MongoDB Explorer
Explore a MongoDB document or collection sample and infer its field schema and types.
Aapke MongoDB documents locally aapke browser mein parse aur analyze hote hain; jo aap paste karte hain woh aapke device se bahar nahi jaata ya kisi server ko upload nahi hota.
Is sample se TypeScript types chahiye? JSON to TypeScript try karein.
MongoDB Explorer ke baare mein
Yeh mongodb schema explorer ek single MongoDB document ya documents ka ek array JSON ke roop mein leta hai aur aapke liye underlying field schema infer karta hai. Compass, mongosh, ya ek application log se ek sample paste karein aur yeh har document walk karta hai, field paths ki ek flat list banata hai (nested objects aur array-of-object elements sahit), har ek ko ek loose BSON-ish type jaise int, double, string, bool, object, array, ya null se label karta hai, aur dikhata hai ki sample ke kitne documents mein har field hai. Yeh un backend developers, data engineers aur QA testers ke liye bana hai jinhe ek collection ka shape samajhna, optional ya inconsistent fields spot karna, aur ek schema jaldi document karna hai. Sab kuch locally aapke browser mein chalta hai, isliye jo documents aap paste karte hain woh kabhi aapke device se bahar nahi jaate aur kisi server ko kuch upload nahi hota.
Features
- Ek single document ya documents ka ek array JSON ke roop mein accept karta hai
- Alphabetically sorted field paths ki ek flat list infer karta hai
- Har field ko ek BSON-ish type se label karta hai: int, double, string, bool, object, array, ya null
- Nested objects mein aur object arrays ke pehle element mein descend karta hai (path[].field)
- Ginta hai kitne documents mein har field hai taaki aap optional fields spot kar sakein
- Jab documents disagree karte hain to per field multiple types merge karta hai (jaise int | null)
- Schema ke top par ek document aur field count summary dikhata hai
- Jaise aap paste karte hain live chalta hai aur poori tarah aapke browser mein offline kaam karta hai
MongoDB Explorer kaise use karein
- Ek MongoDB document ya documents ka ek array JSON ke roop mein input box mein paste karein.
- Right par inferred schema table padhein, field paths, types, aur coverage ke saath.
- Optional ya sparse fields dhoondhne ke liye har field ke paas present/total count check karein.
- Deep structure dekhne ke liye nested paths aur array fields expand karein.
- Sample share karne ke liye normalized JSON copy ya download karein.
Example
Input
[
{ "_id": 1, "name": "Ada", "age": 36, "roles": ["admin"] },
{ "_id": 2, "name": "Linus", "active": true, "address": { "city": "Helsinki" } }
]
Output
_id int 2/2
active bool 1/2
address object 1/2
address.city string 1/2
age int 1/2
name string 2/2
roles array 1/2
Do documents field paths, types, aur per-field coverage mein infer hue.
Common errors aur troubleshooting
- Input ek JSON parse error ke saath reject ho jata hai. — Pakka karein ki sample valid JSON hai: double-quoted keys aur strings, koi trailing commas nahi, aur ObjectId() ya ISODate() jaise koi mongosh helpers nahi.
- Aapne shell se seedha ObjectId(...), ISODate(...), ya NumberLong(...) paste kiya. — Paste karne se pehle in extended-JSON constructors ko plain JSON values (jaise ek quoted string) se replace karein, kyunki explorer standard JSON parse karta hai.
- Aapko ek document ya documents ke array ke liye maangne wala message milta hai. — Ek object ya objects ka ek array dein. Scalars ke bare arrays ya ek single primitive value mein infer karne ke liye koi fields nahi hote.
- Objects ka ek array sirf pehle element ke fields dikhata hai. — Yeh expected hai: array-of-object schemas pehle element (path[]) se infer hote hain. Sample reorder karein taaki ek representative object pehle aaye.
- Ek field do types dikhata hai jaise int | double ya string | null. — Iska matlab hai ki aapke sample ke documents us field ke type par disagree karte hain; yeh informational hai, error nahi.
Aksar pooche jaane wale sawaal
- MongoDB schema explorer kya hai?
- Yeh ek in-browser tool hai jo ek MongoDB document ya documents ka ek sample array JSON ke roop mein leta hai aur schema infer karta hai: har field path, har ek ke liye ek BSON-ish type, aur sample ke kitne documents mein woh field hai.
- Yeh field types kaise infer karta hai?
- Yeh har value inspect karta hai aur ek loose BSON-ish label assign karta hai: integers int bante hain, non-integers double bante hain, plus string, bool, object, array, aur null. Jab documents disagree karte hain, field har type jo usne dekha use pipe se joda hua dikhata hai.
- Kya yeh nested objects aur arrays handle karta hai?
- Haan. Nested objects address.city jaise dotted paths produce karte hain, aur objects ke arrays unke pehle element ke through ek path[].field notation ka use karke explore hote hain.
- Har field ke paas count ka kya matlab hai?
- Yeh field ka coverage hai, present/total ke roop mein dikhaya gaya, matlab aapke paste kiye sample ke kitne documents mein woh field hai. Total se kam value ek optional ya sparse field flag karti hai.
- Kya main mongosh ya Compass se extended JSON paste kar sakta hoon?
- Standard JSON paste karein. Pehle ObjectId(), ISODate() aur NumberLong() jaise constructors ko plain values se replace karein, varna JSON parsing fail ho jayegi.
- Kya is MongoDB schema explorer ka use karte waqt mera data safe hai?
- Haan. Explorer poori tarah aapke browser mein chalta hai, isliye jo documents aap paste karte hain woh kabhi aapke device se bahar nahi jaate aur kisi server ko kuch upload nahi hota.
Related tools
Saare ArrayKit tools