\nCustom Formats / Quality profiles on this site reflect the contents of the [Dictionarry Database](https://github.com/Dictionarry-Hub/database) and what the upcoming Profilarr GUI will clone / import. The old profilarr scripts still use outdated profiles / custom formats! We're currently in a bit of an inbetween state at the moment, so please bare with us as we get the new Profilarr version out!",
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"last_modified": "2025-03-01T10:02:33.299408+00:00",
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"last_modified": "2025-03-07T15:06:31.721032+00:00",
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"title": "home",
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"title": "home",
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"slug": "home",
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"slug": "home",
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"author": "santiagosayshey",
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"author": "santiagosayshey",
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{
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{
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"_id": "profilarr-setup",
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"_id": "profilarr-setup",
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"content": "Profilarr is a **custom format / quality profile management tool** that acts as a middleman between a configuration database and your radarr/sonarr installations. It automatically:\n\n- **Pulls** new updates from your chosen database\n- **Compiles** the database format into specific arr formats\n- **Imports** them to your arr installations\n- Manages **version control** of your configurations\n\n## Installation\n\nProfilarr follows the GitFlow workflow for development:\n\n- New features are first merged into the `develop` branch for testing\n- Once stable, these features move to the `main` branch\n- For early access to new features, use `santiagosayshey/profilarr:beta`\n- For stable use, use `santiagosayshey/profilarr:latest`\n\nOnce installed, you can visit the web UI at `http://[address]:6868` and begin the setup process.\n\n### Docker Compose (recommended)\n\n```yaml\nservices:\n profilarr:\n image: santiagosayshey/profilarr:latest # or :beta\n container_name: profilarr\n ports:\n - 6868:6868\n volumes:\n - /path/to/your/data:/config\n environment:\n - TZ=UTC # Set your timezone\n env_file:\n - .env # Optional: Only needed if contributing to a database\n restart: unless-stopped\n```\n\n### Docker CLI\n\n```bash\ndocker run -d \\\n --name=profilarr \\\n -p 6868:6868 \\\n -v /path/to/your/data:/config \\\n -e TZ=UTC \\\n --env-file .env \\ # Optional: Only needed if contributing to a database\n --restart unless-stopped \\\n santiagosayshey/profilarr:latest # or :beta\n```\n\n### Volumes\n\nWhen configuring the volume mount (`/path/to/your/data:/config`):\n\n- Replace `/path/to/your/data` with the actual path on your host system\n- **Windows users:** The database is case-sensitive. Use a docker volume or the WSL file system directly to avoid issues\n - Docker volume example: `profilarr_data:/config`\n - WSL filesystem example: `/home/username/docker/profilarr:/config`\n\n### Development\n\nIn addition to being a 'sync' tool for end users, Profilarr also acts as a development platform for people to work on, and contribute to, a remote database. Read [here](https://dictionarry.dev/wiki/development) to learn more on how to setup Profilarr for development.\n\n## Usage\n\n### Credentials Setup\n\nThe first time you visit the web UI at `http://[address]:6868`, you'll be prompted to setup login credentials.\n\n- Make sure you keep note of these credentials, as you won't be able to reset the password if you forget it later on (unless you have access to the filesystem and can interact with the docker container.)\n\n\n\n### Configuration Workflows\n\nOnce you've setup your user credentials you can start working on your media configurations. You have the choice to either:\n\n1. Connect to an external database, make changes, receive updates and handle change conflicts.\n - This is what most people will be using if they don't want to build configurations from scratch.\n2. Use Profilarr completely locally, without a database.\n - This option is left for people who want the advantages of Profilarr's compilation system (single definition profiles, tweaks, better management, etc), but don't want to be tied to any one database. Skip ahead to [Making Changes](#making-changes)\n\n#### Connecting to a Database\n\nProfilarr leverages Git to create an open-source configuration sharing system. To get started, navigate to `Settings -> Database`, and link a repository.\n\n\n\n| # | Feature | Description |\n| --- | -------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| 1 | Database information | Contains basic information about the database - Name, Owner, Stars/Issues/PRs |\n| 2 | Status Container | - View outgoing changes (any local changes you've made to the database)<br>- View incoming changes (any changes pushed to a remote database that haven't been applied to your local one)<br>- View merge conflicts (when you've made changes to a file that also has incoming changes) |\n| 3 | Commit / Change Log | - View logs of Line truncated
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"content": "Profilarr is a **custom format / quality profile management tool** that acts as a middleman between a configuration database and your radarr/sonarr installations. It automatically:\n\n- **Pulls** new updates from your chosen database\n- **Compiles** the database format into specific arr formats\n- **Imports** them to your arr installations\n- Manages **version control** of your configurations\n\n## Installation\n\nProfilarr follows the GitFlow workflow for development:\n\n- New features are first merged into the `develop` branch for testing\n- Once stable, these features move to the `main` branch\n- For early access to new features, use `santiagosayshey/profilarr:beta`\n- For stable use, use `santiagosayshey/profilarr:latest`\n\nOnce installed, you can visit the web UI at `http://[address]:6868` and begin the setup process.\n\n### Docker Compose (recommended)\n\n```yaml\nservices:\n profilarr:\n image: santiagosayshey/profilarr:latest # or :beta\n container_name: profilarr\n ports:\n - 6868:6868\n volumes:\n - /path/to/your/data:/config\n environment:\n - TZ=UTC # Set your timezone\n env_file:\n - .env # Optional: Only needed if contributing to a database\n restart: unless-stopped\n```\n\n### Docker CLI\n\n```bash\ndocker run -d \\\n --name=profilarr \\\n -p 6868:6868 \\\n -v /path/to/your/data:/config \\\n -e TZ=UTC \\\n --env-file .env \\ # Optional: Only needed if contributing to a database\n --restart unless-stopped \\\n santiagosayshey/profilarr:latest # or :beta\n```\n\n### Volumes\n\nWhen configuring the volume mount (`/path/to/your/data:/config`):\n\n- Replace `/path/to/your/data` with the actual path on your host system\n- **Windows users:** The database is case-sensitive. Use a docker volume or the WSL file system directly to avoid issues\n - Docker volume example: `profilarr_data:/config`\n - WSL filesystem example: `/home/username/docker/profilarr:/config`\n\n### Development\n\nIn addition to being a 'sync' tool for end users, Profilarr also acts as a development platform for people to work on, and contribute to, a remote database. Read [here](https://dictionarry.dev/wiki/development) to learn more on how to setup Profilarr for development.\n\n## Usage\n\n### Credentials Setup\n\nThe first time you visit the web UI at `http://[address]:6868`, you'll be prompted to setup login credentials.\n\n- Make sure you keep note of these credentials, as you won't be able to reset the password if you forget it later on (unless you have access to the filesystem and can interact with the docker container.)\n\n\n\n### Configuration Workflows\n\nOnce you've setup your user credentials you can start working on your media configurations. You have the choice to either:\n\n1. Connect to an external database, make changes, receive updates and handle change conflicts.\n - This is what most people will be using if they don't want to build configurations from scratch.\n2. Use Profilarr completely locally, without a database.\n - This option is left for people who want the advantages of Profilarr's compilation system (single definition profiles, tweaks, better management, etc), but don't want to be tied to any one database. Skip ahead to [Making Changes](#making-changes)\n\n#### Connecting to a Database\n\nProfilarr leverages Git to create an open-source configuration sharing system. To get started, navigate to `Settings -> Database`, and link a repository.\n\n\n\n| # | Feature | Description |\n| --- | -------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| 1 | Database information | Contains basic information about the database - Name, Owner, Stars/Issues/PRs |\n| 2 | Status Container | - View outgoing changes (any local changes you've made to the database)<br>- View incoming changes (any changes pushed to a remote database that haven't been applied to your local one)<br>- View merge conflicts (when you've made changes to a file that also has incoming changes) |\n| 3 | Commit / Change Log | - View logs of Line truncated
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"last_modified": "2025-03-01T10:02:33.299408+00:00",
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"last_modified": "2025-03-07T15:06:31.721032+00:00",
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"title": "Profilarr Setup",
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"title": "Profilarr Setup",
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"slug": "profilarr-setup",
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"slug": "profilarr-setup",
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"author": "santiagosayshey",
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"author": "santiagosayshey",
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Reference in new issue
Block a user